domain: sdv sde

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Ii Toledo-Alarcón

Fermentation in Mixed Cultures: the Role

Keywords: Electro-Fermentation, Dark fermentation, Microbial Community Interactions, Clostridia species. vii

Dark fermentation (DF) is a biological process used to produce hydrogen (H2). In this process a wide variety of substrates could be used including simple substrates such as glucose or more complex substrates such as industrial wastewaters and waste. Mixed cultures can be used as inoculum that are more robust than pure cultures. However, H2 producers and consumers can coexist in such mixed cultures, so that they often have to be pre-treated to inhibit H2-consumers. Moreover, operational parameters such as pH and temperature play a key role in the selection of H2-producing bacterial community. Up to date, great efforts have been made to optimise the operational parameters, but only few controllers are available to maintain the DF process stable. In this context, an electro-fermentation (EF) process is proposed as a new tool to control bioprocesses through polarised electrodes. Depending on the applied potential, EF can occur at the anode or cathode, acting either as electron sink or additional source of energy, respectively. High current densities are not necessary to have a significant impact on cell metabolism since the electrical current is not the main electrons source, nor the product of interest. The mechanisms behind EF are still unknown, but microbial interactions between fermentative and electroactive bacteria may be the key factor of the process. The objective of this thesis was: "Better understanding of the EF mechanisms through the characterization of microbial interspecies-interactions as well as interactions with the polarized electrode". Our results show that the presence of polarized electrodes led to the selection of H2-producing bacteria, and more particularly from Enterobacteriaceae and Clostridiaceae families. Such microbial selection was concomitant with a significant increase in H2 and butyrate production, at the expense of lactate production. However, when different inoculum were used, different behaviours were observed with an increase, a decreased or no effect on H2 production. This observation evidences that the inoculum microbial community composition, and more particularly the relative abundance of the Clostridiaceae family, can significantly affect the microbial community behaviour in EF, i.e. microbial community trajectories and the related metabolic patterns. Finally, the microbial interactions were further investigated with a mixed inoculum enriched in G. sulfurreducens, as well-known electroactive bacteria. Here, a substantial change in the metabolic pathways towards higher H2 and butyrate production was observed, at the expense of 2,3-butanediol production. This change was associated with an increase in relative abundance of the Clostridiaceae family at the end of fermentation, probably due to a cooperative growth that G. sulfurreducens occurring with the members of the Clostridiaceae family. Overall, although the mechanisms behind the microbial interactions are not yet well know, the EF process showed a great potential as a new type of control for mixed-culture bioprocesses with significant effects of the polarized electrodes on glucose fermentation.

Résumé

La fermentation sombre (DF) est un procédé biologique utilisé pour la production d'hydrogène (H2). Dans ce processus, une grande variété de substrats peut être utilisée, des substrats simples comme le glucose ou plus complexes comme les effluents industriels. De plus, des cultures pures et mixtes peuvent être utilisées comme inoculum, ces dernières étant très attrayantes car conduisent à des systèmes plus robustes. Toutefois, des bactéries productrices et consommatrices d'H2 coexistent dans ces systèmes, de sorte que l'inoculum mixte nécessite d'être pré-traité pour inhiber l'activité des micro-organismes consommateurs d'H2. Les paramètres opérationnels tels que le pH et la température jouent également un rôle clé dans la sélection de la communauté bactérienne productrice de H2. Jusqu'à présent, de grands efforts ont été faits pour optimiser les paramètres de prétraitement et opérationnels, mais seulement peu de leviers sont disponibles pour maintenir la stabilité des bioréacteurs (pH, température, TSH). Dans ce contexte, l'électrofermentation (EF) est proposée comme un nouvel outil de contrôle des bioprocédés par le biais d'électrodes polarisées. Selon le potentiel appliqué, l'EF peut se réaliser au niveau de l'anode ou de la cathode, agissant respectivement comme dissipateur d'électrons ou comme source d'énergie supplémentaire. Des densités de courant élevées ne sont pas nécessaires pour avoir un impact significatif sur le métabolisme cellulaire car le courant électrique n'est pas la principale source d'électrons, ni le produit d'intérêt. Les mécanismes d'action derrière l'EF restent encore inconnus, mais les interactions microbiennes entre les bactéries fermentaires et électroactives peuvent en être la clé. Ainsi, l'objectif de cette thèse est : "Meilleure compréhension des mécanismes EF par la caractérisation des interactions microbiennes inter-espèces ainsi que des interactions avec l'électrode polarisée". Nos principaux résultats montrent que des électrodes polarisées permettent de sélectionner les bactéries productrices de H2, en particulier des entérobactéries et des clostridies. Cette sélection a conduit à une augmentation significative de la production de H2 et de butyrate, au détriment de la production de lactate. Toutefois lorsque différents inocula sont utilisés, 3 comportements différents sont observés : une augmentation, une diminution ou aucun effet sur la production de H2, par rapport à une fermentation conventionnelle. Ceci montre que la composition de la communauté microbienne de l'inoculum, et en particulier l'abondance relative de la famille des Clostridiaceae, affecte significativement le comportement de l'EF, c'est-à-dire la communauté microbienne finale et les voies métaboliques. Enfin, afin d'étudier le processus d'interaction, un inoculum mixte enrichi en G. sulfurreducens (bactéries électroactives connues) a été étudié. Un changement dans les voies métaboliques vers une production plus élevée de H2 et de butyrate a alors été observé, au détriment de la production de 2,3-butanediol. Ce changement a été associé à une augmentation de l'abondance relative de la famille des Clostridiaceae à la fin de la fermentation, probablement en raison d'une croissance coopérative que G. sulfurreducens avec les membres de la famille des Clostridiaceae. Globalement, et même si les mécanismes d'interactions microbiennes restent non élucidés, le procédé EF a montré un certain potentiel en tant que nouveau moyen de contrôle de bioprocédés opérés en cultures mixtes.

Mots-clés : Électro-fermentation ; Fermentation sombre ; Interactions entre les communautés microbiennes ; Clostridia species.

Démarrage de l'électro-fermentation et détermination des paramètres d'EF

Comme l'EF est un concept récent, peu de travaux sont documentés et il n'y a pas assez de connaissances sur les conditions de fonctionnement optimales et les matériaux les plus appropriés pour réaliser une EF efficace. La littérature montre que le matériau de l'électrode et sa taille, ainsi que la tension appliquée sur l'électrode de travail, peuvent altérer la production de courant et générer différentes interactions avec les communautés microbiennes.

En outre, la configuration des réacteurs (c'est-à-dire les réacteurs à un ou deux compartiments) est importante lorsqu'on considère l'efficacité des systèmes électrochimiques.

Dans ce Chapitre, différentes expériences d'EF ont été réalisées sur glucose afin de déterminer les meilleurs paramètres opératoires et de sélectionner les matériaux adéquats.

Après avoir comparé différents matériaux comme électrodes de travail, des grilles en platine ont été sélectionnées sur la base des performances de production d'H2 pour réaliser les expériences suivantes d'EF. De plus, un changement significatif sur les profils métaboliques a été observé lorsqu'une électrode polarisée a été placée dans le milieu de fermentation. Dans ce cas, la production de H2 et de butyrate a augmenté alors que le lactate n'était pas favorisé par rapport au contrôle. L'analyse de la communauté microbienne a montré que les familles dominantes présentes à la fin de l'opération par lots ne pouvaient pas expliquer ces changements. Néanmoins, et malgré une faible abondance relative, la présence de membres de la famille des Aeromonadaceae a montré une corrélation positive et significative avec l'indice d'efficacité de EF (ƞEF). Ceci suggère l'importance des espèces sous-dominantes dans les interactions microbiennes ayant un impact subséquent sur les patterns métaboliques.

Par la suite, différentes tensions ont été appliquées sur l'électrode de travail, mais aucune différence n'a été observée entre les conditions, y compris le contrôle. Dans ce cas, une voltampérométrie cyclique (CV) initiale a été effectuée et on a émis l'hypothèse que la CV

Résumé étendu

x était peut-être la cause de ces performances similaires. En outre, des interférences électriques ont été observées entre le contrôle et les tests EF, en raison de la voltampérométrie cyclique initiale effectuée lors des tests de EF. Bien que le phénomène à l'origine de ce comportement soit inconnu et n'ait pas été étudié plus avant, les réacteurs témoins ont ensuite été placés dans un bain-marie distinct de celui des réacteurs d'électrofermentation et aucune interférence électrique n'a dans ce cas été observée.

Enfin, deux tailles d'électrodes de grilles en platine ont été testées dans des réacteurs à dual compartiment. Les grandes électrodes de 3,5 x 3,5 cm 2 ont été choisies car elles permettent un plus grand échange d'électrons avec le milieu de fermentation et un effet maximal sur la production de H2 a été observé.

Effet de l'électro-fermentation sur la sélection des bactéries productrices de H2

Les cultures mixtes ont été largement utilisées pour la production de H2 par fermentation sombre. Cependant, de nombreux micro-organismes différents peuvent se développer dans les milieux de fermentation et aucune pression de sélection directe ne peut être appliquée pour la sélection de bactéries portant des voies efficaces de production de H2, telles que Clostridium sp. Jusqu'à présent, beaucoup d'efforts ont été faits pour optimiser les paramètres d'exploitation. Cependant, seuls quelques contrôleurs sont disponibles pour maintenir des performances stables de fermentation sombre. Dans ce contexte, l'électro-fermentation a été proposée comme un nouveau type de bioprocédé contrôlé par des électrodes polarisées.

Ce chapitre met en évidence un effet clair des électrodes polarisées sur les voies métaboliques et la structure de la communauté microbienne lors de la fermentation sombre. Une forte corrélation a été observée entre les communautés microbiennes sélectionnées et les

Résumé étendu

xi métabolites produits, y compris H2. Deux comportements métaboliques différents pour la production de H2 ont été observés dans l'EF. Le premier a conduit à une production de H2 plus élevée par rapport au témoin avec une forte sélection de Clostridium sp. Le second comportement a conduit à une production de H2 plus faible avec la production d'éthanol et était fortement corrélé avec la sélection des genres Escherichia et Enterobacter. De tels mécanismes d'interaction entre les électrodes polarisées et la communauté microbienne restent cependant peu clairs mais un nouveau champ d'investigation dans la fermentation de cultures mixtes a été ouvert.

Les effets de l'électro-fermentation sont influencés par la composition microbienne initiale

Lors de la production de H2 par fermentation sombre, la source d'inoculum et leur composition microbienne sont cruciales pour définir les performances des réacteurs finaux.

Pour cela, de nombreux pré-traitements ont été employés pour obtenir un inoculum adéquat capable de produire des rendements élevés en H2 sans production de méthane, comme les chocs thermiques. De plus, certaines conditions opératoires peuvent influencer directement la sélection de la communauté microbienne, notamment le pH, la température, le temps de séjour hydraulique et le type de substrat. En général, ces pré-traitements et conditions opérationnelles sont principalement focalisés sur l'élimination de l'activité méthanogène et non sur la sélection des bactéries productrices de H2.

Selon les résultats observés au chapitre précédent, l'EF est également un moyen de sélectionner les bactéries productrices de H2. Par conséquent, la sélection microbienne peut d'abord dépendre de la structure initiale de la communauté microbienne. Comme l'EF est Résumé étendu xii potentiellement utilisable pour contrôler les bioprocédés, il serait intéressant d'évaluer l'effet des électrodes polarisées lorsque les communautés microbiennes changent au fil du temps.

De ce chapitre, il a été conclu que EF n'avait qu'un impact sur la sélection initiale de la communauté bactérienne en mode de fonctionnement continu de réacteur. Lorsque la communauté microbienne change en raison de la pression de sélection imposée par le temps de séjour hydraulique, l'effet des électrodes polarisées n'est pas observable. Cela nous permet d'émettre l'hypothèse que l'effet de l'EF dépend de la communauté microbienne et donc de l'inoculum initial.

Par la suite, il a été montré que la source d'inoculum avait en effet un impact significatif sur la communauté microbienne finale et la production de métabolites. Sur la base des résultats de production de H2, 3 groupes peuvent être constitués en fonction de l'effet observé lors de l'EF : effet positif, effet négatif et effet neutre. L'abondance relative des bactéries productrices de H2, en particulier de la famille des Clostridiaceae, dans l'inoculum initial semble être un paramètre clé déterminant l'effet de l'EF.

Investigation des mécanismes d'électro-fermentation par l'étude des interactions microbiennes

Comme indiqué dans les chapitres précédents, l'EF est un outil de contrôle prometteur pour les bioprocédés qui dépend de la composition et de la structure de la communauté bactérienne. Le mécanisme d'action étant derrière la sélection des bactéries productrices de

Conclusion

xxv

List of tables

List of figures

Introduction

Industrial Revolution was the most important process of economic, social and technological transformation over the human history. From that moment, a transition was initiated that would end centuries of manual labour and the use of animal traction, being replaced by machinery for the industrial manufacture and goods and transportation of passengers. During this period the wood was replaced by coal, as main energy source. Coal led the industrial growth until the mid-twentieth century, when oil and natural gas emerged as alternative energy sources (Fig. 1-1-A). These provoked new inventions, such as internal combustion engines, that propelled the cars and, later, the planes. The appearance of electricity was also decisive, since it constituted a way for storing and transporting energy in a refined and standardized way, greatly facilitating its consumption and the usages [START_REF] Devries | The industrial revolution and the industrious revolution[END_REF], [2]. Iran and the confrontation of this county with Iraq, delayed the recovery of supplies. This problem opened the debate on energy dependencies and consequently the security of fossil fuels supplies [START_REF] Devries | The industrial revolution and the industrious revolution[END_REF], [2]. Besides, the abusive use of fossil fuels has led to serious environmental problems including ecological damage, water and air pollution, alteration by greenhouse effect and public health problems. To count on clean energies from their production to their final use is urgent. Third, fossil fuel reserves are limited and are currently being faster consumed than they are produced. As an example, in one year the human being consumes what nature has taken one million years to produce [START_REF] Endesa Energia | TWENERGY[END_REF]- [START_REF] Sreedhar | A Bird's Eye view on process and engineering aspects of hydrogen storage[END_REF].

In this context, finding new sources of renewable energy is necessary for clean, unlimited production that is adapted to the natural resources of each country. Renewables energies include solar, wind, geothermal, hydraulic, nuclear, electric and biomass. Today renewable energy grows strongly mainly by the increasing of wind and solar power energy. Projected exponential growth predict to reach 20% of total energy consumption by 2040 (Fig. 1-1-B),

with China and India as main clean energy producers [START_REF] Devries | The industrial revolution and the industrious revolution[END_REF], [2].

Hydrogen (H2) is considered as the fuel of the future and can be considered renewable if it is produced from renewable sources. H2 can be used in internal combustion or jet engines, gas power turbines but also in fuel cells. The main advantage of H2, as a fuel, is attributed to its high net calorific value of 120 kJ.g -1 compared to methane (50 kJ.g -1 ), ethanol (26.8 kJ.g -1 )

and gasoline (46.7 kJ.g -1 ) [START_REF] Łukajtis | Hydrogen production from biomass using dark fermentation[END_REF]. Besides, it is an ecologically clean energy source because its combustion is CO2 free. However, an important limiting factor in the use of H2 as an energy source is its explosivity in a mixture with oxygen and its storage is more difficult compared other fuels [START_REF] Sreedhar | A Bird's Eye view on process and engineering aspects of hydrogen storage[END_REF], [START_REF] Grimes | Light, Water, Hydrogen[END_REF]. Although H2 is slowly beginning to be used as transportation fuel, its main applications include chemical, refinery and pharmaceutical industries. In addition, it is particularly used for ammonia and methanol synthesis and for hydrogenation of liquid oils [START_REF] Łukajtis | Hydrogen production from biomass using dark fermentation[END_REF], [START_REF] Grimes | Light, Water, Hydrogen[END_REF]. At present, about 96% of H2 produced come from fossil fuels mainly by steam reforming, a process very energy-intensive and polluting. H2 can also be produced through water electrolysis using electrical energy [START_REF] Łukajtis | Hydrogen production from biomass using dark fermentation[END_REF], [START_REF] Sinha | An evaluative report and challenges for fermentative biohydrogen production[END_REF].

To stand as an environmental-friendly and renewable alternative, H2 must be produced using sustainable processes such as biological methods. These methods are based on the biological capability of some microorganisms to produce H2 by degradation of the organic matter, thus making it possible to efficiently combine the organic waste treatment and the energy production. This is the case of dark fermentation (DF), a fermentation process in which microorganisms degrade complex organic matter to simpler molecules and simultaneously generate H2. The main co-products are acetate, butyrate, lactate and ethanol. All of them are valuable chemicals that are also used in the chemical industry. Therefore, DF appears as a promising technology that can be included in a concept of environmental biorefinery towards circular economy, where organic residues are not anymore considered as a waste but as a resource of multiple products [START_REF] Toledo-Alarcón | Basics of bio-hydrogen production by dark fermentation[END_REF].

Microbial communities involved in H2 production by dark fermentation can be easily found in Nature, mainly in anaerobic environments, such as in lakes, guts, sludge from wastewater treatment plant or manure digestate [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF]. Many of these communities have been extensively studied, revealing how different microbial populations can coexist under complex interactions and efficient cooperative relationships. These microbial interactions make mixed cultures more attractive than pure cultures for biotechnological purposes. Mixed culturebased bioprocesses are generally more robust, overcoming sudden environmental changes and carrying out more complex activities [START_REF] Hung | Roles of microorganisms other than Clostridium and Enterobacter in anaerobic fermentative biohydrogen production systems--a review[END_REF], [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF]. However, many different microorganisms can grow during dark fermentation including those than can consume H2.

Thus, inocula pre-treatment is generally required to prevent methanogenic activity during dark fermentation. Heat shock is the most applied pre-treatment, aiming to eliminate the nonspore-forming microorganisms (e.g. methanogenic archaea) and favour species from Clostridium genus, well known as the most efficient H2 producers [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Bundhoo | Inhibition of dark fermentative bio-hydrogen production : A review[END_REF]. To date, a lot of efforts have been made on optimizing the different operating parameters, including: carbon sources, macro-micro nutrients, temperature, pH, HRT, organic loading rates, H2 partial pressure [START_REF] Kumar | Enhancement of biofuel production via microbial augmentation : The case of dark fermentative hydrogen[END_REF]- [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. However, only few controllers (pH, OLR, HRT) are available to maintain stable the dark fermentation process, i.e. metabolic patterns and H2 performances [START_REF] Hoelzle | Regulation mechanisms in mixed and pure culture microbial fermentation[END_REF], [START_REF] Schievano | Electro-Fermentation -Merging Electrochemistry with Fermentation in Industrial Applications[END_REF].

Electro-fermentation has been proposed as a new type of bioprocess control in presence of polarized electrodes [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. Electro-fermentation can occur at the anode or cathode, acting either as electron sink (i.e. passing the electrons excess from fermentation medium towards electric circuit) or additional energy source (i.e. passing electrons towards fermentation medium from the circuit), respectively [START_REF] Schievano | Electro-Fermentation -Merging Electrochemistry with Fermentation in Industrial Applications[END_REF], [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. Electro-fermentation is a bioelectrochemical system, in which a high current density is not necessary to have a strong effect on cellular metabolism, and only a small amount of electrons involved has a significant impact on the metabolic patterns [START_REF] Hoelzle | Regulation mechanisms in mixed and pure culture microbial fermentation[END_REF]- [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF]. Indeed, electro-fermentation relies on the modification of cellular metabolism with a low amount of electrons. Thus, the main source of electrons to generate the expected product comes from the organic substrate, as found in conventional fermentation process [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. That differentiates electro-fermentation from microbial electrosynthesis where the main source of electrons is the electrode. As an illustration, electro-fermentation could be considered as a control tool of H2-producing dark fermentation process, while H2 is chemically produced at the cathode in microbial electrolysis cells [START_REF] Parkhey | Improvisations in structural features of microbial electrolytic cell and process parameters of electrohydrogenesis for efficient biohydrogen production: a review[END_REF].

In this context, the general objective of this thesis is to provide a "Better understanding of the electro-fermentation process in microbial communities fermenting glucose". To fulfil this general objective, four specific objectives were investigated and aimed to:

i. Determine the main parameters affecting the glucose electro-fermentation.

ii. Identify the influence of polarized electrodes on microbial community and metabolic patterns during glucose electro-fermentation.

iii. Evaluate the influence of inoculum source on glucose electro-fermentation performances.

iv. Characterize the microbial interactions between electroactive and fermentative bacteria.

This document includes six chapters, and is structured as follows:

Chapter 1 corresponds to the literature review including the metabolic pathways for H2 production by dark fermentation, its microbiology, and the main operational parameters that can affect it. Basis of electro-fermentation are presented as well as the hypothetical mechanisms of EF action and the possible interactions existing between electrodes and fermentative bacteria.

Chapter 2 describes the materials and methods used in this thesis. That includes biochemical analysis, molecular biology techniques and statistical data analytical tools. In addition, the experimental methodology used for each test is presented.

Chapter 3 aims to determine the main parameters affecting the glucose EF. While, the specific objectives are as follows: (i) determine how the electrode material can affect the H2 production during EF; (ii) study different potential applied on the working electrode using a singlechamber reactor; (iii) determine how the electrode size can affect the H2 production during EF.

Chapter 4 aims to identify the influence of polarized electrodes on microbial community and metabolic patterns during glucose EF through different applied potential.

Chapter 5 aims to evaluate the influence of inoculum source on glucose EF performances.

While, the specific objectives are as follows: (i) study the effect of EF on continuous H2 production in chemostat; (ii) study the influence of the initial inoculum on EF in batch mode.

Chapter 6 aims to characterize the microbial interactions between electroactive and fermentative bacteria. While, the specific objectives are as follows: (i) study the changes in metabolic pathways during glucose dark fermentation when a mixed culture is enriched in G.

sulfurreducens; (ii) study the influence on metabolic pattern during glucose EF when an electrode is precolonized with G. sulfurreducens.

Finally, a section of general conclusion from this thesis and prospects are proposed for future research to be carried out beyond this thesis.

CHAPTER 1

Literature review

Context

Nowadays, fossil fuels are extensively used in transport, agriculture, domestic and industrial sectors to generate power. By consequence, the interests in finding alternative energy source have gained more and more followers around the word over the past decades. That aims to decrease the energy dependence and diversify the energy resources by specially focussing on clean, renewable and environment-friendly energies. In this context, hydrogen (H2) is considered as one of the most interesting future fuels because H2 has numerous advantages compared to current fossil fuel-based energy sources. H2 has the main advantage of being cleanly used in both combustion motors and electrical vehicles using fuels cell, reaching an efficiency 30% higher with this last one [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]- [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF]. Additionally, H2 has the highest specific energy (141.9 J.kg -1 ) among known fuels, e.g. methane (55.7 J.kg -1 ), natural gas (50.0 J.kg -1 ), biodiesel (37.0 J.kg -1 ) and ethanol (29.9 J.kg -1 ) [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. Despite these advantages, H2 is not yet commercialized as a fuel mainly due to high production cost, the important technical requirements for storage and distribution methods. However, it is widely used as a reactant for fertilizers production, diesel refining and ammonium synthesis. Only about 4% of all H2 in the world (about 0.1 GT per year [START_REF] Nikolaidis | A comparative overview of hydrogen production processes[END_REF]) is produced by water electrolysis, while about 96% by steam reformer, thermochemical process that use fossil sources [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Das | Hydrogen production by biological processes: a survey of literature[END_REF]. These techniques consume a lot of energy (about of 63.3 kJ.molH2 -1 [START_REF] Nikolaidis | A comparative overview of hydrogen production processes[END_REF]) and has a high environmental impact (10kg of CO2 by kg of H2 are released [START_REF] Muradov | Low to near-zero CO2production of hydrogen from fossil fuels: Status and perspectives[END_REF]). Thus, a massive production of H2 for transportation purposes would not be sustainable with that way.

Alternatively, some promising methods for H2 production are emerging and more particularly by using autotrophic or heterotrophic microorganisms through photobiological and dark fermentation processes. In autotrophic conversions (i.e. direct or indirect biophotolysis), solar energy is converted into H2 via photosynthetic reactions mediated by photosynthetic CHAPTER 1: Literature review microorganisms such as microalgae or photosynthetic bacteria. Under heterotrophic conversions, photo-fermentation carried out by photosynthetic bacteria and dark fermentation carried out by anaerobic bacteria [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Azwar | Development of biohydrogen production by photobiological, fermentation and electrochemical processes: A review[END_REF]. Dark fermentation is the most studied and promising technology for H2 production at larger scale with regards to its high production rates and its capacity for treating complex organic waste [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Azwar | Development of biohydrogen production by photobiological, fermentation and electrochemical processes: A review[END_REF].

Hydrogen production by dark fermentation

Dark Fermentation (DF) is a biological process that is commonly used to produce H2. DF does not require solar energy to occur and hence the configuration of the bioreactor is simpler and cheaper than photo-biological processes. Most importantly, this technology has attracted attention because it can use a wide range of substrates, particularly organically rich residues.

This technology is particularly suitable to be integrated into wastewater or waste treatment systems to produce H2 [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF].

However, the development of dark fermentation processes at industrial scale is still limited since lower H2 yields have been reported when compared to the theoretical maximum. Thus, different ways to increase H2 yields have been tested including the optimization of process design and operation parameters of dark fermentation reactors. Pre-treatments and inoculum enrichment methods can also increase the H2 yields. Recently, to overcome the issue of low H2 yields, several solutions have been proposed by coupling the dark fermentation process with photofermentation or bioelectrochemical systems, making thus the global energetic balance both positive and competitive [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF].

H2 producing enzymes

Molecular H2 is produced when the cells must release their excess of electrons through H2producing enzymes. These enzymes under anaerobic conditions catalyse the simple redox reaction: 2H + + 2e ¯ ↔ H2 [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF]. In order to perform this reaction, most of these enzymes have complex metalloclusters as active sites and require special maturation proteins [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF]. The three main H2-producing enzymes used by most microorganism are nitrogenases, [NiFe]hydrogenases and [FeFe]-hydrogenases [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF].

Nitrogenases catalyse the nitrogen fixation reaction to ammonium, which requires the protons reduction to H2. The nitrogenase is a protein complex composed for two subunits encoded by three structural nif genes. The first subunit is MoFe-protein, encoded by nifD and nifK, and the second subunit is Fe-protein, encoded by nifH. Nitrogenase catalysis reaction requires adenosine triphosphate (ATP) and proceeds at a slow turnover rate of about 6.4 s -1 [28]- [START_REF] Hallenbeck | Biological hydrogen production; Fundamentals and limiting processes[END_REF].

[NiFe]-hydrogenases can work producing H2 but also as uptake hydrogenases, using the electrons from H2 to reduce intracellular NAD + . The catalytic core of the [NiFe]hydrogenases is composed of a heterodimeric protein. The large subunit contains the Ni-Fe active site and the small one contains several Fe-S clusters which serve as electron transfer points [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF], [START_REF] Hallenbeck | Biological hydrogen production; Fundamentals and limiting processes[END_REF], [START_REF] Vignais | Classification and phylogeny of hydrogenases[END_REF].

[NiFe]-hydrogenases work to turnover rate of 98 s -1 , about 15 times faster than nitrogenases for producing H2 and do not require ATP to function as nitrogenases [START_REF] Hallenbeck | Biological hydrogen production; Fundamentals and limiting processes[END_REF].

[FeFe]-hydrogenases enzyme is the most efficient hydrogenase and H2 producing enzyme [START_REF] Morra | Expression of different types of [FeFe]-hydrogenase genes in bacteria isolated from a population of a bio-hydrogen pilot-scale plant[END_REF], which can have an activity 1000 times higher than nitrogenases and about 10-100 times than [NiFe]-hydrogenases. Structurally this enzyme consists of a protein with an Fe-Fe catalytic core that can accept a large variety of electron donors and acceptors. Depending of the environment conditions this enzyme can either produce or consume H2 [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF], [START_REF] Vignais | Classification and phylogeny of hydrogenases[END_REF].

Metabolic pathways to H2 production

In dark fermentation process, a substrate rich in carbohydrates is anaerobically consumed by different fermentative microorganisms including strict and facultative anaerobes. Fig. 1-1 shows the main metabolic pathways observed during glucose fermentation when mixed microbial cultures are used. First, 1 mole of glucose is converted into 2 moles of pyruvate through the glycolytic pathway, producing 2 moles of ATP and 2 moles of reduced nicotinamide adenine dinucleotide (NADH). Pyruvate is further oxidized to acetyl-CoA, and different intermediates and by-products are produced depending on the microbial community composition and the environmental conditions [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. Strict anaerobic bacteria commonly use the pyruvate ferredoxin oxidoreductase pathway (Fig. 1-1, right side). In this pathway, the oxidation of pyruvate into acetyl-CoA requires the reduction of one ferredoxin (Fd) supported by a pyruvate-ferredoxin oxidoreductase (PFOR), reduced Fd (Fdred) is then oxidized by a hydrogenase that regenerates the Fdox and releases H2. Additional H2 can be produced from the NADH that is generated during glycolysis. The NADH is oxidized by Fdred and a NADH-

[FeFe] hydrogenase , but only at very low partial pressures of H2 (<60 Pa) (Fig. 1-3) [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF]. Finally, 2 or 4 mol of H2 per mole of glucose can be obtained, depending on the metabolic pathway, which in turn is directly related to the H2 partial pressure inside the reactor [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF].

In facultative anaerobes the pyruvate formate lyase (PFL) pathway is preferred (Fig. 1-1, left side). In this pathway, the pyruvate is oxidized into acetyl-CoA and formate. The acetyl-CoA is then broken down into acetate and ethanol, while formate is directly converted into H2 and CO2 by a formate hydrogen lyase (FHL) [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF]. With a maximum yield of 2 mol of H2 per mole of glucose [START_REF] Hallenbeck | Strategies for improving biological hydrogen production[END_REF]. (Adapted from [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Lee | Thermodynamic Evaluation on H2 Production in Glucose Fermentation[END_REF], [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF])

Theoretically, a maximum of 12 mol of H2 per mol of glucose can be produced. VFAs accumulation [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF].

In Nature, microorganisms seek to maximize their biomass production and not H2. In this context, there are many metabolic pathways that allow the cell to function in equilibrium including pathways that are not producing H2 and consume reducing equivalents (NADH), and others that directly consume its molecular form (H2). Consumption of NADH prevents Fdred and formate formation, which both lead to H2 production [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF]. Such NADH balance without H2 generation is observed in lactate, propionate, succinate, butyrate, ethanol and butanol pathways (Fig. 1-1).

Molecular H2 consumption is thermodynamically very favourable, and has been evidenced by homoacetogenic bacteria to produce acetate (Table 1-1, Eq.9), as well as metabolic pathways for propionate (Table 1-1, Eq.8) and caproate production (Table 1-1, Eq.10 & Eq.11) [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF].

Microbiology of mixed cultures

Dark fermentation can be carried out by pure or mixed cultures of microorganisms.

According studies using pure cultures important knowledge for H2 production could be provided [START_REF] Elsharnouby | A critical literature review on biohydrogen production by pure cultures[END_REF]. Although higher H2 yields have been reported with pure cultures, mixed cultures are preferred due to the wide variety of substrates that can be potentially used, cheaper systems and easier controls of the bioprocesses [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Mixed cultures are more flexible and resist to environmental stresses including limited availability of the substrates or changes in pH and temperature. Moreover, the diverse microflora present in the mixed culture might provide synergistic interactions that can improve H2 production such as consumption of O2 traces by facultative anaerobes that allows strict anaerobes to emerge safely [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Arimi | Strategies for improvement of biohydrogen production from organic-rich wastewater: A review[END_REF]. Mixed cultures capable of producing H2 are widely present in environment such as anaerobic and aerobic sludge, compost, soil, sediments, leachate and organic wastes etc. and microbial diversity differs with each inoculum source [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. In a H2

producing community coexist microorganisms with different functions, grouped as H2 producers, H2 consumers, as well auxiliary bacteria which are not able to produce H2. But all them are key supporting the microbial community activity according thermodynamic possibilities of the system.

H2 producing bacteria

H2 producing bacteria (HPB) are commonly classified as strict and facultative anaerobes.

Clostridia species and Enterobacter species are the most abundant in H2-producing reactors. This is why those species are the most studied reported as pure culture to inoculate or bioaugment reactors [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Elsharnouby | A critical literature review on biohydrogen production by pure cultures[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Clostridia species are spore-forming bacteria and have a great potential to produce H2 by dark fermentation. They are considered as the most efficient HPB since they are usually predominant in reactors with high H2 yields e.g., from 1.5 to 3.0 molH2.molglucose -1 [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. With strict anaerobes, the most common fermentative pathways correspond to two main routes: acidogenesis and solventogenesis. Acidogenesis refers to organic acid production such as acetate and butyrate, while solventogenesis corresponds to solvent production such as ethanol and butanol [START_REF] Bundhoo | Inhibition of dark fermentative bio-hydrogen production : A review[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF].

The most found strict anaerobes species include C. butyricum, C. pasteurianum, C. beijerinckii and C. acetobutylicum. These species exhibit different H2 production pathways depending mainly on the type of substrate, the operating conditions and the reactors configuration [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. For example, C. acetobutylicum can switch its metabolism from acidogenesis to solventogenesis under conditions of low growth rate, low pH and high concentrations of carbohydrates [START_REF] Baghchehsaraee | The effect of heat pretreatment temperature on fermentative hydrogen production using mixed cultures[END_REF]. However, under optimal conditions, this specie provided the highest H2 production rate from starch-containing waste in pure culture [START_REF] Argun | Microbial culture selection for bio-hydrogen production from waste ground wheat by dark fermentation[END_REF].

Besides, during glucose-fed CSTR, C. histolyticum was dominant during the periods of solventogenesis pathways at pH 4.0-4.5, with highest H2 yields, while C. lituseburense was dominant during periods of acidogenesis pathways at pH 6.0-6.5, with lower H2 yield [START_REF] Song | Effects of pH and ORP on microbial ecology and kinetics for hydrogen production in continuously dark fermentation[END_REF].

Others strict anaerobes species reported are Ethanoligenens harbinens and Acetanaerobacterium elongatum that produce ethanol and H2 simultaneously. These HPB have highly resistant against the bactericidal effect of ethanol during H2 production, probably due to their specific [FeFe] hydrogenase [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Ren | Effects of different pretreatment methods on fermentation types and dominant bacteria for hydrogen production[END_REF]- [START_REF] Zhao | Characterization and overexpression of a [FeFe]hydrogenase gene of a novel hydrogen-producing bacterium Ethanoligenens harbinense[END_REF].

Facultative HPB correspond mainly to members of the Enterobacteriaceae family, such as Enterobacter, Escherichia, Citrobacter, and Klebsiella species. The most important characteristic of this family is the high 'tolerance' of the cells to oxygen. This allows to protect the enzymes not oxygen-tolerant like hydrogenases, as for example, when a reactor is accidentally exposed to oxygen, the presence of facultative anaerobes favours the immediate oxygen consumption to rapidly recover the hydrogenase activity [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. The most studied model species include Enterobacter aerogenes, Enterobacter cloacae, Citrobacter amalonaticus, Escherichia coli and Klebsiella pneumoniae. Similarly to Clostridium species, members from this family could use different H2 production pathways, but commonly are linked with poor H2 production compared to strict anaerobes, because additionally H2 production from NADH is not possible (Section 1.3.2) [START_REF] Bundhoo | Inhibition of dark fermentative bio-hydrogen production : A review[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. For example, high H2 yields are usually reported for E. aerogenes compared with other species from

Enterobacteriaceae family [START_REF] Seol | Comparison of hydrogen-production capability of four different Enterobacteriaceae strains under growing and non-growing conditions[END_REF], [START_REF] Jayasinghearachchi | Fermentative hydrogen production by two novel strains of Enterobacter aerogenes HGN-2 and HT 34 isolated from sea buried crude oil pipelines[END_REF], while Klebsiella spp. is known to produce H2 and alcohols such as ethanol and 2.3-butanediol from a variety of substrates [START_REF] Niu | Characteristics of fermentative hydrogen production with Klebsiella pneumoniae ECU-15 isolated from anaerobic sewage sludge[END_REF].

Bacillales members are other facultative anaerobes found in H2-producing reactors, mainly when operated with complex substrates, maybe due to their capacity to excrete hydrolytic enzymes [START_REF] Kumar | Extending the limits of Bacillus for novel biotechnological applications[END_REF], [START_REF] Patel | Dark fermentative hydrogen production by defined mixed microbial cultures immobilized on ligno-cellulosic waste materials[END_REF]. Particularly, Bacillus megaterium withstand high salinity levels (up to 15%) making possible the H2 production from high salt-content wastewaters or polluted sea waters [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Liu | Hydrogen production of a salt tolerant strain Bacillus sp. B2 from marine intertidal sludge[END_REF]. Studies with this species have not been deepened, so the reasons for its salt tolerance are unknown.

H2 consuming bacteria

Probably, the most famous H2-consuming microorganism are methanogenic archaea (Table 1-1, Eq.12) and many efficient methods to eliminate or inhibit them have been developed.

However, other H2 consuming bacteria (HCB) can also be present in mixed cultures such as sulfate-reducing bacteria, lactic acid bacteria and homoacetogens.

Sulfate-reducing bacteria are lithotrophic and use H2 as electron donor to reduce sulfate to hydrogen sulfide (Table 1-1, Eq.13 & Eq.14) [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Thermodynamically, sulfate reduction is the most efficient H2-consuming reaction. Besides, is highly competitive for H2, even at very low sulfate concentration because they can grow through an interspecies H2 transfer by cooperating with methanogens and syntrophic bacteria [START_REF] Raskin | Competition and coexistence of sulfate-reducing and methanogenic populations in anaerobic biofilms[END_REF]. Some genera include Desulfovibrio, Desulfomicrobium, Desulfobulbus, Desulfobotulus and Desulfococcus [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. For example, a high abundance of sulfate-reducing bacteria has been reported in an anaerobic CSTR under sulfate-limiting condition [START_REF] Cheng | Influence of retention time on reactor performance and bacterial trophic populations in anaerobic digestion processes[END_REF]. This is likely because many of these species can grow using a variety of fermentative metabolites as electron acceptor. However, generally short HRT as 2 h is not enough to inhibit the sulfate-reducing bacteria, but pH values lower than 6 significantly inhibit their activity [START_REF] Mizuno | The behavior of sulfate-reducing bacteria in acidogenic phase of anaerobic digestion[END_REF], [START_REF] Lin | Sulfate effect on fermentative hydrogen production using anaerobic mixed microflora[END_REF].

Several lactic acid bacteria such as Lactobacillus paracasei, Lactobacillus ferintoshensis and Enterococcus sp . have already been reported in H2-producing reactors, especially in reactors operated at low pH and at high organic loads [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Sikora | Lactic Acid Bacteria in Hydrogen-Producing Consortia: On Purpose or by Coincidence?[END_REF]. Some studies reported that the presence of acid lactic bacteria acted as an inhibitor of H2 producers due to (i) substrate competition and (ii) excretion of bacteriocins [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], [START_REF] Sikora | Lactic Acid Bacteria in Hydrogen-Producing Consortia: On Purpose or by Coincidence?[END_REF]. This toxin inhibit the growth of other bacteria and more particularly clostridial species [START_REF] Noike | Inhibition of hydrogen fermentation of organic wastes by lactic acid bacteria[END_REF]. Contradictorily, many reports have suggested that these lactic acid bacteria could contribute to H2 production. Indeed, lactate is a rapid way for the cells to release the excess of electrons, but in mixed cultures lactate could be consumed by some Clostridia spp. such as C. diolis to produce butyrate, CO2 and H2 [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF].

Another type of H2 consumers are fermentative homoacetogens that are strict anaerobes using H2 as electron donor to autotrophically reduce CO2 into acetate, through the acetyl-CoA pathway (Table 1-1, Eq.9). Because some homoacetogens are spore-forming, they difficult to remove them from the anaerobic reactors because they are resistant to pre-treatment. Besides, they are facultatively hydrogenotrophic, i.e. can grow autotrophically on H2/CO2 or heterotrophically on organic compounds such as sugars. Their presence results in lower H2

production because can consume about 11% and 43% of H2 produced accumulating the acetate [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Homoacetogenic microorganisms include several clostridial species that exhibit a reverse metabolism of either production or uptake of H2 through bidirectional hydrogenases [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Some bacteria belonging to Acetobacterium, Butyribacterium, Clostridium, Eubacterium, Peptostreptococcus and Sporomusa have been classified as homoacetogens [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF].

Contribution of auxiliary non H2-producing bacteria in microbial community behaviour

As reported in many cases, the presence of auxiliary bacteria which are not able (or less efficient) to produce H2 could be playing an important role supporting the microbial community with activities that include: (i) oxygen consumption often attributed to Bacillus and Klebsiella; (ii) pH regulation by lactic acid bacteria; (iii) hydrolysis of complex substrates attributed to lactic acid bacteria, Bacillus sp. and Pseudomonas sp. and Ruminococcus; (iv) formation of cellular aggregates attributed to lactic acid bacteria, Bacillus racemilacticus, Paenibacillus polymyxa and Prevotella sp. [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Rafrafi | Sub-dominant bacteria as keystone species in microbial communities producing bio-hydrogen[END_REF].

Main operating conditions for H2 production 1.3.4.1 Mixed cultures: inoculum pre-treatments

Mixed cultures are composed of not only HPB, but also HCB that redirect the electron fluxes towards methane production or VFA (lactic, acetic, butyric acid etc.) accumulation , thus decreasing the total amount of accumulated H2 [START_REF] Bundhoo | Inhibition of dark fermentative bio-hydrogen production : A review[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Therefore, it is essential to initially eliminate/inhibit the activity of HCB and enrich the inoculum in native HPB by applying physical or chemical pre-treatment methods [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. Compared to untreated mixed cultures (<1.0 molH2.molglucose -1 ), generally successful improvement of the H2 yields has been reported when pre-treated mixed cultures are used. This effect was confirmed by the level of hydrogenase activity in the pre-treated sludge that was three fold higher when compared to untreated sludge [START_REF] De Sá | Hydrogenase activity monitoring in the fermentative hydrogen production using heat pretreated sludge: A useful approach to evaluate bacterial communities performance[END_REF]. Fig. 1-2 summarizes the main pre-treatment methods reported in the literature, as discussed here below. Besides Table 1-2 shows the H2 yields obtained with different pre-treatments when glucose was used as substrate [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF].

i. Heat pre-treatment

Heat pre-treatment is a physical treatment, considered as the most effective one. For that reason, it is the most reported inoculum treatment in literature. Heat shock pre-treatment aims to eliminate non-spore forming microorganisms such as methanogens. This is considered as a simple and efficient method to eliminate HCB with a high potential for industrialization.

However, some non-spore forming HPB could also be eliminated such as Enterobacter spp.

and Bacillus spp., Both are well-known HPB and particularly Bacillus spp could participate to the efficient degradation of complex substrates [START_REF] Baghchehsaraee | The effect of heat pretreatment temperature on fermentative hydrogen production using mixed cultures[END_REF], [START_REF] Bundhoo | Effects of pre-treatment technologies on dark fermentative biohydrogen production: A review[END_REF]- [START_REF] Chang | Evaluation of different pretreatment methods for preparing hydrogen-producing seed inocula from waste activated sludge[END_REF].

Temperatures and exposition duration time are ranging from 65 °C -100 °C and 10 min -10 h, respectively [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Intuitively, it is believed that higher temperatures require shorter exposure times, however the best combination to improve H2 yields is strongly dependent on the inoculum source, i.e. native microbial diversity. Nonetheless, 2.49 molH2mol -1 hexose is the highest H2 yield obtained using heat pre-treatment, in this case from anaerobic sludge treated at 100 °C for 60 min, using sucrose as substrate [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] De Sá | Pentoses, hexoses and glycerin as substrates for biohydrogen production: An approach for Brazilian biofuel integration[END_REF]- [START_REF] O-Thong | Evaluation of methods for preparing hydrogen-producing seed inocula under thermophilic condition by process performance and microbial community analysis[END_REF]. (Adapted from [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF])

ii. Acid-base pre-treatment Acid-base inoculum pre-treatment is a chemical method causing changes in the extracellular pH that affect the net charge on the cell surface and consequently the enzyme activity and microbial nutrient absorption [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. In principle, extreme pH induces spores formation, or lysis of not sporulating cells [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. This method has been used to reduce the methanogenic activity in mixed cultures. The pH for acid pre-treatment commonly ranges from 2 to 4 with an exposition time from 30 min to 24h. The most common combination seems to be pH=4 for 24h. While the pH of basic pre-treatment is usually ranging from 10 to 12 with an exposition B time from 30 min to 24h, the most frequently found combination seems to be pH=10 for 24h [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Although a higher H2 yield has been reported using a basic pretreatment (3.1 molH2mol -1 hexose), from sucrose as substrate [START_REF] Zhu | Evaluation of alternative methods of preparing hydrogen producing seeds from digested wastewater sludge[END_REF], no conclusive evidence to define on whether acidic or basic pre-treatment is better to enrich HPB and increase H2 production.

Because different studies comparing both treatment differ when concluding which was the best [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Chang | Evaluation of different pretreatment methods for preparing hydrogen-producing seed inocula from waste activated sludge[END_REF], [START_REF] Zhu | Evaluation of alternative methods of preparing hydrogen producing seeds from digested wastewater sludge[END_REF].

iii. Chemical inhibitors Some chemical inhibitors can selectively inhibit methanogenic activity without impacting H2 production, including chloroform, bromoethanesulphonic acid (BESA), iodopropane and unsaturated fatty acids. Particularly, Chloroform and BESA can inhibit the Methyl-coenzyme M reductase (MCR), the key enzyme responsible for methane production. However, these inhibitors are often also lethal to the HPB and highly toxic and harmful to humans and the environment, which restricts their wide application [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Zhu | Evaluation of alternative methods of preparing hydrogen producing seeds from digested wastewater sludge[END_REF].

iv. Aeration

Aeration pre-treatment applies an oxidative stress aiming to deactivate strict anaerobic HCB such as methanogens, but also to enrich the inoculum in facultative HPB such as Enterobacter sp. However, the oxidative stress also severely damages strict anaerobic HPB like Clostridium spp. For that reason, aeration pre-treatment has been shown as inefficient by lowering the H2 yields, compared with heat pre-treatment [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Zhu | Evaluation of alternative methods of preparing hydrogen producing seeds from digested wastewater sludge[END_REF]. Commonly, aeration conditions correspond to continuous aeration during dark fermentation or intermittent aeration and aeration times before to inoculate the reactor from 30 min to 4 d [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Ren | Effects of different pretreatment methods on fermentation types and dominant bacteria for hydrogen production[END_REF], [START_REF] Zhu | Evaluation of alternative methods of preparing hydrogen producing seeds from digested wastewater sludge[END_REF].

v. Other pre-treatments

Other physical and chemical pretreatments have been reported to a lower extent in the literature as shown in Fig. 1-2B.

Ultrasonication is a physical-chemical pre-treatment that uses sound waves to eliminate HCB and keeping the spore-former HPB. Micro bubbles are formed and collapse, generating shear forces, high localized temperature (5000 K) and pressure (180 MPa), and highly active radicals [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Although same damages can be caused on HPB, they can be prevented by controlling the pre-treatment duration and energy input [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Elbeshbishy | Enhancement of biohydrogen producing using ultrasonication[END_REF], [START_REF] Guo | Impacts of sterilization, microwave and ultrasonication pretreatment on hydrogen producing using waste sludge[END_REF], [START_REF] Kim | Effects of Various Pretreatments for Enhanced Anaerobic Digestion with Waste Activated Sludge[END_REF].

Freezing and thawing implies the use of extreme and abrupt changes of temperature for several cycles leading to ice crystal formation inside the cells and thus making irreversible damages in the microbial structures. In general, this method causes cell lysis of HCB but also HPB, and very low H2 yield were reported compared to heat pre-treatment (0.04 -0.17 molH2.mol -1 hexose). Thus it can be considered as inefficient [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Liu | Enrichment of the hydrogen-producing microbial community from marine intertidal sludge by different pretreatment methods[END_REF], [START_REF] Mohammadi | Effects of different pretreatment methods on anaerobic mixed microflora for hydrogen production and COD reduction from palm oil mill effluent[END_REF].

Ultraviolet radiation (UV) can denature the intracellular DNA, leading to the death or cell inactivation. The recommended pre-treatment condition is 15 min of UV irradiation. Such conditions successfully eliminate methanogens increasing the H2 yield of 1.39-fold respect to untreated mixed cultures. However, HCB inside dark coloured sludge particles are protected from UV irradiation and only bacteria present on the surface are eliminated [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Wang | Effects of sludge pretreatments and organic acids on hydrogen production by anaerobic fermentation[END_REF], [START_REF] Wang | Effects of pretreatment of natural bacterial source and raw material on fermentative biohydrogen production[END_REF].

Electric current was also found to have the capacity of destructing cell membranes while preserving the microorganisms capable of forming spores. However, the mechanism of action of the electric current is not totally clear. Different values of electrical field have been applied within a range of 3.0 -12 V, but using 10V the highest H2 yield was observed (1.43 molH2mol -1 hexose) [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Jeong | Application of an electric field for pretreatment of a seeding source for dark fermentative hydrogen production[END_REF], [START_REF] Park | Inactivation of bacteria in seawater by low-amperage electric current[END_REF].

Microwaves are another kind of electromagnetic radiation with frequencies ranging from 0.3

GHz to 300 GHz and wave lengths in air from 1 m to 0.0001 m. In general, the effectiveness of microwaves in destructing microorganisms depends on the time of exposure and the power of the electromagnetic field used. The specific frequency of the microwares for enriching HPB was found at 2450 MHz Although the effectiveness of pre-treatment depends on the inoculum microbial community, Clostridia spp. is generally the most favoured [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Kuglarz | Microwave and thermal pretreatment as methods for increasing the biogas potential of secondary sludge from municipal wastewater treatment plants[END_REF], [START_REF] Singhal | Effect of microwave pretreatment of mixed culture on biohydrogen production from waste of sweet produced from Benincasa hispida[END_REF].

Ionizing radiation comprises gamma rays (0.5 -10.0 KGy), X-rays and the higher UV part of the electromagnetic spectrum. When aqueous solutions are irradiated by such ionizing radiations, highly reactive chemical species are formed that can react with other substances existing in the solutions. Due to the low water content of the spores, less hydroxyl radicals are generated inside microbes in the form of spores during ionizing irradiation process. Thus, spore-forming bacteria are expected to be more likely to survive under such ionizing radiation, increasing H2 production [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Yin | Enriching hydrogen-producing bacteria from digested sludge by different pretreatment methods[END_REF], [START_REF] Yin | Optimization of Hydrogen Production by Response Surface Methodology Using γ-Irradiated Sludge as Inoculum[END_REF].

In addition, pre-treatments are sometimes combined to ensure the efficient HCB elimination, while seeking to enrich the inoculum with HPB. In this context has been reported a high H2 yields of 2.45 molH2.molglucose -1 by combining heat (100°C, 30 min) and base (pH 10, 24h) pre-treatment [START_REF] Liu | Enhanced hydrogen production in a UASB reactor by retaining microbial consortium onto carbon nanotubes (CNTs)[END_REF].

Simple and complex substrate

For proper bacterial growth, appropriate sources of carbon, nitrogen, phosphorus and other micronutrients must be available in the fermentation medium and in correct proportions.

Generally, carbon source is considered as the most important element and is commonly referred as THE substrate. Glucose has been the most used substrate and is considered as model because is consumed by most of the microorganisms. In the literature, substrates are distinguished as simple or complex. Monomeric or pure polymeric sugars such as sucrose, lactose, fructose, xylose, starch, cellulose and pure glycerol are considered as simple substrates, while industrial wastewaters or waste including rice winery, food waste, dairy wastewaters, beer lees and crude glycerol are considered as complex substrates [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF].

Organic substrates found in wastewaters are moreover cheap and easily available. However, industrial wastewaters may not be sufficiently nutritious to support H2 production and it is not practical to continuously supply the fermentation process with costly supplements such as peptone or yeast extract. One of the solutions is to improve the nutrient content using a combination of different types of wastewaters, for instance by mixing different waste streams rich in carbohydrate or nitrogen [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. For example, when Wang et al. (2011) used as substrate a combination of 75% food wastewater (carbohydrate rich) and 25% sewage sludge (nitrogen rich), a higher H2 yield was obtained, compared with the yield observed with each substrate alone [START_REF] Wang | Biohydrogen and methane production by codigestion of cassava stillage and excess sludge under thermophilic condition[END_REF].

Besides, a balanced concentration of substrate plays an important role in H2 production.

Increasing the substrate concentration may increase H2 production but it must be appropriate as it has also been evidenced that beyond certain substrates concentrations the H2 yields decreaseq [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Lo | Dark H2 fermentation from sucrose and xylose using H2-producing indigenous bacteria: Feasibility and kinetic studies[END_REF], [START_REF] Van Ginkel | Biohydrogen Production as a Function of pH and Substrate Concentration[END_REF]. Furthermore, excess substrate decreases H2 production by shifting fermentation pathways to produce alcohol or lactic acid [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. For example, Levin et al.

(2006) reported during Clostridium thermocellum dark fermentation, that lactate and H2 production were increased and decreased, respectively, when using high levels of cellulosic biomass as substrate (4.5 g.l -1 ) [START_REF] Levin | Hydrogen production by Clostridium thermocellum 27405 from cellulosic biomass substrates[END_REF].

Macro and micro-nutrients requirements

As already mentioned in the previous section, the carbon source in not the only requirement to support proper bacterial growth. Microorganisms need other elements for their growth, such as nitrogen, phosphorus and other important micronutrients. That is why the nutritional requirements and the culture medium composition are important variables that directly affect the microbial metabolism in dark fermentation and therefore are critical for H2 production [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF], [START_REF] Lin | A nutrient formulation for fermentative hydrogen production using anaerobic sewage sludge microflora[END_REF], [START_REF] Lin | Carbon/nitrogen-ratio effect on fermentative hydrogen production by mixed microflora[END_REF].

Nitrogen is an important component of the cells to synthetize proteins, nucleic acids and enzymes such as hydrogenases. However, there are still disagreements with respect to the optimum concentration. But a nitrogen excess could be detrimental to the intracellular pH and can eventually inhibit the bacterial growth and enzymatic activity [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF]. High nitrogen concentrations can induce ammonification, which is not favorable for H2 production [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF]. Phosphate is also required to synthetize ATP and other nucleic acids, as well as to provide a buffering capacity [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF]. But high phosphorus concentration can also stimulate excessive VFAs production, which leads to significant decrease in H2 production [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF]. On top of the optimal concentrations to be adjusted prior to fermentation, appropriate C/N and C/P ratios are fundamental to balance the carbon fluxes between biomass production and H2producing pathways. Among the studies that dealt with this aspect, there is no common agreement on the optimal values and the ratios to be respected, with a wide range from 47 to 200 and 559 to 1000 for C/N and C/P, respectively [START_REF] Lin | Carbon/nitrogen-ratio effect on fermentative hydrogen production by mixed microflora[END_REF]- [START_REF] O-Thong | Optimization of simultaneous thermophilic fermentative hydrogen production and COD reduction from palm oil mill effluent by Thermoanaerobacterium-rich sludge[END_REF]. Such substantial differences in optimal values of these ratios are probably due to different carbon source, inoculum source and operational conditions were used.

In addition, metal ions are necessary to activate enzymes and co-enzymes related to microbial metabolism and consequently are essential for cell growth and any fermentation processes [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF]. The most studied metal in H2 production is iron (Fe 2+ ) since the most efficient hydrogenases have bimetallic Fe-Fe active sites surrounded by Fe-S protein clusters [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Tsaousis | A Nonmitochondrial hydrogen production in naegleria gruberi[END_REF]. For example, has been reported an increase in the H2 production by 1.5-fold when Fe concentration in the fermentation medium increased from 15 to 55 mg.l -1 [START_REF] Kim | Sewage sludge addition to food waste synergistically enhances hydrogen fermentation performance[END_REF].

Light metal ions have also been studied including magnesium (Mg 2+ ), sodium (Na + ) and calcium (Ca 2+ ). Magnesium ions are present in cellular walls and membranes and are required for building cellular proteins and they are also serving as activators and cofactors of many enzymes such as kinases and synthetases, mainly useful during glycolysis [START_REF] Sinha | An evaluative report and challenges for fermentative biohydrogen production[END_REF]. For example, [START_REF] Alshiyab | Effect of salts addition on hydrogen production by C. acetobutylicum[END_REF] reported an increase in the H2 yields when was added MgSO4.7H2O in range of 50-500 mg.l -1 [START_REF] Alshiyab | Effect of salts addition on hydrogen production by C. acetobutylicum[END_REF].

Sodium ions have been reported as a micronutrient for bacterial growth [START_REF] Hao | Effect of sodium ion concentration on hydrogen production from sucrose by anaerobic hydrogen-producing granular sludge[END_REF]. For example, a maximum H2 production was obtained with 1 gNa + .l -1 , while using 2 gNa + .l -1 caused a decrease due to Na + inhibition. Probably, more ATP was used to maintain the cellular viability than for growth under high Na + concentration conditions [START_REF] Lee | Sodium (Na+) concentration effects on metabolic pathway and estimation of ATP use in dark fermentation hydrogen production through stoichiometric analysis[END_REF].

Calcium (Ca 2+ ) has been reported to enhance bacterial growth and mechanical strength of granular sludge while also promoting cell retention [START_REF] Alshiyab | Effect of salts addition on hydrogen production by C. acetobutylicum[END_REF], [START_REF] Lee | Sodium (Na+) concentration effects on metabolic pathway and estimation of ATP use in dark fermentation hydrogen production through stoichiometric analysis[END_REF], [START_REF] Yuan | Increased performance of continuous stirred tank reactor with calcium supplementation[END_REF]. Besides, some studies report increase of H2 production associated to addition of Ca 2+ [START_REF] Kim | Sewage sludge addition to food waste synergistically enhances hydrogen fermentation performance[END_REF], [START_REF] Lee | Sodium (Na+) concentration effects on metabolic pathway and estimation of ATP use in dark fermentation hydrogen production through stoichiometric analysis[END_REF], [START_REF] Wu | Effect of calcium ions on biohydrogen production performance in a fluidized bed bioreactor with activated carbon-immobilized cells[END_REF].

pH and Temperature

The most crucial operational parameters that affect the H2 production pathways are pH and the temperature. pH is an important parameter during de H2 production impacting: (i) the enzymatic activities and more particularly the hydrogenases that present an optimal pH between 6.0 and 6.5 [START_REF] Mnatsakanyan | Hydrogenase 3 but not hydrogenase 4 is major in hydrogen gas production by Escherichia coli formate Hydrogenlyase at acidic pH and in tyhe presence of external formate Acidic pH and in the Presence of External Formate[END_REF], [START_REF] Tsygankov | Measuring the pH dependence of hydrogenase activities[END_REF]; (ii) the microbial community selection through e.g. methanogen inhibition at pH lower than 6; (iii) the metabolic pathways and consequently the H2 yields. In the last case, acetate and butyrate pathways are mostly favoured at neutral (pH 6.5-7.0) and acid (pH 5.0-5.5) pH, respectively; (iv) the hydrolysis of complex substrates [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Azwar | Development of biohydrogen production by photobiological, fermentation and electrochemical processes: A review[END_REF]. In general, the operational pH is set within a range that supports the growth of many HPB , i.e. between 4.5 and 8.0 [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF], [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Azwar | Development of biohydrogen production by photobiological, fermentation and electrochemical processes: A review[END_REF]. An optimum pH helps to maintain the surface change on the cell membrane which facilitates nutrient uptake and sustains bacterial growth [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. Indeed, for simple substrates such as glucose, the highest H2 yields were reported at pH of 6.0 (1.83 molH2.molglucose -1 ) in batch experiments [START_REF] Li | Effects of pH value and substrate concentration on hydrogen production from the anaerobic fermentation of glucose[END_REF]. When fermenting a complex substrate (as food waste), maximum H2 yields were reported at pH 8.0 (1.92 molH2.molhexose -1 ) [START_REF] Gioannis | Biohydrogen production from dark fermentation of cheese whey: Influence of pH[END_REF]. However, there is an agreement of the negative effect of pH values below 4.5 -5.5, generally caused by the accumulation of VFAs, which can reduce H2 production due to shifts in the metabolite production pathways towards solventogenesis (acetone, butanol, ethanol) [START_REF] Xie | Control strategies for hydrogen production through co-culture of Ethanoligenens harbinense B49 and immobilized Rhodopseudomonas faecalis RLD-53[END_REF].

Temperature is also a key parameter determining the physiological activities of the microbial community and similarly to pH, temperature can affect substrate hydrolysis, in particular for lignocellulosic compounds. Operational temperatures are classified as ambient (15 -27 ºC ), mesophilic (30 -45 ºC), thermophilic (50 -60 ºC) or extreme thermophilic (>60 ºC) [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], [START_REF] Chandrasekhar | Biohydrogen Production : Strategies to Improve Process Efficiency through Microbial Routes[END_REF], [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. Varying the temperature affects greatly the Microbial community structure. [START_REF] Lazaro | Sugarcane vinasse as substrate for fermentative hydrogen production: The effects of temperature and substrate concentration[END_REF] explained that significant differences between the microbial communities at 37 °C and 55 °C exist. A shift from Clostridium at mesophilic conditions to Thermoanaerobacterium when thermophilic conditions were applied was shown. However, the H2 yield was not significantly impacted by the temperature regime (2.31 and 2.23 mmolH2.gCODinfluent -1 at mesophilic and thermophilic, respectively [START_REF] Lazaro | Sugarcane vinasse as substrate for fermentative hydrogen production: The effects of temperature and substrate concentration[END_REF]. As reported by [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], temperature also affects the metabolic pathways, thus modifying the by-products produced during DF [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. Consistently, the study of Valdez-Vasquez et al.

(2005) showed a significant difference in the average distribution of metabolites between thermophilic and mesophilic conditions. The predominant metabolite produced under mesophilic temperatures was butyrate, while in thermophilic conditions acetate was the main metabolite [START_REF] Valdez-Vazquez | Semi-continuous solid substrate anaerobic reactors for H2 production from organic waste: Mesophilic versus thermophilic regime[END_REF].

H2 partial pressure

The main objective for optimizing H2 production is to maximize the H2 yields with subsequent accumulation in reactors headspace. However, such H2 over-accumulation can lead to a strong inhibition further resulting in lower H2 yields than expected [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF]. In general,

H2 production is thermodynamically limited by the enzymatic reaction of the [Fe Fe]

hydrogenases involved in the PFOR pathway (Fig. 1-1). When the H2 partial pressure is less than 0.3 atm (3×10 4 Pa), H2 could be produced via Fdred producing a maximum of 2 moles of H2 per mole of glucose with butyrate as final product (Fig. 123a). When the H2 partial pressure is < 60 Pa, additional H2 could be produced from NADH excess by NADH- [FeFe] hydrogenase to produce an additional 2 moles of H2 i.e. a maximum of 4 moles of H2 per mole of glucose, with acetate as final product (Fig. 123b) [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Angenent | Production of bioenergy and biochemicals from industrial and agricultural wastewater[END_REF]. Several strategies have been proposed to decrease the H2 partial pressure in dark fermentation including a continuous gas release, larger headspace volume in reactor, vacuum stripping or sparging with inert gas like N2 or CO2 [START_REF] Hussy | Continuous fermentative hydrogen production from sucrose and sugarbeet[END_REF]- [START_REF] Bastidas-Oyanedel | Gas controlled hydrogen fermentation[END_REF]. In general, all these strategies evidence an efficient increase in the H2 production.

Hydraulic retention time

The hydraulic retention time (HRT) is an important parameter also impacting H2 production in continuous systems. HRT in suspended-cell systems e.g. CSTR, is the inverse of the dilution rate (D, Eq. 1). When the system reaches the steady-state i.e. equilibrium, D is equal to the microbial growth rate (µ). Thus, manipulating D makes possible the selection of growing microorganisms that become rapidly dominant in the system. When using mixed cultures, two situations may occur in the system: (i) D > µmax, all the microorganisms under this condition are washed-out from the reactor; (ii) D ≤ µmax, all the microorganisms under this condition are kept in the reactor. To modify the D value, the input flow of the reactor can be changed since the reactor volume remains generally constant.

Eq. 1

𝐷[ℎ -1 ] = 𝐹𝑙𝑜𝑤 𝑖𝑛𝑝𝑢𝑡 [𝑙 • ℎ -1 ] 𝑉𝑜𝑙𝑢𝑚𝑒 𝑟𝑒𝑎𝑐𝑡𝑜𝑟 [𝑙]
Since methanogens (HRT ≥ 1 d) are growing more slowly than HPB, HRT values around 4 to 24h are usually preferred to favour H2 production. In general, this value depends on the type of substrate and which HPB type is desired in the reactor [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]. Typically, short HRTs (< 24h) and low pHs (pH 5.5 -6.0) are coupled to decrease the methanogenic activity and reach efficient H2 production [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF], [START_REF] Ramírez-Morales | Simultaneous production and separation of biohydrogen in mixed culture systems by continuous dark fermentation[END_REF], [START_REF] Si | The role of hydraulic retention time on controlling methanogenesis and homoacetogenesis in biohydrogen production using upflow anaerobic sludge blanket (UASB) reactor and packed bed reactor (PBR)[END_REF].

Oxidation-reduction potential and fermentation

The fermentation process is defined as a cascade of oxidation-reduction reactions occurring in equilibrium to provide enough energy to the cells for their growth and maintenance. Under fermentative conditions, the substrate is only partially oxidized and the energy yield is lower than in respiration, i.e. when using oxygen as final electron acceptor (Fig. 1234) [START_REF] Brock | Biology of microorganisms[END_REF].

The importance of the "redox" potential, also called Oxidation-Reduction Potential (ORP), on the microbial activity has been well addressed and anaerobes during any fermentation are particularly sensitive to its changes [START_REF] Hirano | Electrochemical control of redox potential affects methanogenesis of the hydrogenotrophic methanogen Methanothermobacter thermautotrophicus[END_REF], [START_REF] Bagramyan | Redox potential is a determinant in the Escherichia coli anaerobic fermentative growth and survival: effects of impermeable oxidant[END_REF]. ORP reflects the overall electrons transfer and redox balance involved in extracellular metabolism. Two compounds are required for an oxidation-reduction reaction to occur, during which the reducing compound donates electrons to an oxidizing compound. Each redox pair has its intrinsic ORP value. The higher is the affinity to the electrons, the higher the ORP of a redox pair would be [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF]. Table 1-3 shows the reduction potential of some redox pairs of microbiological importance [START_REF] Brock | Biology of microorganisms[END_REF]. The conjugated redox pairs and their homeostasis are fundamental in the intracellular metabolism, since many biological functions are sensitive to ORP changes including genetic expression, enzymatic synthesis and metabolic patterns [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF], [START_REF] Murray | Redox regulation in respiring Saccharomyces cerevisiae[END_REF]- [START_REF] Kültz | Molecular and Evolutionary Basis of the Cellular Stress Response[END_REF]. NAD + /NADH cofactor is the most important redox pairs of catabolism. NADH is formed from NAD + during the oxidation of molecules such as glucose. However, the cell seeks to regenerate the NAD + and release the electrons excess by transferring these electrons to intermediary metabolites such as ethanol, butyrate and H2 [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF], [START_REF] Kültz | Molecular and Evolutionary Basis of the Cellular Stress Response[END_REF]. Particularly, in clostridia, H2 is produced to regenerate the NADH through a ferredoxin oxidoreductase and a hydrogenase [START_REF] Girbal | Regulation of metabolic shifts in Clostridium acetobutylicum ATCC 824[END_REF], [START_REF] Jones | Acetone-Butanol Fermentation Revisited[END_REF]. The activity of these H2 evolving enzymes is regulated by the intracellular NADH/NAD + and acetyl-CoA/CoA ratios and all excess of reducing power is disposed as H2 [START_REF] Adams | Hydrogenase[END_REF]. Meanwhile, in facultative anaerobes, NADH is usually regenerated through the 2,3butanediol, ethanol and lactate pathways with no H2 generation [START_REF] Nakashimada | Hydrogen production of Enterobacter aerogenes altered by extracellular and intracellular redox states[END_REF]. Nonetheless, some studies operated with E. aerogenes reported that H2 production was highly dependent on the NADH/NAD + ratio, suggesting that NADH accumulation is a critical factor for H2 production [START_REF] Tanisho | Effect of CO2 removal on hydrogen production by fermentation[END_REF]. Different strategies have been tested and implemented to better control the cellular ORP including metabolic engineering, chemical addition, gas bubbling and supply of external energy by bioelectrochemical reactors. For instance, redox reactants such as potassium ferricyanide, methyl viologen and neutral red can act as electron transporters affecting the redox balance and thus the cellular metabolism [START_REF] Bagramyan | Redox potential is a determinant in the Escherichia coli anaerobic fermentative growth and survival: effects of impermeable oxidant[END_REF], [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF], [START_REF] Peguin | Modulation of metabolism of Clostridium acetobutylicum grown in chemostat culture in a three-electrode potentiostatic system with methyl viologen as electron carrier[END_REF]. Active redox gases such as oxygen, H2 and CO can also be bubbled into the fermentation medium to control the ORP.

Oxygen increases the ORP while H2 decreases it. Other inert gases such as nitrogen or helium can be bubbled, eliminating oxygen and H2 and changing indirectly the ORP of the medium [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF]. Finally, energy can also be supplied in the form of an electric current in bioelectrochemical reactors (BES). BES are equipped with electrodes to control the ORP during fermentation. The efficiency of these systems mainly depends on the interactions existing between the microorganisms and the surface of the working electrode [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF], [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF].

In the next section, more details about BES are given and more particularly about electrofermentation.

Electro-fermentation: how to drive fermentation using electrochemical systems?

As described in previous Section 1.3, many parameters have been used to control bioprocesses. However, only few controllers are available to maintain stable the metabolic patterns i.e. H2 and metabolite production. In this context, electro-fermentation (EF) has been proposed as a new type of bioprocess control in presence of polarized electrodes. EF aims to maximize the performances of production in a high valuable end-products through a better control of the metabolic patterns. Besides, depending on specific operational conditions could allow to decrease purification and separation cost, face to possible industrial applications.

Despite EF is a new technology and the action mechanisms are not totally understood, EF is a promising technology.

Basics of Electro-fermentation

EF is a BES that couples fermentation and electrochemical processes to better control the microbial metabolism through extracellular ORP regulation [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF]. Typically, a BES is composed of an anode, a cathode and sometimes a reference electrode. This last one has a stable and known equilibrium potential and is placed in the working electrode chamber (anode or cathode depending on working potential) to facilitate the control of the system.

Then, a potential is applied at the working electrode by changing the potential on the counter electrode [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF]. Single or dual-chamber reactors can be used, although dual chamber BES requires the presence of a membrane to separate each chamber. Classically, an ion exchange membrane is used, selective either for cations or anions (a. and b., Fig. 123456) [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF]. Fig. 123456shows a classical EF reactor and three possible types of interaction between the electrode and the fermentation medium to support this system.

Fig. 1-6: Process configurations of electro-fermentation system including possible interactions between electrode and fermentation medium

Three possible interaction between electrode and fermentation medium could be supporting this system: (1) a redox mediator that can be oxidized (Medox) or reduced (Medred) by an electrode and then used by fermentative bacteria (in light yellow); (2a) electroactive bacteria (in red) to perform a direct electron transfer to fermentative bacteria with nanowires or (2b) to catalyse the regeneration of a redox mediator then used by fermentative bacteria; [START_REF] Endesa Energia | TWENERGY[END_REF] electroactive bacteria that can also perform fermentation. The overall process can be voltage controlled to avoid electrochemically produced by-products, or current controlled to ensure a high reaction rate. Different membranes can be used to separate the anodic and cathodic chamber depending on the compounds produced (Figure source [START_REF] Moscoviz | Electrochemical control of a biological process : glycerol electro-fermentation[END_REF])

Different types of BES exist including microbial fuel cells (MFC) to produce electricity, microbial electrolysis cells (MEC) to produce hydrogen, microbial electrosynthesis (MES) to produce chemical products from CO2 reduction and microbial desalination cells (MDC) to desalinate saline waters [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. The common denominator of all these processes is the requirement of large current density because electrons are either the final product of interest (in MFC) or the main driving force [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Arends | 100 years of microbial electricity production: Three concepts for the future[END_REF].

EF implies the fermentation of an organic substrate in presence of polarized electrodes.

Depending on the potential applied, the system can provide a supplementary source of electrons, or act as an electron acceptor. When electrodes provide more electrons to the fermentation medium the operation can be called cathodic electro-fermentation. Meanwhile if the system is acting as electron sink the operation is called anodic electro-fermentation [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF].

The function of polarized electrodes during EF is only to assist the microbial metabolism and is not the main energy source supporting the microbial growth and activity because the main energy source during fermentation comes from the organic substrate and the main electron acceptors are intermediate products of fermentation (Fig. 1234). Consequently, a high current density is not involved in the process [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF]. This point is the main difference between EF and others BES. To illustrate this, a coefficient of electro-fermentation efficiency, 𝜂 𝐸𝐹 , can be estimated, as detailed in Section 2.4.1.

How polarized electrodes are affecting the metabolic patterns depends on many factors, including (i) the type of inoculum: pure or mixed cultures; (ii) the composition of the microbial community with complex interactions; (iii) the presence in the fermentation medium of redox mediators, naturally produced such as H2 and formate, or artificially added such as methyl viologen and neutral red; (iv) the microbial interactions with the polarized electrode surface.

First evidence of metabolic pattern changes and microbial community selection in electro-fermentation

The first research works in EF have been performed with both pure and mixed cultures. In both cases, a clear effect of polarized electrodes was shown on the fermentation processes. In pure cultures, a substantial change of the metabolic pathways was observed [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], while in mixed culture, the metabolic patterns changes were probably due to the selection of specific microbial community [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF].

When using pure cultures different strategies were employed to ensure the extracellular electron transfer (EET) between the fermentative microorganisms and the polarized electrode. Choi et al., 2014 showed that Clostridium pasteurianum, a fermentative bacteria, was capable to receive electrons directly from a cathode poised +0.045V vs SHE, suggesting some electroactive properties of this microorganism. Butanol and 1,3-propanediol production were then enhanced 3 and 2 folds using glucose and glycerol as substrates, respectively [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF].

Metabolic engineering was also used aiming to use electroactive bacteria such as Shewanella Oneidensis to ferment a wider range of substrates. Flynn et al., (2010) worked with a genetically modified strain of S. Oneidensis to produce ethanol from glycerol. This pathway is only possible by removing two electrons through an external reaction. In this case an anode poised at +0.4V vs SHE acting as electron sink, was enough to target the metabolic flow towards the ethanol production [START_REF] Flynn | Enabling Unbalanced Fermentations by Using Engineered Electrode[END_REF]. Also, Escherichia coli was genetically modified to give its electroactive properties, allowing to accelerate the electron transfer by 183% via periplasmic heterologous expression of the c-type cytochromes CymA, MtrA, and STC.

However, methylene blue as electron shuttle was required [START_REF] Sturm-Richter | Unbalanced fermentation of glycerol in Escherichia coli via heterologous production of an electron transport chain and electrode interaction in microbial electrochemical cells[END_REF].

Another strategy consists in the addition in the fermentation medium of redox mediators such as methylene blue [START_REF] Sturm-Richter | Unbalanced fermentation of glycerol in Escherichia coli via heterologous production of an electron transport chain and electrode interaction in microbial electrochemical cells[END_REF], neutral red [START_REF] Choi | Butyrate production enhancement by clostridium tyrobutyricum using electron mediators and a cathodic electron donor[END_REF], methyl viologen [START_REF] Kim | Electron flow shift in Clostridium acetobutylicum fermentation by electrochemically introduced reducing equivalent[END_REF] and cobalt sepulchrate [START_REF] Emde | Enhanced propionate formation by Propionibacterium freudenreichii subsp. freudenreichii in a three-electrode amperometric culture system[END_REF]. These redox mediators are not degraded and act as electron shuttles since they can be oxidized or reduced by fermentative bacteria and then be recycled at the electrode surface [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF]. An interesting study reported propionate as unique fermentation product from glucose after addition of 0.4mM cobalt sepulchrate and using Propionibacterium freudenreichii. In this study, a three-electrode amperometry culture system was poised at -0.39V vs SHE [START_REF] Emde | Enhanced propionate formation by Propionibacterium freudenreichii subsp. freudenreichii in a three-electrode amperometric culture system[END_REF].

The syntrophic relationship between electroactive and fermentative bacteria can be harnessed and replicated to ensure the transfer of electrons. S. Oneidensis and Geobacter sulfurreducens are famous for interacting directly with the electrode surface (more detail in Section 1.4.3).

For example, ethanol production and glycerol consumption were increased when using C.

cellobioparum and polarized electrodes previously colonized with G. sulfurreducens during MEC system poised at +0.46V vs SHE [START_REF] Speers | Fermentation of glycerol into ethanol in a microbial electrolysis cell driven by a customized consortium[END_REF].

The few research made using mixed cultures have shown changes in microbial communities with a consequence on the metabolic patterns. Geobacter sulfurreducens, in glycerol EF by mixed cultures. This study showed an increase in 1,3propanediol production supported by the selection of a specific microbial community in a system poised at -0.9V vs SCE [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF]. Unfortunately, molecular biology analyses have not been performed in all mixed cultures studies making difficult the comparison of the microbial communities between these systems operated with polarized electrodes [START_REF] Zhou | Carbon and electron fluxes during the electricity driven 1,3-propanediol biosynthesis from glycerol[END_REF], [START_REF] Zhou | Development of bioelectrocatalytic activity stimulates mixed-culture reduction of glycerol in a bioelectrochemical system[END_REF].

Possible microbial interactions with the polarized electrodes

When considering the microbial interactions with the electrodes, the microbial community can take/release electrons from/towards electrode surface through indirect and direct EET, also called MIET and DIET respectively. MIET involves the production or use of electron shuttles to transport the electrons, while DIET not. Fig. 1234567summarize the main EET mechanisms reported in literature [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF], [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF].

The idea of an electrically connected microbial community through DIET has begun to be recognized as key to diverse environments. Three potential strategies for DIET have been reported to date as evidence the Fig. 1-8 [START_REF] Lovley | Syntrophy Goes Electric: Direct Interspecies Electron Transfer[END_REF]. These strategies include electron transfer through electrically conductive pili, conductive materials and electron transfer between proteins associated to outer membrane as cytochromes [START_REF] Lovley | Syntrophy Goes Electric: Direct Interspecies Electron Transfer[END_REF]. Particularly, DIET has been studied in pure cultures of G. sulfurreducens and S. Oneidensis [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF]. S. Oneidensis is a fermentative bacteria exhibiting electroactive properties [START_REF] Doyle | Weak electricigens: A new avenue for bioelectrochemical research[END_REF]. This bacteria uses metal reducing (Mtr) pathway, which includes a series of protein components (i.e., CymA, MtrB, MtrC and OmcA) that transfer electrons from the quinone (soluble electron shuttles) pool embedded in the cytoplasmic membrane (i.e. inner membrane) to outer membrane and finally outside the cell towards insoluble materials [START_REF] Flynn | Enabling Unbalanced Fermentations by Using Engineered Electrode[END_REF], [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF], [START_REF] Cheng | Hardwiring microbes: Via direct interspecies electron transfer: Mechanisms and applications[END_REF].

Besides, S. Oneidensis can release flavins to transfer electrons, but also the flavins can bind to Mtr proteins and enhance extracellular electron transfer rates [START_REF] Flynn | Enabling Unbalanced Fermentations by Using Engineered Electrode[END_REF], [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF], [START_REF] Edwards | Redox Linked Flavin Sites in Extracellular Decaheme Proteins Involved in Microbe-Mineral Electron Transfer[END_REF].

Periplasmic membrane vesicles excreted by this bacteria have also been documented as extracellular electron carrier [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF]. Similarly, G. sulfurreducens uses a trans-outer membrane porin-cytochrome complex containing OmcB and porin-like outer membrane proteins along with a periplasmic c-type cytochrome to transfer electrons across the outer membrane [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF].

This bacteria use also nanofilaments or bacterial nanowires to establish electron transport with the electrodes surface but also with other microorganisms even a long-range (50 µm or more when assembled to form biofilm) [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF], [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF]. These nanowires have been comparable

with doped silicon nanowires or conductive polymers [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF].

Mediated interspecies electron transfer (MIET)

MIET implies the use of electroactive substances so-called electron shuttles. Examples of electron shuttles produced by microorganisms are phenazines, flavins, H2 and formate [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF], [START_REF] Creasey | Microbial nanowires -Electron transport and the role of synthetic analogues[END_REF]. External electron shuttles that can be added to the system include humic substances, methyl viologen, and neutral red [START_REF] Rabaey | Microbial electrosynthesis -revisiting the electrical route for microbial production[END_REF], [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF]. Microorganisms can selectively oxidize or reduce these species without consuming them, leaving them free for recycling at the electrode [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF]. The best-known form of MIET is interspecies hydrogen transfer, a key-concept that revolutionized the understanding of how methanogenic microbial community worked during anaerobic digestion [START_REF] Lovley | Syntrophy Goes Electric: Direct Interspecies Electron Transfer[END_REF].

Action mechanisms of electro-fermentation

The action mechanisms in EF are still not well understood and resolved. Moscoviz et al., 2016 proposed three hypothetical mechanisms. Fig. 1-9 shows the hypothetical mechanisms that could be occurring the anode, however, the same mechanisms are expected in the cathode. The first one considers a direct conversion of the substrate to a product of interest.

Here the electrodes act as an unlimited source or sink of electrons, depending on the working potential [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF].

The second one considers a modification of the oxidation-reduction potential through (i) a partial dissipation of the electrons in excess (i.e. towards polarized electrode) produced by substrate fermentation or (ii) a small addition of extra electrons (i.e. from polarized electrode)

to the fermentation medium. In both cases, a change in the NADH/NAD + ratio is promoted, contributing to metabolic regulation of many important cellular functions, including genetic expression and enzymatic synthesis [START_REF] Schievano | Electro-Fermentation -Merging Electrochemistry with Fermentation in Industrial Applications[END_REF], [START_REF] Liu | Redox potential control and applications in microaerobic and anaerobic fermentations[END_REF], [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF]. This second hypothesis is probably responsible for why the electric current during EF is not always sufficient to explain the change in metabolic patterns [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Zhou | Carbon and electron fluxes during the electricity driven 1,3-propanediol biosynthesis from glycerol[END_REF], [START_REF] Zhou | Development of bioelectrocatalytic activity stimulates mixed-culture reduction of glycerol in a bioelectrochemical system[END_REF]. However, this small current densities that are passing through polarized electrodes is enoguh to observe a significative impact [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. The third mechanism consists in a syntrophic interaction between fermentative (e.g.

Clostridia species) and electroactive bacteria (e.g. Geobacter species) [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF], [START_REF] Kouzuma | Microbial interspecies interactions : recent findings in syntrophic consortia[END_REF]. This is considered as syntrophic because the fermentative partner provides a substrate to the electroactive bacteria that in return makes the fermentation thermodynamically more favourable by removing the by-products [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. Interactions between fermenters and electroactive bacteria rely on the mechanisms of interspecies electron transfer, either indirectly through the diffusion of electron shuttles such as H2, formate, or other metabolites or directly through the use of conductive pili, membrane to membrane contacts, or via a conductive support onto which a biofilm can attach (See section 1.4.3) [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Kouzuma | Microbial interspecies interactions : recent findings in syntrophic consortia[END_REF].

In general, all the mechanisms proposed above (Fig. 123456789) may affect the selection of microbial communities when mixed cultures are used. Through the use of polarized electrodes, electroactive species can be favoured, leading to the formation of mixed biofilm with a different microbial community than the fermentation bulk [START_REF] Xafenias | Electrochemical startup increases 1 , 3-propanediol titers in mixed-culture glycerol fermentations[END_REF], [START_REF] Dennis | Dynamics of cathodeassociated microbial communities and metabolite profiles in a glycerol-fed bioelectrochemical system[END_REF], [START_REF] Zhou | Development of bioelectrocatalytic activity stimulates mixed-culture reduction of glycerol in a bioelectrochemical system[END_REF].

Likewise, the microbial community selection in the fermentation bulk could be influenced by establishing cooperative partnerships with bacteria attached to the biofilm. Then, significant changes in metabolism patterns could be observed [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF].

On the other hand, the polarized electrode could affect the microbial community not only by taking or releasing electrons from the fermentation medium [START_REF] Park | Inactivation of bacteria in seawater by low-amperage electric current[END_REF]. Illustratively, the presence of a polarized electrode can lead to changes in the zeta potential of cell membranes. This could favour biofilm formation or make some bacteria more (or less) competitive [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Schär-Zammaretti | Influence of Fermentation Medium Composition on Physicochemical Surface Properties of Lactobacillus acidophilus Influence of Fermentation Medium Composition on Physicochemical Surface Properties of Lactobacillus acidophilus †[END_REF]. A study run with Clostridium pasteurianum showed that the presence of a polarized electrode of graphite felt caused large changes in cell structure and, more particularly, the formation of extracellular appendages. Polarized electrodes can also affect electrostatic interactions between the cells and the polarized electrode, making the cells less electronegative and thus facilitating the biofilm formation on a poised electrode (0.045V vs SHE) [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF].

CHAPTER 2 Materials and methods

Synopsis

This chapter summarizes the experimental and analytical methodology used during this thesis. Information on the sampling procedures and storage is detailed. The different techniques to analyse liquid and gaseous samples, as well as molecular biology samples are presented. Statistical tools for data analysis are described, together with the calculations made to compare the experiments. Experimental design is detailed per chapter including the specific materials used, microbial inoculum and the modes of operation.

Biomass determination and chemical analysis 2.2.1 Liquid samples collection and biogas quantification

Liquid samples were collected from the reactor to evaluate the chemical composition. 2 ml of liquid were collected in a screw-top tube and were then centrifuged at 13400 rpm for 15 min. Supernatants were filtered with 0.2µm syringe filters and then stored in a clean safe-lock tube at 4 ºC until HPLC analysis. Additionally, pellets were stored at -20 ºC in the initial tubes for molecular biology analysis.

Biogas production was quantified by two different ways depending on the test. First, when used 1L reactor, the biogas was measured by liquid displacement using an inverted graduated cylinder. Second, when the tests were performed in 100 mL bottles, the biogas production was estimated by measuring the gas pressure in the bottle head space according Eq. 2-1.

Where Pf and Pi are final and initial gas pressure. V correspond to volume of bottles head space. T is the measuring temperature.

Eq. 2-1 𝐵𝑖𝑜𝑔𝑎𝑠 [𝑚𝑚𝑜𝑙] = (𝑃 𝑓 -𝑃 𝑖 )[𝑏𝑎𝑟] × 𝑉 𝐻𝑒𝑎𝑑𝑆𝑝𝑎𝑐𝑒 [𝑚𝐿] 𝑇[𝐾] × 0.083[𝑚𝐿. 𝑏𝑎𝑟. 𝐾 -1 . 𝑚𝑚𝑜𝑙 -1 ]

Volatile suspended solids and volatile solids

Volatile suspended solids (VSS) corresponds to the biomass concentration measured by dry weight technique. During this thesis, VSS were measured at the end of the tests at least in duplicates. First, a known volume was centrifuged at 7 830 rpm for 15 min. The supernatant was then discarded, and the pellet fraction was resuspended with a small amount of distilled water and placed into an aluminum dish. Samples were dried in an oven at 105 ºC until constant weight (about 8 h). Before weighing (A), the sample was placed in a desiccator to balance temperature. Then, samples were ignited to constant weight (about 3 h) in a muffle at 550 ºC. Before weighing (B), it was placed in desiccator to balance temperature. Finally, the biomass concentration is estimated according the Eq. 2-2 [START_REF] Rice | Standard Methods for the Examination of Water and Wastewaster[END_REF].

Eq. 2-2 𝑉𝑆𝑆 [𝑔. 𝐿 -1 ] = (𝐴 -𝐵)[𝑔] × 1000[𝑚𝐿. 𝐿 -1 ] 𝑉𝑜𝑙𝑢𝑚𝑒[𝑚𝐿]
Besides, volatile solids (VS) determination was performed in some cases to characterize the inoculum. VS is performed following the same protocol described above for VSS. As a single exception, in VS the centrifugation is not necessary because VS consider all volatile mass present in the sample. When the sample has a low water content, VS could be a useful estimate of VSS.

High-performance liquid chromatography

Principle: High-performance liquid chromatography (HPLC) is an analytical technique in which a liquid mobile phase transports a sample through a column containing a solid stationary phase. The interaction of the sample with the stationary phase selectively retains individual compounds and permits the separation of the sample components. Detection of the separated sample compounds is achieved using different detectors types including conductivity, electro-chemical, fluorescence, ultraviolet, refractive index and others [START_REF] Rice | Standard Methods for the Examination of Water and Wastewaster[END_REF].

Concentration of glucose, succinate, lactate, formate, acetate, propionate, ethanol, butyrate and 2.3-butanediol were measured by HPLC coupled to a refractive index (RI) detector (Waters R410). HPLC analysis were performed using an Aminex HPX-87H, 300 x 7.8 mm (Bio-Rad) column at 35 ºC. H2SO4 at 4mM was used as mobile phase. The firsts tests were carried out at a flow rate of 0.4 mL.min -1 , then the method was changed to 0.3 mL.min -1 to shorten the analysis.

Gas chromatography

Principle: Gas chromatography (GC) uses a mobile phase (a carrier gas) and a stationary phase (column packing or capillary column coating) to separate individual compounds. The carrier gas is nitrogen, argon-methane, helium or hydrogen. For packed columns, the stationary phase is a liquid that has been coated on an inert granular solid, called the column packing that is held in borosilicate glass tubing. The column is installed in an oven with the inlet attached to a heated injector block and the outlet attached to a detector. Precise temperature of the injector block, oven, and detector is maintained constant [START_REF] Rice | Standard Methods for the Examination of Water and Wastewaster[END_REF].

Biogas composition was determined using a GC Clarus 580, Perkin Elmer equipped with a thermal conductivity detector (TCD) and argon as carrier gas at 3.5 bar. The columns used were RtMolsieve for CO2 determination and RtQbond for H2, O2, N2 and CH4 determination.

Molecular biology techniques 2.3.1 DNA extraction

In the experiments described in Chapter 4, DNA was extracted with the QIAamp fast DNA stool mini kit in accordance with manufacturer's instructions (Qiagen, Hilden -Germany).

For all other experiments, DNA was extracted with FastDNA TM SPIN Kit in accordance with manufacturer's instructions (MP Biomedical; Santa Ana, California -USA). Extractions were confirmed, and DNA concentration was obtained using Infinite 200 PRO NanoQuant (Tecan Group Ltd., France).

MiSeq sequencing

The V3-V4 regions of the 16S rRNA genes were amplified using the primers W338F (http://www.genotoul.fr). Sequences were retrieved after demultiplexing, cleaning and affiliating sequences using Mothur [START_REF] Schloss | Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities[END_REF]. Sequences reported in Chapter 4 have been submitted to GenBank, under the accession numbers from KX632761 to KX632946.

Real-times polymerase chain reaction (qPCR)

PCRs were prepared using [START_REF] Levin | Hydrogen production by Clostridium thermocellum 27405 from cellulosic biomass substrates[END_REF]

Calculations and statistical analysis 2.4.1 Electro-fermentation efficiency

The electro-fermentation (EF) efficiency coefficient, 𝜂 𝐸𝐹 , was used to compare the EF with other bioelectrochemical systems. It corresponds to the ratio of electrons passing through for the electrical circuit on the number of electrons recovered in the product of interest, i.e.

hydrogen (Eq. 2-3). For EF systems, this value should be between 0 and 1 showing that electricity production or consumption was not predominating H2 production. A value higher than 1 means electricity production, direct electrosynthesis or electrolysis.

Estimation of the theoretical chemical oxygen demand

Mass balances were calculated after all experiments to verify whether most of the metabolic products were detected and quantified. In environmental area, mass balances based on the chemical oxygen demand (COD) is often used. In principle, the COD is defined as the amount of a specified oxidant that reacts with the samples under controlled conditions. The quantity of oxidant consumed is expressed in terms of oxygen equivalents. COD could be calculated by experimental methods (including open reflux, titrimetric and colorimetric methods), generally used when complex samples need to be analysed such as wastewaters and natural waters [START_REF] Rice | Standard Methods for the Examination of Water and Wastewaster[END_REF]. However, it is also possible to estimate the theoretical COD of each individual compound knowing the chemical composition of the sample (Eq. 2-5).

Eq. 2-5

𝐶 𝑛 𝐻 𝑎 𝑂 𝑏 𝑁 𝑑 + 𝑥𝑂 2 → 𝑦𝐶𝑂 2 + 𝑤𝐻 2 𝑂 + 𝑧𝑁𝐻 3 According to Eq. 2-5 , it is just necessary to balance this equation based on the empirical formula of each compound and then to calculate the ratio gO2.g -1 compound. Then, the theoretical CODglucose is estimated as follows: HPLC or GC analysis) and theoretical COD ratio for each compound. Table 2-1 shows the theoretical COD ratio (go2.gcompound -1 ) calculated for each compound measured in this thesis.

6𝑚𝑜𝑙 𝑂2 1𝑚𝑜𝑙 𝐺𝑙𝑢𝑐𝑜𝑠𝑒 × 32𝑔 𝑂2 𝑚𝑜𝑙 𝑂2 × 𝑚𝑜𝑙 𝐺𝑙𝑢𝑐𝑜𝑠𝑒 180𝑔 𝐺𝑙𝑢𝑐𝑜𝑠𝑒 = 𝟏. 𝟎𝟕 [𝒈 𝑶𝟐 𝒈 𝑮𝒍𝒖𝒄𝒐𝒔𝒆 ⁄ ]
As an example, considering that 5 g.l -1 of initial glucose is totally consumed to produce acetate (1.5 g.l -1 ), butyrate (1.2 g.l -1 ) and ethanol (0.5 g.l -1 ). COD is 5.

Pearson correlations

Principle: The Pearson correlation index is used to calculate the linear correlation between quantitative variables no mattering the scale of measurement. Index value (r) ranges between -1 and 1, both included. When 0< r <1 a positive correlation is observed, while r =0 means no correlation and -1< r <0 represents a negative correlation. Pearson correlation was calculated using PAST (PAleontological STatistics) version 3.20.

Analysis of Variance (ANOVA)

Principle: Analysis of variance (ANOVA) allows to compare the variability existing between several data groups with the average data variability of each group. A statistical value is used to accept or reject the null hypothesis. If null hypothesis is accepted, it is concluded in no difference between the data, while if it is rejected, that means that at least one group is different. ANOVA test was calculated using PAST (PAleontological STatistics) version 3.20.

Principal component analysis

Principle: Principal component analysis (PCA) is a statistical technique used to reduce the dimensionality of a data set. Independent factors are obtained, that are a linear combination of the original variables. PCA allow identifying patterns in data and expressing the data in such a way as to highlight their similarities and differences. PCA tests were calculated using PAST (PAleontological STatistics) version 3.20.

Mantel test and partial Mantel test

The

Non-metric multidimensional scaling

Non-metric multidimensional scaling (NMDS) is an indirect gradient analysis approach which produces an ordination based on a distance or similarity matrix. In this thesis were used matrix based on Bray-Curtis similarity index. Contrary to methods which attempt to maximize the variance as PCA, NMDS attempts to represent, as closely as possible, the pairwise similarity between objects in a low-dimensional space. NMDS is a rank-based approach meaning that the original distance data is substituted with ranks [START_REF] Taguchi | Relational patterns of gene expression via non-metric multidimensional scaling analysis[END_REF]. NMDS test was performed using PAST (PAleontological STatistics) version 3.20.

ANOSIM & SIMPER

ANOSIM (Analysis of similarities) is a non-parametric test of significant difference between two o more groups, based on any distance measure. This test has some similarity with ANOVA however, distances between groups with distances within groups are compared. For that, ANOSIM to evaluate a similarity matrix. Large positive R (up to 1) signifies dissimilarity between groups. The significance of R statistic is determined by permuting group membership.

SIMPER (Similarity percentage) is a simple method attempts assessing which average percent contribution of individual variable to the dissimilarity between objects in a Bray-Curtis similarity matrix. This method is useful to identify variables that are likely to be the major contributors to difference between groups detected by using e.g. ANOSIM [START_REF] Clarke | Non-parametric multivariate analyses of changes in community structure[END_REF], [START_REF] Warton | Distance-based multivariate analyses confound location and dispersion effects[END_REF].

ANOSIM & SIMPER tests were performed using PAST (PAleontological STatistics) version 3.20.

Mantel test

Evaluate the correlation existing between the inoculum microbial community, the metabolites produced and the final microbial community Chapter 5

Partial Mantel test

Know whether the inoculum microbial community is affecting the correlation between metabolites produced and the final microbial community Chapter 5

NMDS

Represent the gradient of inoculum microbial community from different sources Chapter 5

ANOSIM

Determine whether the differences between the inoculum microbial community are statistically significant Chapter 5

SIMPER

Determine which families of inoculum microbial community were contributing in a major percentage to the differences between different inoculum sources. Chapter 5

Electro-fermentation systems 2.5.1 Fermentation medium composition

During all EFs tests, only glucose was used as substrate along with others macro and micro nutrients as is detailed in Table 2-3. When dual-chamber reactors were used the fermentation medium and inoculum were added in the working electrode chamber, while in the counter electrode chamber only fermentation medium free of glucose was added.

Electro-fermentation reactors set-up

All EFs tests were performed using dual-chamber reactors (Fig. 2-1A), except in 3 of 4 tests showed in Chapter 3 (See section 2.6.1, 2.6.2 and 2.6.3), that were performed using single chamber reactors (Fig. 2-1B). Conventional fermentation as control tests were performed also using single chamber reactors. When used dual-chamber reactor a membrane of cation exchange (FKE-50, FuMA-Tech GmbH, Germany) was placed between both chambers (Fig.

2-2D

). The EF systems were composed of three electrodes: working, counter and reference electrodes. These electrodes were connected to a VSP Potentiostat/Galvanostat interfaced to a VMP3B-80 Current Booster unit (BioLogic Science Instruments, France) to maintain a constant the applied potential at the working electrode. For all EFs tests as reference electrode was used calomel (SCE) (Fig. 2-2E). While, as counter electrodes were used grids

A B

of 90% platinum -10% iridium (Fig. 2-2C). Working electrode used in Chapter 3 were planar graphite plate (Fig. 2-2A), graphite felt (Fig. 2-2B) and grids of 90% platinum -10% iridium (Fig. 2-2C), as is detailed in Section 2.6. While that in EF test performed in Chapter 4

and Chapter 5, the working electrodes were grids of 90% platinum -10% iridium of 3.5 x 3.5 cm 2 (Fig. 2-2C). In the Chapter 6 as working electrode were used planar graphite plate (Fig.

2-2A

) as is detailed in Section 2.9.2. In all EF tests, the temperature was maintained at 37 °C using a water bath equipped with a thermocirculator. The stirring was set at 250 rpm using a magnetic stirrer and the initial pH was adjusted at 6.0 with 2 M NaOH during batch EF. When the operation was performed in continuous mode in Chapter 5 (Section 2.8.1), the pH was continuously adjusted at 6.0 with 2M NaOH using a peristaltic pump connected to a pH sensor.

The Fig. 2

Experimental design in Chapter 3

The inoculum used was anaerobic sludge sampled from a sewage treatment plant in Narbonne (3.5 gVS.l -1 ). Tests were inoculated at a ratio of S/X = 10, where S is substrate (g.l - 1 ) and X is initial biomass (gVS.l -1 ) calculated from Eq. 2-2. Glucose was used as substrate along with others macro and micro nutrients (Table 2-3).

CHAPTER 2: Materials and methods

To remove oxygen traces, the reactor medium and headspace were bubbled with N2 gas (purity ≥ 99.9%) for 30 minutes before experiments, using a commercial aquarium air stone.

The Table 2-4 summarize the experiments show in the Chapter 3.

Study on 'the selection of the Electrode material'

Batch EF experiences were performed for 24 hours using a single chamber reactor with 0.5 L of fermentation volume (50% of total volume). Three different materials were used as working electrodes: Graphite felt with a size of 5.2 cm x 3.5 cm x 3.5 cm, planar graphite plate with a size of 2.5 cm x 2.5 cm and grids of 90% platinum -10% iridium with a size of 2.5 cm x 2.5 cm. In all cases, grids of 90% platinum -10% iridium were used as counter electrodes. The applied potential at working electrode was -0.9V vs SCE. Control tests were also performed using a single-chamber reactor, in absence of polarized electrodes.

All the experiments were carried out in duplicates

Study on the 'effect of the Platinum electrode on metabolic patterns'

Batch EF experiences were performed for 24 hours using a single chamber reactor with 0.5 L of fermentation volume (50% of total volume). Grids of 90% platinum -10% iridium with a size of 2.5 cm x 2.5 cm were used as working and counter electrodes. The applied potential at working electrode was -0.9V vs SCE.

Two control tests were performed. On the first one the electrodes were placed on fermentation medium but not connected to circuit electric, i.e. not polarized electrodes. This is to evaluate whether the electrode material has any effect on metabolism patterns. On the second control polarized electrodes were placed in the fermentation medium free of inoculum i.e. abiotic control. This to evaluate if is possible the chemical H2 production by water hydrolysis under conditions used. All experiments were carried out in duplicates.

Study on 'the effect of different potential applied on the working electrode'

Batch EF experiences were performed for 24 hours using a single chamber reactor with 0.5 L of working volume (50% of total volume). Grids of 90% platinum -10% iridium with a size of 2.5 cm x 2.5 cm were used as working and counter electrodes. Four potential values were applied at the working electrode: -0.9, -0.7, -0.5 and -0.3 V vs SCE. Control tests were also performed using a single-chamber reactor, in absence of polarized electrodes. All the experiments were carried out in duplicates.

Study on the effect of the electrode size

Batch EF experiences were performed for 24 hours using a dual-chamber reactor with 0.5 L of working volume (50% of total volume) in each chamber. Two grids of 90% platinum -10% iridium were used: 2.5 cm x 2.5 cm and 3.5 cm x 3.5 cm. The applied potential at working electrode was -0.9V vs SCE. Control test were also performed in absence of polarized electrodes using a single-chamber reactor. The experiments were carried out in duplicates.

Experimental design in Chapter 4

The inoculum used in this chapter corresponded to an anaerobic sludge sampled from a labscale anaerobic digester treating sewage sludge (37.7 gVS.l -1 ). The sludge was heat-treated at 90°C for 30 minutes using a water bath before inoculation at ratio S/X = 10, where S is substrate (g.l -1 ) and X is initial biomass (gVS.l -1 ) calculated from Eq. 2-2. Glucose was used as substrate along with others macro and micro nutrients (Table 2-3). Batch EF experiences were performed for 20 hours using a dual-chamber reactor with 0.5 L of working volume and 0.5 L of headspace in each cell. The values of applied potentials at working electrode were -0.9, -0.4, +0.4 and +0.9 V vs SCE. To remove oxygen traces, the reactor medium and headspace were bubbled with N2 gas (purity ≥ 99.9%) for 30 minutes before experiments, using a commercial aquarium air stone. Batch control experiments were also performed using a single-chamber reactor, in absence of polarized electrodes under similar operating conditions. The experiments were carried out in duplicates (-0.9V and -0.4V), triplicates (+0.4V and +0.9V) and quintuplicates (controls).

Experimental design in Chapter 5

Electro-fermentation in continuous operation mode

The inoculum used was an acidogenic sludge sampled from H2-producing reactor fed with molasses (9.9±0.3 gVS.l -1 ). Fresh sludge was added corresponding to 14.3% of fermentation volume (100 mL). Glucose was used as substrate along with others macro and micro nutrients (Table 2-3).

EF test in continuous operation mode was performed for 40 days (143.3 HRTs) in dualchamber reactors with 0.7 L of fermentation volume and 0.3 L of headspace in each cell. The applied potential at working electrode was -0.4V vs SCE. Before starting continuous operation, a batch was performed for 24 hours to grow biomass and for its acclimatization.

The input/output of working electrode chamber were continuously supplied/retired by peristaltic pump. The pump flows were adjusted to maintain the HRT at 6.7 hours.

Control tests were also performed using a single-chamber reactor, in absence of polarized electrodes under similar operating conditions.

Electro-fermentation in batch operation mode: Comparison of different inoculum source

Four types of inoculum were used to compare the batch EF: (i) acidogenic sludge from H2producer reactor fed with glucose (1.5 gVS.l -1 ); (ii) anaerobic sludge from a lab-scale anaerobic digester treating food waste (7.1 gVS.l -1 ). The sludge was heat-treated at 90°C for 30 minutes using water bath before inoculation; (iii) anaerobic sludge from a lab-scale anaerobic digester treating volatile fatty acids (9.5 gVS.l -1 ) and (iv) activate sludge from sewage treatment plant at Narbonne (10.0 gVS.l -1 ). Glucose was used as substrate along with others macro and micro nutrients (Table 2-3). Batch EF tests were performed for 24 hours using a dual-chamber reactor with 0.9 L of working volume. The applied potential at working electrode was -0.4V vs SCE. Batch control tests were also performed using a single-chamber reactor, in absence of polarized electrodes and operated under similar conditions.

Experimental design in Chapter 6

Microbial interaction between different mixed cultures and electroactive bacteria 2.9.1.1 Inoculum and fermentation medium

Two different sludge were used as inoculum: (i) acidogenic sludge from H2-producer reactor fed with molasses (9.9±0.3 gVS.l -1 ). The sludge was stored in a freezer at -20°C and defrost at room temperature and (ii) activate sludge from sewage treatment plant at Narbonne (10.0 gVS.l -1 ). In all cases, the sludge was enriched with Geobacter sulfurreducens DSMZ 12127, which was precultured as shown in Section 2.9.1.2. Fermentation medium was composed for 5 g.l -1 glucose and 1.65 g.l -1 acetate as carbon sources along with others macro and micro nutrients (Table 2-3).

Electroactive bacteria growth: G. sulfurreducens DSMZ 12127

Geobacter sulfurreducens DSMZ 12127 was cultivated in 100 mL bottles with 50 mL of culture medium. This was composed as follow: 0.82 g.l -1 Naacetate, 1.5 g.l -1 NH4Cl, 0.1 g.l -1 KCl, 0.6 g.l -1 Na2HPO4, 10 mL.l -1 trace element solution, 10 mL.l -1 vitamin solution (Table 2345), 8.0 g.l -1 Na2fumarate and 2.5 g.l -1 NaHCO3. 1 L of culture medium was prepared without vitamin solution and Na2fumarate. 1 mg.l -1 of resazurin was added as redox indicator. pH was adjusted at 6.8 and then 50 mL were distributed in each 100 mL bottles. The bottles were closed with butyl rubber stoppers and aluminium crimp caps. Anaerobic conditions were established bubbling N2 gas (purity ≥ 99.9%) for at least 30 min.

Then bottles were autoclaved at 121°C for 20 min. Before inoculation vitamin solution, Na2fumarate and 0.5 g.l -1 L-cysteine were added using a sterile 0.2µm filter. Inoculated bottles were cultivated in a room acclimatized at 35°C under agitation.

Fermentation bottles and start-up

Batch fermentation experiences were performed using 100 mL bottles with 50 mL of working volume. The experiments were carried out until glucose was totally consumed between 24 and 72 hours in a room acclimatized at 35°C under agitation. Initial pH was adjusted at 6.0 with 2 M NaOH. To remove oxygen traces, bottles were bubbled with N2 gas (purity ≥ 99.9%) for 30 min before experiments, using a commercial aquarium air stone. Each bottle was inoculated with 2.5 mL of sludge and 2.5 of G. sulfurreducens DSMZ 12127. Control experiences were performed by inoculating only 5.0 mL of sludge and were operated under similar conditions.

The experiments were carried out in triplicates and quadruplicates when used activate sludge from sewage treatment plant at Narbonne and acidogenic sludge from H2-producer reactor fed with molasses, respectively.

Mixed culture electro-fermentation using electrodes colonized by

Geobacter sulfurreducens

Inoculum and fermentation medium

The inoculum used was acidogenic sludge from a H2-producing reactor fed with molasses (9.9±0.3 gVS.l -1 ). The sludge was stored in a freezer at -20°C and defrost at room temperature. Glucose was used as substrate along with others macro and micro nutrients (Table 2-3)

Pre-colonization of the electrode with G. sulfurreducens DSMZ 12127

Geobacter sulfurreducens DSMZ 12127 pre-cultivated as showed in the Section 2.9.1.2, was used to pre-colonize electrode in a single-chamber reactor with 0.8 L of medium. The fermentation medium was composed as follows: 1.65 g.l -1 Naacetate, 0.63 g.l -1 NH4Cl, CHAPTER 2: Materials and methods 0.26 g.l -1 KCl, 50 mM MES Buffer (9.75 g.l -1 ), 20 mL.l -1 trace element solution and 20 mL.l -1 vitamin solution (Table 2345). The temperature was maintained at 37 °C using a water bath equipped with a thermocirculator. The stirring was set at 250 rpm using a magnetic stirrer and initial pH was adjusted at 6.8 with 2 M NaOH. Anaerobic conditions were established bubbling N2 gas (purity ≥ 99.9%) after inoculation for 30 min.

Planar graphite plate with a size of 5.0 cm x 5.0 cm x 0.25 cm and grids of 90% platinum -10% iridium with a size of 3.5 cm x 3.5 cm were used as working and counter electrode, respectively. The applied potential at working electrode was +0.2V vs SCE. The working electrode, counter electrode and calomel reference electrode (SCE) were connected to a VSP Potentiostat/Galvanostat interfaced to a VMP3B-80 Current Booster unit (BioLogic Science Instruments, France) to maintain a constant the applied potential at the working electrode.

The experiment was stopped when no more electric current was produced. The Fig. 234show a typical curve of current production during electrode colonization.

Introduction

EF is not only a new operating configuration for BES, but it also introduces a new type of control for anaerobic bioprocesses. As EF is a recent concept, only few works are documented and there is not enough knowledge about the optimal operating conditions and which are the most suitable materials for performing efficient EF. To date EF is carried out under the same laws that dominate in traditional BES. However, it is well admitted and obvious that it is not the same to work with a MEC or an MFC, although both configurations are BES, each configuration having its own particularities, as well as EF.

The literature evidences that electrode material and size, as well as the potential applied at the working electrode, can alter the current production and generate different interactions with the microbial community. Besides, reactor configuration (i.e. single or dual-chamber reactors) is important when considering the efficiency of electrochemical systems. Then, this first chapter aims to determine the main parameters affecting EF. The specific objectives are as follows:

i. Determine how the electrode material can affect H2 production during EF.

ii. Study different potential applied at the working electrode using a singlechamber reactor.

iii. Determine how the electrode size can affect H2 production during EF.

Selection of electrode material

This section aims to select the better electrode material according to H2 production for the next experiments. For that, three types of electrode material were tested as working electrode in single chamber reactors: graphite felt (Felt -Pt), planar graphite plate (Graf -Pt) and grids of 90% platinum -10% iridium (Pt -Pt). In all cases, grids of 90% platinum -10% iridium were used as counter electrodes. The applied potential at working electrode was -0.9V vs SCE. Besides, conventional fermentation as control was performed without electrodes in the fermentation medium.

After 24 hours of batch operation, the glucose was totally consumed in all conditions (3.8±0.6 gCOD.l -1 ). Total COD mass balance measured as soluble and H2 gas, was between 74.2 and 88.6%. It is assumed that 10-15% of the missing COD was corresponding to biomass growth. The rest COD could correspond to unknown metabolites.

Fig. 3-1 shows the H2 yield obtained for each electrode. A significant increase of the H2 yield by a factor of 1.36 was observed using Pt -Pt (1.76±0.08 molH2.mol -1 glucose), when compared to control (1.29±0.05 molH2.mol -1 glucose). Using Graf -Pt (1.26±0.02 molH2.mol -1 glucose), the H2 yield was almost same than in the control, while a lower H2 yield was obtained using Felt -Pt (0.98±0.003 molH2.mol -1 glucose). The metabolites were measured but no important difference among the conditions was observed.

The electrons transferred as electric charge in Coulombs (C) from the polarized electrode to the fermentation medium during batch operation time were of -424.7±27.8 C, -69.2±96.0 C and -115.2±43.3 C for Pt -Pt, Graf -Pt and Felt -Pt, respectively. While, EF efficiency (ηEF) (Section 2.4.1 -Materials and methods) respect to H2 production were of 0.12±0.01, 0.04±0.06 and 0.06±0.02, respectively. This means that as maximum only 12% of the H2 produced came from the electrons supplied by the electrodes. Particularly, in the case of Pt -Pt, the electrons supply was more stable between the replicates, as shown by the low standard deviation value observed in the average of electrical charge. Contrary, using Graf -Pt and Felt -Pt, large differences between the duplicates were observed, evidencing an unstable supply of electrons under the operational conditions used here. The critical parameters governing any bioelectrochemical system include the composition of the electrolyte (in this thesis, it is the same as the fermentation medium) [START_REF] Merrill | Electrolyte effects on hydrogen evolution and solution resistance in microbial electrolysis cells[END_REF], pH [START_REF] Babu | Bio-electrolytic conversion of acidogenic effluents to biohydrogen: An integration strategy for higher substrate conversion and product recovery[END_REF],

electrode materials [START_REF] Cheng | High hydrogen production rate of microbial electrolysis cell (MEC) with reduced electrode spacing[END_REF], applied potential [START_REF] Venkata Mohan | Dehydrogenase activity in association with poised potential during biohydrogen production in single chamber microbial electrolysis cell[END_REF] and composition of the microbial community [START_REF] Pisciotta | Enrichment of microbial electrolysis cell biocathodes from sediment microbial fuel cell bioanodes[END_REF]. Except the composition of the microbial community, these parameters determine which abiotic reactions (i.e. not catalysed by microorganism or biological enzymes) could take place on electrode surface, consequently affecting microbial community behaviour [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF], [START_REF] Arunasri | Polarized potential and electrode materials implication on electro-fermentative di-hydrogen production: Microbial assemblages and hydrogenase gene copy variation[END_REF]. Particularly, electrodes based on metallic materials as platinum are highly reactive due to a good electrical conductivity, thus transporting electrons more rapidly than others with low conductivity capacity [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF], [START_REF] Arunasri | Polarized potential and electrode materials implication on electro-fermentative di-hydrogen production: Microbial assemblages and hydrogenase gene copy variation[END_REF], [START_REF] Zhou | An overview of electrode materials in microbial fuel cells[END_REF]. Consistently, ours results evidence a major electric charge transferred when Pt -Pt was used compared to carbon-based electrodes tested.

Besides, H2 can likely be produced from water electrolysis, when highly negative potential are applied, i.e. -0.9 V vs SCE, especially when metallic-based electrodes are used [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF], CHAPTER 3: Starting with electro-fermentation and determination of parameters [START_REF] Zhou | An overview of electrode materials in microbial fuel cells[END_REF]. This could explain the increase of the H2 yield when Pt -Pt electrodes were used.

However, an abiotic control (i.e. EF tests without inoculum) was not performed to corroborate or discard this hypothesis. This point will be discussed in more detail in the following section.

As a conclusion, it was decided to use Pt -Pt electrodes for the next experiments because higher H2 yields were obtained and the electron supply was more stable compared with the other materials tested. Besides, interestingly Pt electrodes do not facilitate biofilm formation due to the smooth surface [START_REF] Wei | Recent progress in electrodes for microbial fuel cells[END_REF]. This property can be interesting to study the interaction between polarized electrodes and microbial community without biofilm attached.

Effect of platinum electrode on fermentation patterns

This section seeks to deepen the results observed in previous section. For that, EF experiences were carried out under similar conditions with grids made of 90% platinum -10% iridium as working and counter electrodes (Pt -Pt). The applied potential at working electrode was -0.9V vs SCE. Besides, two control tests were performed: (i) in the first one the electrodes were placed on fermentation medium but not connected to circuit electric, i.e. not polarized electrodes. This is to evaluate whether the electrode material has any effect on metabolism patterns; and (ii) in the second control polarized electrodes were placed in the fermentation medium free of inoculum i.e. abiotic control. This to evaluate if is possible the chemical H2 production by water hydrolysis under conditions used. All experiments were carried out in duplicates.

After 24 hours of batch operation, the glucose was totally consumed in all reactors (4.5±0.7

gCOD.l -1 ), except in the abiotic control. Total COD mass balance measured as soluble and H2

gas, was 82.5±1.1%. It is assumed that the 10-15% of the missing COD was corresponding to biomass growth.

Hydrogen production and metabolite distribution

During EF, the H2 yield was 70% higher (0.97±0.09 molH2.mol -1 glucose) than in conventional fermentation or control (0.57±0.09 molH2.mol -1 glucose, Fig. 3-2). Besides, not H2 production was observed in the abiotic control (i.e. EF tests without inoculum). Despite, literature evidence of electrochemical H2 production at potential applied of -0.9 V vs SCE, our results corroborate that electrolyte or fermentation medium in our case (because single chamber reactors are used), are affecting the abiotic reactions occurring in the electrode surface [START_REF] Thrash | Review : Direct and Indirect Electrical Stimulation of Microbial Metabolism[END_REF],

[178], [START_REF] Lu | Microbial electrolysis cells for waste biorefinery: A state of the art review[END_REF]. Thus, even by applying a so low potential, the chemical H2 production by water electrolysis is not assured. Consequently, the H2 produced is the result of biological microbial community activity. Interestingly, during EF significant changes were observed on lactate and butyrate pathways.

Lactate decreased down to 3.4±0.7%COD and butyrate increased up to 34.4±8.2%COD. Such shifts of the metabolic pattern can explain the higher H2 production in EF. This is consistent with literature since lower H2 yields are related to lactate accumulation [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Palomo-Briones | Dark-fermentative biohydrogen pathways and microbial networks in continuous stirred tank reactors: Novel insights on their control[END_REF], while higher H2 production is often associated with butyrate [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Lee | Thermodynamic Evaluation on H2 Production in Glucose Fermentation[END_REF]. Other metabolites were not affected by polarized electrodes. Thus, ethanol, acetate and succinate also accumulated in EF, ranging 20.6±1.0%COD, 13.1±4.6%COD and 2.5±0.2%COD, respectively. previously reported during H2 production by dark fermentation [START_REF] Rafrafi | Sub-dominant bacteria as keystone species in microbial communities producing bio-hydrogen[END_REF] but also during 1.3propanediol production in mixed cultures fermentation [START_REF] Moscoviz | Consistent 1,3-propanediol production from glycerol in mixed culture fermentation over a wide range of pH[END_REF].

Fig. 3-5: Family distribution of microbial community observed during control and electro-fermentation tests using single chamber reactors and Pt-Pt electrodes

In addition, Table 3-1 shows the Pearson correlation matrix that was performed to evaluate the influence of microbial family abundance on metabolic patterns. Lactate production negatively correlated with H2 production (R 2 = -0.93, p < 0.05) and positively with the following families: Lactobacillaceae (R 2 = 0.95, p < 0.05), Saprospiraceae (R 2 = 0.88, p < 0.05) and other bacteria <1.0% (R 2 = 0.96, p < 0.05). Many bacteria can produce lactate, either to rapidly release their excess of electrons or because they are natural lactate producers.

In both cases, H2 production is affected and lactate and H2 are mostly negatively correlated [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Palomo-Briones | Dark-fermentative biohydrogen pathways and microbial networks in continuous stirred tank reactors: Novel insights on their control[END_REF], [START_REF] Jo | Process stability and microbial community structure in anaerobic hydrogen-producing microflora from food waste containing kimchi[END_REF]. However, a positive correlation could occur by using lactate to produce H2 along with butyrate [START_REF] Noblecourt | Hydrogen production by dark fermentation from pre-fermented depackaging food wastes[END_REF]. In this case, lactate production during dark fermentation could act as an "electron reservoir" for H2 production when the substrate (e.g. glucose) is totally depleted [START_REF] Duncan | Lactate-Utilizing Bacteria , Isolated from Human Feces , That Produce Butyrate as a Major Fermentation Product Lactate-Utilizing Bacteria , Isolated from Human Feces , That Produce Butyrate as a Major Fermentation Product[END_REF]. Besides, our results are consistent with the literature, and species belonging to the family Lactobacillaceae are well known as lactate producers [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. present in a low relative abundance, but their contribution in lactate production seems to be significant, evidencing once again the importance of subdominant bacteria in the main microbial community activities.

Despite the low amount of propionate in the control tests, two correlations were observed with microbial family abundance including a Bacilli_unclassified (R 2 = 0.93, p < 0.05) and

Streptococcaceae (R 2 = -0.95, p < 0.05). Similarly and consistently with literature, ethanol production shows a positive correlation with Enterobacteriaceae family (R 2 = 0.95, p < 0.05) [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF]. The data used include all replicates from electro-fermentation and control reactors. In bold were marked the significant correlations with a p-values ≤0.05. Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour depending on value.

Table 3-1 shows also the correlation existing between the EF efficiency (ηEF), metabolic patterns and family distribution of the microbial communities. The ηEF shows a positive correlation with the H2 yields (R 2 = 0.89, p < 0.05), and the presence of Aeromonadaceae (R 2 = 0.90, p < 0.05) and Prevotellaceae (R 2 = 0.96, p < 0.05). Interestingly, some members of the Aeromonadaceae family were previously reported in anodic (i.e. being part of the transfer electrons toward electrode) biofilms in MFCs, including anodes made with metallic materials such as titanium [START_REF] Pham | A novel electrochemically active and Fe(III)-reducing bacterium phylogenetically related to Aeromonas hydrophila, isolated from a microbial fuel cell[END_REF]- [START_REF] Chung | Characterization of electrochemical activity of a strain ISO2-3 phylogenetically related to Aeromonas sp. isolated from a glucose-fed microbial fuel cell[END_REF]. This electrochemical activity could also occur in the opposite direction, i.e. taking electrons from the cathodic surface, thus, being able to actively participate in the electrons transfer from the electrode to the fermentation medium. In addition, members of the Prevotellaceae family are associated to the production of extracellular polymeric substances for cellular aggregation and possibly could favour biofilm formation [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Li | Fermentative hydrogen production in packed-bed and packaging-free upflow reactors[END_REF]. The positive correlation between ηEF and the selection of both Aeromonadaceae and Prevotellaceae families, could explain the increase in electron transfer from the electrode surface toward the fermentation medium. Even they were not dominant in the soluble microbial community, their contribution to metabolic pattern changes should not be neglected.

Effect of the applied potential on metabolic patterns

In this section, the influence of the applied potential on metabolic patterns was investigated.

For that, four potential values were applied at the working electrode: -0.9, -0.7, -0.5 and -0.3 V vs SCE. Batch EF tests were performed using a single chamber reactor using as working and counter electrodes grids of 90% platinum -10% iridium. Besides, conventional fermentation as control tests were also performed using a single chamber reactor, in absence of polarized electrodes. All the experiments were carried out in duplicates.

After 24 hours of batch operation, the glucose was totally consumed in all reactors (4.9±0.3 gCOD.l -1 ). Total COD mass balance measured as soluble and H2 gas, was 85.3±6.6%. It was assumed that the 10-15% of the missing COD corresponded to biomass growth.

Hydrogen production and metabolite distribution

The maximum H2 yield was reached at -0.7V and -0.5V, with 1.09±0.07 molH2.mol -1 glucose (Fig. 3456) that represented an increase of 42% with respect to the control (0.77±0.002 molH2.mol -1 glucose). A lower H2 yield was obtained at -0.9V and -0.3V, with only 0.83±0.02 molH2.mol -1 glucose and 0.85±0.05 molH2.mol -1 glucose, respectively. Only the tests made at -0.7V and -0.5V were statistically different (ANOVA: F=10.89, p=0.011) from the control. The tests at -0.9V and -0.3V did not show significant differences with the control (ANOVA:

F=3.48, p=0.1656).

Fig. 3-6: Hydrogen yield observed during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors

Regarding the metabolites produced, no significant difference was observed in all conditions including the control. The ANOVA analysis performed did not show a significant p-value to reject the null hypothesis i.e. group means are all equal. The F / p-value for acetate, 0,0 0,4 0,8 Illustratively, Fig. 34567shows the metabolic distribution based on COD mass balance in the control and at -0.7V. A focus on this particular condition was made since the H2 yield was significantly different from the control. Butyrate was the main metabolite in all the cases, ranging between 36.8±1.0%COD and 52.8±6.3%COD. Acetate, propionate and ethanol were also produced, in a range between 10.4±0.3%COD and 12.5±1.9%COD, 4.0±3.2%COD and 12.2±7.9%COD and 8.7±3.4%COD and 11.7±2.0%COD, respectively. Low quantities of lactate were also detected, i.e. between only 1.9±0.3%COD and 8.4±11.9%COD.

Fig. 3-7: Metabolite distribution observed during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors

As not significant differences were found on metabolic pattern during any EF conditions and control, illustratively only the control and -0.7V are shown.

Analysis of bio-electrochemical parameters

In EF, the electric charges transferred from (i.e. negative sign) or to (i.e. positive sign) the electrodes were -304.8±98.1 C, -26.1±20.2 C, +0.09±0.07 C and +1.0±1.2 C for -0.9V, -0.7V, -0.5V and -0.3V, respectively. The ηEF, considering H2 as interest product was 0.093±0.027 for -0.9V, while that for the others conditions the values were <0.003.

According to the ηEF, a maximum between 0.3% and 9.3% of the total electrons that have passed by the electrical circuit could have contributed to H2 production.

During the experiments showed in this section, a cyclic voltammetry (CV) was performed during 3.3 hours at the beginning and at the end of the batch operation. The CV was performed 10 times from -1.0 V to 1.0 V with a scan rate of 1 mV.s -1 . CV is a standard tool in electrochemistry and has regularly been exploited to study and characterize electron transfer interactions between microorganisms or microbial biofilms and electrodes [START_REF] Fricke | On the use of cyclic voltammetry for the study of anodic electron transfer in microbial fuel cells[END_REF], [START_REF] Harnisch | A basic tutorial on cyclic voltammetry for the investigation of electroactive microbial biofilms[END_REF]. However, after EF tests no conditions studied i.e. potential applied, allowed to observe any active site in the CV profile. This means that there was no electroactive biofilm formation on the electrode surface. During the CV, the potential swapped and the electrode polarization changes over a short period of time. Since EF systems need only small amount of electron supplied (or harvest) to have a high impact [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], probably this initial CV performed was enough to cause a change in the microbial community. Besides, as CV was performed under the same parameters in all EF reactors, it could be responsible for the similar performances observed. Surprisingly, the ORP profile of the control showed similar disturbances, coinciding with the CV performed in EF reactors. Probably for cable ORP system electrical insulation reasons, the CV seemed to have also affected the control and for that not significative differences were observed with the EF tests.

Fig. 3-8: ORP measurement in the fermentation bulk during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors

The ORP measured (Fig. 345678) in the control had a typical shape for biological kinetics, where fermentation products accumulate and stabilize the ORP, here around a negative value of -0.57±0.03V.

In EF reactors, after the initial CV, a constant ORP value of -0.75±0.01 V, -0.52±0.01 V, -0.35±0.01 V and -0.15±0.01 V was reached when the potential applied at the working electrode was -0.9 V, -0.7 V, -0.5 V and -0.3 V, respectively (Fig. 345678). A linear correlation between ORP and applied potential was shown (Fig. 3456789). However, ORP values

Size electrode selection

In this last section, the influence of electrode size on H2 production and metabolic pathways during glucose EF was evaluated. For that, two electrode sizes of working and counter electrode of 2.5x2.5 cm 2 (SE) and 3.5x3.5 cm 2 (BE) were tested. It should be noted that working and counter electrodes always have the same size. So when BE (or SE) was used, the same size was used for both electrodes. Dual-chamber reactors were used to avoid low reproducibility as observed in simple-chamber reactors (data not shown). Besides, control test were performed in absence of polarized electrodes using a single-chamber reactor and all the experiments were carried out in duplicates. After 24 hours of batch operation, glucose was totally consumed in all reactors (5.3±0.1 gCOD.l -1 ). Total COD mass balance measured as soluble and H2 gas, was 76.5±9.1%. 10-15% of missing COD was likely corresponding to biomass growth. The rest of missing COD probably correspond to unknown metabolites.

A maximum H2 yield of 1.39±0.17 molH2.mol -1 glucose (Fig. 3-10) was reached when BE was used, but no significant difference (ANOVA: F=4.73, p=0.118) was observed when compared to the control (1.26±0.09 molH2.mol -1 glucose) and when SE (1.04±0.05 molH2.mol - 1 glucose) was used.

Fig. 3-10: Hydrogen yield observed during electro-fermentation tests comparing two electrodes sizes using dual chamber reactors

Two electrodes size were compared of 2.5x2.5 cm 2 (SE) and 3.5x3.5 cm 2 (BE).

With respect to metabolites distribution (Fig. 3 performed in this chapter the same inoculum was used under similar operational conditions, the metabolite distributions observed show great differences compared to results from previous sections. Probably, this is due to an effect of inoculum age it has been stored at -4°C for around 4 months before the experiment observed in this section. However, as no microbial analysis was performed, it is not possible to compare the differences in the microbial community composition.

In EF tests, the electric charges transferred from the electrodes surface to the fermentation medium were -747.9±126.0 C and -244.1±61.9 C for BE and SE, respectively. The ηEF indices calculated on H2 production were 0.20±0.01 and 0.09±0.02 respectively. That suggests that a maximum of 19.8% and 9.0% of the electrons passing through the electrical circuit could have contributed to H2 production. Besides, respect to all fermentation product a global coefficient of ηEF = 0.031±0.002 and 0.009±0.002 for BE and SE, respectively, was obtained. This value means that only a maximum of 3.1% of all fermentation product are affected for the electrons supplied by the electrodes.

As already shown no significant differences on the H2 production was observed here.

Moreover, a direct relationship between the electrode size and the electric charge was observed, as already reported in the literature [START_REF] Doyle | Weak electricigens: A new avenue for bioelectrochemical research[END_REF], [START_REF] Santoro | Microbial fuel cells: From fundamentals to applications. A review[END_REF], [START_REF] Logan | Exoelectrogenic bacteria that power microbial fuel cells[END_REF]. Indeed, [START_REF] Oh | Cathode performance as a factor in electricity generation in microbial fuel cells[END_REF] reported an increase of 22% in the power density during electricity generation in microbial fuel cells by tripling the cathode surface area [START_REF] Oh | Cathode performance as a factor in electricity generation in microbial fuel cells[END_REF].

Conclusion

In this chapter, different electro-fermentation experiments using glucose were performed to determinate the best operational parameters and select adequate materials. After comparing different materials as working electrode, platinum grids were selected based on H2 production CHAPTER 3: Starting with electro-fermentation and determination of parameters performances to carry out the next electro-fermentation experiences. Besides, a significant change on the metabolic patterns was observed when a polarized electrode was placed in the fermentation medium. In this case, H2 and butyrate production were both increased while lactate was unfavoured when compared to the control. Microbial community analysis showed that the dominant families present at the end of the batch operation could not explaining these changes. Nonetheless, and despite a low relative abundance, the presence of members of the Aeromonadaceae family showed a positive and significant correlation with the electrofermentation efficiency index. This suggests the importance of subdominants species in the microbial interactions having a subsequent impact on metabolic patterns.

Afterwards, different potential were applied on the working electrode, but not differences were observed between the conditions including the control. In this case, an initial cyclic voltammetry was performed, and it was hypothesized that the CV was possibly the cause of such similar performances. Besides, some electrical interferences were observed between the control and the EF tests, due to the initial cyclic voltammetry performed in electrofermentation tests. Although the phenomenon behind this behaviour is unknown, and was not further investigated, the control reactors were then placed in another water bath that electrofermentation reactors and no longer electrical interference was observed.

Finally, two sizes of platinum grids electrodes were tested using dual-chamber reactors. The big electrodes of 3.5 x 3.5 cm 2 were selected because more electrons, i.e. Coulombs, were supplied to the fermentation medium.

CHAPTER 4 Electro-fermentation triggering H 2producing bacteria

Introduction

Mixed cultures have been widely used for H2 production by dark fermentation. However, many different microorganisms can grow in fermentation media and no selection pressure can be directly applied for the selection of bacteria carrying efficient H2-producing pathways, such as Clostridium sp. Besides, not only the action of dominant species is crucial, subdominant species also play a key role supporting the microbial community [START_REF] Rafrafi | Sub-dominant bacteria as keystone species in microbial communities producing bio-hydrogen[END_REF].

Consistently, in the Chapter 3 the results evidence that only members of the subdominant family Aeromonadaceae showed a positive and significant correlation with the EF efficiency index. This suggests the importance of subdominants species in the microbial community interactions. However, there is not much research focused on the microbial interactions studies.

To date, lot of efforts have been made on optimizing operating parameters, including: carbon sources, macro-micro nutrients, temperature, pH, HRT, organic loading rates, H2 partial pressure. However only few controllers (pH, OLR, HRT) are available to maintain stable dark fermentation performances, i.e. metabolic patterns and H2 production. In this context, the electro-fermentation process has been proposed as a new type of bioprocess controlled by polarized electrodes.

The objective of this chapter is to use polarized electrodes in glucose fermentation to evaluate their influence in the fermentation medium on metabolic pathways and H2 production, with a special focus on how the bacterial populations could be affected.

This chapter has been written based on the article accepted in International Journal of

Hydrogen Energy: Toledo-Alarcón J., Moscoviz R., Trably E. and Bernet N. Glucose electro-fermentation as main driver for efficient H2-producing bacteria selection in mixed cultures.

Context and specific experimental methodology

In this Chapter the effect of polarized electrodes was evaluated by testing four different values of applied potential at working electrode i.e. -0.9, -0.4, +0.4 & +0.9 V vs SCE. Batch operation was performed using dual-chamber reactor and as working and counter electrode were used grids of 90% platinum -10% iridium of 3.5 x 3.5 cm 2 . Conventional fermentation i.e. without electrodes, was performed as control in single chamber reactor, under similar conditions than electro-fermentation test. More details are provided in Chapter 2 (Materials and methods).

Increase in H2 production and changes in metabolite distribution during glucose electro-fermentation

After 20 hours of batch operation, glucose was totally consumed in all conditions (5.2±0.2 gCOD.l -1 ). Total COD mass balance, calculated from soluble products and H2 gas accumulation, ranged between 73.2% and 80.6%. Approximately 10-15% of the missing COD was likely corresponding to the biomass growth. Whatever the conditions, no methane was detected in headspace.

First, a low H2 yield of 0.74±0.09 molH2.mol -1 glucose was observed in the control (conventional fermentation). H2 production was significantly enhanced by a factor between 1.8 and 2.5 in presence of the polarized electrodes. The highest H2-yield was 1.81±0.32 molH2.mol -1 glucose and was reached at the applied potentials of -0.4V and +0.9V. Lower H2 yields were observed at -0.9V and +0.4V, i.e. 1.49±0.06 and 1.34±0.12 molH2.mol -1 glucose, respectively.

The H2 yields were statistically different only between the control and the EF experiments (ANOVA: F=20.68, p=0.0001), but not between EF tests. This result suggests that placing a polarized electrode, whatever the applied potential, in the fermentation medium is enough to observe a clear effect on H2 production. The maximum H2 yield obtained in this study is comparable to reported for glucose dark fermentation in batch operation using mixed cultures as inoculum (2.5 molH2.mol -1 glucose) [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF]. However, depending on inoculum source and the pre-treatment employed, the H2 yields could be between 0.1 and 3.0 molH2.mol -1 glucose [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Wang | Comparison of different pretreatment methods for enriching hydrogen-producing bacteria from digested sludge[END_REF], [START_REF] Liu | Enrichment of the hydrogen-producing microbial community from marine intertidal sludge by different pretreatment methods[END_REF], [START_REF] Wang | Effects of various pretreatment methods of anaerobic mixed microflora on biohydrogen production and the fermentation pathway of glucose[END_REF].

Fig. 4-1 shows the metabolites distribution according to the COD mass balance. In the control, lactate was the main metabolite reaching to 66.9±4.9%COD. Ethanol and acetate were also observed representing 14.0±2.5%COD and 9.5±1.0%COD, respectively. In less quantity butyrate and propionate were produced, representing 1.6±3.1%COD and 0.4±0.9%COD, respectively.

In EFs tests, lactate production was significantly decreased representing between 1.1 -32.1%COD. Regardless of the applied potential, ethanol and acetate productions were increased representing between 24.7 -38.6%COD and 14.0 -18.5%COD, respectively.

Particularly, in -0.4V and +0.9V experiments, butyrate production increased by 14.6 and 16.8-fold, when compared to the control. While it represented about 24.6 and 29.3%COD at -0.4V and +0.9V, respectively. As minority compounds, succinate production (not detected in the control) also increased to a lesser extent, representing 1.0 -6.9%COD. Propionate was produced at only very low concentrations (<1.6%COD).

Fig. 4-1: Metabolite distribution based on COD mass balance in final samples of glucose electro-fermentation

Values were calculated based on total glucose consumed. Values represent the average from quintuplicates (Control), triplicates (+0.4V and +0.9V) or duplicates (-0.9V and -0.4V).

Error bars represent the standard deviation of the data.

In general, high lactate production is consistent with low H2 performances like in our control tests. This, because lactate is directly produced from pyruvate (not by the acetyl-coA pathway) by consuming NADH, allowing the cell to quickly get rid of the excess in electrons through NAD + regeneration without H2 production [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Increasing H2 yields were observed in EF tests and correlated with ethanol and acetate accumulation. Acetate is a key molecule for H2 production due to the high energy gain of this pathway through ATP production [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Khanal | Biological hydrogen production: Effects of pH and intermediate products[END_REF] Although ethanol is a more reduced molecule than glucose and its production allows to release the excess of electrons by direct NAD+ regeneration, ethanol is also associated with H2 production [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. Finally, this study show the maximum H2 was linked with the butyrate production. This metabolite has been often associated with additional ATP production and butyrate production was suggested as the most thermodynamically favourable reaction during dark fermentative H2 production [START_REF] Lee | Thermodynamic Evaluation on H2 Production in Glucose Fermentation[END_REF]. As a consequence, butyrate production is often associated with high H2 producing reactors [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF].

Microbial community analysis

DNA samples were taken from inoculum and after 20 hours of batch operation to analyse the effect of the polarized electrodes on the microbial communities. A total of 589 operational taxonomic units (OTUs) were found after MiSeq sequencing in all samples. The dominant family found in the inoculum was Clostridiaceae representing 17.6±1.6% of the microbial community (Fig. 4-2). Families with an abundance relative lower than 5.0% represented 46.9±3.1% of the microbial community in the inoculum, evidencing a high diversity (Simpson index of 0.955±0.003) at start of the experiments. Only 8 OTUs showed a relative abundance higher than 1.0% in at least one sample (Table 4-1). In the control, Streptococcaceae (57.9±5.1%) and Enterobacteriaceae (34.0±5.2%) families were the most representative families, and OTU2 and OTU1 were dominant with 57.7±5.2 and 28.9±4.9% of the total bacterial community, respectively. These two OTUs were related to Escherichia fergusonii (99% 16S rRNA sequence similarity with OTU1) and Streptococcus equinus (99% 16S rRNA sequence similarity with OTU2).

The Clostridiaceae family was mainly represented by OTU3 and was enriched at -0.4V (35.7±4.2%) and +0.9V (38.1±11.2%). OTU3 had 99% of 16S rRNA sequence similarity with Clostridium butyricum. The Enterobacteriaceae family was the most abundant in all EF reactors, reaching 77.8±2.9, 57.7±12.0, 56.9±17.5 and 42.2±12.8% of total microbial community at -0.9V, -0.4V, +0.4V and +0.9V, respectively. Two main OTUs represented this family, i.e. OTU1 and OTU4. OTU1 was already described at the beginning of this section and OTU4 had 99% of 16S rRNA sequence similarity with Enterobacter cloacae. In all the samples, H2-producing bacteria were selected, and their relative abundances increased, and more specially members of the Enterobacteriaceae and Clostridiaceae families. Despite the inoculum was heat-treated before reactor inoculation, none-spore forming bacteria of the Enterobacteriaceae family such as OTU1 and OTU4 were selected and dominated at the end of operation. Probably these species can survive due to limitations in heat transfer depending on the system used for pre-treatment. Consistently, it has been reported in literature that even methanogens can survive after some operation days after heat shock pre-treatment, and the type of inoculum source plays a key role in its effectiveness [START_REF] Wong | A review of sustainable hydrogen production using seed sludge via dark fermentation[END_REF], [START_REF] Kumar | Impact of pH control and heat pre-treatment of seed inoculum in dark H2 fermentation: A feasibility report using mixed microalgae biomass as feedstock[END_REF].

The three mains metabolic pathways for H2 production in electro-fermentation resulted from microbial community selection

To represent the relationships between microbial communities and reactor performances, a principal component analysis (PCA) was performed. Fig. 4-3 shows the PCA based on bacterial population in EF and control reactors evidencing the categorical differences between using or not polarized electrodes. Three main H2 production pathways correlated well with the selection of specific microbial communities. In the first pathway (Fig. 4-3 on the right side) observed in control reactors, Streptococcaceae family abundance was correlated with high lactate production (R 2 = 0.92, p<0.01) and with a low H2 production (R 2 = -0.73, p<0.01).

Details of the correlation matrix are presented Fig. 4-4. Streptococcus equinus belongs to a known lactic acid bacteria group [START_REF] Ferrer-Valenzuela | Metabolic Fluxes in Lactic Acid Bacteria -A Review[END_REF], that was previously found in low H2-producing reactors [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Hung | Interactions between Clostridium sp . and other facultative anaerobes in a self-formed granular sludge hydrogen-producing bioreactor[END_REF]- [START_REF] Chu | Phase holdups and microbial community in high-rate fermentative hydrogen bioreactors[END_REF]. Overall, lactic acid bacteria act as a suppressor of H2 production through substrate competition (i.e. pyruvate) and produce lactate at the expense of H2, resulting in lower yields or the release of bactericides inhibiting the growth of H2 producing bacteria [START_REF] Bundhoo | Inhibition of dark fermentative bio-hydrogen production : A review[END_REF], [START_REF] Ferrer-Valenzuela | Metabolic Fluxes in Lactic Acid Bacteria -A Review[END_REF].

Fig. 4-3: Principal component analysis (PCA) based on microbial population distribution

Black plain lines and dotted lines represent correlations between PCA axes and taxonomic families and metabolic yields, respectively. Stars, squares, triangles, circles and diamonds represent control (n=2), -0.9V, +0.4V, -0.4V and +0.9V reactors, respectively.

In the second pathway (Fig. 4-3 on the left upper side), as observed at -0.4V and +0.9V, Clostridiaceae abundance correlated well with high H2 yields (R 2 = 0.79, p<0.01, Fig. 4-4) and high butyrate production (R 2 = 0.94, p<0.01, Fig. 4-4). Additionally, a negative correlation was evidenced with lactate production (R 2 = -0.63, p<0.05, Fig. 4-4). By selecting Clostridium species, up to 45% of the theoretical H2yield (4 molH2.molglucose -1 ) was reached [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Lee | Thermodynamic Evaluation on H2 Production in Glucose Fermentation[END_REF], along with an important increase in the butyrate production. In this case, OTU3 (related to Clostridium butyricum) was greatly favoured when compared to the control. This species was the most abundant in only one condition (+0.9V) but, at the family level, the Enterobacteriaceae dominated in all other EF experiences. Clostridium butyricum is a wellknown efficient H2 producer producing butyrate as main metabolite [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF], [START_REF] Sivagurunathan | Batch fermentative hydrogen production by enriched mixed culture : Combination strategy and their microbial composition[END_REF], [START_REF] Fang | Microbial diversity of a mesophilic hydrogen-producing sludge[END_REF] which is consistent with the present findings. More generally, species belonging to the Clostridia genus are considered as efficient H2 producers [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF] and they have been found in most of the mixed culture-based H2 producing fermentative systems. [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF].

Fig. 4-4: Pearson correlation matrix based on metabolite production and microbial family abundance

The data used include all data from electro-fermentation and control reactors. • = pvalue<0.05; * = pvalue<0.01 A third pathway (Fig. 4-3 on the left bottom) was observed at -0.9V and +0.4V and was related to the Enterobacteriaceae abundance which positively correlated with succinate (R 2 = 0.86, p <0.01, Fig. 4-4), ethanol (R 2 = 0.93, p <0.01, Fig. 4-4) and acetate (R 2 = 0.71, p <0.05, Fig. 4-4). The Enterobacteriaceae selection in EF tests led to a lower H2 production than when the second pathway was promoted, but H2 yields were still higher than in the control. In these reactors the OTU3 related to Clostridium butyricum was not favoured and the Enterobacteriaceae family was largely dominating. OTUs 1 and 4, related to Escherichia fergusonii and Enterobacter cloacae, respectively, were the main species and both belong to genera that have been widely used in pure cultures for H2 production [START_REF] Elsharnouby | A critical literature review on biohydrogen production by pure cultures[END_REF], [START_REF] Seppala | Fermentative hydrogen production by Clostridium butyricum and Escherichia coli in pure and co-cultures[END_REF]- [START_REF] Nath | Effect of some environmental parameters on fermentative hydrogen production by Enterobacter cloacae DM11[END_REF].

However, species from the Enterobacteriaceae family were already found during periods of poor H2 production [START_REF] Cho | Variations of hydrogen production and microbial community with heavy metals during fermentative hydrogen production[END_REF]. Consistently, our results show that this family is positively correlated with succinate and ethanol accumulation [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF].

Electro-fermentation patterns: low current is enough to trigger high changes in fermentation patterns

During EF, the electric charges transferred from (i.e. negative sign) / to (i.e. positive sign) the electrodes were -615.4 ±378.6 C, -0.17 ±0.11 C, +2.85 ±1.75 C and +1.89 ±0.83 C at an applied potential of -0.9V, -0.4V, +0.4V and +0.9V, respectively. Although the measured current was significant, the quantity of electrons at -0.9V represented only 1.9% of the total electrons, i.e. the electrons issued from glucose or from and the electric current. Current was close to zero in all other EF conditions (Table 4-2). To differentiate EF from other bioelectrochemical systems, an efficiency coefficient of EF (ƞEF), analogous to the coulombic efficiency in conventional BES, could be estimated, as previously proposed by Moscoviz et al. (2016). ƞEF values range between 0 and 1 in EF systems and values higher than 1 indicate the possible occurrence of direct bio-electrosynthesis. When considering H2 as targeted product, the ƞEF value at -0.9V was 0.16, meaning that the electric current could not directly contribute to more than 16.0% of the total accumulated H2. Thus, hydrogen production mainly resulted from glucose catabolism. In other EF conditions, the ƞEF was <0.001, meaning that the electric current did not significantly contribute to the whole metabolic reaction (<0.1% of H2 production). Consequently, only a small amount of energy was sufficient to generate a great impact, as evidenced by the low values of ƞEF [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. This is consistent with EF articles already published, where current was not the main source of energy for microbial metabolism [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF], [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF]. Overall, such low amount of energy could explain the relative independence of the H2 yields to the applied potential since electrons are not directly converted to H2 and polarized electrodes rather contribute to change the local environment around the electrode leading to microbial selection and subsequently different H2 yields. Electric charge (Qe-, Coulomb) transferred from/toward circuit electric through working electrode placed in fermentation medium. Molar ratio (mmolQe-/mole-total) of electrons transferred through circuit electric per total electrons feed on the system (electrons from glucose + or -current electric). The electrofermentation efficiency (ƞEF) was calculated considering hydrogen as metabolite of interest.

Hypothetical action mechanisms during glucose electrofermentation

To better understand the mechanisms that drive the EF process, Arunasri et al. (2016) reported that the microbial community could be affected by exposure to different applied potentials during the H2 production in a single chamber microbial electrolysis cell (MEC).

These authors showed that members of the Firmicutes phylum were favored by increasing the applied potentials [START_REF] Arunasri | Polarized potential and electrode materials implication on electro-fermentative di-hydrogen production: Microbial assemblages and hydrogenase gene copy variation[END_REF]. In contrast, in the present study, no significant linear relationship between the applied potential and population selection was observed. The only OTU which had an abundance that linearly correlated to the applied potential was OTU 1 (Escherichia fergusonii) which was selected at low applied potential (R 2 = -0.71, p<0.05). However, substantial changes in the microbial community were triggered by small amounts of current that could not sustain an electrochemical H2 production that would explain the difference between controls and EF conditions.

One hypothetical action in EF is related to the changes that could occur on the net charge of the cell surface. Choi et al. ( 2014) reported that the zeta potential of C. pasteurianum DSM 525 cells grown with electricity was near to zero, whereas cells were electronegative in open circuit [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF]. The selection of OTU1 could have resulted from a change in the net charge of the cell surface in response to the potential applied on the working electrode. This would have likely caused physiological changes on growth rate and cell division and would consequently disadvantage it in substrate competition while giving the opportunity to other species to emerge [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Wilson | Status of methods for assessing bacterial cell surface charge properties based on zeta potentil measurements[END_REF]. In addition, changes in cell surface net charge towards values close to zero in microorganisms such as Clostridium could have made them more resistant to bactericide produced by OTU 2 (related to Streptococcus equinus). As an illustration, nisin is a known toxin released by lactic acid bacteria causing a depolarization of energized bacterial membranes, especially affecting Clostridia species. This toxin stimulates the formation of potential-dependent multi-state pores when membrane potential is negative (-80 to -100 mV vs SHE). Through these pores, vital gradients equilibrate with the extracellular medium and metabolites and salts can be lost causing cell deaths [START_REF] Sikora | Lactic Acid Bacteria in Hydrogen-Producing Consortia: On Purpose or by Coincidence?[END_REF], [START_REF] Noike | Inhibition of hydrogen fermentation of organic wastes by lactic acid bacteria[END_REF], [START_REF] Riley | Bacteriocins: Evolution, Ecology, and Application[END_REF], [START_REF] Schuller | The peptide antibiotic subtilin acts by formation of voltage-dependent multi-state pore in bacterial and artificial membanes[END_REF]. By modifying the cell surface net charge, the EF process could help sensitive bacterial species to counter this effect.

A second hypothetical mechanism is related to small changes in the extracellular redox potential caused by the polarized electrodes. That would affect the regulation of key membrane-bound enzymes involved in H2 production (hydrogenases), due to their high sensitivity to redox potential variations [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF], [START_REF] Xing | Genetic diversity of hydrogen-producing bacteria in an acidophilic ethanol-H2-coproducing system, analyzed using the [Fe]-hydrogenase gene[END_REF], [START_REF] Arunasri | Polarized potential and electrode materials implication on electro-fermentative di-hydrogen production: Microbial assemblages and hydrogenase gene copy variation[END_REF]. However, such mechanisms are still difficult to clearly identify in mixed cultures. In all cases, interactions among species within microbial community are crucial to structure this community and the subsequent metabolism.

Conclusion

This chapter evidences a clear effect of polarized electrodes on both metabolic pathways and microbial community structure in dark fermentation. A strong correlation was observed between the selected microbial communities and the metabolites produced including H2. In all EF conditions, an increase in the H2-yields was shown, independently on the applied potential. The effects on microbial community were mostly non-linear except for specific OTUs related to Escherichia fergusonii and Streptococcus equinus. Such interaction mechanisms between polarized electrodes and microbial community remain however unclear but a new field of investigation in mixed cultures fermentation has been opened.

CHAPTER 5 Electro-fermentation is affected by initial microbial composition

Introduction

During H2 production by dark fermentation, the inoculum source and their microbial composition are crucial for defining final reactor performances. However, different scenarios could lead to a specific selection of the microbial community with consequent changes in the H2 production and in the metabolic pathways. For that, many strategies have been employed

to obtain an adequate inoculum capable to produce H2 high yields without methane production. These strategies include inoculum pre-treatment and setting of important operational parameters as pH, temperature and hydraulic retention time for continuous systems. Recently, it has been reported that the sugar type and the polymerization degree of complex sugars are also determine a specific microbial community, so it could be considered as a new strategy [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF].

Particularly, the results shown in Chapter 4 evidence that an efficient tool for selecting H2producing bacteria is proposed through polarized electrodes. Therefore, microbial selection may first depend on the initial structure of the microbial community, so-called inoculum.

Second, since electro-fermentation seeks to control bioprocesses, it is interesting to evaluate the effect of polarized electrodes when microbial communities change over time. For that continuous reactors that allow to study dynamic behaviors of ecosystems were used.

In this context the objectives of this chapter are the following:

i. Study the effect of electro-fermentation on continuous H2 production in chemostat.

ii. Study the influence of the initial inoculum on electro-fermentation in batch mode

Glucose electro-fermentation during reactor operation in continuous mode

Context and specific experimental methodology

Continuous operation was performed for 40 days at a hydraulic retention time (HRT) of 6.7

h. Electro-fermentation (CEF) operation was performed in dual-chamber reactor, while the control, as conventional fermentation test (CF), was performed in single chamber reactor. In CEF only the working electrode chamber was operated in continuous. Electrodes present in CEF were connected to the potentiostat only the first 23 operation days (CEF-A). Then, electrodes were disconnected but left in the reactor until the end of operation (CEF-B).

During steady state operation, the glucose feed concentration was 5.2±0.2 gCOD.l -1 , 5.0±0.3 gCOD.l -1 and 5.3±0.2 gCOD.l -1 , while glucose consumption was 87.8±7.3%, 82.7±10% and 86.5±5.3%, for CF, CEF-A and CEF-B, respectively. Total COD mass balance, calculated from soluble products and H2 gas, ranged between 72.0±4.2 and 74.1±6.2%. Approximately 10-15% of the missing COD was likely corresponding to biomass growth, while the rest (10-15%) was attributed to unknown metabolites.

Hydrogen and metabolite production

Fig. 5-1 shows the H2 productivity during all time of reactors operation. At the beginning of CF (d9-d10) and CEF-A (d9-d10 and d14-d15) operation, H2 production was unstable due to operational problems related with pH control. The software had a limit in the data acquisition and when the system was overcharged it lost its functionality, leading to uncontrolled pH in the reactors. Thus, due to volatile fatty acids production, the pH decreased at values so low that H2 production was inhibited [START_REF] Khanal | Biological hydrogen production: Effects of pH and intermediate products[END_REF]. To avoid future setbacks the software was restarted every four days of operation.

Operation days

Zone B Zone A B Steady-state was considered after 16 days of operation for CF and CEF-A, 25 days for CEF-B. The H2 volumetric productivity was 2.7±0.2, 2.4±0.2 and 2.6±0.3 lH2.d -1 .l -1 for CF, CEF-A and CEF-B, respectively. According to the ANOVA test, significant differences were observed within the group of CF, CEF-A and CEF-B (F=6.084 and p-value= 0.004).

Furthermore, and according to Mann-Whitney pairwise test, a significant difference was found between CF and CEF-A (p-value= 0.003). The high H2 volumetric productivity reached in CF, CEF-A and CEF-B is comparable to those obtained with a pure culture of Clostridium bifermentans (2.65 lH2.d -1 .l -1 ) under similar operational conditions i.e. pH 5.5, HRT 6 h and 35°C [START_REF] Zhang | Effects of OLRs and HRTs on hydrogen production from high salinity substrate by halophilic hydrogen producing bacterium (HHPB)[END_REF]. Therefore, our results show a high productivity compared the study performed by [START_REF] Wu | HRT-dependent hydrogen production and bacterial community structure of mixed anaerobic microflora in suspended, granular and immobilized sludge systems using glucose as the carbon substrate[END_REF] where anaerobic sludge was used as inoculum (0.6 lH2.d -1 .l -1 ) [START_REF] Wu | HRT-dependent hydrogen production and bacterial community structure of mixed anaerobic microflora in suspended, granular and immobilized sludge systems using glucose as the carbon substrate[END_REF].

Moreover, H2 yields were 1.54±0.18, 1.48±0.07 and 1.40±0.10 molH2.molglucose -1 for CF, CEF-A and CEF-B, respectively. The ANOVA test showed significant differences between CF, CEF-A and CEF-B (F=3.594 and p-value= 0.039). According to Mann-Whitney pairwise test the only significant difference was found between CF and CEF-B (p-value= 0.017).

Overall, the H2 yields obtained in CF, CEF-A and CEF-B reached between 70 and 77% of the theoretical maximum when butyrate is the main metabolite. These values are comparable with the reported values found in literature [START_REF] Wu | HRT-dependent hydrogen production and bacterial community structure of mixed anaerobic microflora in suspended, granular and immobilized sludge systems using glucose as the carbon substrate[END_REF], [START_REF] Zhang | Effects of OLRs and HRTs on hydrogen production from high salinity substrate by halophilic hydrogen producing bacterium (HHPB)[END_REF]- [START_REF] Fang | Effect of pH on hydrogen production from glucose by a mixed culture[END_REF].

Regarding the metabolite production, no significant difference was observed between CF, CEF-A and CEF-B. Illustratively, Fig. 5-2 shows the metabolite distribution at steady state of the CF reactor. The main metabolite was butyrate that represented between 37.4±2.0 and 38.6±4.6 %COD. An important percentage of the COD, between 25.9±6.2 and 28.0±4.2 %COD, was associated to the production of biomass and other unknown metabolites. Acetate and lactate represented only between 13.8±0.8 -15.1±1.6 %COD and between 6.8±1.3 -8.2±0.9 %COD, respectively.

No difference was observed in metabolite patterns between CF, CEF-A and CEF-B. This fact is evidencing that, in continuous operation, the polarized electrodes in CEF-A were not affecting the metabolite production compared to conventional fermentation (CF). Then, same trend was observed when the electrodes were disconnected from the potentiostat (CEF-B).

Microbial community analysis and link with metabolic patterns

Microbial community analyses were performed with MiSeq sequencing. The samples were taken at different operational days. Fig. 5-3 shows the relative distribution of the major families in the microbial communities. Before starting the continuous operation, a batch was performed for 24 hours to acclimatize the inoculum to glucose substrate and medium. In the case of CEF the electrodes were placed in the fermentation medium but was not connected to the potentiostat. In Fig. 5-3A, data from d2 until d17 correspond to CEF-A while data d25 and d26 to CEF-B. The microbial community after the batch period (d1) was more diverse in CEF than in CF, with a Simpson diversity index of 0. respectively. Clostridiaceae family has several well-known H2 producing species [START_REF] Elsharnouby | A critical literature review on biohydrogen production by pure cultures[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF].

Species from Lactobacillaceae, Sporolactobacillaceae and Streptococcaceae family are lactate producers widely reported in literature and found in reactors during H2 production by dark fermentation [START_REF] Hung | Roles of microorganisms other than Clostridium and Enterobacter in anaerobic fermentative biohydrogen production systems--a review[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Palomo-Briones | Dark-fermentative biohydrogen pathways and microbial networks in continuous stirred tank reactors: Novel insights on their control[END_REF], [START_REF] Silva-Illanes | Impact of hydraulic retention time (HRT) and pH on dark fermentative hydrogen production from glycerol[END_REF]. More scarcely, species from the Pseudomonadaceae family have been reported in H2-producing reactors mainly associated with the degradation of complex substrates [START_REF] Hung | Roles of microorganisms other than Clostridium and Enterobacter in anaerobic fermentative biohydrogen production systems--a review[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Interestingly, they have also been reported in electroactive biofilms [START_REF] Saratale | A comprehensive overview on electro-active biofilms, role of exoelectrogens and their microbial niches in microbial fuel cells (MFCs)[END_REF], [START_REF] Saratale | Microbiome involved in microbial electrochemical systems (MESs): A review[END_REF]. Probably species belonging to this family benefited from the presence of a conductive material in the fermentation medium, despite electrodes were not connected to the potentiostat. The literature reports that when conductive materials carbon-based are placed in anaerobic reactors, the microbial community composition and their interactions changes leading to increase the methane production, as well as the kinetic of degradation of volatile fatty acids [START_REF] Dang | Enhancing anaerobic digestion of complex organic waste with carbon-based conductive materials[END_REF], [START_REF] Capson-Tojo | Addition of granular activated carbon and trace elements to favor volatile fatty acid consumption during anaerobic digestion of food waste[END_REF]. This process is known as direct interspecies electron transfer and has been widely documented and recently reviewed in [START_REF] Lovley | Syntrophy Goes Electric: Direct Interspecies Electron Transfer[END_REF] [START_REF] Lovley | Syntrophy Goes Electric: Direct Interspecies Electron Transfer[END_REF]. Thus, conductive materials would act as efficient redox mediators [START_REF] Liu | Promoting direct interspecies electron transfer with activated carbon[END_REF]. However, here, only small differences were observed in initial batch between CF and CEF likely because of the initial microbial community structure. After the batch period, continuous operation was started, and the electrodes were connected to the potentiostat (CEF-A). After 24 hours of operation (d2, Fig. 5 PCA-right in Fig. 5-4, shows the relation between microbial community and metabolic patterns. Consistently, H2 production was related to acetate and ethanol production, while Others+biomass (i.e. biomass production and unknown metabolite) and Lactobacillaceae family were opposite in the PCA, evidencing a negative correlation. Butyrate production was correlated with the Clostridiaceae family and anticorrelated with Enterobacteriaceae family, which is consistent with the literature because high butyrate production is often associated to members of Clostridiaceae as C. tyrobutyricum [START_REF] Hung | Roles of microorganisms other than Clostridium and Enterobacter in anaerobic fermentative biohydrogen production systems--a review[END_REF], [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Choi | Butyrate production enhancement by clostridium tyrobutyricum using electron mediators and a cathodic electron donor[END_REF], [START_REF] Palomo-Briones | Hydrogen metabolic patterns driven by Clostridium-Streptococcus community shifts in a continuous stirred tank reactor[END_REF].

Left PCA shows the operation days distribution for continuous conventional fermentation (CF) and electro-fermentation (CEF-A and CEF-B).

Right figure shows a biplot representing correlations between PCA axes, taxonomic families and metabolic yields. Diamonds and circles represent operation of CF and CEF-A&CEF-B, respectively. Only are presented the families and metabolites that which showed stronger contributions to PCA axes.

In general, no substantial difference was observed in the microbial community from d2 to d26 in all CF, CEF-A and CEF-B tests. This point is shown in the left PCA in Fig. 5-4, where operation days are independently grouped whatever if it is CF, CEF-A or CEF-B. Apparently, differences between electro-fermentation and conventional fermentation can only be evidenced during a batch operation, as shown in this section and observed in Chapter 4.

Probably, the microbial selection pressure imposed by the HRT was pre-dominant over the selection pressure made by the polarized electrodes. Indeed, HRT is directly related with maximum growth rate (μmax) allowing to maintain in the reactor the microorganisms that can grow faster than the rate fixed by the HRT value. The HRT used here (i.e. 6.7h) is in the range of typically applied values for H2 production in suspend biomass systems as CSTRs [START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF], being considered efficient to select H2 producing bacteria from glucose, while the methanogenic activity is often negligible. However, possible selection of electroactive CHAPTER 5: Electro-fermentation is affected by microbial community composition 123 bacteria due to polarized electrode seems to be complicated, maybe because electroactive bacteria grow slower than fermentative bacteria in these conditions and higher HRT values would be necessary [START_REF] Speers | Fermentation of glycerol into ethanol in a microbial electrolysis cell driven by a customized consortium[END_REF], [START_REF] Moscoviz | Cooperative growth of Geobacter sulfurreducens and Clostridium pasteurianum with subsequent metabolic shift in glycerol fermentation[END_REF], [START_REF] Lee | Effects of Substrate Diffusion and Anode Potential on Kinetic Parameters for Anode-Respiring Bacteria[END_REF].

Glucose electro-fermentation effect is influenced by inoculum microbial community

Context and specific experimental methodology

In this section, the inoculum source was evaluated for its influence on the electrofermentation. For that, 5 different inocula (Table 5-1) were tested at -0.4 V vs SCE using as working and counter electrodes grids of 90% platinum -10% iridium with a size of 3.5 x 3.5 cm 2 . Particularly, the experiments performed with inoculum InA correspond to results showed in Chapter 4 (EF, -0.4V). However, they are shown here for a better comparison with the results obtained using the others inoculum source.

InE

Anaerobic sludge sampled from a lab-scale anaerobic digester treating volatile fatty acids 9.5

After batch operation, the glucose was totally consumed in all reactors (5.3±0.2 gCOD.l -1 ).

Total COD mass balance calculated from soluble products and H2 gas ranged between 72.5% and 87.7%, except for Inoculum D that was only 42.1±1.2% where probably the most metabolites were unknown. Approximately 10-15% of the missing COD was likely corresponding to biomass growth. While the rest of the COD correspond to unknown metabolites.

Hydrogen and metabolite production

Fig. 5-5 shows the H2 yields obtained during conventional fermentation (F) and electrofermentation (EF) tests for each inoculum. When InA was used, H2 production was favoured in EF (1.80±0.31 molH2.mol -1 glucose) with respect to F (0.70±0.12 molH2.mol -1 glucose). In contrast, when InB was used, H2 production was disfavoured in EF (0.57±0.17 molH2.mol - 1 glucose) compared to F (1.14±0.09 molH2.mol -1 glucose). Interestingly, no difference was observed in H2 production between EF and F when InC, InD and InE were used as inoculum.

The H2 yields obtained were of 0.88±0.02 molH2.mol -1 glucose, 0.49±0.01 molH2.mol -1 glucose and 0.73±0.004 molH2.mol -1 glucose respectively. In general, maximal H2 yields yield were associated with butyrate production (InA-EF and InB-F), as well as decreased in lactate. Consistently, the literature often refers to high H2 yields when butyrate and acetate are the most important metabolites [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF], [START_REF] Lee | Thermodynamic Evaluation on H2 Production in Glucose Fermentation[END_REF], [START_REF] Palomo-Briones | Hydrogen metabolic patterns driven by Clostridium-Streptococcus community shifts in a continuous stirred tank reactor[END_REF]. While lactate production is commonly associated with lower H2 yields because its production leads to the consumption NADH i.e. allows the cells to release electron excess [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF]. Thus, the conversion of NADH into additional H2 production by Clostridia species is constrained [START_REF] Mathews | Metabolic pathway engineering for enhanced biohydrogen production[END_REF].

Link between final microbial community and metabolite patterns

Microbial communities present at the end of the batch were analysed. Fig. 5 For better visualization and comparison of all reactors, a PCA analysis was performed using variance-covariance matrices from both metabolic patterns and final family distribution (Fig. 5678). All data from F and EF were used in the analysis, however, only the biplot representation shows the most important variables in the components determination. The PCA shows that tests performed using InC, InD and InD are grouped in the left side.

Consistently, none of these inoculums showed significant differences between F and EF respect to metabolic patterns. Besides, these reactors were related to the emergence of members of the Enterobacteriaceae family and with the production of ethanol and others+biomass.

At the right side of the PCA, the reactors showed some effect during EF. On the right above is InA-EF and along the horizontal axis is InB-F. Both are related to H2 yield, Clostridiaceae [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Lee | Thermodynamic evaluation on H2 production in glucose fermentation[END_REF]. Prevotellaceae has been widely reported as a subdominant species in H2 production reactors, and its function is not entirely clear. Prevotellaceae could contribute to the decomposition of complex substrates, but they may also be competing for the substrate [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Tapia-Venegas | Adaptation of acidogenic sludge to increasing glycerol concentrations for biohydrogen production[END_REF]. Butyrate production is positively correlated with microbial diversity of Clostridiaceae and Prevotellaceae, and negatively correlated with Enterobacteriaceae. This is consistent with literature, since butyrate production is a typical metabolic product of Clostridia spp. but not of Enterobacter spp. [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. Lactate production is positively correlated with Streptococcaceae and negatively with ethanol production. Streptococcaceae family is known as lactate producers commonly reported in H2 production reactors [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Ferrer-Valenzuela | Metabolic Fluxes in Lactic Acid Bacteria -A Review[END_REF], [START_REF] Castelló | Possible causes for the instability in the H2production from cheese whey in a CSTR[END_REF].

Particularly, lactate production could be negatively correlated with ethanol production because they are produced by bacteria that commonly outcompete for the substrate [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF].

Finally, ethanol production was positively correlated with Enterobacteriaceae and negatively with butyrate, microbial diversity and Streptococcaceae family. Ethanol production could be linked to solventogenic fermentation by Clostridia spp. Some species from the Enterobacteriaceae family can produce it during the H2 production, as evidenced by our results [START_REF] Nakashimada | Hydrogen production of Enterobacter aerogenes altered by extracellular and intracellular redox states[END_REF], [START_REF] Palomo-Briones | Dark-fermentative biohydrogen pathways and microbial networks in continuous stirred tank reactors: Novel insights on their control[END_REF], [START_REF] Wietzke | The redox-sensing protein Rex, a transcriptional regulator of solventogenesis in Clostridium acetobutylicum[END_REF]. On the other hand, ethanol was an important metabolite when InC, InD and InE were used, which at the end of operation had a low microbial diversity because Enterobacteriaceae family was widely dominating. 5-2 also provides interesting information about ecological interactions occurring between species. Thus, Enterobacteriaceae is negatively correlated with Clostridiaceae and Streptococcaceae, evidencing a possible competitive interaction. Besides, Clostridiaceae is positively correlated with Prevotellaceae suggesting a cooperation interaction between both families.

Inoculum source is influencing the glucose electro-fermentation effect

Bacterial communities of the inoculum were also studied with the objective to study how the microbial distribution was affecting the EF. Fig. 56789shows the phylum distribution of the microbial communities of all inocula. The dominant phylum in InA, InC and InD was Firmicutes, representing 45.6±2.6%, 96.5±2.3% and 56.2±0.9%, respectively. Meanwhile InB and InE were dominated by Proteobacteria (48.4±3.8%) and Bacteroidetes (40.5±0.3%), respectively. Firmicutes are commonly linked to H2 production systems mainly for Clostridia spp. and Bacillus spp. [START_REF] Si | The role of hydraulic retention time on controlling methanogenesis and homoacetogenesis in biohydrogen production using upflow anaerobic sludge blanket (UASB) reactor and packed bed reactor (PBR)[END_REF]. Besides, Firmicutes play a very important role in anaerobic environments such as in the lakes depths and landfill sediments, associated with the degradation of organic matter [START_REF] Maintinguer | Bacterial diversity from environmental sample applied to bio-hydrogen production[END_REF]. Species belonging to Proteobacteria have also been widely studied in the H2 production, thanks to their ability to maintain anaerobic conditions in the reactors (e.g. Enterobacter spp.) [START_REF] Fang | Effect of pH on hydrogen production from glucose by a mixed culture[END_REF], [START_REF] Maintinguer | Bacterial diversity from environmental sample applied to bio-hydrogen production[END_REF], [START_REF] Patel | Enhancing biological hydrogen production through complementary microbial metabolisms[END_REF]. Proteobacteria are widely reported in anaerobic sludge, aerobic sludge and food waste [START_REF] Maintinguer | Bacterial diversity from environmental sample applied to bio-hydrogen production[END_REF]. Bacteroidetes have also been reported in H2-producing reactors, but since their function is not clearly elucidated since it has not received a great attention [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. inoculum was heat pre-treated, it is expected that spore-forming bacteria were preferentially selected [START_REF] Baghchehsaraee | The effect of heat pretreatment temperature on fermentative hydrogen production using mixed cultures[END_REF], [START_REF] Guo | Hydrogen production from agricultural waste by dark fermentation: A review[END_REF], [START_REF] Navarro-Díaz | Ecological perspectives of hydrogen fermentation by microbial consortia: What we have learned and the way forward[END_REF]. In InB the dominant families were Saprospiraceae and Rhodocyclaceae, representing 14.6±1.4% and 11.3±0.6%, respectively. Both families have been reported in wastewater treatment systems, performing important functions such as the degradation of complex organic matter and in denitrification processes, respectively [START_REF] Kim | Use of food wasterecycling wastewater as an alternative carbon source for denitrification process: A full-scale study[END_REF]- [START_REF] Xu | Microbial community compositions in different functional zones of Carrousel oxidation ditch system for domestic wastewater treatment[END_REF]. In InC, Sporolactobacillaceae was dominant, representing 83.8±2.4%. Generally, this lactate-producing bacteria is not dominant in H2-producing reactors. However, since the inoculum was taken from the reactor outlet storage, probably uncontrolled pH conditions favoured its abundance. In InD, the dominant families were group_MBA03 (Clostridia), Bacteroidaceae and Ruminococcaceae, representing 15.8±0.3%, 13.9±0.1% and 13.3±0.2%, respectively. Particularly uncultured group_MBA03 (Clostridia), has recently been reported in an anaerobic reactor processing wastewater with high oil content [START_REF] Nazina | Phylogenetic Diversity of Microorganisms from the Sludge of a Biogas Reactor Processing Oil-Containing and Municipal Waste[END_REF]. Although the InD, as already been reported in literature [START_REF] Bundhoo | Effects of pre-treatment technologies on dark fermentative biohydrogen production: A review[END_REF]. In the case of Ruminococcaceae family, this family has been reported with an important hydrolytic activity when complex substrates are used during H2 production [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF], [START_REF] Navarro-Díaz | Ecological perspectives of hydrogen fermentation by microbial consortia: What we have learned and the way forward[END_REF]. Finally, uncultured group_vadinHA17 (Bacteroidetes) family was dominant in InE, representing 19.5±0.4%. Particularly, this family has been reported as dominant in a UASB reactor treating poultry slaughterhouse wastewater [START_REF] Mota | Biohydrogen production at pH below 3.0: Is it possible?[END_REF]. First, a Mantel test was performed to evaluate the correlation existing between the initial inoculum microbial community, the final metabolites produced and the final microbial community. For that, three matrices with Euclidean distance data were prepared, including conventional fermentation (F) and electro-fermentation (EF) data. As observed in Then, to know whether the inoculum microbial community distance matrix was affecting the correlation between the other two matrices i.e. metabolites produced and final microbial community, a Partial Mantel test was performed. Interestingly, this new test shows that the inoculum source affected the correlation between final microbial community and the metabolites produced (ZM= 6.33, rM= 0.301 and pvalue= 0.003).

As the inoculum source influences the effect of electro-fermentation, it is interesting to find which are the bacterial families that mainly contribute to the differences and similarities between inocula. To start, a Non-metric multidimensional scaling (NMDS) was performed with Bray Curtis similarity index matrix from inoculum data (Fig. [START_REF] Sreedhar | A Bird's Eye view on process and engineering aspects of hydrogen storage[END_REF][START_REF] Grimes | Light, Water, Hydrogen[END_REF][START_REF] Sinha | An evaluative report and challenges for fermentative biohydrogen production[END_REF][START_REF] Toledo-Alarcón | Basics of bio-hydrogen production by dark fermentation[END_REF][START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF][START_REF] Hung | Roles of microorganisms other than Clostridium and Enterobacter in anaerobic fermentative biohydrogen production systems--a review[END_REF][START_REF] Wang | Factors influencing fermentative hydrogen production: A review[END_REF]. This figure shows that inocula are separated depending on the source, through their microbial community distances. Different points for the same inoculum correspond to the number of replicates analysed. All inocula were tested in duplicate, except for InB which was quadruplicate.

Then, to determine whether the differences between the different inoculum sources (Fig. 5-11) are statistically significant, an analysis of similarities was made, ANOSIM. This analysis was performed with 9999 permutations using Bray Curtis similarity index, reporting a mean rank within inoculum of 5.5, mean rank between inoculum of 38.5, R=1 and pvalue=0.0001. According to this analysis, when R is close to 1, more differences exist between the analysed data, i.e. in our case the inocula. Thus, it is possible to conclude that the differences observed in Fig. 5 that, a similarity of percentages (SIMPER) test was performed to determine which families was mainly contributing to the differences between inoculum and in what percentage (Table 5-4). Enterobacteriaceae family is contributing with 3.0% in dissimilarity between these two inoculum groups. In particular, Clostridiaceae family was more abundant in Ep inoculum.

From the statistical analyses it can be concluded that the members of the Clostridiaceae family are key. Because the Clostridiaceae family was negligible in the InC, InD and InE inocula, no effect of the polarized electrodes was observed. However, members of this family were significantly present in InA and InB, but with a higher relative abundance in InA leading to this inoculum causing a positive effect due to polarized electrodes, increasing the production of H2.

In short, our findings are insufficient to ensure that polarized electrodes have a special effect on Clostridia species, but their relative abundance in the inoculum plays a crucial role.

Conclusion

In this Chapter was studied the influence of initial microbial community during the electrofermentation operated in both continuous and batch mode.

Our results evidence that electro-fermentation had only an impact on the initial bacterial community selection that is lost in continuous operation. The effect of selection of H2producing bacteria in presence of polarized electrodes observed in Chapter 4 was not predominant, maybe because the selection pressure was more important by imposing the hydraulic retention time. However, different inoculum source were used in both cases, which could explain different EF behaviour.

Thereafter, inocula from different sources showed a significant impact on the existing correlations between final microbial community and metabolic patterns. The relative abundance of H2-producing bacteria, especially Clostridiaceae family, in the initial inoculum seems to be a determining parameter affecting the final electro-fermentation behaviour.

CHAPTER 6

Investigating the electrofermentation mechanisms by studying microbial interactions

Introduction

As seen in the previous chapters, electro-fermentation is a promising control tool for bioprocesses that depends on the bacterial community composition and structure. However, the mechanism of actions behind the selection of hydrogen-producing bacteria that contribute to the changes in metabolic pathways are still unknown. One hypothesis could be that electroactive bacteria, such as G. sulfurreducens, play a key role in transferring electrons, even though they were subdominant species. Electroactive bacteria can take/release electrons directly from/toward the polarized electrodes, while at the same time they establish different types of interactions within the bacterial community in the bulk. But, many of the possible interactions that can occur are unknown to date [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF].

In this context, this chapter aims to study the metabolic pattern changes in presence of G. sulfurreducens, during conventional dark fermentation and electro-fermentation. Specific objectives are: i. Study the changes in metabolic pathways during glucose dark fermentation when a mixed culture is enriched in G. sulfurreducens.

ii. Study the influence on metabolic pattern during glucose electro-fermentation when a electrode is precolonized with G. sulfurreducens.

Increased fermentative hydrogen production using acidogenic sludge as inoculum enriched with G. sulfurreducens

Context and specific experimental methodology

In this section, the effect on metabolic patterns, mainly focused on H2 production by dark fermentation, of an inoculum enriched in electroactive bacteria was investigated. In this case acidogenic sludge was used as inoculum and was previously enriched with G. sulfurreducens (MG) at the ratio 1:1. As control, non-enriched inoculum from the same source, was used (M). All tests were performed in 100 ml bottles in quadruplicate using glucose and acetate as carbon source.

Hydrogen production and metabolite distribution

After 24 hours of batch operation, the glucose was totally consumed in all reactors (4.6±0.03 gCOD.l -1 ). Total COD mass balance calculated from soluble products and H2 gas ranged between 81.7 and 88.8%. The biomass concentration at the end of operation was 0.54±0.05 gVSS.l -1 and 0.40±0.03 gVSS.l -1 for MG and M, respectively. H2 production increased by 55.5% in MG (0.28±0.04 molH2.mol -1 glucose) with respect to M (0.18±0.01 molH2.mol -1 glucose). Despite the increase, only 7.0% of the theoretical maximum yield was reached [START_REF] Ghimire | A review on dark fermentative biohydrogen production from organic biomass : Process parameters and use of by-products[END_REF]. The low H2-yields observed are related with the high alcohol production, including 2,3-butanediol (2,3-BDO) and ethanol (Fig. 6-1). In M tests Ethanol and 2.3-BDO are more reduced than glucose, so their production is an alternative pathway to release the excess electrons from the cell catabolism. Consequently, H2 yields are lowered because acetate was not the main pathway for equilibrating the intracellular redox [START_REF] Hoelzle | Regulation mechanisms in mixed and pure culture microbial fermentation[END_REF], [START_REF] Niu | Characteristics of fermentative hydrogen production with Klebsiella pneumoniae ECU-15 isolated from anaerobic sewage sludge[END_REF].

Microbial community analysis and its link with the metabolic patterns

Microbial community analysis of the inoculum and after batch operation were performed. Enterobacteriaceae. Butyrate production was positively correlated with H2 production, Geobacteraceae and Clostridiaceae, while negatively with Enterobacteriaceae. As observed in previous chapters and consistently with the literature, high productions of H2 along with butyrate, are associated to an increase in the relative abundance of Clostridiaceae [START_REF] Palomo-Briones | Hydrogen metabolic patterns driven by Clostridium-Streptococcus community shifts in a continuous stirred tank reactor[END_REF], [START_REF] Lee | Thermodynamic evaluation on H2 production in glucose fermentation[END_REF].

Moreover, 2,3-BDO production was negatively correlated with H2 production, Geobacteraceae and Clostridiaceae, and positively correlated with abundance of Enterobacteriaceae. This is consistent with the literature since 2,3-BDO production is often associated to the presence of species from the Enterobacteriacea family, such as

Enterobacter aerogenes [START_REF] Zhang | Regulation of hydrogen production by Enterobacter aerogenes by external NADH and NAD+[END_REF] and Klebsiella pneumoniae [START_REF] Niu | Characteristics of fermentative hydrogen production with Klebsiella pneumoniae ECU-15 isolated from anaerobic sewage sludge[END_REF]. With respect to H2 and 2,3-BDO production, as mentioned above, they are two pathways available to control the intracellular redox potential, so that a high production of one leads to a decrease of the others [START_REF] Niu | Characteristics of fermentative hydrogen production with Klebsiella pneumoniae ECU-15 isolated from anaerobic sewage sludge[END_REF].

In particular, members of the Geobacteraceae family strongly correlated with the main metabolites, i.e. H2, butyrate and 2,3-BDO, evidencing the same tendency than

Clostridiaceae. This suggests that Geobacteraceae promoted changes in microbial interactions leading to an increase in H2 and butyrate production while 2,3-BDO production decreased. This point will be further investigated in the next section (Section 6.2.4).

CHAPTER 6:

Investigating the electro-fermentation mechanisms by microbial interactions studies 145 Enterobacteriaceae and Clostridiaceae families are composed of numerous well-known H2producing species. Commonly, in dark fermentation systems, many species from both families are interacting and contributing together for H2 production [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Unlike Enterobacter spp., Clostridia spp. are linked to higher H2 yields. Nonetheless, Enterobacter spp. are also considered as key species to maintain the anaerobic conditions that are strictly necessary for the growth of Clostridia spp. [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. Our results are evidencing that high both H2 yields and butyrate production are linked with an increase in the relative abundance of Clostridiaceae.

Electroactive bacteria are promoting novel microbial interaction to increase hydrogen production

In addition, a positive correlation between Clostridiaceae and Geobacteraceae, was found to be responsible for changes in the carbon flux from more reduced metabolites (i.e. 2,3-BDO) toward the H2 and butyrate production. Consistently, it was previously reported in the literature that C. pasteurianum and G. sulfurreducens can cooperatively grow through direct interspecies electron transfer [START_REF] Moscoviz | Cooperative growth of Geobacter sulfurreducens and Clostridium pasteurianum with subsequent metabolic shift in glycerol fermentation[END_REF]. In other words, G. sulfurreducens could oxidize the acetate from fermentation medium as sole electron source using C. pasteurianum as sole electron acceptor. This electron transfer would be favorable for both species, causing changes in metabolic pathways, as already reported in literature [START_REF] Moscoviz | Cooperative growth of Geobacter sulfurreducens and Clostridium pasteurianum with subsequent metabolic shift in glycerol fermentation[END_REF].

Decrease of fermentative hydrogen production using

anaerobic sludge as inoculum artificially enriched with G. sulfurreducens

Context and specific experimental methodology

In this section, anaerobic sludge was used as inoculum and was enriched with G. sulfurreducens (MC+G) at the ratio 1:1. As control, a non-enriched inoculum was used (MC). Tests were performed in 100 ml bottles in triplicate using glucose and acetate as carbon sources.

Hydrogen production and metabolite distribution

After 48 hours of batch operation, glucose was totally consumed in all reactors (5.6±0.2 gCOD.l -1 ). Total COD mass balance calculated on the basis of soluble products and H2 gas ranged between 72.1% and 86.9%. The biomass concentration at the end of operation was 1.45±0.03 gVSS.l -1 and 1.06±0.06 gVSS.l -1 for MC and MC+G, respectively. Contrary results were observed in the Section 6.2, where higher biomass concentration was obtained after fermentation in the inoculum enriched with G. sulfurreducens (MG) compared to wild inoculum (M).

Weirdly, the H2 yields decreased by 93% during MC+G tests (0.05±0.02 molH2.mol - In this case, the changes in the microbial interactions motivated by the inoculum enrichment with G. sulfurreducens, was detrimental to H2 production. Unlike to results observed in Section 6.2, neither H2 nor butyrate production were increased. Instead, lactate production was increased.

Microbial community analysis and its link with the metabolic patterns

Microbial community analysis of the inoculum and after batch operation were performed. (MC+G.i), the microbial composition was as follows: Geobacteraceae (13.9±1.5%), Saprospiraceae (12.8±0.05%) and Rhodocyclaceae (11.3±0.02%). Correlations existing between metabolic patterns and microbial communities were analysed by a Pearson correlation test (Table 6-3). H2 production positively correlated with the abundance of Clostridiaceae, but negatively with Streptococcaceae and Geobacteraceae.

Lactate production positively correlated with Streptococcaceae and negatively with H2 production. While, butyrate production negatively correlated with Streptococcaceae. The results are consistent with literature where Streptococcaceae family is a known lactate producer and often is linked to low H2 yields [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Noike | Inhibition of hydrogen fermentation of organic wastes by lactic acid bacteria[END_REF], [START_REF] Castelló | Possible causes for the instability in the H2production from cheese whey in a CSTR[END_REF]. The data used include all replicates from MC and MC+G. In bold were marked the significant correlations with p-values ≤0.05 (*) and pvalues ≤0.01 (**). Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour depending on value.

Influence of electroactive bacteria on fermentative hydrogen production

On the other hand, and contrary to the observations made in the past section (Section 6.2)

Clostridiaceae and Geobacteraceae families negatively correlated, so a cooperative growth did not occur in that case. Possibly, G. sulfurreducens was oxidizing the H2 produced by Clostridia spp. evidencing a extremely low H2 yield as observed in MC+G tests [START_REF] Coppi | Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Other Electron Acceptors by Geobacter sulfurreducens Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Ot[END_REF], [START_REF] Caccavo | Geobacter sulfurreducens sp. nov., a Hydrogen-and Acetate-Oxidizing Dissimilatory Metal-Reducing Microorganism[END_REF].

However, a final electron acceptor such as Fe(III), fumarate and quinines are required by G.

sulfurreducens, but any of them were supplied in the fermentation medium [START_REF] Coppi | Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Other Electron Acceptors by Geobacter sulfurreducens Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Ot[END_REF], [START_REF] Caccavo | Geobacter sulfurreducens sp. nov., a Hydrogen-and Acetate-Oxidizing Dissimilatory Metal-Reducing Microorganism[END_REF]. An alternative hypothesis would be that G. sulfurreducens was donating its electrons to some unknown species, analogously to what has been evidenced with C. pasteurianum [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF]. However, it is not possible to affirm it since more research is necessary. are not always harmful [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Castelló | Possible causes for the instability in the H2production from cheese whey in a CSTR[END_REF]. However, they have a toxic effect by bactericide synthesis, especially on Clostridia spp., mostly leading to a decrease of H2 yields [START_REF] Noike | Inhibition of hydrogen fermentation of organic wastes by lactic acid bacteria[END_REF], [START_REF] Rafrafi | Sub-dominant bacteria as keystone species in microbial communities producing bio-hydrogen[END_REF], [START_REF] Jo | Process stability and microbial community structure in anaerobic hydrogen-producing microflora from food waste containing kimchi[END_REF].

On the other hand, and contrary to the observations made in the past section (Section 6.2)

Clostridiaceae and Geobacteraceae families negatively correlated, so a cooperative growth did not occur in that case. Possibly, G. sulfurreducens was oxidizing the H2 produced by Clostridia spp. evidencing a extremely low H2 yield as observed in MC+G tests [START_REF] Coppi | Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Other Electron Acceptors by Geobacter sulfurreducens Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Ot[END_REF], [START_REF] Caccavo | Geobacter sulfurreducens sp. nov., a Hydrogen-and Acetate-Oxidizing Dissimilatory Metal-Reducing Microorganism[END_REF].

However, a final electron acceptor such as Fe(III), fumarate and quinines are required by G.

sulfurreducens, but any of them were supplied in the fermentation medium [START_REF] Coppi | Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Other Electron Acceptors by Geobacter sulfurreducens Identification of an Uptake Hydrogenase Required for Hydrogen-Dependent Reduction of Fe ( III ) and Ot[END_REF], [START_REF] Caccavo | Geobacter sulfurreducens sp. nov., a Hydrogen-and Acetate-Oxidizing Dissimilatory Metal-Reducing Microorganism[END_REF]. An alternative hypothesis would be that G. sulfurreducens was donating its electrons to some unknown species, analogously to what has been evidenced with C. pasteurianum [START_REF] Chatellard | The type of carbohydrates specifically selects microbial community structures and fermentation patterns[END_REF]. However, it is not possible to affirm it since more research is necessary. The data used include all replicates from MC and MC+G. In bold were marked the significant correlations with p-values ≤0.05 (*) and pvalues ≤0.01 (**). Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour depending on value.

Mixed culture electro-fermentation using electrodes

precolonized by G. sulfurreducens

Context and specific experimental methodology

In the previous sections it was seen how electroactive bacteria could influence the metabolic patterns during conventional dark fermentation. In this section, the effect on metabolic patterns during glucose electro-fermentation by using an electrode precolonized of planar graphite plate with G. sulfurreducens was investigated. For that, two sequential batchs were performed, GEF1 and GEF2 at -0.4 V vs SCE. Precolonized electrodes were used, while fresh inoculum + fermentation medium was added each time. Besides, conventional fermentation (F) was performed in duplicate as control.

Hydrogen production and metabolite distribution

After 24 hours of batch operation, the glucose was totally consumed in all reactors (5.3±0.1 gCOD.l -1 ). Total COD mass balance calculated from soluble products and H2 gas ranged between 60.7 and 70.5%. H2 yields and metabolic patterns (Fig. showed no significant difference between F, GEF1 and GEF2. The H2 yields were 0.34±0.07 molH2.mol -1 glucose, 0.30 molH2.mol -1 glucose and 0.31 molH2.mol -1 glucose respectively. In all the cases, the main metabolites were ethanol and 2,3-BDO, representing between 33.4 -34.4 %COD and 33.4 -34.4 %COD, respectively.

However, a large amount of COD was associated to "Others+Biomass", representing between 31.1 -34.4%COD. Lactate, acetate and butyrate were also detected, but in lower concentrations (<6.4%COD).

The electrons passing from fermentation medium to circuit electric was 43.9 C and 2.0 C for GEF1 and GEF2, respectively. Besides, considering H2 as the interest product, ƞEF calculated was low, representing 0.031 and 0.001, respectively. So, the biological H2

production was influenced at maximum 3.1% of the electrons passing through the polarized electrodes. These low ƞEF values are consistent with the literature for electro-fermentation process [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF].

Microbial community analysis

Initial and final microbial communities were analysed for samples taken in the fermentation bulk and electroactive biofilm (Fig. 6 The results show that using an electrode pre-colonized by G. sulfurreducens had no effect on metabolic pathways during glucose electro-fermentation. Contrary results have been reported

in literature, where important changes in both metabolic pathways and microbial community, have been linked to the interaction between G. sulfurreducens attached as biofilm and fermentative bacteria in the bulk [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF]. Probably, the applied potential during the electrofermentation (i.e. -0.4 V vs SCE) was not adequate to promote interactions between G.

sulfurreducens and fermentative bacteria and to favour its growth in the biofilm because its relative abundance decreased considerably between GEF1 and GEF2.

More probably, the inoculum microbial community structure and its composition are key factors in electro-fermentation process as it been evidenced in Chapter 5. Literature evidence that G. sulfurreducens can take electrons from electrode and release them to the fermentation medium through reduction reactions using redox mediators or with some bacteria such as Clostridia species by establishing a syntrophic relationship. In all cases, a better understanding of the microbial interactions occurring between electroactive and fermentative bacteria are essential for better controlling the process, but to date these interactions have not been intensively investigated. So, possibly the inoculum used was not adequate due to the absence of bacteria that could establish a cooperative growth with G. sulfurreducens

Conclusion

In this chapter, we investigated the microbial interactions using two different mixed cultures enriched with G. sulfurreducens during conventional H2 production by dark fermentation as well as the interaction between a mixed culture and G. sulfurreducens attached on the electrode during glucose electro-fermentation.

Significant changes in metabolic pathways related to bacterial communities selection when the inoculum was enriched with G. sulfurreducens were observed. The first inoculum, mainly composed of Enterobacteriaceae and Clostridiaceae, showed an increase in both H2 yield and butyrate production, associated with an increase in relative abundance of Clostridiaceae.

This change was assumed to result from a cooperative growth between Clostridiaceae and G.

sulfurreducens. The second inoculum, mainly composed of Saprospiraceae and Rhodocyclaceae, showed a decrease in H2 production, associated with increased in lactate production and the emergence of members of the Streptococcaceae family. However, in this case G. sulfurreducens action was not clear because of all the possible interactions that could have been established with the different fermentative bacteria, are still unknown.

Finally, no effect on the metabolic pathways was observed when a pre-colonized electrode with G. sulfurreducens was used during glucose electro-fermentation. These results were probably due to the impossibility of G. sulfurreducens to find an electron acceptor (not added in the fermentation medium) and therefore did not interact with bulk bacteria to establish a cooperative interaction. In this context, once again it is evident that initial microbial community is playing a crucial role in all electro-fermentation system.

Conclusion & Perspectives

Polarized electrodes physically affect the microbial community

An efficient selection of H2-producing bacteria and consequent changes in metabolism patterns was observed in Chapter 4. Two main metabolic behaviors were observed in EF. The first one was associated with high H2 yields and butyrate production and related to Clostridium butyricum selection. The second H2 producing pathway was associated to ethanol and acetate production related to Escherichia fergusonii and Enterobacter cloacae selection.

During conventional fermentation, a third metabolic pathway was observed and was associated to low H2 yields and lactate production due to Streptococcus equinus selection.

Our results are not fully explained for the electric current passing through the electrodes, which is consistent with the literature [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF], [START_REF] Moscoviz | Electro-fermentation triggering population selection in mixed-culture glycerol fermentation[END_REF], [START_REF] Zhou | Carbon and electron fluxes during the electricity driven 1,3-propanediol biosynthesis from glycerol[END_REF], [START_REF] Zhou | Development of bioelectrocatalytic activity stimulates mixed-culture reduction of glycerol in a bioelectrochemical system[END_REF].

In particular, [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF] reported that the zeta potential of C. pasteurianum can be more positive in the presence of a polarized electrode, while the cells are more

electronegative with an open circuit [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF]. Polarized electrodes could cause physiological changes in the surface cell affecting growth rates, which would disadvantage some species and thus giving others species the opportunity to emerge [START_REF] Wilson | Status of methods for assessing bacterial cell surface charge properties based on zeta potentil measurements[END_REF]. However, this physiological change could be positive by providing an advantage over the action of an inhibitor such as bacteriocin nisin (produced by lactate-producing bacteria), as proposed in Chapter 4. On the other hand, Jeong et al. 2013 efficiently applied an electric field as a inoculum pre-treatment for H2 production by dark fermentation, by selecting mainly Clostridia species [START_REF] Jeong | Application of an electric field for pretreatment of a seeding source for dark fermentative hydrogen production[END_REF].

In this context, it is interesting to study the glucose EF using keys species found in Chapter 4, through mono and co-cultures, as proposed in Table C&P.1. Studies with mono-cultures can show how each species is affected by the presence of polarized electrode with a special focus on how the zeta potential and cell morphology are changed. Then, co-culture studies could provide valuable information about changes in microbial interactions between two species due to polarized electrode influence. Finally, the EF mecanisms can be studied by simulating a mixed culture using a mixture of all these key species, as synthetic microbial consortium.

Regarding the operational parameters, the same ones used in the Chapter 4 experiments should be tested.

Importance of Clostridia spp. abundance in the inoculum

Our results evidence that the inoculum source has a significative impact on final microbial community and metabolite production (See Chapter 5). By using five different inoculum sources, three different EF behaviours were observed with respect to H2 production: positive, negative and neutral effect. Clostridiaceae family and their relative abundance seem to be critical in determining the final EF behaviours. Although Clostridia spp., specially C. pasteurianum is a known species collecting electrons directly from an electrode, the mechanism behind the EF on this genus selection remains unclear [START_REF] Choi | Electricity-driven metabolic shift through direct electron uptake by electroactive heterotroph Clostridium pasteurianum[END_REF].

Influence of inoculum source on H2 production by dark fermentation is often not considered and only few research studies are available [START_REF] Navarro-Díaz | Ecological perspectives of hydrogen fermentation by microbial consortia: What we have learned and the way forward[END_REF], [START_REF] Akutsu | Hydrogen production potentials and fermentative characteristics of various substrates with different heat-pretreated natural microflora[END_REF]. Depending of the microbial community composition in the inoculum, different metabolic patterns can be observed during dark fermentation [START_REF] Akutsu | Hydrogen production potentials and fermentative characteristics of various substrates with different heat-pretreated natural microflora[END_REF]. In addition, along with dominant bacteria, subdominant bacteria are known to play a key role during H2 production [START_REF] Rafrafi | Sub-dominant bacteria as keystone species in microbial communities producing bio-hydrogen[END_REF]. This evidence the importance of microbial interactions that govern the microbial community, which could be changed in the presence of polarized electrodes [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. On the other hand, bioaugmentation is a strategy used to increase the relative abundance of key H2-producing species, in a mixed cultures already containing a high microbial diversity [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF]. This strategy has been reported as efficient to increase H2 production between 1.5 -4 times, because the whole microbial community is supporting the H2 producing bacteria performances [START_REF] Cabrol | Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function[END_REF], [START_REF] Kotay | Novel dark fermentation involving bioaugmentation with constructed bacterial consortium for enhanced biohydrogen production from pretreated sewage sludge[END_REF], [START_REF] Marone | Hydrogen production from vegetable waste by bioaugmentation of indigenous fermentative communities[END_REF].

In this context, Clostridia spp. such as C. pasteurianum (known as electroactive and H2producing bacteria) and C. butyricum (species selected in Chapter 4) could be used to bioaugment mixed cultures with different microbial communities. Then, these bioaugmented inocula could be tested in glucose -fed EF. Additionally, different percentages of Clostridia spp. could be tested to study the influence of their relative abundance on the final EF behaviour. Overall, this study could provide key information about microbial interactions and how the microbial community interacts with the polarized electrode.

Interaction between G. sulfurreducens and fermentative bacteria

To date, EF mechanisms are not clearly elucidated. One hypothesis is that electroactive bacteria may be interacting with the polarized electrode, but also with fermentative bacteria [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. G. sulfurreducens is a known electroactive bacteria, which has evidenced a cooperatively growth with C. pasteurianum, a famous H2 producing bacteria [START_REF] Moscoviz | Cooperative growth of Geobacter sulfurreducens and Clostridium pasteurianum with subsequent metabolic shift in glycerol fermentation[END_REF]. Based on this cooperative growth, G. sulfurreducens was used to enrich two inocula with different microbial community compositions. The first inoculum, mainly composed of Enterobacteriaceae and Clostridiaceae, showed an increase in both H2 yield and butyrate

Conclusion & Perspectives

production, associated with an increase in relative abundance of Clostridiaceae. While the second inoculum mainly composed of Saprospiraceae and Rhodocyclaceae showed a decrease in H2 production, associated with an increase in lactate production and the emergence of members of the Streptococcaceae family.

Our results evidence that depending on the inoculum and probably the presence of Clostridia spp., the interactions between G. sulfurreducens and the fermentation bacterial community change. However, G. sulfurreducens has limited metabolic capacity and can only use acetate and H2 as electron donors, and only acetate as carbon source [START_REF] Caccavo | Geobacter sulfurreducens sp. nov., a Hydrogen-and Acetate-Oxidizing Dissimilatory Metal-Reducing Microorganism[END_REF], [START_REF] Lovley | Reach out and touch someone: Potential impact of DIET (direct interspecies energy transfer) on anaerobic biogeochemistry, bioremediation, and bioenergy[END_REF]. The number of electron acceptors that can be used by G. sulfurreducens is also limited, including metal ions such as Fe +3 , elemental sulphur, malate and fumarate. But none of them was added to the fermentation medium. The only option was that G. sulfurreducens releases its electrons by direct electron transfer toward fermentative bacteria as Clostridia spp. or other undetermined species.

In this context, it is proposed to study the interactions in co-cultures of G. sulfurreducens and fermentative bacteria keys reported in the Chapter 4. These species include C. butyricum, E.

fergusonii, E. cloacae and S. equinus. This study would reveal whether G. sulfurreducens can use other bacteria than C. pasteurianum as electron acceptors, providing new insights into microbial interactions. On the other hand, in addition to monitoring metabolism patterns during H2 production. It would also be interesting to evaluate changes on important redox regulators such as NAD + /NADH, as well as hydrogenases gene expression. The latter could evidence the H2 consumption as electron source by G. sulfurreducens.

CHAPTER 2 :

 2 H2 et qui contribue aux changements dans les voies métaboliques reste encore inconnu. Une hypothèse serait que les bactéries électroactives, telles que G. sulfurreducens, joueraient un rôle clé dans le transfert d'électrons, même s'il s'agit d'espèces sous dominantes. Les bactéries Résumé étendu xiii électroactives peuvent prendre/donner des électrons directement à des électrodes polarisées, tout en établissant différents types d'interactions avec la communauté bactérienne. Dans ce contexte, ce chapitre a pour objectif d'étudier les changements du profil métabolique en présence de G. sulfurreducens, pendant la fermentation sombre conventionnelle et l'EF. Des changements significatifs dans les voies métaboliques liés à la sélection des communautés bactériennes lorsque l'inoculum a été enrichi avec G. sulfurreducens ont été observés. Le premier inoculum, composé principalement d'Enterobacteriaceae et de Clostridiaceae, a montré une augmentation du rendement en H2 et de la production de butyrate, associée à une augmentation de l'abondance relative des Clostridiaceae. Ce changement a été supposé résulter d'une croissance coopérative entre Clostridiaceae et G. sulfurreducens. Le deuxième inoculum, composé principalement de Saprospiraceae et de Rhodocyclaceae, a montré une diminution de la production de H2, associée à une augmentation de la production de lactate et à l'émergence de membres de la famille des Streptococcaceae. Cependant, dans ce cas, l'action de G. sulfurreducens n'était pas claire parce que toutes les interactions possibles avec les différentes bactéries fermentaires restent encore inconnues. Enfin, aucun effet sur les voies métaboliques n'a été observé lorsqu'une électrode précolonisée avec G. sulfurreducens a été utilisée pendant l'EF du glucose. Ces résultats étaient probablement dus à l'impossibilité pour G. sulfurreducens de trouver un accepteur d'électrons (non ajouté dans le milieu de fermentation) et son impossibilité d'interagir avec les bactéries en solution pour établir une interaction coopérative. Résumé étendu xiv Perspectives En général, les changements observés pendant l'EF ne sont pas associés au courant qui passe à travers les électrodes polarisées, il serait donc intéressant d'évaluer les changements physiques possibles que les cellules subiraient pendant l'EF et, ensuite, comment ces changements peuvent modifier les interactions microbiennes en culture mixte. Dans ce contexte, il serait intéressant d'étudier l'EF du glucose en utilisant des mono et co-cultures de bactéries clés observées au cours de cette thèse, en particulier C. butyricum, E. fergusonii, E. cloacae et S. equinus. en se concentrant sur l'étude des changements du potentiel zêta et de la morphologie cellulaire. D'autre part, nos résultats montrent que l'abondance relative de Clostridia spp. dans l'inoculum semble être la clé du type d'effet qui sera observé pendant l'EF. Dans ce contexte, il serait intéressant d'utiliser des Clostridia spp. comme C. pasteurianum (bactérie électroactive et producteur de H2) et C. butyricum (espèce sélectionnée lors de cette thèse), pour bioaugmenter des cultures mixtes avec différentes communautés microbiennes. Ces inocula bioaugmentés pourraient alors être testés en EF. De plus, différents pourcentages de Clostridia spp. pourraient être testés pour étudier l'influence de leur abondance relative sur le comportement final de EF. Cette étude pourrait fournir des informations cruciales sur les interactions microbiennes et la façon dont la communauté microbienne interagit avec l'électrode polarisée. Enfin, l'une des hypothèses sur les mécanismes d'action de l'EF suggère que les bactéries électroactives comme G. sulfurreducens, peuvent agir comme médiateur redox entre l'électrode polarisée et les bactéries de fermentation dans la communauté microbienne. Ainsi, la croissance coopérative entre G. sulfurreducens et C. pasteurianum a été montrée précédemment au LBE. Dans ce contexte, il est proposé d'étudier l'interaction dans les co-Résumé étendu xv cultures de G. sulfurreducens et de bactéries fermentaires clés telles que rapportées lors de cette thèse. Ces espèces comprennent C. butyricum, E. fergusonii, E. cloacae et S. equinus. En outre, il serait intéressant d'évaluer les changements sur les régulateurs d'oxydoréduction cellulaire tels que NAD + /NADH, ainsi que l'expression des gènes des hydrogénases. Ce dernier pourrait mettre en évidence la consommation de H2 comme source d'électrons par G. sulfurreducens. xvi 1.4 Electro-fermentation: how to drive fermentation using electrochemical systems? ................. 1.4.1 Basics of Electro-fermentation ........................................................................................ 1.4.2 First evidence of metabolic pattern changes and microbial community selection in electro-fermentation ..................................................................................................................... 1.4.3 Possible microbial interactions with the polarized electrodes ......................................... 1.4.3.1 Direct interspecies electron transfer (DIET) .......................................................... 1.4.3.2 Mediated interspecies electron transfer (MIET) ..................................................... 1.4.4 Action mechanisms of electro-fermentation ................................................................... Materials and methods ...............................................................................................

  & Perspectives ............................................................................................................... References ..........................................................................................................................................

Fig. 1 - 1 : 1 Fig. 1 - 1 : 13 Fig. 1 - 2 : 21 Fig. 1 - 3 : 31 Fig. 1 - 4 : 33 Fig. 1 - 5 : 35 Fig. 1 - 6 : 37 Fig. 1 - 7 : 42 Fig. 1 - 8 : 43 Fig. 1 - 9 : 45 Fig. 2 - 1 : 60 Fig. 2 - 2 : 61 Fig. 2 - 3 : 63 Fig. 2 - 4 : 72 Fig. 3 - 1 : 78 Fig. 3 - 2 : 80 Fig. 3 - 3 : 81 Fig. 3 - 4 : 83 Fig. 3 - 5 : 84 Fig. 3 - 6 : 88 Fig. 3 - 7 :

 111111312211331143315351637174218431945216022612363247231783280338134833584368837 Fig. 1-1: Shares of primary energy since 1900 and its projection until 2040 ......................................... 1 Fig. 1-1: Metabolic pathways during dark fermentation when mixed cultures are used. ..................... 13 Fig. 1-2: Principals pretreatments reported using on mixed cultures to increase the H2 yields. A: Main pretreatments used. B: Details of "Others" pretreatments shown in A. ................................................ 21 Fig. 1-3: H2 partial pressure effect on dark fermentation pathway ....................................................... 31 Fig. 1-4: Simplified diagram of a fermentation process ....................................................................... 33 Fig. 1-5: Main factors affecting extracellular and intracellular redox .................................................. 35 Fig. 1-6: Process configurations of electro-fermentation system including possible interactions between electrode and fermentation medium ....................................................................................... 37 Fig. 1-7: Main extracellular electron transfer mechanism reported on literature .................................. 42 Fig. 1-8: Proposed mechanisms for interspecies electron transfer through Direct interspecies electron transfer (DIET)...................................................................................................................................... 43 Fig. 1-9: Hypothetical mechanisms that could be occurring during anodic electro-fermentation ........ 45 Fig. 2-1: Referential image showing reactors design used during this thesis ....................................... 60 Fig. 2-2: Materials used to equip electro-fermentation reactors in this thesis ...................................... 61 Fig. 2-3: Schematic diagram of experimental start-up for electro-fermentation tests performed in dualchamber reactors ................................................................................................................................... 63 Fig. 2-4: Typical curve of current production during electrode colonization by G. sulfurreducens ..... 72 Fig. 3-1: Hydrogen yield observed during Electro-fermentation tests using single chamber reactors and different electrode materials ........................................................................................................... 78 Fig. 3-2: Hydrogen yield observed in fermentation control and electro-fermentation tests using single chamber reactors and Pt-Pt electrodes. ................................................................................................. 80 Fig. 3-3: Metabolite distribution observed during electro-fermentation tests using single chamber reactors and Pt-Pt electrodes ................................................................................................................. 81 Fig. 3-4: Phylum distribution of microbial community observed in inoculum and at the end of both control and electro-fermentation tests ................................................................................................... 83 Fig. 3-5: Family distribution of microbial community observed during control and electrofermentation tests using single chamber reactors and Pt-Pt electrodes ................................................. 84 Fig. 3-6: Hydrogen yield observed during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors ........................................................................... 88 Fig. 3-7: Metabolite distribution observed during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors.......................................................... 89

Fig. 5 - 1 : 116 Fig. 5 - 2 : 118 Fig. 5 - 3 : 120 Fig. 5 - 4 : 122 Fig. 5 - 5 : 124 Fig. 5 - 6 : 125 Fig. 5 - 7 : 127 Fig. 5 - 8 : 128 Fig. 5 - 9 : 132 Fig. 5 - 10 : 133 Fig. 5 -

 5111652118531205412255124561255712758128591325101335 Fig. 5-1: Hydrogen volumetric productivity during all time of continuous operation ........................ 116 Fig. 5-2: Metabolite distribution observed during steady state of continuous operation when conventional fermentation (CF) was performed ................................................................................. 118 Fig. 5-3: Family distribution of microbial community observed during continuous operation of electro-fermentation and conventional fermentation. ......................................................................... 120 Fig. 5-4: Principal component analysis (PCA) based on microbial population distribution and metabolite production. ........................................................................................................................ 122 Fig. 5-5: Hydrogen yields during glucose electro-fermentation using different inoculum ................. 124 Fig. 5-6: Metabolite distribution during glucose electro-fermentation using different inoculum ....... 125 Fig. 5-7: Family distribution of final microbial community from glucose electro-fermentation using different inoculum ............................................................................................................................... 127 Fig. 5-8: Principal component analysis (PCA) performed with variance-covariance matrix from microbial population distribution after batch operation and metabolic patterns ................................. 128 Fig. 5-9: Phylum distribution of microbial community in the inoculum from different sources ........ 132 Fig. 5-10: Family distribution of microbial community in the inoculum from different sources ....... 133 Fig. 5-11: Non-metric multidimensional scaling (NMDS) performed with Bray Curtis Similarity index from inoculum data. ............................................................................................................................ 135

Fig. 1 - 1 :

 11 Fig. 1-1: Shares of primary energy since 1900 and its projection until 2040

Fig. 1 - 1 :

 11 Fig. 1-1: Metabolic pathways during dark fermentation when mixed cultures are used.

Fig. 1 - 2 :

 12 Fig. 1-2: Principals pretreatments reported using on mixed cultures to increase the H2 yields. A: Main pretreatments used. B: Details of "Others" pretreatments shown in A.

  For example, Hussy et al. (2005) reported an increase in the H2 yield from 1.0 to 1.9 molH2.molhexoxe -1 by continuous N2 sparging at 40 ml.min -1 [116]. Similarly, Bastidas-Oyanedel et al. (2012) reported an H2 yield increase from 1.0 to 3.25 molH2.molglucose -1 by continuous N2 flushing at 40.5 ml.min -1 [122].

Fig. 1 - 3 :

 13 Fig. 1-3: H2 partial pressure effect on dark fermentation pathway

Fig. 1 - 4 :

 14 Fig. 1-4: Simplified diagram of a fermentation process (Adapted from [124])

Fig. 1 - 5 :

 15 Fig. 1-5: Main factors affecting extracellular and intracellular redox

Fig. 1 - 7 :

 17 Fig. 1-7: Main extracellular electron transfer mechanism reported on literature

Fig. 1 - 8 :

 18 Fig. 1-8: Proposed mechanisms for interspecies electron transfer through Direct interspecies electron transfer (DIET)

Fig. 1 - 9 :

 19 Fig. 1-9: Hypothetical mechanisms that could be occurring during anodic electrofermentation

  ) contained 0.5 U of Pfu Turbo DNA polymerase, Pfu Turbo buffer, 200 mM of each dNTP, 500nM of each primer and 10 ng of genomic DNA. Reactions were performed in a Mastercycler thermal cycler (Eppendorf, Hamburg, Germany) as follows: denaturing at 94 ºC for 2 min, 35 cycles of 94 ºC for 1 min, 65 ºC for 1 min and 72 ºC for 1 min, with a final elongation at 72 ºC for 10 min. The amount and size of PCR products were determined using a Bioanalyzer 2100 (Agilent). The community composition was evaluated using MiSeq v3 (Illumina) with 2x300 bp paired-end reads at the GenoToul platform

  -well real-time PCR plates (Eppendorf, Hamburg, Germany) and Mastercycler ep gradient S (Eppendorf, Hamburg, Germany). Then, 6.5 µL of Express qPCR Supermix with premixed ROX (Invitrogen, France), 2 µL of DNA extract with three appropriate dilutions, 100 nM forward primer F338-354 (5'-ACTCC TACGG GAGGC AG-3'), 250 nM reverse primer R805-785 (5'-GACTA CCAGG GTATC TAATC C-3'), 50 nM TaqMan probe, and water were added to obtain a final volume of 12.5 µL for all analyses.An initial incubation of 20 min at 95 ºC and 40 cycles of denaturation (95 ºC, 7 s; 60 ºC, 25 s) were performed. One standard curve was generated from each assay by using 10-fold dilutions in sterilized water (Aguettant Laboratory, Lyon France) of a target plasmid (Eurofins Genomics, Germany). The initial DNA concentrations were quantified using the Infinite 200 PRO NanoQuant (Tecan Group Ltd., France). The average number of bacterial cells were estimated by dividing the average number of 16S rRNA gene copies per cell by factor of 4.1[START_REF] Braun | Development and application of an enzymatic and cell flotation treatment for the recovery of viable microbial cells from environmental matrices such as anaerobic sludge[END_REF].

  Mantel test is a permutation test for correlation between two distance or similarity matrices derived from either multi or univariate data. The test compares the matrix in pairs under the null hypotheses: 'the distances among objects in the first matrix are not linearly correlated with the second matrix'.The Mantel statistic, ZM, is computed adding the cross products of the two similarity matrices being tested. As similarity matrices are symmetrical about their diagonals, half of each matrix (excluding values on the diagonal) is unfolded i.e. vectorized by stacking the values in each row below those of the previous the row, to compute their cross products. The rM value is simply the Pearson's correlation coefficient between all the entries in the two matrices. It ranges from -1.0 to + 1.0. The permutation test compares the original rM to rM computed in 9999 random permutations. Depending of p-value obtained the null hypothesis will be accepted or refused. In this thesis a p-value <0.05 was considered statically significant leading to refuse the null hypothesis, accepting the alternative hypothesis: 'the distances among objects in the first matrix are linearly correlated with the second matrix'[START_REF] Diniz-Filho | Mantel test in population genetics[END_REF]-[START_REF] Mantel | The detection of disease clustering and a generalized regression approach[END_REF]. Partial Mantel test allows to include the influence of a third data matrix. Only have sense to perform Partial-Mantel test when significative correlations were found between the two first data matrices tested. Thus, partial Mantel test is performed for the correlation of two first matrices, controlling for similarities given in the third data matrix[START_REF] Diniz-Filho | Mantel test in population genetics[END_REF],[START_REF] Legendre | Numerical Ecology[END_REF]. Mantel test and partial-Mantel test were calculated using PAST (PAleontological STatistics) version 3.20.

Fig. 2 - 1 :

 21 Fig. 2-1: Referential image showing reactors design used during this thesis

Fig. 2 - 2 :

 22 Fig. 2-2: Materials used to equip electro-fermentation reactors in this thesis

CHAPTER 2 : 63 Fig. 2 - 3 : 2 . 5 . 3

 26323253 Fig. 2-3: Schematic diagram of experimental start-up for electro-fermentation tests performed in dual-chamber reactors

Fig. 2 - 4 :

 24 Fig. 2-4: Typical curve of current production during electrode colonization by G. sulfurreducens

Fig. 3 - 1 :

 31 Fig. 3-1: Hydrogen yield observed during Electro-fermentation tests using single chamber reactors and different electrode materials

Fig. 3 - 2 :

 32 Fig. 3-2: Hydrogen yield observed in fermentation control and electro-fermentation tests using single chamber reactors and Pt-Pt electrodes.

Fig. 3 -

 3 Fig. 3-3 shows the metabolites distribution according to the COD mass balance. In the

Fig. 3 - 3 :Fig. 3 - 4 :

 3334 Fig. 3-3: Metabolite distribution observed during electro-fermentation tests using single chamber reactors and Pt-Pt electrodes

Fig. 3 -

 3 Fig. 3-8 shows the ORP measurements during batch operation time. Initially, a similar ORP

Fig. 3 - 9 :

 39 Fig. 3-9: Linear correlation between ORP measured in fermentation bulk and potential applied at working electrode

Fig. 3 - 11 :

 311 Fig. 3-11: Metabolite distribution observed during electro-fermentation tests comparing two electrodes sizes using dual-chamber reactors

Fig. 4 - 2 :

 42 Fig. 4-2: Family distribution of the microbial communities found in final samples of glucose electro-fermentations and fermentation controls

  with <1.0% relative abundance.

Fig. 5 - 1 :

 51 Fig. 5-1: Hydrogen volumetric productivity during all time of continuous operation

Fig. 5 - 2 :

 52 Fig. 5-2: Metabolite distribution observed during steady state of continuous operation when conventional fermentation (CF) was performed

Fig. 5 - 3 :

 53 Fig. 5-3: Family distribution of microbial community observed during continuous operation of electro-fermentation and conventional fermentation.

Figure A

 A Figure A shows the electro-fermentation operation (CEF).Figure B Shows the conventional fermentation (CF) i.e. without electrodes.

  Figure A shows the electro-fermentation operation (CEF).Figure B Shows the conventional fermentation (CF) i.e. without electrodes.

  -3), Clostridiaceae family remained dominant in CF (78.5%) and CEF-A (93.8%). Particularly, Clostridiaceae was favored with the electrode polarization in CEF-A, displacing Sporolactobacillaceae, Pseudomonadaceae and Streptococcaceae families. This is consistent with the result observed in Chapter 4, where H2-producing bacteria were favoured during the electrofermentation tests, while that Streptococcaceae family was disadvantaged.After 8 days of operation, Enterobacteriaceae family was favoured in CF, CEF-A and CEF-B, representing between 18.3% and 35.8% of microbial community, respectively. The only exception was day 16 where Enterobacteriaceae represented only between 5.4 and 7.0%. In fact, at day 9 a problem with the pH control led to system instability decreasing the H2 production, with an increase in Sporolactobacillaceae was observed, when compared with d8.

Fig. 5 - 4 :

 54 Fig. 5-4: Principal component analysis (PCA) based on microbial population distribution and metabolite production.

Fig. 5 - 5 :

 55 Fig. 5-5: Hydrogen yields during glucose electro-fermentation using different inoculum

Fig. 5 - 7 :

 57 Fig. 5-7: Family distribution of final microbial community from glucose electrofermentation using different inoculum

Fig. 5 - 8 :

 58 Fig. 5-8: Principal component analysis (PCA) performed with variance-covariance matrix from microbial population distribution after batch operation and metabolic patterns

Fig. 5 - 9 :

 59 Fig. 5-9: Phylum distribution of microbial community in the inoculum from different sources

Fig. 5 - 10 :

 510 Fig. 5-10: Family distribution of microbial community in the inoculum from different sources

Fig. 5 -

 5 Fig. 5-11: Non-metric multidimensional scaling (NMDS) performed with Bray Curtis Similarity index from inoculum data.

Fig. 6 - 1 :

 61 Fig. 6-1: Metabolite distribution observed during dark fermentation using acidogenic sludge as inoculum enriched with G. sulfurreducens

Fig. 6 -

 6 Fig.6-2 shows the family distribution of the microbial communities. In the inoculum (M.i)

Fig. 6 - 3 :

 63 Fig. 6-3: Metabolite distribution observed during dark fermentation using anaerobic sludge as inoculum enriched with G. sulfurreducens

Fig. 6 -

 6 Fig. 6-4 shows the family distribution of the microbial communities. The dominant families

Fig. 6 - 4 :

 64 Fig. 6-4: Family distribution of microbial community during dark fermentation using anaerobic sludge as inoculum enriched with G. sulfurreducens

CHAPTER 6 :

 6 Investigating the electro-fermentation mechanisms by microbial interactions studies 154 Table 6-4 shows the correlation matrix from family distribution of microbial communities at final time of batch operation. Significative correlations were observed between several families during this experiment. Clostridiaceae family negatively correlated with Streptococcaceae and Geobacteraceae. The influence of lactic acid bacteria such as members from the Streptococcaceae family, in H2-producing reactors, has been in debate because they

Fig. 6 - 5 :

 65 Fig. 6-5: Metabolite distribution observed during electro-fermentation using precolonized electrodes with G. sulfurreducens

CHAPTER 5: Electro-fermentation is affected by initial microbial composition

  Introduction ............................................................................................................................. 3.2 Selection of electrode material ................................................................................................ 3.3 Effect of platinum electrode on fermentation patterns ............................................................. 3.3.1 Hydrogen production and metabolite distribution........................................................... 3.3.2 Microbial community analysis and link with metabolic patterns .................................... 3.4 Effect of the applied potential on metabolic patterns .............................................................. 3.4.1 Hydrogen production and metabolite distribution........................................................... 3.4.2 Analysis of bio-electrochemical parameters ................................................................... Context and specific experimental methodology .......................................................... 5.3.2 Hydrogen and metabolite production ............................................................................ Introduction ........................................................................................................................... 6.2 Increased fermentative hydrogen production using acidogenic sludge as inoculum enriched with G. sulfurreducens .................................................................................................................... 6.2.1 Context and specific experimental methodology .......................................................... 6.2.2 Hydrogen production and metabolite distribution......................................................... 6.2.3 Microbial community analysis and its link with the metabolic patterns ....................... 6.2.4 Electroactive bacteria are promoting novel microbial interaction to increase hydrogen production .................................................................................................................................. 6.3 Decrease of fermentative hydrogen production using anaerobic sludge as inoculum artificially enriched with G. sulfurreducens ...................................................................................

	5.3 Glucose electro-fermentation effect is influenced by inoculum microbial community ..........
	5.3.1

2.1 Synopsis ................................................................................................................................... 2.2 Biomass determination and chemical analysis ........................................................................ 2.2.1 Liquid samples collection and biogas quantification ...................................................... 2.2.2 Volatile suspended solids and volatile solids .................................................................. CHAPTER 3: Starting with electro-fermentation and determination of parameters ..................

3.1 3.5 Size electrode selection ............................................................................................................ 3.6 Conclusion ............................................................................................................................... CHAPTER 4: Electro-fermentation triggering H2-producing bacteria ......................................... 4.1 Introduction .............................................................................................................................

4.1.1 Context and specific experimental methodology ............................................................ 4.2 Increase in H2 production and changes in metabolite distribution during glucose electrofermentation ...................................................................................................................................... 4.3 Microbial community analysis ............................................................................................... 4.4 The three mains metabolic pathways for H2 production in electro-fermentation resulted from microbial community selection ....................................................................................................... 4.5 Electro-fermentation patterns: low current is enough to trigger high changes in fermentation patterns ........................................................................................................................................... 4.6 Hypothetical action mechanisms during glucose electro-fermentation ................................. 4.7 Conclusion ............................................................................................................................. ....................... 5.1 Introduction ........................................................................................................................... 5.2 Glucose electro-fermentation during reactor operation in continuous mode........................ 5.2.1 Context and specific experimental methodology .......................................................... 5.2.2 Hydrogen and metabolite production ............................................................................ 5.2.3 Microbial community analysis and link with metabolic patterns .................................. 5.3.3 Link between final microbial community and metabolite patterns ............................... 5.3.4 Inoculum source is influencing the glucose electro-fermentation effect ....................... 5.4 Conclusion ............................................................................................................................. xxiv CHAPTER 6 ............. : Investigating the electro-fermentation mechanisms by studying microbial interactions ....................................................................................................................................... 6.1 6.3.1 Context and specific experimental methodology .......................................................... 6.3.2 Hydrogen production and metabolite distribution......................................................... 6.3.3 Microbial community analysis and its link with the metabolic patterns ....................... 6.3.4 Influence of electroactive bacteria on fermentative hydrogen production .................... 6.4 Mixed culture electro-fermentation using electrodes precolonized by G. sulfurreducens .... 6.4.1 Context and specific experimental methodology .......................................................... 6.4.2 Hydrogen production and metabolite distribution......................................................... 6.4.3 Microbial community analysis ...................................................................................... 6.5 Conclusion .............................................................................................................................

Table 1 -

 1 1: Main reactions during H2 production by dark fermentation ................................................ 14

Table 1 -

 1 2: H2 yields reported in literature when different inoculum pre-treatments where used during glucose dark fermentation ..................................................................................................................... 23

Table 1 -

 1 3: Reduction potential of important redox pairs involved in biological process ..................... 34

Table 2 -

 2 1: Theoretical COD ratio calculated for each compound measured in this thesis. .................. 54

Table 2 -

 2 2: Summary of the statistical analyses performed during this thesis ....................................... 58

Table 2 -

 2 3: Composition of fermentation medium used during electro-fermentation tests during this thesis ..................................................................................................................................................... 59

Table 2 -

 2

4: Summary of electro-fermentation tests show in the Chapter 3............................................ 66

Table 2 -

 2

5: Composition of trace element solution and vitamin solution .............................................. 70

Table 3 -

 3

1: Pearson correlation matrix based on metabolite production and microbial family abundance .............................................................................................................................................................. 86 Table 4-1: Relative abundance (%) of microbial community after 20 hours of batch operation based on MiSeq sequencing of 16S rRNA gene ........................................................................................... 104

Table 4 -

 4

2: Summary of ƞEF calculations for all replicates from each condition evaluated ............... 109

Table 5 -

 5

1: Inoculum from different sources used during glucose electro-fermentation ..................... 123

Table 5 -

 5

2: Pearson correlation matrix from microbial population distribution after batch operation and metabolic pattern using different inoculum ........................................................................................ 130 Table 5-3: Mantel tests performed with Euclidean distance matrix from inoculum microbial composition, metabolite production and final microbial composition ................................................ 134

Table 5 -

 5

4: Similarity of percentage analysis (SIMPER) performed to compare the family microbial composition of all inoculum data. ....................................................................................................... 136

Table 6 -

 6

1: Pearson correlation matrix from family distribution of final microbial community and metabolic patterns ............................................................................................................................... 145

Table 6 -

 6

2: Pearson correlation matrix from family distribution of final microbial community ......... 147

Table 6 -

 6

3: Pearson correlation matrix from family distribution of final microbial community and metabolic patterns ............................................................................................................................... 152

Table 6 -

 6

4: Pearson correlation matrix from family distribution of final microbial community ......... 155 Table C&P. 1: Experimental design proposed to study electro-fermentation using mono and cocultures of main OTU selected in Chapter 4 ....................................................................................... 162 xxvi

  3-8: ORP measurement in the fermentation bulk during electro-fermentation tests at different potential applied on the working electrode using single chamber reactors........................................... 91 Fig. 3-9: Linear correlation between ORP measured in fermentation bulk and potential applied at working electrode .................................................................................................................................. 92 Fig. 3-10: Hydrogen yield observed during electro-fermentation tests comparing two electrodes sizes using dual chamber reactors .................................................................................................................. 93 Fig. 3-11: Metabolite distribution observed during electro-fermentation tests comparing two electrodes sizes using dual-chamber reactors ....................................................................................... 95 Fig. 4-1: Metabolite distribution based on COD mass balance in final samples of glucose electrofermentation ........................................................................................................................................ 101 Fig. 4-2: Family distribution of the microbial communities found in final samples of glucose electro-

fermentations and fermentation controls ............................................................................................. 102 Fig. 4-3: Principal component analysis (PCA) based on microbial population distribution ............... 106 Fig. 4-4: Pearson correlation matrix based on metabolite production and microbial family abundance ............................................................................................................................................................ 107

  Family distribution of microbial community during dark fermentation using acidogenic sludge as inoculum enriched with G. sulfurreducens. ........................................................................ 143 Fig. 6-3: Metabolite distribution observed during dark fermentation using anaerobic sludge as inoculum enriched with G. sulfurreducens ......................................................................................... 149 Fig. 6-4: Family distribution of microbial community during dark fermentation using anaerobic sludge as inoculum enriched with G. sulfurreducens ..................................................................................... 150 Fig. 6-5: Metabolite distribution observed during electro-fermentation using precolonized electrodes with G. sulfurreducens ........................................................................................................................ 157 Fig. 6-6: Family distribution of microbial community observed during electro-fermentation using precolonized electrodes with G. sulfurreducens ................................................................................. 158

	Hydrogen	H2
	Dark fermentation	DF
	Electro-fermentation	EF
	Hydrogen-consuming bacteria	HCB
	Hydrogen-producing bacteria	HPB
	Volatile fatty acids	VFA
	Maximum growth rate	µmax
	Adenosine triphosphate	ATP
	Nicotinamide adenine dinucleotide oxidized/reduced	NAD + /NADH
	Saturated calomel reference electrode	SCE
	Electro-fermentation efficiency coefficient	ηEF
	Ferredoxin oxidized/reduced	Fd, Fdox/Fdred
	Pyruvate-ferredoxin oxidoreductase	PFOR
	Pyruvate formate lyase	PFL
	Formate hydrogen lyase	FHL
	Hydraulic retention time	HRT
	Oxidation-reduction potential	ORP
	Bioelectrochemical reactors	BES
	Microbial fuel cells	MFC
	Microbial electrolysis cells	MEC
	Microbial electrosynthesis	MES
	Microbial desalination cells	MDC
	Extracellular electron transfer	EET
	Indirect extracellular electron transfer	MIET
	Direct extracellular electron transfer	DIET
	Chemical oxygen demand	COD
	Paleontological statistics	PAST
	Analysis of variance	ANOVA
	Principal component analysis	PCA
	Non-metric multidimensional scaling	NMDS
	Analysis of similarities	ANOSIM
	Similarity percentage	SIMPER
	Chronoamperometry	CA
	Cyclic Voltammetry	CV
	xxx

11: Non-metric multidimensional scaling (NMDS) performed with Bray Curtis Similarity index from inoculum data. ............................................................................................................................ 135 Fig. 6-1: Metabolite distribution observed during dark fermentation using acidogenic sludge as inoculum enriched with G. sulfurreducens ......................................................................................... 142 xxviii Fig. 6-2: xxix List of abbreviations

1.1 Synopsis

	This chapter aims to put in context the research questions addressed by this thesis. The main
	aspects of hydrogen production by dark fermentation are presented, including the different
	metabolic routes, the main bacterial species involved in the fermentative process and their
	known interactions in mixed cultures. Typical operational parameters such as substrate, pH,
	inoculum source is also reviewed, as well as how they affect the microbial communities and
	subsequent hydrogen performances. Finally, basics of electro-fermentation are presented
	together with the operational parameters that can affect it. So far not well documented, the
	possible mechanisms behind electro-fermentation and the use of polarized electrodes are
	discussed.
	This chapter has been written based on the following scientific publications:
	i. J. Toledo-Alarcón, G. Capson-Tojo, A. Marone, F. Paillet, A. D. N. Ferraz Júnior, L.
	Chatellard, N. Bernet, and E. Trably, Basics of bio-hydrogen production by dark
	fermentation, no. 9789811076763. 2018.
	ii. R. Moscoviz, J. Toledo-Alarcón, E. Trably, and N. Bernet, "Electro-Fermentation:
	how to drive fermentation using electrochemical systems" Trends Biotechnol., vol.
	34, no. 11, pp. 856-865, 2016.

Table 1 -1: Main reactions during H2 production by dark fermentation (from

 1

	However,

Table 1 -2: H2 yields reported in literature when different inoculum pre-treatments where used during glucose dark fermentation (Adapted from

 1

	Inoculum Source	Pre-treatment	Glucose (g.l -1 )	Operational conditions	H2 yields (molH2.molglucose -1 )	Ref.
	Anaerobic sludge	Heat (65 -121 °C 10 -90 min)	2 -25	30 -40 °C pH 5.5 -7.5	0.9 -2.41	[64], [68]-[76]
	Compost	Heat (105 °C, 2 h)	13.1	33.5 °C, pH 5.0	2.15	[77]
	Anaerobic sludge	Acid (pH 3, 24 h)	8 -20	35 -37 °C pH 6.5 -7.0	0.27 -1.51	[42], [63], [69], [71]-[73]
	Anaerobic sludge	Base (pH 10, 24 h)	8 -20	35 -37 °C pH 6.5 -7.0	0.25 -1.72	[63], [69], [71]-[73]
	Anaerobic sludge	Aeration (DO < 0.5 mg.l -1 , 12 h)	10	35 °C, pH 6.8	1.96	[42]
	Anaerobic sludge	Aeration (Continuous 24 h)	10	35 °C, pH 7.0	0.86	[69]
	Anaerobic sludge	Chloroform (2%, 24 h)	10	37 °C, pH 7.0	0.66	[69]
	Anaerobic sludge	Ultrasonication (20 -79 Kj.gTS -1 , 24 h)	8 -8.5	37 °C, pH 6.5 -6.8	1.03 -1.70	[72], [78]
		Freeze & thaw
	Anaerobic sludge	(-25 °C, 24 h and room	20	37 °C, pH 7.2	0.17	[79]
		temperature, 5h)
	Anaerobic sludge	Electric current (10V, 10 min)	20	37 °C, pH 7.0	1.43	[80]
	Anaerobic sludge	Ionizing radiation (0.5 -10 kGy)	10	36 °C, pH 7.0	1.41 -2.14	[71], [81], [82]
	Anaerobic sludge	Heat (100°C, 30 min) & Base (pH 10, 24 h)	10	35 °C, pH 6.5	2.45	[83]

[START_REF] Wang | Principle and application of different pretreatment methods for enriching hydrogen-producing bacteria from mixed cultures[END_REF]

)

Table 1 -3: Reduction potential of important redox pairs involved in biological process

 1

	Redox pairs	E 0 (V)	Redox pairs	E 0 (V)
	2H + /H2	-0.41	Pyruvate -/lactate -	-0.19
	Ferredoxin ox/red	-0.38	Fumarate/Succinate	+ 0.03
	NAD + /NADH	-0.32	Cytochrome b ox/red	+ 0.03
	Cytochrome c3 ox/red	-0.29	NO2 -/NO	+ 0.36
	CO2/Acetate -	-0.29	NO3 -/NO2 -	+ 0.43
	CO2/CH4	-0.24	O2/H2O	+ 0.82

  Clostridium population was dominant and valerate production was also increased[START_REF] Dennis | Dynamics of cathodeassociated microbial communities and metabolite profiles in a glycerol-fed bioelectrochemical system[END_REF].Moscoviz et al., 2017 studied the influence of polarized electrodes, previously colonized with

	was shown [151]. Consistently, Dennis et al., 2013 showed that an electrical current of -240
	mA impacted the microbial community leading to the production of different molecules,
	depending the microbial community selected during 9 weeks of operation. Thus, during the

[START_REF] Xue | Efficient bioconversion of organic wastes to high optical activity of L-lactic acid stimulated by cathode in mixed microbial consortium[END_REF]

reported an increase of 4.7 times in lactate production from organic wastes when working with a cathodic EF poised at -0.1V vs SHE. This change was attributed to a strong selection of Lactobacillus and Caldicoprobacter genera

[START_REF] Xue | Efficient bioconversion of organic wastes to high optical activity of L-lactic acid stimulated by cathode in mixed microbial consortium[END_REF]

. In contrast, Xafenias et al., 2015 reported an increase of 1.3 propanediol production related to Clostridium sp. selection during glycerol EF, while in the control test (without electrode) lactate production related to the presence of Lactobacillaceae first week Citrobacter population was dominant, with 1,3-propanediol and ethanol as main metabolites. Then, Pectinatus population was increased at expenses of Citrobacter population, and propionate was the main metabolite. After about 6 weeks of operation,

  𝑁(𝐶 𝑤 𝑁 𝑥 𝑂 𝑦 𝐻 𝑧 ) = 4𝑤 -3𝑥 -2𝑦 + 𝑧 𝑄 𝑒-is estimated from chronoamperometry by integrating the electric current over the operation time. 𝑄 𝐻 2 is calculate from 𝑛 𝐻 2 × 𝑁 𝐻 2 × 𝐹. Where 𝑛 𝐻 2 is moles of H2 produced, 𝑁 𝐻 2 is 2 mol H2/ mol e -(Eq. 2-4) and F is Faraday constant (96,485 C/mol e -).

	Eq. 2-3
	𝜂 𝐸𝐹 =	𝑄 𝑒-𝑄 𝐻 2	=	∫ 𝐼𝑑𝑡 𝑛 𝐻 2 × 𝑁 𝐻 2 × 𝐹
	Eq. 2-4

Table 2 -

 2 1 summarize the theoretical COD ratio for each compound measured in this thesis. As an example, considering glucose the balanced equation is 𝐶 6 𝐻 12 𝑂 6 + 𝟔𝑂 2 → 6𝐶𝑂 2 + 6𝐻 2 𝑂.

Table 2 -1: Theoretical COD ratio calculated for each compound measured in this thesis.

 2

	Compound	Empirical formula	Molar weight [g.mol -1 ]	Theoretical COD [go2.g -1 compound]
	Glucose	𝐶 6 𝐻 12 𝑂 6	180.2	1.07
	Dihydrogen	𝐻 2	2.0	8.00
	Formic Ac.	𝐶𝐻 2 𝑂 2	46.0	0.35
	Succinic Ac.	𝐶 4 𝐻 6 𝑂 4	118.1	0.95
	Lactic Ac.	𝐶 3 𝐻 6 𝑂 3	90.1	1.07
	Ethanol	𝐶 2 𝐻 6 𝑂	46.1	2.09
	Acetic Ac.	𝐶 2 𝐻 4 𝑂 2	60.1	1.07
	Propionic Ac.	𝐶 3 𝐻 6 𝑂 2	74.1	1.51
	Butyric Ac.	𝐶 4 𝐻 8 𝑂 2	88.1	1.82
	2,3-Butanediol	𝐶 4 𝐻 10 𝑂 2	90.1	1.95
	Biomass	𝐶 5 𝐻 7 𝑂 2 𝑁	113.1	1.41
	COD Mass balance is performed by comparing the COD of each final fermentation products
	and COD of substrate consumed through multiplication of final concentration (obtained from

  [START_REF] Saady | Homoacetogenesis during hydrogen production by mixed cultures dark fermentation: Unresolved challenge[END_REF], 1.61. 2.18 and 1.05 gO2.l -1 for the glucose consumed, acetate, butyrate and ethanol, respectively. Then, by dividing each fermentation products by the glucose consumed and multiplying per 100, estimation of the mass balance is obtained. In this example the balance is 30.1%, 40.7% and 19.6% for acetate, butyrate and ethanol respectively.

Table 2 -2: Summary of the statistical analyses performed during this thesis Type of analysis Objective of analysis Chapter

 2

	Pearson correlation	Correlation between metabolite production and final microbial community	Chapter 3, 4, 5 & 6
	Pearson correlation	Correlation between members of final microbial community	Chapter 6
	ANOVA	Determine whether H2 yields have statistically significant differences between the conditions studied	Chapter 4
	PCA	Represent the relationships between final microbial communities and reactor performances	Chapter 4 & 5

Table 2 -3: Composition of fermentation medium used during electro-fermentation tests during this thesis

 2

	Compound	Concentration (g.l -1 )	Solution A (Oligoelements)	Concentration (g.l -1 )
	Glucose	5.0	HCl 37%	46.0 mL
	𝐍𝐇 𝟒 𝐂𝐥	2.0	MgCl 2 × 6H 2 O	55.0
	𝐊 𝟐 𝐇𝐏𝐎 𝟒	0.5	FeSO 4 (NH 4 ) 2 SO 4 × 6H 2 O	7.0
	𝐅𝐞𝐂𝐥 𝟐 × 𝟒𝐇 𝟐 𝐎	8.6 mg	CoSO 4 × 7H 2 O	1.3
	Solution A	1 mL	MnCl 2 × 4H 2 O	1.2
	𝐌𝐄𝐒 (𝟏𝟎𝟎 𝐦𝐌)	19.5	ZnCl 2 × 2H 2 O	1.0
			Mo 7 O 24 (NH 4 ) 6 × 4H 2 O	1.0
			CuSO 4 × 5H 2 O	0.4
			BO 3 H 3	0.1
			NiCl 2 × 6H 2 O	0.05
			Na 2 SeO 3 × 5H 2 O	0.01
			CaCl 2 × 2H 2 O	60.0

Table 2 -4: Summary of electro-fermentation tests show in the Chapter 3 Study Material of working electrode Potential applied (V vs SCE) Reactor type

 2

		i. Graphite felt (5.2x3.5x3.5
		cm 3 )
	Selection of the electrode material	ii. Planar graphite plate (2.5x2.5 cm 2 )	-0.9	Single chamber
		iii. Grids of 90% platinum-
		10% iridium (2.5x2.5 cm 2 )
	Effect of the platinum electrode on metabolic patterns	Grids of 90% platinum-10% iridium (2.5x2.5 cm 2 )	-0.9	Single chamber
	Effect of different potential applied on the working electrode	Grids of 90% platinum-10% iridium (2.5x2.5 cm 2 )	-0.9, -0.7, -0.5 & -0.3	Single chamber
		Grids of 90% platinum-10%
	Effect of the electrode size	iridium of two sizes: i. 2.5x2.5 cm 2	-0.9	Dual chamber
		ii. 3.5x3.5 cm 2

Table 2 -5: Composition of trace element solution and vitamin solution

 2

	Trace element solution	Concentration (g.l -1 )	Vitamin solution	Concentration (mg.l -1 )
	𝐍𝐢𝐭𝐫𝐢𝐥𝐨𝐭𝐫𝐢𝐚𝐜𝐞𝐭𝐢𝐜 𝐚𝐜𝐢𝐝	1.50	Biotin	2.0
	𝐌𝐠𝐒𝐎 𝟒 × 𝟕𝐇 𝟐 𝐎	3.00	Folic acid	2.0
	𝐌𝐧𝐒𝐎 𝟒 × 𝐇 𝟐 𝐎	0.50	Pyridoxine -HCl	10.0
	𝐍𝐚𝐂𝐥	1.00	Thiamine -HCL × 2H 2 O	5.0
	𝐅𝐞𝐒𝐎 𝟒 × 𝟕𝐇 𝟐 𝐎	0.10	Riboflavin	5.0
	𝐂𝐨𝐒𝐎 𝟒 × 𝟕𝐇 𝟐 𝐎	0.18	Nicotinic acid	5.0
	𝐂𝐚𝐂𝐥 𝟐 × 𝟐𝐇 𝟐 𝐎	0.10	D -Ca -pantothenate	5.0
	𝐙𝐧𝐒𝐎 𝟒 × 𝟕𝐇 𝟐 𝐎	0.18	Vitamin B 12	0.10
	𝐂𝐮𝐒𝐎 𝟒 × 𝟓𝐇 𝟐 𝐎	0.01	p -Aminobenzoic acid	5.0
	𝐊𝐀𝐈(𝐒𝐎 𝟒 ) 𝟐 × 𝟏𝟐𝐇 𝟐 𝐎	0.02	Lipoic acid	5.0
	𝐇 𝟑 𝐁𝐎 𝟑	0.01
	𝐍𝐚 𝟐 𝐌𝐨𝐎 𝟒 × 𝟐𝐇 𝟐 𝐎	0.01
	𝐍𝐢𝐂𝐥 𝟐 × 𝟔𝐇 𝟐 𝐎	0.03
	𝐍𝐚 𝟐 𝐒𝐞𝐎 𝟑 × 𝟓𝐇 𝟐 𝐎	0.30 mg
	𝐍𝐚 𝟐 𝐖𝐎 𝟒 × 𝟐𝐇 𝟐 𝐎	0.40 mg

  The dominant families included

		70%
	(%) Distribution Phylum	18% 35% 53%		Proteobacteria Firmicutes Bacteroidetes Actinobacteria Chloroflexi Nitrospirae Ignavibacteriae Saccharibacteria Bacteria_unclassified Others (<1.0%)
		0%
		Initial	Control	EF
	Enterobacteriaceae, Clostridiaceae, Streptococcaceae and Aeromonadaceae that represented
	52.9±6.2% / 51.5±3.3%, 11.6±4.1% / 14.4±9.2%, 17.1±3.0% / 19.5±1.4% and 3.9±1.4% /
	6.9±2.2% in Control / EF, respectively. Only small differences between the control and EF
	within the low abundant families were observed. In particular, the control test had more
	families lower than 1.0% than the EF test. Probably, theses sub-dominants families generate a
	different support for dark fermentation in each case, changing the microbial interactions and
	consequently the metabolic patterns. Consistently, the key role of sub-dominant species was

Table 3 -1: Pearson correlation matrix based on metabolite production and microbial family abundance

 3

		Enterobacteriaceae	Clostridiaceae	Streptococcaceae	Aeromonadaceae	Prevotellaceae	Bacilli_unclassified	Planococcaceae	Lactobacillaceae	Rhodocyclaceae	Saprospiraceae	(<1.0%) Others	H2
	Succinate	0.64	0.04	-0.45	0.51	0.20	-0.01	-0.71	-0.74	-0.78	-0.67	-0.63	0.23
	Lactate	0.00	-0.27	-0.29	-0.85	-0.67	0.46	0.68	0.95	0.83	0.88	0.96	-0.93
	Acetate	0.78	-0.68	-0.17	0.79	0.77	0.14	-0.56	-0.45	-0.50	-0.60	-0.44	0.30
	Propionate	0.66	-0.21	-0.95	-0.17	-0.37	0.93	-0.34	0.37	-0.12	-0.01	0.20	-0.61
	Butyrate -0.47	0.55	0.57	0.48	0.39	-0.70	-0.30	-0.76	-0.50	-0.54	-0.73	0.86
	Ethanol	0.95	-0.40	-0.68	0.42	0.20	0.36	-0.61	-0.39	-0.56	-0.48	-0.31	-0.12
	ƞEF	0.05	-0.21	0.57	0.90	0.96	-0.56	-0.39	-0.78	-0.51	-0.68	-0.71	0.89
	H2 -0.25	0.25	0.54	0.81	0.74	-0.52	-0.50	-0.80	-0.64	-0.76	-0.86

Table 4 -1: Relative abundance (%) of microbial community after 20 hours of batch operation based on MiSeq sequencing of 16S rRNA gene

 4

	OTU	Putative identification (16S rRNA sequence similarity)	Control n=1 n=2 n=1 n=2 n=1 n=2 n=1 n=2 n=3 n=1 n=2 n=3 -0.9V -0.4V 0.4V 0.9V
	Enterobacteriaceae
	1	Escherichia fergusonii (99)	25.4 32.3 70.8 32.4 64.7 45.7 40.6 18.6 29.2 38.5 9.6 15.0
	4	Enterobacter cloacae (99)	4.9 5.3 9.1 43.4 1.5 3.5 26.6 48.1 7.5 18.4 27.5 17.9
	Total a		30.8 38.6 80.7 76.5 66.5 49.9 68.0 67.3 36.9 57.2 38.5 33.6
	Streptococcaceae
	2	Streptococcus equinus (99)	61.4 54.0 3.0 9.4 0.0 1.4 24.6 27.3 48.5 10.7 9.6 31.1
	Clostridiaceae
	3	Clostridium butyricum (99)	6.7 2.3 10.8 6.4 29.8 37.8 1.8 0.3 10.6 29.9 49.3 33.

Table 4 -2: Summary of ƞEF calculations for all replicates from each condition evaluated

 4

	Test		Qe-(C) mmolQe-/mole-total	ƞEF
	-0.9V	(n=1) -347.71 (n=2) -883.17	-11.309 -26.516	8.93E-02 2.26E-01
	-0.4V	(n=1) -0.10 (n=2) -0.25	-0.003 -0.008	2.22E-05 4.59E-05
		(n=1)	4.30	0.135	1.13E-03
	+0.4V	(n=2)	3.35	0.105	1.04E-03
		(n=3)	0.91	0.028	2.50E-04
		(n=1)	1.25	0.039	3.22E-04
	+0.9V	(n=2)	2.83	0.087	5.06E-04
		(n=3)	1.60	0.049	3.10E-04

  80 and 0.65 respectively. CF was dominated by Clostridiaceae and Lactobacillaceae families, representing 78.5 and 15.9% respectively. Meanwhile, CEF was dominated by Clostridiaceae, Sporolactobacillaceae, Pseudomonadaceae and Streptococcaceae families, representing 63.7, 11.8, 6.4 and 5.0%

Table 5 -1: Inoculum from different sources used during glucose electro-fermentation Inoculum Source Inoculum biomass (gVS.l -1 )

 5

	InA	Heat-treated anaerobic sludge sampled from a lab-scale anaerobic digester treating sewage sludge	37.7
	InB	Activated sludge sampled from sewage treatment plant in Narbonne	10.0
	InC	Acidogenic sludge sampled from H2-producing reactor fed with glucose	1.5
	InD	Heat-treated anaerobic sludge sampled from a lab-scale anaerobic digester treating food waste.	7.1

  However, there are species that can consume lactate to produce propionate, which could explain the great variability of these two metabolites in the duplicates[START_REF] Hoelzle | Regulation mechanisms in mixed and pure culture microbial fermentation[END_REF].

	In addition, Fig. 5-6 shows the metabolic distribution for each inoculum used. When InA was important part of the COD was attributed to Others+Biomass (57.9±1.2%COD). In InE, the
	used, butyrate (19.0±10.4%COD), acetate (14.3±1.2%COD) and ethanol (22.7±2.4%COD) main metabolites were propionate (35.5±1.8%COD) and ethanol (30.5±0.2%COD).
	increased during EF, with regards to F where the main metabolite was lactate
	(56.9±2.1%COD). When InB was used, the main metabolites during EF were butyrate
	(26.8±9.2%COD) and lactate (25.7±33.7%COD), while in F, butyrate reached 57.5±0.1%COD. In
	this case, a large difference was observed in lactate and propionate production between the
	2,0 When InC, InD and InE were used, not difference between EF and F was observed with H 2 Yield (mol H2 inoculum .mol -1 glucose ) 0% 25% 50% 75% 100% F EF F EF F EF F EF F EF InA InB InC InD InE Metabolite distribution (%COD Balance) EF duplicates. Fig. 5-6: Metabolite distribution during glucose electro-fermentation using different Lactate Butyrate Ethanol Acetate Propionate Others+Biomass
	respect to the metabolic patterns. In InC, the main metabolites were butyrate (24.5±1.6%COD)
	F	EF	F	EF	F	EF	F	EF	F	EF
	InA and ethanol (20.2±2.2%COD). While, ethanol (29.2±0.8%COD) was predominant in InD, an InB InC InD InE

  -7 shows the distribution of microbial families, evidencing that in all cases the main families were Enterobacteriaceae, Streptococcaceae and Clostridiaceae. In InA Streptococcaceae family

	was dominating during F (57.9±5.1%). However, during EF was replaced by
	Enterobacteriaceae (57.7±12.1%) and Clostridiaceae (36.5±5.5%). In InB, the
	Streptococcaceae family was dominant in both F (42.1±3.2%) and EF (56.2±23.7%). Despite
	the differences observed in the duplicates in EF, a lower relative abundance of
	Enterobacteriaceae (10.6±4.7%) and Clostridiaceae (23.7±19.9%) than in F was observed.
	In InC, InD and InE the main family was Enterobacteriaceae for EF and F, representing
	86.0±5.6%, 95.3±0.3% and 97.9±0.9%, respectively.

Table 5

 5

	-2Table 5-2). H2 yield

Table 5 -2: Pearson correlation matrix from microbial population distribution after batch operation and metabolic pattern using different inoculum

 5

	H2Y	Succinate	Lactate	Ethanol	Acetate	Butyrate	Other+Biomass	Diversity	Enterobacteriaceae	Streptococcaceae	Clostridiaceae	Prevotellaceae
	H2Y	0.41	-0.35	-0.05	0.49	0.40	-0.35	0.44	-0.14	-0.26 0.74** 0.67**
	Succinate 0.41		-0.49 0.73** 0.29 -0.39	0.29	-0.49	0.66* -0.77** -0.05	-0.14
	Lactate -0.35	-0.49		-0.57* -0.33 -0.24 -0.22	0.23	-0.48	0.79** -0.31	-0.30
	Ethanol -0.05 0.73** -0.57*		-0.03 -0.60* 0.53 -0.80** 0.95** -0.91** -0.44	-0.25
	Acetate 0.49	0.29	-0.33	-0.03		0.20	-0.23	0.32	-0.05	-0.27	0.54*	0.42
	Butyrate 0.40	-0.39	-0.24 -0.60* 0.20		-0.48 0.73** -0.62*	0.30	0.76** 0.56*
	Other+Biomass -0.35	0.29	-0.22	0.53	-0.23 -0.48		-0.54*	0.56*	-0.44	-0.45	-0.38
	Diversity 0.44	-0.49	0.23 -0.80** 0.32 0.73** -0.54*		-0.86** 0.59* 0.80** 0.57*
	Enterobacteriaceae -0.14	0.66*	-0.48 0.95** -0.05 -

0.62* 0.56* -0.86** -0.87** -0.60* -0.43 Streptococcaceae -0.26 -0.77** 0.79** -0.91** -

	CHAPTER 5: Electro-fermentation is affected by initial microbial composition
	Table
				0.27 0.30	-0.44	0.59* -0.87**		0.14	0.03
	Clostridiaceae 0.74** -0.05	-0.31	-0.44 0.54* 0.76** -0.45 0.80** -0.60*	0.14	0.77**
	Prevotellaceae 0.67** -0.14	-0.30	-0.25	0.42 0.56* -0.38	0.57*	-0.43	0.03	0.77**
	All data were used including F and EF in duplicates when correspond. In bold were marked the significant correlations with p-values ≤0.05
	(*) and p-values ≤0.01 (**). Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour
	depending on value

Table 5

 5

	-3,

Table 5 -3: Mantel tests performed with Euclidean distance matrix from inoculum microbial composition, metabolite production and final microbial composition

 5

	Inoculum microbial community	Metabolic patterns	Final microbial community
	Inoculum microbial community	ZM=56.3 rM= -0.179 pvalue=0.300	ZM=46.9 rM= 0.070 pvalue=0.458
	Metabolic patterns		ZM=89.0 rM=0.283
			pvalue=0.004
	Final microbial
	community

ZM is the Mantel statistic; rM value is simply the Pearson's correlation coefficient and ranges from -1.0 to + 1.0. Significance of the test was calculated from 9999 permutation. In this thesis a p-value <0.05 was considered statically significant to refuse the null hypothesis.

  -11 are statistically significative, i.e. all inocula used are

	InA
	InB
	InC
	InD
	InE
	significative different.
	Based on H2 production results, 3 groups can be made according to the effect observed during
	EF: positive effect (EP; InA), negative effect (EN; InB) and neutral effect (E0; InC, InD and

InE). In this context, studying the similarities and differences between bacterial communities could reveal what are the key bacteria determining the effect of electro-fermentation. For

Table 5 -4: Similarity of percentage analysis (SIMPER) performed to compare the family microbial composition of all inoculum data.

 5

		EN & E0		EP & E0		EN & EP
	Family	Dissim. contrib. %	Total %	Dissim. contrib. %	Total %	Dissim. contrib. %	Total %
	Sporolactobacillaceae	22.3	22.3	23.4	23.4	0.0	0.0
	Clostridiaceae	1.8	24.1	7.3	30.7	12.2	12.2
	Saprospiraceae	6.3	30.4	0.0	30.7	10.7	22.9
	Rhodocyclaceae	4.9	35.3	0.1	30.8	8.1	31.0
	Bacteroidetes vadinHA17	5.6	40.9	5.7	36.5	0.8	31.8
	Family_XI	1.5	42.4	3.2	39.7	5.6	37.4
	MBA03	4.6	47.0	4.8	44.5	0.0	37.4
	Unknown	1.9	48.9	3.0	47.4	4.3	41.7
	Ruminococcaceae	4.2	53.1	4.1	51.5	0.5	42.2
	Draconibacteriaceae	1.1	54.2	2.5	54.0	4.1	46.2
	Planococcaceae	0.1	54.3	2.4	56.4	4.1	50.3
	Bacteroidaceae	3.8	58.1	3.9	60.4	0.0	50.3
	Christensenellaceae	0.1	58.2	1.8	62.2	3.0	53.3
	Enterobacteriaceae	0.6	58.7	2.1	64.3	3.0	56.3
	Peptostreptococcaceae	1.0	59.7	2.0	66.3	2.9	59.2
	uncultured	1.8	61.5	0.4	66.7	2.8	62.1
	Acidimicrobiales_I.S.*	0.3	61.8	1.8	68.5	2.6	64.6
	Rikenellaceae	2.3	64.1	2.6	71.1	1.2	65.9
	Rhodospirillaceae	1.5	65.5	0.0	71.1	2.5	68.4
	Porphyromonadaceae	2.4	68.0	2.3	73.4	1.2	69.6
	Intrasporangiaceae	0.2	68.1	1.5	74.8	2.2	71.8
	Desulfuromonadaceae	1.9	70.1	2.0	76.9	0.0	71.8
	Xanthomonadales_I.S.*	1.2	71.3	0.0	76.9	2.0	73.8
	*I.S: abreviation of Incertae Sedis. EN: negative effect. EP: positive effect. E0: neutral effect.
	Dissim. contrib. % correspond to percentage that each family is contributing to dissimilarity
	between the groups compared. Total % correspond to accumulative contribution of each
	family to dissimilarity percentage.

Table 5 -

 5 [START_REF] Łukajtis | Hydrogen production from biomass using dark fermentation[END_REF] summarizes the results obtained in the SIMPER test, showing only families with a contribution to dissimilarity ≥2.0%. Comparing EN and E0, a dissimilarity of 92.7% was observed, mainly due to Sporolactobacillaceae (22.3%) and Saprospiraceae (6.3%).

	Sporolactobacillaceae was present in E0 and abundantly in InC but was absent in EN. Well-
	known families producing H2 such as Enterobacteriaceae and Clostridiaceae are found in
	very low concentrations in both inoculum groups and contributing less than 2.0% in the
	dissimilarity of these groups.
	By comparing EP and E0 a dissimilarity of 84.3% was observed, determined mainly by
	Sporolactobacillaceae (23.4%) and Clostridiaceae (7.3%) families. Clostridiaceae family is
	present in EP with a greater abundance than E0, while Sporolactobacillaceae is only present
	in E0. Besides, Enterobacteriaceae family is contributing with 2.1% in dissimilarity between
	these two groups. By comparing EP y EN a dissimilarity of 85.6% was observed, determined

mainly by Clostridiaceae (12.2%) and Saprospiraceae (10.7%) families. Besides

2: Family distribution of microbial community during dark fermentation using acidogenic sludge as inoculum enriched with G. sulfurreducens.

  Investigating the electro-fermentation mechanisms by microbial interactions studies 143 Enterobacteriaceae and Clostridiaceae were dominant, representing 73.8±2.1% and 14.9±1.6%, respectively. After inoculum was enriched with G. sulfurreducens (MG.i), the microbial community distribution was as follows: Enterobacteriaceae (54.8±1.3%),

	CHAPTER 6: Investigating the electro-fermentation mechanisms by microbial interactions
	studies
	Geobacteraceae (31.0±1.6%) and Clostridiaceae (8.5±1.3%).
	After 24 hours of operation, the microbial community in M (M.f) tests was similar to the
	inoculum and Enterobacteriaceae (69.3±5.7%) and Clostridiaceae (23.9±5.8%) remained
	dominants. However, in MG tests Clostridiaceae became dominant, representing 52.7±0.9%.
	While Enterobacteriaceae (38.7±0.8%) and Geobacteraceae (1.9±0.1%) decreased in terms
	of relative abundance.
	100%					Others (<2.0%)
	(%)						Flavobacteriaceae
	Distribution	50% 75%					Bacteroidaceae Streptococcaceae Enterococcaceae
	Family	25%					Geobacteraceae Clostridiaceae
		0%	M.i	MG.i	M.f	MG.f	Enterobacteriaceae
	Fig. 6-samples taken before
	and after fermentation are marked with "i" and "f", respectively. The figures represent the
	average of all replicates for each test. Error bars are representing the standard deviation.
	Significative correlations between metabolic patterns and final microbial community were
					144

In the inoculum (M.i) CHAPTER 6: M: wild inoculum. MG: inoculum enriched with G. sulfurreducens. The statistically analysed with a Pearson correlation test (Table 6-1). H2 production positively correlated with Geobacteraceae and Clostridiaceae abundances and negatively with

Table 6 -1: Pearson correlation matrix from family distribution of final microbial community and metabolic patterns

 6

		H2Y	Succinate	Lactate	Ethanol	Acetate	Propionate	Butyrate	2,3-BDO	Others+biomass
	H2Y		0.90**	-0.06	-0.61	-0.08	-0.92**	0.93**	-0.89**	-0.24
	Enterobacteriaceae	-0.90**	-0.97**	0.11	0.61	-0.13	0.97**	-0.98**	0.99**	0.08
	Clostridiaceae	0.90**	0.97**	-0.10	-0.61	0.15	-0.97**	0.97**	-0.99**	-0.05
	Geobacteraceae	0.93**	1.00**	-0.23	-0.71*	0.00	-1.00**	1.00**	-0.95**	-0.24
	Enterococcaceae	-0.81*	-0.93**	0.00	0.53	-0.25	0.93**	-0.92**	0.97**	-0.01
	Streptococcaceae	-0.38	-0.31	0.68	0.79*	-0.03	0.33	-0.29	0.17	-0.03
	Bacteroidaceae	0.89**	1.00**	-0.26	-0.74*	0.03	-1.00**	0.99**	-0.94**	-0.21
	Flavobacteriaceae	-0.72*	-0.69	-0.43	0.12	0.05	0.71*	-0.71*	0.75*	0.29
	Others (<2.0%)	-0.75*	-0.79*	-0.08	0.47	-0.16	0.81*	-0.78*	0.78*	0.18
	The data used include all replicates from M and MG. In bold were marked the significant correlations with p-values ≤0.05 (*) and p-values
	≤0.01 (**). Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour depending on
	value.

Table 6 -

 6 2 shows the correlation matrix constructed by family distribution of the microbial communities sampled at the end of batch operation. Enterobacteriaceae family negatively correlated with Clostridiaceae and Geobacteraceae, while Clostridiaceae and Geobacteraceae positively correlated.

Table 6 -2: Pearson correlation matrix from family distribution of final microbial community

 6

		Enterobacteriaceae	Clostridiaceae	Geobacteraceae	Enterococcaceae	Streptococcaceae	Bacteroidaceae	Flavobacteriaceae	Others (<2.0%)
	Enterobacteriaceae		-1.00**	-0.98**	0.95**	0.25	-0.97**	0.69	0.74*
	Clostridiaceae	-1.00**		0.97**	-0.95**	-0.26	0.96**	-0.68	-0.74*
	Geobacteraceae	-0.98**	0.97**		-0.91**	-0.33	0.99**	-0.68	-0.77*
	Enterococcaceae	0.95**	-0.95**	-0.91**		0.19	-0.93**	0.74*	0.87**
	Streptococcaceae	0.25	-0.26	-0.33	0.19		-0.34	-0.25	0.24
	Bacteroidaceae	-0.97**	0.96**	0.99**	-0.93**	-0.34		-0.68	-0.79*
	Flavobacteriaceae	0.69	-0.68	-0.68	0.74*	-0.25	-0.68		0.80*
	Others (<2.0%)	0.74*	-0.74*	-0.77*	0.87**	0.24	-0.79*	0.80*
	The data used include all replicates from M and MG. In bold were marked the significant correlations with p-values ≤0.05 (*) and p-values
	≤0.01 (**). Positive ( for 1.0), negative ( for -1.0) and null ( for zero) correlations were marked with gradient colour depending on
	value.

Table 6 -3: Pearson correlation matrix from family distribution of final microbial community and metabolic patterns

 6

		H2Y	Succinate	Lactate	Formate	Acetate	Propionate	Ethanol	Butyrate	Others+Biomass
	H2Y		-0.98*	-0.96*	0.91	0.84	0.76	0.89	0.95	-0.79
	Clostridiaceae	0.99**	-0.99**	-0.92	0.86	0.89	0.69	0.84	0.90	-0.73
	Streptococcaceae	-0.98*	0.92	0.97*	-0.94	-0.78	-0.84	-0.92	-0.96*	0.81
	Enterobacteriaceae	-0.43	0.59	0.33	-0.27	-0.36	-0.12	-0.34	-0.37	0.38
	Geobacteraceae	-0.98*	0.99**	0.88	-0.80	-0.91	-0.61	-0.79	-0.86	0.68
	Saprospiraceae	0.26	-0.15	-0.53	0.64	-0.28	0.82	0.66	0.56	-0.75
	Rhodocyclaceae	0.87	-0.80	-0.97*	1.00**	0.47	0.98*	0.99**	0.98*	-0.96*
	Aeromonadaceae	0.43	-0.29	-0.66	0.76	-0.07	0.90	0.75	0.67	-0.79
	Bacillaceae	0.33	-0.20	-0.59	0.69	-0.20	0.86	0.69	0.60	-0.76
	Pseudomonadaceae	0.65	-0.55	-0.84	0.91	0.16	0.99*	0.91	0.86	-0.94
	Bacillales_unclassified	-0.67	0.78	0.63	-0.58	-0.46	-0.46	-0.65	-0.66	0.68

Table 6 -4: Pearson correlation matrix from family distribution of final microbial community

 6

		Clostridiaceae	Streptococcaceae	Enterobacteriaceae	Geobacteraceae	Saprospiraceae	Rhodocyclaceae	Aeromonadaceae	Bacillaceae	Pseudomonadaceae	Bacillales_unclassified
	Clostridiaceae		-0.95*	-0.48	-0.99**	0.15	0.81	0.32	0.22	0.56	-0.68
	Streptococcaceae	-0.95*		0.24	0.91	-0.38	-0.92	-0.57	-0.46	-0.74	0.52
	Enterobacteriaceae	-0.48	0.24		0.54	0.16	-0.22	0.24	0.22	-0.04	0.94
	Geobacteraceae	-0.99**	0.91	0.54		-0.06	-0.75	-0.22	-0.12	-0.48	0.72
	Saprospiraceae	0.15	-0.38	0.16	-0.06		0.71	0.96*	0.99**	0.90	-0.13
	Rhodocyclaceae	0.81	-0.92	-0.22	-0.75	0.71		0.81	0.75	0.94	-0.55
	Aeromonadaceae	0.32	-0.57	0.24	-0.22	0.96*	0.81		0.99*	0.95*	-0.09
	Bacillaceae	0.22	-0.46	0.22	-0.12	0.99**	0.75	0.99*		0.93	-0.10
	Pseudomonadaceae	0.56	-0.74	-0.04	-0.48	0.90	0.94	0.95*	0.93		-0.38
	Bacillales_unclassified	-0.68	0.52	0.94	0.72	-0.13	-0.55	-0.09	-0.10	-0.38

Fig. 6-6: Family distribution of microbial community observed during electro- fermentation using precolonized electrodes with G. sulfurreducens Inoculum: initial

  -6). Dominant families in the inoculum were Enterobacteriaceae and Clostridiaceae, representing 64.5±2.3% and 23.6±0.6%, respectively. Initial biofilm in the precolonized electrode (We.i) was mainly composed by Geobacteraceae (94.9%), as expected because G. sulfurreducens was used to form the biofilm. Investigating the electro-fermentation mechanisms by microbial interactions studies 158 After batch fermentation, the dominants families in the inoculum remained dominant in F and GEF1, evidencing only small differences in their relative abundances. Enterobacteriaceae and Clostridiaceae families represent 76.4±12.5% and 18.1±11.7% respectively in F, while that in GEF1 55.0% and 35.0%, respectively. Besides, the microbial composition of the biofilm (We.1) changed and Geobacteraceae (28.2%) was no longer dominant and species from fermentation bulk, such as Enterobacteriaceae (31.6%) and Clostridiaceae (31.1%), were also attached to biofilm. sample from bulk fermentation. F:final conventional fermentation. GEF1: final of first electro-fermentation batch performed using precolonized electrode with G. sulfurreducens. GEF2: final of second electro-fermentation batch performed using precolonized electrode with G. sulfurreducens. We.i: initial sample from electrode biofilm. We.1: electrode biofilm after first batch. We.2: electrode biofilm after second batch. Inoculum and F represent the average of all replicates. Error bars are representing the standard deviation.After second batch (CEF2) the microbial composition in the fermentation bulk was still dominant for Enterobacteriaceae and Clostridiaceae, representing 64.7% and 17.2%, respectively. Besides, an increase in relative abundance of Bacteroidaceae (8.9%) family was observed. With respect to the biofilm (We.2), Geobacteraceae (9.4%) decreased in relative abundance, while Enterobacteriaceae (40.4%) and Bacteroidaceae (21.7%) became dominant. Additionally, our results show that ƞEF is positively linked to the relative abundance of Geobacteraceae in the biofilm.

	0% 25% 50% 75% 100% 25% (%COD balance) 100% Family Metabolite Distribution CHAPTER 6: 0% 50% Distribution 75% (%)	F	GEF1	GEF2	Others+Biomass H2 Butyrate Acetate Lactate Ethanol 2.3-BDO
	Inoculum	F	GEF1	GEF2	We.i	We.1	We.2
	Geobacteraceae	Enterobacteriaceae	Clostridiaceae
	Bacteroidaceae	Streptococcaceae		Others (<3.0%)

Table C&P . 1: Experimental design proposed to study electro-fermentation using mono and co-cultures of main OTU selected in Chapter 4

 C&P

		C. butyricum E. fergusonii	E. cloacae	S. equinus
	C. butyricum Mono-culture Co-culture	Co-culture	Co-culture
	E. fergusonii	Mono-culture Co-culture	Co-culture
	E. cloacae		Mono-culture Co-culture
	S. equinus			Mono-culture

Acknowledgements

Electro-fermentation reactors and start-up

Batch EF experiences were performed for 18 hours using a dual-chamber reactor with 0.9 L of working volume and 0.1 L of headspace in each chamber. Precolonized electrode with G. sulfurreducens (Section 2.9.2.2) and 90% platinum -10% iridium grids with a size of 3.5 cm x 3.5 cm were used as working and counter electrodes, respectively. The values of applied potentials at working electrode were -0.4 V vs SCE. Batch control experiments were also performed using a single-chamber reactor, in absence of polarized electrodes under similar operating conditions.

The EF experiments were carried out in two batch series keeping only the precolonized electrode. While controls were performed in duplicates.

CHAPTER 3

Starting with electro-fermentation and determination of parameters medium during the first 24 hours of batch operation (-322.5±229.8 C). That was confirmed by a low EF efficiency of ηEF = 0.18±0.12, with respect to H2 production. This value means that a maximum of 18% of the H2 produced came from the electrons supplied by the electrodes [START_REF] Moscoviz | Electro-Fermentation: How To Drive Fermentation Using Electrochemical Systems[END_REF]. Besides, a global coefficient of ηEF = 0.010±0.007, respect to all fermentation product was obtained. This value means that only a maximum of 1.0% of all fermentation product are affected for the electrons supplied by the electrodes, evidencing that only few extra electrons can substantially impact the metabolic patterns by dark fermentation.

Microbial community analysis and link with metabolic patterns

Microbial community analyses were performed with MiSeq sequencing. The samples were taken from the inoculum and at the end of the batch operation in the control and electrofermentation experiments. The main phyla found in the inoculum (Fig. 34) were Proteobacteria, Bacteroidetes and Actinobacteria, representing 56.3±1.7%, 26.0±0.8% and 4.0±0.8% of the total abundance, respectively. No OTU reached a relative abundance higher than 4.0%, that is consistent with a high diversity Simpson index of 0.992±0.001. In control tests, the main phyla were Proteobacteria and Firmicutes representing 62.4±6.5% and 33.9±6.0 of the abundance, respectively. Meanwhile, in EF tests, the main phyla were Proteobacteria, Firmicutes and Bacteroidetes representing 59.4±5.8%, 18.8±8.1% and 14.0±2.1, respectively. In both cases the Simpson diversity indexes decreased to 0.855±0.028 and 0.840±0.016 for Control and EF, respectively. As is expected, the microbial community after a fermentation process is less diverse compared with the inoculum. This because the operating conditions applied allow to this selecting of species.