David Ranava
email: david.ranava@northwestern.edu

Cassandra Backes

Ganesan Karthikeyan

Olivier Ouari

Audrey Soric

Marianne Guiral

María Luz Cárdenas

Marie Thérèse Giudici-Orticoni

Metabolic exchange and energetic coupling between nutritionally stressed bacterial species: the role of QS molecules

Formation of multi-species communities allows nearly every niche on earth to be colonized and exchange of molecular information among neighbouring bacteria in such communities is key for bacterial success. To clarify the principles controlling inter-species interactions, we previously developed a co-culture model with two anaerobic bacteria, Clostridium acetobutylicum (Gram-positive) and Desulfovibrio vulgaris Hildenborough (Gram-negative, sulfate-reducing). In conditions of nutritional stress for D. vulgaris, the existence of tight cell-cell interactions between the two bacteria induced emergent properties. Here we show that the direct exchange of carbon metabolites produced by C. acetobutylicum allows D vulgaris to duplicate its DNA and to be energetically viable even without its substrates. We identify the molecular basis of the physical interactions, and how AI-2 molecules control the interactions and metabolite exchanges between C. acetobutylicum and D. vulgaris (or Escherichia coli and D. vulgaris). With nutrients D. vulgaris produces a small molecule that inhibits in vitro the AI-2 activity, and could act as an antagonist in vivo.

Sensing of AI-2 by D. vulgaris could induce formation of an intercellular structure that allows directly or indirectly metabolic exchange and energetic coupling between the two bacteria IMPORTANCE Bacteria have usually been studied in single culture in rich media or in specific starvation conditions. However, in nature they coexist with other microorganisms, and build an advanced society. The molecular bases of the interactions controlling this society are poorly understood. Using synthetic consortium and reducing complexity allow us to shed light on the bacterial communication at the molecular level. This study presents evidence that QS molecule AI-2 allows physical and metabolic interactions in the synthetic consortium and provides new insights into the link between metabolism and bacterial communication.

Introduction

Microbial communities are ubiquitous and exert a large influence in geochemical cycles and health [START_REF] Conrad | Soil microorganisms as controllers of atmospheric trace gases (H 2 , CO, CH 4 , OCS, N 2 O, and NO)[END_REF][START_REF] Newman | Geomicrobiology: how molecular-scale interactions underpin biogeochemical systems[END_REF][START_REF] Falkowski | The microbial engines that drive Earth's biogeochemical cycles[END_REF][START_REF] Gibbons | Microbial diversity--exploration of natural ecosystems and microbiomes[END_REF]. In natural environments, stress factors such as nutrient deficiencies and the presence of toxic compounds can induce interactions between microorganisms from the same or different species and the establishment of communities which can occupy ecological niches otherwise inaccessible to the isolated species [START_REF] Haruta | Intertwined interspecies relationships: approaches to untangle the microbial network[END_REF][START_REF] Phelan | Microbial metabolic exchange-the chemotype-to-phenotype link[END_REF]. Interactions between microorganisms can affect the behaviour of the community either positively or negatively [START_REF] Little | Rules of engagement: interspecies interactions that regulate microbial communities[END_REF].

For studying ecological communities, it is crucial to understand how the different members communicate with each other and how this communication is regulated.

Interactions may occur either by release of molecules into the environment [START_REF] Morris | Black Queen evolution: the role of leakiness in structuring microbial communities[END_REF], or by direct contact between the microorganisms through structures like nanowires [START_REF] Pirbadian | Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components[END_REF] or nanotubes [START_REF] Dubey | Intercellular nanotubes mediate bacterial communication[END_REF]. Dubey and Ben-Yehuda were the first to demonstrate a contactdependent exchange of cytoplasmic molecules via nanotubes in Bacillus subtilis which contributes to proper colony [START_REF] Dubey | Architecture and Characteristics of Bacterial Nanotubes[END_REF][START_REF] Mamou | Early Developmental Program Shapes Colony Morphology in Bacteria[END_REF]. The evolution of how metabolites came to be transferred between bacteria, and its functioning today, were both well described [START_REF] Souza | Ecology and evolution of metabolic cross-feeding interactions in bacteria[END_REF].

The type and extent of nutritional interactions between microbes partly determine the metabolism of an entire community in a given environment [START_REF] Souza | Experimental Evolution of Metabolic Dependency in Bacteria[END_REF]. Very little is known about the molecular basis of interactions between species, as this is difficult to investigate, especially in Nature, on account of community complexity. The use of a synthetic microbial ecosystem has considerable interest because the reduced complexity means that the investigation is more manageable, allowing not only identification of the specific community response, but also description of the different events at the molecular and cellular level [START_REF] Roy | Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities[END_REF].

To further investigate interactions between bacterial species we developed a synthetic microbial consortium constituted by two species: C. acetobutylicum, Grampositive, and D. vulgaris, Gram-negative, sulfate reducing. There are both involved in anaerobic digestion of organic waste matter [START_REF] Heidelberg | The genome sequence of the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough[END_REF][START_REF] Muyzer | The ecology and biotechnology of sulphate-reducing bacteria[END_REF]. Glucose, a substrate that cannot be used by D. vulgaris [START_REF] Heidelberg | The genome sequence of the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough[END_REF], is the sole carbon source in this synthetic consortium. Under this condition, the consortium produces three times more H 2 than C. acetobutylicum alone, moreover D. vulgaris is able to grow even in the absence of sulfate, its final electron acceptor for the respiration process [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF]. Although D. vulgaris can ferment lactate, a metabolite produced by C. acetobutylicum, this process is greatly inhibited by high H 2 concentrations, preventing D. vulgaris from growing in the absence of methanogens [START_REF] Walker | Functional responses of methanogenic archaea to syntrophic growth[END_REF]. We observed a form of bacterial communication between adjacent cells of both types of bacteria by cell-cell interaction, in conditions of nutritional stress, with exchange in both directions of cell material, associated with the modification of the metabolism [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF]. In some cases, the interactions between C. acetobutylicum and D. vulgaris, resembled those described by Dubey and Ben-Yehuda [START_REF] Dubey | Intercellular nanotubes mediate bacterial communication[END_REF]. Moreover, this type of cell-cell interactions has been seen also in other systems, which give support to its existence and functionality [START_REF] Dubey | Intercellular nanotubes mediate bacterial communication[END_REF][START_REF] Souza | Ecology and evolution of metabolic cross-feeding interactions in bacteria[END_REF].

Nutritional stress appears crucial to induce physical contact between bacteria, as this interaction was prevented by the presence of lactate and sulfate, nutrients of D. vulgaris. Furthermore, Pande et al [START_REF] Pande | Metabolic cross-feeding via intercellular nanotubes among bacteria[END_REF] in a synthetic co-culture of E. coli and Acinetobacter baylyi, after depletion of aminoacids such as histidine and tryptophan by genetic manipulation, observed nanotubular structures between the auxotrophs allowing cytoplasmic exchange. As in our case, the communication between the mutants was prevented by the presence of the nutrients. The formation of nanotubes between aminoacid-starved bacteria might be a strategy to survive under aminoacid limiting conditions [START_REF] Souza | Ecology and evolution of metabolic cross-feeding interactions in bacteria[END_REF]. Further evidence for the role of cell-cell connections to exchange nutrients can be found in these reviews [START_REF] Pande | Bacterial Unculturability and the Formation of Intercellular Metabolic Networks[END_REF][START_REF] Pande | Chimeric Synergy in Natural Social Groups of a Cooperative Microbe[END_REF][START_REF] Baidya | Bacterial nanotubes: a conduit for intercellular molecular trade[END_REF].

Altogether these studies suggest that for some species, cell-cell interaction (either by tight cell junctions, nanotube formation, vesicle chains, or flagella) can allow them to overcome nutrient starvation and that many materials, from small molecules to proteins or plasmids, can be passed from one cell to another. However, this requires not only an energetic investment to establish the connecting structures, but also to find the suitable partners. Several questions arise: what sorts of signals are involved? What is the molecular mechanism? The fact that in several cases a nutritional stress induces interaction, but addition of nutrients prevents it, raises the question whether there is a distress signal that is released from the starving bacteria, and another (a quenching factor) when nutrients are there? Specific signalling between cells is of great importance in the proper development of the community and in its stability in the long term [START_REF] Abisado | Bacterial Quorum Sensing and Microbial Community Interactions[END_REF].

Here we partially answer these questions; in particular, we examine if the nutritional stress, which appears to be necessary, is also sufficient. We have investigated the possible role that quorum-sensing molecules could play in attaching the two bacterial cells involved in the consortia previously studied: D. vulgaris and C. acetobutylicum or D. vulgaris and E. coli, and we have examined how satisfactory the energetic state of D. vulgaris is in the co-culture when it is deprived of sulfate, and why the presence of nutrients prevents interaction between these bacteria. [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF]. A similar phenomenon was observed between D. vulgaris and E. coli DH10B (18) (Supplementary Fig. 1). This growth suggests an adequate energetic state of D. vulgaris in co-culture, despite of the lack of sulfate, its final electron acceptor, and shows that it can use metabolites from C. acetobutylicum, as D. vulgaris cannot use glucose [START_REF] Heidelberg | The genome sequence of the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough[END_REF].

Results

Tight bacterial interaction in the co

To evaluate the physiological impact that C. acetobutylicum has on D. vulgaris in co-culture, we labelled D. vulgaris cells with Redox Sensor Green (RSG), a small molecule that can easily pass through the membranes of Gram-negative and Grampositive bacteria, used as a respiration sensor to identify metabolically active cells. It has been tested on numerous bacteria, as an indicator of active respiration in pure or co-cultures [START_REF] Pirbadian | Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components[END_REF][START_REF] Kalyuzhnaya | Real-time detection of actively metabolizing microbes by redox sensing as applied to methylotroph populations in Lake Washington[END_REF]. If D. vulgaris became metabolically active due to its physical interaction with C. acetobutylicum, then a RSG fluorescence should be detected as for D. vulgaris cultivated in GY medium supplemented by lactate and sulfate (respiration) (Fig. 1a). As expected, in respiration conditions i.e. in the presence of lactate and sulfate, substrates of D. vulgaris, D. vulgaris in pure culture grows well and all the cells show intense RSG fluorescence, in contrast to the culture in GY medium, where there is no growth and very few cells fluoresce (Fig. 1a andb). As a control, we added CCCP, which by dissipating the proton gradient and abolishing the ATP synthesis, tightly impacts RSG fluorescence (Supplementary Fig. 2). When D. vulgaris is labelled with RSG, as above, and then cultivated for 20h with C. acetobutylicum in GY medium, despite the lack of sulfate it shows a significant RSG fluorescence indicating that the cells have enough reducing power to reduce redox green and are metabolically active (Fig. 1c-e). Furthermore, C. acetobutylicum, which was not labelled by RSG at the beginning, also fluoresce intensely, indicating that RSG has been transferred from D. vulgaris. To investigate carbon exchange between the two bacteria, we used Stable Isotope Probing, growing C. acetobutylicum, either alone or in co-culture with unlabelled D. vulgaris, on 13 C-glucose medium. Total DNA were extracted from cells collected at the end of the exponential phase and 13 C-DNA (heavier) and 12 C-DNA (lighter) were separated by density-gradient centrifugation and examined on an agarose gel (Supplementary Fig. 3). Analysis of the different fractions using specific gene markers for the two bacteria shows that in the co-culture DNA from D. vulgaris is "heavy" ( 13 C-labelled), indicating that metabolites derived from 13 C-glucose were transferred between the two bacteria and used by D. vulgaris, despite the absence of sulphate. Quantitative PCR emphasized the presence of D. vulgaris 13 C-labelled-DNA with C. acetobutylicum 13 C-labelled-DNA in the same fraction (Fig. 2). A small amount of 12 C-unlabelled-DNA (from the two bacteria) can be detected in this highdensity fraction when an unlabelled co-culture is used, but not significant in relation to the total DNA and probably in line with the initial D. vulgaris inoculum. As D. vulgaris cannot grow on glucose or other hexoses, the 13 C-labelled-DNA from D. vulgaris must have been formed using metabolites produced by C. acetobutylicum.

C. acetobutylicum produces AI-2

As nutritional restrictions of D. vulgaris appear indispensable for inducing physical interactions between C. acetobutylicum and D. vulgaris, we investigated whether in addition to being necessary they were also sufficient, or if another element, such as quorum-sensing (QS) molecules, often associated with bacterial communication [START_REF] Pearson | Structure of the autoinducer required for expression of Pseudomonas aeruginosa virulence genes[END_REF][START_REF] Teplitski | Chlamydomonas reinhardtii secretes compounds that mimic bacterial signals and interfere with quorum sensing regulation in bacteria[END_REF] was required under our conditions. As the co-culture is composed by an association of Gram-positive and Gram-negative bacteria, AI-2, known to be involved in interspecies communication, appears as a good candidate to be tested [START_REF] Bassler | Bacterially speaking[END_REF]. It is widely accepted as the universal cell-to-cell signal in prokaryotic microorganisms [START_REF] Vendeville | Making 'sense' of metabolism: autoinducer-2, LuxS and pathogenic bacteria[END_REF][START_REF] Waters | Quorum sensing: Cell-to-cell communication in bacteria[END_REF]. Clostridium species are known to develop QS systems based on peptides, but QS remains relatively unknown in sulfate-reducing bacteria (SRB) although inferences on the presence of putative QS systems in them can be made [START_REF] Kawaguchi | Rapid screening of quorumsensing signal N-acyl homoserine lactones by an in vitro cell-free assay[END_REF] and that more recently a role of QS (AHL molecules) in D. vulgaris biofilm formation, electron transfer and metabolism was proposed [START_REF] Scarascia | Effect of Quorum Sensing on the Ability of[END_REF]. However, no AI-2 signalling/sensing had been described in C. acetobutylicum or D. vulgaris. To determine whether C. acetobutylicum could generate AI-2-like activity, a cell-free supernatant of exponential phase C. acetobutylicum culture was tested for its ability to induce luminescence in Vibrio harveyi BB170 AI-2 reporter strain. This cell-free supernatant stimulated luminescence in a similar manner to cell-free supernatant of exponential phase E. coli DH10B (AI-2 producer) culture (Fig. 3a). The last step of the AI-2 biosynthetic pathway is catalysed by the luxS gene product [START_REF] Chen | Structural identification of a bacterial quorum-sensing signal containing boron[END_REF], which is present in the C. acetobutylicum genome (CA_C2942) annotated as Sribosylhomocysteinase and could encode for the LuxS protein. Genetic engineering on genus Clostridium remains difficult and requires the utilization of specific genetic tools. To avoid this, and to test if this gene is involved in AI-2 production, the putative luxS gene from C. acetobutylicum was introduced in E. coli DH5α. which does not produce AI-2 due to a 60-amino-acid deletion stemming from a 1-bp deletion resulting in early truncation of luxS (formerly ygaG.) [START_REF] Surette | Quorum sensing in Escherichia coli, Salmonella typhimurium, and Vibrio harveyi: a new family of genes responsible for autoinducer production[END_REF]. E. coli DH5α is commonly used as negative control for AI-2 production in different bacterial strains [START_REF] Surette | Quorum sensing in Escherichia coli, Salmonella typhimurium, and Vibrio harveyi: a new family of genes responsible for autoinducer production[END_REF][START_REF] Xue | LsrR-binding site recognition and regulatory characteristics in Escherichia coli AI-2 quorum sensing[END_REF][START_REF] Mitra | Integration of AI-2 Based Cell-Cell Signaling with Metabolic Cues in Escherichia coli[END_REF]. As hypothesised, the cell-free supernatant of exponential phase of E. coli DH5α (luxS) culture, expressing the luxS gene of C. acetobutylicum has AI-2 activity (Fig. 3a). In contrast, D. vulgaris does not have a homolog of the luxS gene and the cell-free culture supernatant collected from exponential phase of D. vulgaris culture, grown in Starkey medium, does not have AI-2 activity, this agrees with what is observed with the cell-free culture supernatant of E. coli DH5α (Fig. 3a). As D. vulgaris does not produce AI-2, the AI-2 molecules present in the co-culture are likely to be produced by C. acetobutylicum. To verify whether C. acetobutylicum AI-2 production follows the growth, cell-free culture supernatant from C. acetobutylicum or from C. acetobutylicum and D. vulgaris co-culture taken at different times were used in the V. harveyi bioluminescence assay, as described in Materials and Methods. As shown in Fig. 3b andc, C. acetobutylicum can synthesize functional AI-2 molecules, the synthesis following the growth in single culture as well as in co-culture, indicating that its production is independent of the presence of D. vulgaris.

Cytoplasmic exchanges of molecules between bacteria in the co-culture as well as metabolic activity of D. vulgaris depend on the presence of AI-2.

As C. acetobutylicum and E. coli DH10B, used in the previous studies [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF], both produce AI-2, this raised the question of the situation if AI-2 was not present, that is if E. coli DH5α, were used. So E. coli DH5α or E. coli DH10B, both harbouring the pRSET-B mCherry plasmid containing the gene mCherry, was mixed with D. vulgaris cells lacking the mCherry gene but labelled with calcein or not, and the co-culture was analyzed by microscopy. Calcein-AM ester is a small non-fluorescent derivative of calcein which is sufficiently hydrophobic to pass readily through cell membranes.

Once it is inside, the AM group is cleaved by esterases, yielding the more hydrophilic calcein (623Da), which is unable to cross membranes and is sequestered in the cytoplasm. The loss of the AM group also enables calcein to readily bind intracellular calcium, resulting in a strong yellowish-green fluorescence. When D. vulgaris cells were cultivated on GY medium with E. coli DH10B, more than 90% of D. vulgaris cells acquired a mCherry fluorescence signal after 20h of culture (Fig. 4a panel Taken together, these results suggest that AI-2 is essential for cell-to-cell communication and exchange of cytoplasmic molecules in co-culture, but not sufficient, as nutritional stress is also required. These results may explain why in the work reported by Pande et al [START_REF] Pande | Metabolic cross-feeding via intercellular nanotubes among bacteria[END_REF] nanotubes, used to transfer amino acids, were observed between E. coli auxotrophe mutants, and between E. coli and Acinetobacter baylyi mutants, as in both cases there is the possibility of AI-2 produced by E. coli. In contrast, no nanotubes were observed between mutants of A. baylyi in which luxS is absent, in agreement with our genome bioinformatic analysis. So when AI-2 is not produced there may be no physical interaction even if there is a nutritional stress.

In view of the necessity of AI-2 to allow growth of D. vulgaris in the co-culture, we tested its effect on the energetic state of the cells with RSG, as in Fig. 1

D. vulgaris produces an antagonist of AI-2 in the presence of sulfate and under respiratory conditions.

The effect of AI-2 in the co-culture suggests that D. vulgaris can detect it.

However, lactate and sulfate in the co-culture medium allow the growth of the two bacteria but prevent physical contact between the two bacteria and the transfer of cytoplasmic molecules [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF] despite the fact that C. acetobutylicum and E. coli can produce AI-2. This suggests a regulatory mechanism linked to the presence of lactate and sulfate in the culture medium and/or to the sulfate respiration metabolism of D. vulgaris. At least two hypotheses may explain this: (i) in the presence of lactate and sulfate, C. acetobutylicum does not produce AI-2; (ii) D. vulgaris in the presence of sulfate produces one or several compound interfering with AI-2 activity.

The addition of lactate and sulfate to pure culture of C. acetobutylicum does not impair the production of AI-2 (Fig. 6a) and the C. acetobutylicum metabolism with 5--6 mM of butyrate produced. In contrast, in co-culture with D. vulgaris, the AI-2 activity detected in the sterile filtered culture supernatant of exponential phase, greatly decreased even in the presence of low quantity of lactate and sulfate (5mM), and was not detected by growing the co-culture in the presence of 10mM (Fig. 6a), suggesting that in sulfate respiratory conditions D. vulgaris could produce one or more metabolites that inhibit the activity of AI-2. To exclude the possibility that the supernatant taken from the culture grown in the presence of lactate/sulfate could inhibit the growth of the reporter strain, the growth of V. harveyi was measured. As shown in the supplementary figure 6, the addition of different supernatants does not affect the growth the V. harveyi An important point is that in these conditions butyrate was produced (5mM), indicating that C. acetobutylicum is metabolically active and that the lack of AI-2 is not due to a metabolic inactivity of C. acetobutylicum.

To test the presence of molecules that could interfere with AI-2 activity in sulfate respiratory conditions, we followed the AI-2 activity present in the exponential phase supernatants culture of E. coli or C. acetobutylicum in the presence of increasing amounts of supernatant culture of D. vulgaris grown in Starkey medium for 30h.

Sterile filtered culture supernatant of D. vulgaris inhibits AI-2 activity of C. acetobutylicum (Fig. 6b) and E. coli DH10B (Fig. 6c) cell-free supernatant, in a dosedependent manner, indicating that D. vulgaris, in the presence of lactate and sulfate and independently of the presence of the other bacteria, released into the culture medium an AI-2 inhibiting compound (or a mixture of such compounds) Figure 6: Inhibition of AI-2 activity. Addition of lactate and sulfate to the co-culture impaired AI-2 activity. Exponentially growing C. acetobutylicum in 2YTG medium or D. vulgaris in Starkey medium under anaerobic conditions was washed two times with fresh GY medium. Next, C. acetobutylicum was inoculated alone (black) or mixed with D. vulgaris (gray) into GY medium supplemented with increasing of lactate/sulfate (5 and 10mM). After 30h of incubation at 37°C, the AI-2 activity was then analyzed using the V. harveyi reporter strain BB170 (a). D. vulgaris supernatant inhibits AI-2 activity. C. acetobutylicum (C. a) strain was grown in GY medium during 30h at 37°C. The activity of AI-2 in the filtered samples was then analyzed using V. harveyi reporter strain BB170 in the presence of various quantities (1, 2, 4 and 8µL) of D. vulgaris filtered (0.2µm) supernatant grown on Starkey medium for 30h (b). AI-2 activity is reported as relative light unit (RLU) of BB170 bioluminescence. E. coli DH10B strain was grown in GY medium during 30h at 37°C. The activity of AI-2 in the filtered samples was then analyzed using V. harveyi reporter strain BB170 in the presence of various quantities ( We followed the production kinetics of the AI-2 inhibiting compound by D.

vulgaris by taking samples of sterile filtered supernatant at different times of the culture of D. vulgaris in Starkey medium. An AI-2 inhibitor is detected 3 hours after the beginning of growth (Supplementary Fig. 5). The production kinetics suggests a QS controlled expression. Microscopy analysis of E. coli and D. vulgaris co-culture in the presence of the D. vulgaris supernatant shows the loss of the interaction (Fig. 7).

The sulfate respiration process is probably associated with the production of an antagonist or antagonists that inhibit the AI-2 activity. This production requires to the presence of sulfate, and is independent of the presence of C. acetobutylicum or E. coli. To identify the compounds that interfere with the activity of AI-2, the cell-free supernatant of D. vulgaris, grown in Starkey medium for 30h, was analyzed by HPLC.

All the major peaks (P1-P5) were recorded and their ability to inhibit AI-2 activity was determined on the supernatant of exponential phase E. coli DH10B culture. Under our test conditions, the peak P5 has a stronger effect on AI-2 activity than to P1-P4 (Fig. 8a andb). The peak (P5), which contains a 186Da molecule (Fig. 8a, indicated by black arrow) significantly, inhibits the AI-2 activity in a dose-dependent manner (Fig. 8c). Interestingly, we observed similar inhibition of AI-2 activity in the presence of peak 5 when using an in vitro synthesized AI-2. As the addition of D. vulgaris supernatant does not impair the growth of V. harveyi (Supplementary Fig. 6), the bioluminescence reporter strain, this result suggests the direct impact of molecules produced by D.vulgaris on AI-2 activity. The peak 5 analysis by mass spectrometry reveal a compound which has a molecular mass equivalent to that of AI-2 (192,9Da), suggesting a similar type of molecule that could act as a competitive inhibitor. Taken together, these data show that the AI-2 receptor LuxP of V. harveyi can recognize the compound present in peak P5. However, it is still unclear whether this compound also binds to the AI-2 binding site or whether LuxP contains an independent binding site for this new compound. Different strategies for obtaining the structure did not succeed, probably because as with AI-2, there is an equilibrium between various forms [START_REF] Roy | Synthetic Analogs Tailor Native AI-2 Signaling Across Bacterial Species[END_REF]. To test the hypothesis that the P5 can compete with AI-2, V. harveyi reporter strain BB170 was grown in AB medium (100µl) supplemented with 500nM of synthetic AI-2 and in the presence of various quantities (0,1, 2, 4 and 5µL) of P5 and bioluminescence was measured after 4h (c).

Discussion

The growth. We previously demonstrated that proteins are able to be transferred via nanotube-like structures [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF] which obviously could also be involved in the transfer of metabolites from one bacterium to another. However, we cannot exclude the possibility that these structures minimize the distance between the bacteria and create more or less a stable network that can prevent the diffusion of metabolites into the medium and thus increase their local concentration allowing the transfer by diffusion.

The presence of 13 How these kinds of interactions are initiated and controlled is at present poorly understood. Ben-Yehuda's group showed that YmdB is involved in the late adaptive responses of B. subtilis in the early stage of nanotube development [START_REF] Mamou | Early Developmental Program Shapes Colony Morphology in Bacteria[END_REF]. In various types of cells, it is the cell undergoing stress that develops the formation of nanotubes, suggesting that this might be directly induced by stress and constitutes a defense mechanism [START_REF] Wang | Tunneling-nanotube development in astrocytes depends on p53 activation[END_REF] as apparently also in this consortium.

Surprisingly, the role and the consequence of the QS molecules, well described in pure culture, are poorly investigated and understood in bacterial consortia, closer to those found in Nature. However, this has attracted the attention of researchers studying mixed cultures in bioreactors for treating waste water. Although the real mechanism involved in QS regulation, of complex microbial consortia, remained to be elucidated, studies of this type have shed light on it [START_REF] Yong | Engineering quorum sensing signaling of Pseudomonas for enhanced wastewater treatment and electricity harvest: A review[END_REF][START_REF] Shrout | Monitoring bacterial twitter: does quorum sensing determine the behavior of water and wastewater treatment biofilms?[END_REF]. More recently one study investigated this question using a mathematical model to demonstrate how QS control the population trajectories in synthetic consortium [START_REF] Stephens | Bacterial co-culture with cell signaling translator and growth controller modules for autonomously regulated culture composition[END_REF].

The QS molecule AI-2 is crucial for metabolic interaction between the two bacteria of the co-culture, as there is no metabolic exchange in its absence. Thus C.

acetobutylicum produces a molecule with AI-2 activity that had not been described before; furthermore, the C. acetobutylicum gene luxS can restore the AI-2 production by E coli DH5α. Our results explain why E. coli can connect to other bacterial cells to exchange cytoplasmic molecules.

Some organisms can produce and sense AI-2 whereas others only sense the AI-2 signal [START_REF] Pereira | Sinorhizobium meliloti, a bacterium lacking the autoinducer-2 (AI-2) synthase, responds to AI-2 supplied by other bacteria[END_REF][START_REF] Brito | Natural genome diversity of AI-2 quorum sensing in Escherichia coli: conserved signal production but labile signal reception[END_REF]. D. vulgaris appears to be in this last category, as it lacks the luxS gene, but appears to sense AI-2. This suggests the presence of AI-2 receptors in D.

vulgaris. However, no genes similar to lsrB (coding for LsrB, protein receptor of AI-2 in enterobacteria) or to luxP (gene coding for LuxP, the protein receptor of AI-2 in vibrionaceae) are present in the genome of D. vulgaris [START_REF] Heidelberg | The genome sequence of the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough[END_REF]. On the other hand, some bacteria can respond to an exogenous AI-2 signal (44, 45) despite lacking the genes luxS, lsrB or luxP. Furthermore, two proteins, AibA and AibB, can bind AI-2 in Helicobacter pylori. And the deletion of the genes (hppA and modA) encoding for these two proteins, induces deficiencies in chemotaxis and biofilm organization [START_REF] Anderson | Chemorepulsion from the Quorum Signal Autoinducer-2 Promotes Helicobacter pylori Biofilm Dispersal[END_REF].

By bioinformatic analysis we have detected their homologues (oppA and modA respectively) in D. vulgaris, and experiments are in progress to study whether D.

vulgaris internalizes AI-2, as preliminary results suggest. So, the issue of the cellular receptor of AI-2 remains an open problem and our results may contribute to clarify it.

Although the original QS concept was focused on the detection of cell density for the regulation of gene expression, studies in microbial ecology suggest a wider function. For example, the efficient-sensing concept [START_REF] Hense | Core principles of bacterial autoinducer systems[END_REF] assumes that the ecologically relevant function of AI-2 sensing is to pre-assess the efficiency of producing extracellular effectors or "public goods". Cooperative genes regulated by QS molecules can also be sensitive to nutrient conditions, suggesting that metabolic information is integrated into the decision to cooperate. The correlation between QS and cell activity rather than bacterial growth has been recently underlined in D.

vulgaris [START_REF] Scarascia | Effect of Quorum Sensing on the Ability of[END_REF]. AI-2 molecules are involved in the mechanism stimulating viable but no cultivable cell exits from dormancy, perhaps signalling to dormant cells when conditions are now favourable for growth [START_REF] Bari | Quorum-sensing autoinducers resuscitate dormant Vibrio cholerae in environmental water samples[END_REF][START_REF] Ayrapetyan | Interspecific quorum sensing mediates the resuscitation of viable but nonculturable vibrios[END_REF]. This supports the idea that AI-2dependent signalling reflects the metabolic state of the cell, and can function as a proxy for the production of effectors such as enzymes, or the formation of nanotubes.

Integrating metabolic information with QS offers a possible mechanism to prevent cheating, as cells can only cooperate when they have the appropriate nutritional resources to do so, reducing the cost of cooperation to the individual cell [START_REF] Boyle | Integration of Metabolic and Quorum Sensing Signals Governing the Decision to Cooperate in a Bacterial Social Trait[END_REF].

We and most of them include synthetic molecules as quencher [START_REF] Roy | Synthetic Analogs Tailor Native AI-2 Signaling Across Bacterial Species[END_REF][START_REF] Shen | Design and synthesis of substrate and intermediate analogue inhibitors of S-ribosylhomocysteinase[END_REF][START_REF] Singh | Structure and inhibition of a quorum sensing target from Streptococcus pneumoniae[END_REF]. It proposed that C1 alkyl, analogues of AI-2, could compete with AI-2 for the LsrR transcriptional regulator in the lsr system [START_REF] Roy | Synthetic Analogs Tailor Native AI-2 Signaling Across Bacterial Species[END_REF][START_REF] Roy | AI-2 analogs and antibiotics: a synergistic approach to reduce bacterial biofilms[END_REF] and the presence of the competitor is linked to a decrease in AI-2 production. As AI-2 consists of a group of molecules in equilibrium, not a unique defined structure [START_REF] Roy | Synthetic Analogs Tailor Native AI-2 Signaling Across Bacterial Species[END_REF], analogy with enzymes and alternative substrates suggests that different types of AI-2 molecules may interact with a receptor, with only some of them inducing a response. We cannot discard the possibility that the QQ molecule identified in D. vulgaris supernatant could bind to an AI-2 receptor in C.

acetobutylicum and induce an effect at the level of gene transcription that could be translated into metabolic modification. Moreover, we also cannot discard the possibility that the QQ molecule identified represents a QS signal for D. vulgaris.

Our analysis provides new insights into metabolic prudence (58) and bacterial communication, and about how metabolic signals influence social behaviour but many details of its molecular implementation remain to be discovered. Which proteins detect the metabolic signals? How do they interact with QS regulation at the molecular level? However, one should also be cautious in using the word "signalling" because every change in a living organism affects every other, and thus acts as a signal of some kind [START_REF] Letelier | From L'Homme Machine to metabolic closure: steps towards understanding life[END_REF][START_REF] Noble | A theory of biological relativity: no privileged level of causation[END_REF]. In all of these studies it is important to keep in mind the ecological context, but the analysis of how the components of an ecological system influence one another has barely begun [START_REF] Cárdenas | Rosennean complexity and its relevance to ecology[END_REF]. Anyway, we can see in these microbial communities established, thanks to QS molecules, the preliminary steps in the evolutionary pathway of multicellular organisms and eukaryotes.

Materials and Methods

Media and growth conditions

Strains were grown to steady state in Hungate tubes under anaerobic conditions, in LB medium for E. coli DH10B and DH5, in Starkey medium (containing lactate and sulfate) for D. vulgaris [START_REF] Traore | Energetics of Growth of a Defined Mixed Culture of Desulfovibrio vulgaris and Methanosarcina barkeri: Interspecies Hydrogen Transfer in Batch and Continuous Cultures[END_REF] and 2YTG medium for C. acetobutylicum [START_REF] Nölling | Genome sequence and comparative analysis of the solvent-producing bacterium Clostridium acetobutylicum[END_REF] to an optimal absorbance of 0.6. The growth medium (Glucose-Yeast extract (GY) medium) used for studying the consortium was prepared with glucose (14mM), 0.1% yeast extract, and supplemented with the similar inorganic nutrients used for the Starkey preparation (but with MgCl 2 instead of MgSO 4 ). GY medium was inoculated with either washed D. vulgaris or C. acetobutylicum or E. coli or with the combination of different strains to constitute an artificial consortium in a 1:1 ratio according to the absorbance at 600nm. D. vulgaris is not able to grow alone in GY medium [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF]. In some cases, the growth medium was supplemented with 5 or 10mM lactate or/and 5 or 10mM sulfate. The experiments were carried out at least in triplicate.

Construction of E. coli DH5α (luxS) strain

The luxS ORF (corresponding to gene CA_C2942) was amplified using the genome of C. acetobutylicum as a template and oligonucleotide primers LuxS 5' GAAACCGGTAAAACAAAGGAGGACGTTTATGGAAAAAATCGCAAGTTTTACTG-3' LuxS-RevpB coli DH5α(luxS) strain. As a negative control, E. coli DH5α was also transformed with empty plasmid pBGF4.

Labeling of D. vulgaris with calcein-acetoxymethyl-ester (AM)

The labelling of D. vulgaris cells by calcein was carried out as described by Benomar et al. [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF]. Briefly, D. vulgaris cells were grown in Starkey medium [START_REF] Traore | Energetics of Growth of a Defined Mixed Culture of Desulfovibrio vulgaris and Methanosarcina barkeri: Interspecies Hydrogen Transfer in Batch and Continuous Cultures[END_REF] under anaerobic conditions, then exponentially growing D. vulgaris cells (5ml) was harvested at room temperature by centrifugation at 4000g for 10min, washed twice with Starkey medium and resuspended in 5ml fresh Starkey medium. 100μl of calcein-AM (1mg/ml in dimethylsulfoxide, SIGMA) were then added to the medium.

The suspension was incubated in the dark at 37°C for 2 hours under anaerobic conditions. Cells were subsequently harvested and washed three times in fresh, dyefree GY medium and used in the exchange experiments.

Labelling of E. coli DH5α and E. coli DH10 with mCherry

The labelling was carried out by transforming E. coli DH5α and E. coli DH10 with pRSET-B mCherry (Addgene, Plasmid #108857).

Exchange of cytoplasmic molecules between D. vulgaris and E. coli

To study the exchange of molecules between the two bacteria, D. vulgaris labelled with calcein was mixed with several strains of E. coli labelled with mCherry:

E. coli DH10B strain, producer of AI-2 molecule, E. coli DH5α non-producer of AI-2 molecule, DH5α(luxS). In some cases, unlabelled cells of D. vulgaris were mixed with E. coli labelled with mCherry. The mixture was diluted in 5ml fresh GY medium and put in a tube containing a coverslip and incubated at 37°C for 20h. The coverslip was removed after 20h of growth and bacterial cells attached to coverslip were visualized by fluorescence confocal microscopy as previously described by Benomar et al [START_REF] Benomar | Nutritional stress induces exchange of cell material and energetic coupling between bacterial species[END_REF].

AI-2 activity assay

AI-2 activities of cell-free culture supernatants were measured by using Vibrio harveyi reporter strain BB170 as described by Bassler et al [START_REF] Bassler | Intercellular signaling in vibrio-harveyi -sequence and function of genes regulating expression of luminescence[END_REF]. Briefly, an overnight culture of V. harveyi (grown for 16h in AB medium) was diluted 1/5,000 in fresh AB The presence and relative amount of DNA in fraction 28 (see supplementary Fig. 3), from each bacterium were followed by qPCR. The primers used for the qPCR (dsrA and endoG) are listed in Supplementary

Imaging and quantification of microscopy images

Cells attached to the coverslip were observed by the Confocal Olympus FV1000 microscope (Japan) using the UPLSAPO 100X objective (oil immersion). The excitation and emission wavelengths are 488 nm and 515 nm for calcein and RSG, and 558 nm and 583 nm for mCherry. The laser beams were activated in sequential mode to avoid fluorescence overlaps. The microscopy fields analyzed were obtained from 3 biological replicates obtained independently containing between 100-150 cells. These fields were chosen according to the local cell density. Since we made a morphological discrimination to identify the different bacterial species, we scanned the entire coverslip to find microscopy fields with small clumps of bacteria where the morphology of each was observable. They were counted manually using ImageJ software.

Statistical analysis

All the data were obtained from at least 3 biologically independent replicates.

Data analysis was performed using the R statistical analysis software v3.

  -culture allows D. vulgaris to be metabolically active and to grow by using carbon metabolites produced by C. acetobutylicum Based on metabolic and microscopic experiments, our previous results demonstrated that conditions of nutritional stress of D. vulgaris induce a tight interaction between D. vulgaris and C. acetobutylicum, in co-culture, which allows the exchange of cytoplasmic molecules and the growth of D. vulgaris. If the tight interaction is prevented when either D. vulgaris or C. acetobutylicum are confined in a dialysis tube, D. vulgaris cannot grow

Figure 1 :

 1 Figure 1: The presence of C. acetobutylicum is required for energetic activation of D. vulgaris. D. vulgaris growing exponentially in Starkey medium was washed twice and starved by incubation in GY medium, 20h at 37°C. A starved culture was divided into three subcultures and supplemented with 1µM of RSG (final concentration). The first was activated with 10mM of lactate/sulfate (LS) (a) and the second remained starved (b). The two subcultures were sampled and visualized by

Figure 2 :

 2 Figure 2: Quantification of D. vulgaris (dsrA) and C. acetobutylicum (endoG) on fractions (corresponding to the fractions 28 in Supplementary Fig. 3) containing 13 C from C. a 13 C + DvH 12 C in 13 C glucose medium DNA and on corresponding fractions containing 12 C from C. a 12 C + DvH 12 C in 12 C glucose medium DNA. Data are represented as mean  SD with n = 3, in comparison to 12 C samples. p-values calculated in Tukey HSD tests, * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 3 :

 3 Figure 3: Extracellular AI-2 activity. (a) From left to right, pure culture of E. coli DH10B (AI-2 producer; positive control), pure culture of. coli DH5α expressing luxS gene of C. acetobutylicum, pure culture of C. acetobutylicum, co-culture of C. acetobutylicum and D. vulgaris, pure culture of E. coli DH5α (AI-2 non-producer;negative control) all grown in GY medium to exponential phase (ie. OD 600  0.8). At the right extreme D. vulgaris wild-type strain was grown in Starkey medium. Aliquots of different cultures were taken at exponential phase and filtered to remove cells. AI-2 activity in the cell culture supernatant was measured using the V. harveyi BB170

2 ,

 2 Fig.4b(2) and Supplementary Fig.4 panel 1).

Figure 4 :

 4 Figure 4: AI-2 is required for cytoplasmic molecules exchange between D. vulgaris and E. coli. D. vulgaris growing exponentially (OD of 0.6) in Starkey medium was labelled with calcein, washed with GY medium, and mixed with E. coli

4 panel 3 )

 3 Fig.4b(3) and Supplementary Fig.3 panel 2).

  . Lack of AI-2 should prevent RSG fluorescence in D. vulgaris by preventing physical interaction between E. coli and D. vulgaris in GY medium. Cells of D. vulgaris were incubated with RSG as described above and mixed with E. coli DH5α or with E. coli DH10B harbouring the gene of mCherry and the co-culture was analyzed by microscopy after 20h incubation at 37°C. D. vulgaris cells displayed a significant RSG fluorescence (90% of cells) when they are mixed with E. coli DH10B (Fig. 5

  panel 1 and 5c(1)). In contrast, no RSG fluorescence was observed in D. vulgaris cells when co-cultured with E. coli DH5α (Fig. 5 panel 2 and 5c(2)). Moreover E. coli DH5α does not show RSG fluorescence as E. coli DH10B and C. acetobutylicum (Fig. 1), which supports the absence of cytoplasmic exchange. In contrast, D. vulgaris cells co-cultivated with E. coli DH5α complemented with luxS gene displayed RSG fluorescence (about 80% of cells) similar to that observed with E. coli DH10B (Fig. 5 panels 3 and 5c(3)). These results strongly support that the AI-2 molecule is important for physical interaction between D. vulgaris and E. coli and thus in metabolic activation of D. vulgaris. All these results suggest that D. vulgaris can detect AI-2.

Figure 5 :

 5 Figure 5: AI-2 is required for energetic activation of D. vulgaris. D. vulgaris was grown exponentially in Starkey medium, and was then washed twice and starved by incubation in GY medium, 20h at 37°C. A starved culture was divided into three subcultures and supplemented with 1µM of RSG (final concentration). The subcultures were incubated at 37°C for 1h and then E. coli strains DH10B (panel 1), DH5α (panel 2) and DH5α(luxS) (panel 3) labelled with mCherry were added. The

  1, 2, 4, and 8µL) of D. vulgaris filtered (0.2µm) supernatant grown on Starkey medium for 30h (c). Data are represented as mean  SD with n = 3, AI-2 activity measured for C. acetobutylicum in GY medium with 5 and 10mM of lactate/sulfate in comparison to C. acetobutylicum in GY medium (black) and C. acetobutylicum & D. vulgaris in GY medium with 5 and 10mM of lactate/sulfate in comparison to C. acetobutylicum & D. vulgaris in GY medium (gray) (a). In comparison to AI-2 activity measured for AI-2 produced by C. acetobutylicum and E. coli without D. vulgaris supernatant (b and c respectively). p-values calculated in Tukey HSD tests, * p < 0.05; ** p < 0.01; *** p < 0.001. Abbreviations: C. a, Clostridium acetobutylicum; DvH, Desulfovibrio vulgaris Hildenborough.

Figure 7 :

 7 Figure 7: Impact of supernatant of D. vulgaris growing in Starkey on cytoplasmic molecule exchange. D. vulgaris growing exponentially in Starkey medium was washed with GY medium and mixed with E. coli DH10B (AI-2 producer) labelled with mCherry and grown in 5ml of GY medium supplemented (+S) or not(-S) with 100µl of D. vulgaris filtered (0.2µm) supernatant grown on Starkey medium. The culture was visualized by fluorescence confocal microscopy after 20h incubation at 37°C. Scale bar, 2µm in all panels. Data are represented as mean  SD with n = 3, in comparison to the percentage of mCherry D. vulgaris fluorescent cells when cocultured with E. coli DH10B in GY medium supplemented with D. vulgaris Starkey supernatant. p-values calculated in Tukey HSD tests, * p < 0.05; ** p < 0.01; *** p < 0.001. Abbreviations: C. a, Clostridium acetobutylicum; DvH, Desulfovibrio vulgaris Hildenborough; DH10B: Escherichia coli DH10B.

Figure 8 :

 8 Figure 8: Identification of AI-2 inhibitor in D. vulgaris supernatant. D. vulgaris strain was grown in Starkey medium during 30h at 37°C and the filtered supernatant was analyzed by RP-HPLC (a). The peak P5 which presents an AI-2 inhibitor activity was analyzed mass spectrometry (A, indicated by black arrow). The AI-2 inhibitor activity of different peaks collected (P1 to P5) was determined on synthetic AI-2 ((S)-4,5-dihydroxy-2,3-pentandione, DPD) (2,5µM) or on AI-2 produced by E. coli strain DHI0B grown on GY medium (b).To test the hypothesis that the P5 can compete with AI-2, V. harveyi reporter strain BB170 was grown in AB medium (100µl) supplemented with 500nM of synthetic AI-2 and in the presence of various quantities (0,1, 2, 4 and 5µL) of P5 and bioluminescence was measured after 4h (c).

  demonstrate the quenching of the AI-2 activity by a quorum quenching (QQ) molecule produced by D. vulgaris in the presence of lactate/sulfate. Quorum quenching has been suggested to be achieved in three ways: (i) blocking synthesis of autoinducers; (ii) interfering with signal receptors; and (iii) degrading the autoinducers (51-54). As we show competition between AI-2 present in C. acetobutylicum or E. coli supernatant, or even synthetic AI-2 and an AI-2 quencher, a small molecule presents in the D. vulgaris supernatant, we can exclude the first and the third hypotheses. Only a few AI-2 interfering mechanisms have been reported

  . The PCR amplification of luxs was digested and introduced into the AgeI and KpnI sites of pBGF4 plasmid under the control of the hydrogenase constitutive strong promoter[START_REF] Bender | Analysis of a ferric uptake regulator (Fur) mutant of Desulfovibrio vulgaris Hildenborough[END_REF] to obtain pRD4 plasmid. The DNA sequence was analyzed by DNA sequencing (Cogenics). Next, the pRD4 was transformed in E. coli DH5α to obtain E.

Analysis and purification of the Antagonist AI- 2

 2 compounds from D. vulgaris D. vulgaris cells were grown in Starkey medium under anaerobic conditions for 30h at 37°C. The culture was then centrifuged at 10,000rpm for 5min and filtered through 0.2µm membranes to remove the cells. The cell-free supernatants were stored at -20°C or immediately analysed by HPLC. The analysis was carried out on an Agilent 1200 HPLC system equipped with a UV detector and a refractometer (Agilent technologies). Separation (20-50µl of samples are injected) was achieved on an Agilent POROSHELL EC-C18 reverse-phase column (C18, 4.6x150mm, 2.7µm) set at 30°C. The compounds were eluted with 8% solution A (Acetonitrile + 1% (v/v) formic acid) and 92% of solution B (Deionized water + 1%(v/v) formic acid), at a flow rate of 0.6ml/min. Purified compounds were directly used for bioluminescence assay or lyophilized and stored at -20°C.Mass spectrometry analysisAnalyzes of samples were performed with a 3200 QTRAP (Applied Biosystems SCIEX) mass spectrometer equipped with a pneumatically assisted atmospheric pressure ionization (API) source. The sample was ionized in positive electrospray mode under the following conditions: electrospray voltage (ISV): 5500 V; orifice voltage (OR): 10 V; nebulizing gas pressure (air): 10 psi. The sample was also ionized in negative electrospray mode under the following conditions: electrospray voltage (ISV): -4500 V; orifice voltage (OR): -10 V; nebulizing gas pressure (air): 10 psi. Mass spectra (MS) were obtained with a quadrupole analyzer. Samples are dissolved in 300 µL of acetonitrile and then diluted 1/10 in a 3 mM methanol solution of ammonium acetate. Sample solutions are introduced into the ionization source by infusion (Harvard Apparatus syringe pump) at a flow rate of 10µL/min.Carbon exchange by Stable isotope probing (SIP)SIP method described by Neufeld et al[START_REF] Neufeld | DNA stable-isotope probing[END_REF] and derived from Meselson and Stahl was slightly modified. Glucose-yeast extract (GY) medium was prepared with D-glucose-13 C6 (14mM) from Cortecnet and 0.1% yeast extract ( 12 C), supplemented with similar inorganic nutrients as used for the Starkey preparation (MgCl 2 instead of MgSO 4 ) and N 2 in the headspace.13 C-GY medium was inoculated (10%) with either washed C. acetobutylicum enriched in13 C via 26 subculturing or D. vulgaris12 C at exponential growth phase, or with the two strains, to constitute an artificial consortium in a 1:1 ratio according to the absorbance at 600nm. At the end of the exponential phase, genomic DNA was extracted from the cell pellets using the NucleoBond AXG20 kit (Macherey-Nagel), and DNA purity and concentration were determined with the Nanodrop 2000c spectrophotometer (Thermoscientific).To separate labelled/heavier ( 13 C-DNA) from unlabelled/lighter ( 12 C-DNA), density gradient centrifugation was performed in 5,1ml quick-seal tubes in a NVT 65.2 rotor (near vertical) using Optima L-90K centrifuge (Beckman coulter). CsCl medium having an average density of 1,72g/ml was loaded with 6µg of total extracted DNA. After centrifugation at 20°C for 66h at 41500rpm 169000g av , each gradient ( 13 C-labelled-C. acetobutylicum + 12 C-unlabelled-D. vulgaris and 12 C-unlabelled-C. acetobutylicum + 12 C-unlabelled-D. vulgaris) was fractioned from the bottom to the top by displacement with mineral oil. DNA in each fraction was precipitated as described by Neufeld et al[START_REF] Neufeld | DNA stable-isotope probing[END_REF]

  dioxolane (3): To a solution of amide 2 (1.74g, 10mmol) in anhydrous diethyl ether (10mL) at 0 °C under an Argon atmosphere, 21.0mL of a 0.5M solution of isopropenylmagnesium bromide in THF was added and stirred for 15minutes. The reaction mixture was quenched with 1M HCl and extracted

4 (S)- 4 , 5 -

 445 Dihydroxy-pentane-2, 3-Dione (5): To a solution of diketone 4 (3.0mg, 0.017mmol) in D 2 O (0.5mL) and d 6 -DMSO (0.2mL) under an Argon atmosphere, H 2 SO 4 (0.005mL) was added and stirred at RT for 1h. The reaction mixture was quenched with 5mg Na 2 CO 3 , filtered to get 0.0249M solution of AI-2 (5) and its cyclic anomeric products in D 2 O and d 6 -DMSO. Spectral data were consistent with those previously reported.

  bacterial community established in batch culture by C. acetobutylicum and D. vulgaris, or E. coli DH10B and D. vulgaris, and in conditions of nutritional stress for

	D. vulgaris: (i) exchanges metabolites, allowing a satisfactory energetic state and
	growth of D. vulgaris, and (ii) is regulated by AI-2 molecules that allow physical and
	metabolic interactions in the co-culture. Furthermore, in the presence of sulfate, D.
	vulgaris produces an AI-2 antagonist. Production of the antagonist is independent of
	the presence of C. acetobutylicum or E. coli and may prevent formation of other
	consortia. Altogether, our studies revealed how QS molecules coordinate interactions
	between species and this modulation follows the environmental stress. Moreover,
	they illustrate how experiments with multiple species or synthetic ecological models
	can provide new insight into bacterial sociability.

The presence of C. acetobutylicum or E. coli (DH10B) allows D. vulgaris to be energetically viable despite the lack of sulfate. The observation that without C. acetobutylicum or E. coli DH10B, D. vulgaris is not energized explains why the presence of one or the other of these two bacteria is indispensable for D. vulgaris

Use of RedoxSensor Green as a probe for active respiration in D. vulgaris.

	and diluted in 5ml fresh GY medium containing 1μM RSG reagent. The cultures were
	supplemented with 10 mM lactate and 10mM sulfate or not and bacterial cells were
	imaged by fluorescence microscopy following incubation at 37°C for 20h. After 20h of
	incubation at 37°C, the co-culture was left for 5min in contact with FM4-64 to
	visualize the bacterial membrane and to be able to see C. acetobutylicum, which was
	not labelled at the beginning of the experiment. Also, the effect of the electron
	transport chain uncoupler CCCP on RSG fluorescence was verified to further confirm
	the redox sensing functionality of RSG in D. vulgaris as previously reported for other
	bacteria (9).
	medium (300mM NaCl, 50mM MgSO 4 , 2% [wt/v] Casamino Acids, 10mM potassium
	phosphate [pH 7], 1mM L-arginine, 1% [wt/v] glycerol). The diluted cells (90μL) were
	added to 96-well plates (Corning) containing 10μL of the cell-free culture supernatant
	of E. coli or D. vulgaris or C. acetobutylicum obtained after centrifugation and filtration
	through 0.2m membranes to remove bacterial cells, or synthetic AI-2 molecule. The
	microtiter plate was incubated at 30°C with shaking at 160rpm and bioluminescence
	was measured each hour over the course of 4-6h using a Tecan GENioS plate
	reader (Tecan, USA). AI-2 activity is reported as induction of bioluminescence which
	is expressed in Relative light units (RLU). The reported values represent the average
	bioluminescence stimulated by three independent preparations of cell-free culture
	fluids or synthetic AI-2 molecule. Similar experiments were performed in presence of
	various amounts of D. vulgaris culture supernatant in Starkey medium. Cell-free
	culture supernatants of E. coli or D. vulgaris or C. acetobutylicum were taken at
	exponential phase (OD 600  0.7/0.8).
	RedoxSensor Green (RSG) (Backlight™ RedoxSensor™ Green Vitality Kit, Life
	Technologies) was used to assess cellular respiration activity of D. vulgaris. D.
	vulgaris cells were taken from Starkey medium culture in mid-log phase, washed
	twice and starved by incubation in GY medium (without lactate and sulfate) for 20
	hours at 37°C. Following starvation, D. vulgaris cells were harvested at room
	temperature by centrifugation at 4,000g for 10min, washed twice with GY medium

Table 1

 1

	. The reaction was performed

in the presence of N-methylmorpholine-N-oxide and subsequent cleavage of generated diol with NaIO 4 produced ketone (4). Finally, the hydrolysis of dioxolane ring in acidic condition yields AI-2 (5) and its cyclic anomeric products. Spectral data were consistent with those previously reported. Details of each step are detailed below.

N,

N-Dimethyl (S)-α,β-isopropylidene glyceramide (2). To

	the solution containing
	dimethylamine (20mL, 30 vol. % in ethanol) was added methyl (S) -α, β-
	isopropylidene glycerate (3g, 18.5mmol) at 0°C. The mixture was stirred for 24h.
	After adding an additional 10 mL of the dimethylamine solution, the stirring was
	continued for further 24 h. The volatile compounds were evaporated and the residue
	was purified by column chromatography to yield 2.8g of amide 2 (86%, colorless
	liquid); R f = 0.2 (pentane / ethyl acetate, 3:2); 1 H NMR (400MHz, CDCl 3 ) ∂ = 4.62 (t, J
	= 6.65Hz, 1H), 4.31 (dd, J = 8.28, 6.53Hz, 1H), 4.07 (dd, J = 8.53, 6.78Hz, 1H), 3.05
	(s, 3H), 2.90 (s, 3H), 1.34 (s, 6H).

  3 times with diethyl ether and the combined organic phase dried over Na 2 SO 4 and evaporated to dryness. The residue was purified by chromatography on SiO 2 to

	afford 3 (0.8g, 46%). R f = 0.33 (pentane / ethyl acetate, 9:1); 1 H NMR (300 MHz,
	CDCl 3 ) δ= 6.06 (s, 1H), 5.91 (d, J = 1.38, 1H), 5.08 (dd, J = 7.26,6.03, 1H), 4.22 (dd,
	J = 8.34, 7.4, 1H), 4.09 (dd, J = 8.43,5.94, 1H), 1.89 (s, 3H), 1.41 (s, 6H).
	1-(2,2-Dimethyl-[1,3]dioxolan-4-yl)-propane-1,2-dione (4): The alkene (3) (40mg,
	0.23mmol) was dissolved in a mixture of acetone/water (4mL/1mL). N-Methyl
	morpholine-N-oxide monohydrate (39mg, 0.23mmol) was added slowly and the
	reaction mixture was stirred at room temperature for 10min. Then 4% aqueous
	solution of osmium tetraoxide (0.1mL, 0.011mmol) was added to the above reaction
	mixture and stirred overnight at room temperature. The mixture was quenched with
	Na 2 SO 3 and extracted with dichloromethane. The organic layer was dried (Na 2 SO 4 ),
	filtered and the filtrate concentrated under reduced pressure. The crude diol was
	used in next step as such. To the diol in methanol (3.5mL) and water (1.5mL) was
	added sodium periodate (0.146g, 0.69mmol) and stirred at RT for 30min. The
	reaction mixture was diluted with water and extracted with dichloromethane. The
	organic layer was dried (Na 2 SO 4 ), filtered and the filtrate was concentrated under
	reduced pressure. The residue was purified by chromatography on SiO 2 to afford 4
	(15.9mg, 40% over 2 steps). R f = 0.65 (pentane / ethyl acetate, 6:4); 1 H NMR (400
	MHz, CDCl

3 ) δ= 5.14 (dd, J = 7.8, 5.8, 1H), 4.37 (t, J = 8.4, 1H), 4.0 (dd, J = 9.00, 5.4, 1H), 2.39 (s, 3H), 1.47 (s, 3H), 1.42 (s, 3H).

  1 H-NMR (300MHz, D 2 O): 4.25 (t, J= 6.4Hz, 1H), 4.10-4.02 (m, 2H), 3.93 (dd, J= 3.4, 5.6Hz,1H), 3.76-3.67 (m, 2H), 3.84-3.81 (m, 1H), 3.53 (dd, J= 7.5, 11.6Hz, 1H), 3.45 (dd, J=5.4, 9.2Hz, 1H), 2.27 (s, 3H), 1.34 (s, 3H), 1.31 (s, 3H). HRMS (ESI-TOF) m/z: [M -H] -calcd for C 5 H 7 O 4 -131.0350; found 131.0354.

  6.0. Statistical data were accomplished using R base function "aov" for Tukey test. Tukey test was used because it is a statistical test to perform a multiple comparison in one step. Data were compared with base condition and significances were estimated with p-values : * p < 0.05; ** p < 0.01; *** p < 0.001. In all cases, p values < 0.05 was

	O considered significant. For details regarding statistical tests, see supplementary table HO O Fig. 6b DvH supernantant moy AI-2 activity sqr HO C. a 0ul 1604.333333 46.1747887 2. Fig. 1e D.vulgaris fluorescents sqr C. a 1ul 330.3333333 6.437735972 5 Cab+DvH-RSG(FM4-64) 92.072306 3.729872576 C. a 2ul 182.6666667 32.27141838
	DvH -RSG+Lactate/sulfate C. a	4ul	98.62396038		0.701246665 54.66666667	6.227180564
	DvH -RSG without Lactate/sulfate C. a	8ul	5.778061386		0.423639888 7	1
	Fig. 2 Fig. 6c	fractions DvH supernatant		genome copies AI-2 activity	sqr sqr
	dsrA E. coli DH10B	f13C 0ul				627265.6679 6263	74793.20234 74.80864478
	dsrA E. coli DH10B	f12C 1ul				169173.4765 3503	107211.4977 130.001282
	endoG E. coli DH10B	f13C 2ul				4.18E+06 1563.666667	9.50E+05 176.606279
	endoG E. coli DH10B	f12C 4ul				5.77E+05 843.6666667	1.93E+05 102.1377066
	E. coli DH10B	8ul				160.3333333	28.81164888
	Fig. 3a	moy AI-2 activity			sqr
	DH10B Fig. S4	2535 D.vulgaris fluorescents	167.003992 sqr
	DH5+LuxS DH10B+DvH		2491 94.71268076		40.61198509 2.144019364
	C. a DH5aLuxS+DvH		2255 93.28478302		127.4414898 1.881735585
	C. aDvH DH5a+DvH		1325.333333 0		18.55921454 0
	DH5a			61		5.033222957
	DvH	34.33333333 C. a + supernatant		3.179797338 sqr	DH10B + supernatant	sqr
	C		2114.333333		101.6666667	3419	54
	0h		2206.666667		98.41634914	3335.666667 46.4626493
	Fig . 4 3h	D.vulgaris fluorescents 104.6666667	sqr 64.34369519	E .coli fluorescents 1487.333333 93.0238918 sqr
	DH10B +DvH 6h		92.40671576 52.33333333		4.577081152 13.86041526	92.71624802 1.97201277 1459 107.704844
	DH5aLuxS+DvH 9h		94.69515689 50.33333333		0.926391377 9.527737285	89.21247563 3.39795829 1370.5 1.5
	dh5a+DvH 12h		0 4.666666667		0 2.905932629	0 930 274.049266 0
	26h			1		1	3.5	2.5
	30h			7		4	0	0
	Fig. 5c	D.vulgaris fluorescents
	DH10B+DvH		92.02128464		0.86568809
	DH5a+DvH Fig. S6	Lactate/sulfate	0	0 V. harveyi growth	sqr
	DH5aLuxS+DvH V. harveyi with C. a supernatant	0mM	79.73385264		1.551688763 0.0373	0.001014889
	V. harveyi with C. a supernatant	5mM				0.0372	0.001509967
	V. harveyi with C. a supernatant	10mM				0.037366667	0.000945163
	Fig. 6a V. harveyi with C. a/DvH supernatant 0mM Lactate/sulfate		moy AI-2 activity 0.001014889	sqr 0.005071489
	C. a V. harveyi with C. a/DvH supernatant 5mM 0mM				2295 0.001509967	17.21433511 0.003879863
	C. a V. harveyi with C. a/DvH supernatant 10mM 5mM				2403 0.000945163	12.7410099 0.002650157
	C. a V. harveyi no supernatant	10mM /				2609.666667 0.038633333	2.962731472 0.00322542
	C. a + DvH	0mM				1530.666667	49.00793587
	C. a + DvH	5mM				248	10.39230485
	C. a + DvH	10mM				10	0.577350269

Acknowledgements

We acknowledge Pascale Infossi and Dr Deborah Byrne for help with some experiments. This work has benefited from the facilities and expertise of the Platform for Microscopy of IMM and from the transcriptomic platform of IMM. We thank Dr Jean-Philippe Steyer and Dr Chantal Iobbi for helpful discussions. Dr A. Cornish-Bowden for helpful discussions and correction of the English. This work was supported by the A*MIDEX project (nANR-11-IDEX-0001-02) from Aix Marseille University.


Maria Grazia Concilio

Corentin Jacquemmoz

Dina Boyarskaya

Géraldine Masson

Jean-Nicolas Dumez
email: author.jeannicolas.dumez@cnrs.fr

Ultrafast Maximum-Quantum NMR Spectroscopy for the Analysis of Aromatic Mixtures

Keywords: liquid sate NMR methods, small molecules, spin dynamics

Introduction

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the analysis of complex mixtures of small molecules in solution. Advanced NMR methods, often based on sophisticated multidimensional (ND) schemes [1][2][START_REF] Ernst | Principles of Nuclear Magnetic Resonance in One and Two Dimensions[END_REF], have been developed to overcome the issues of signal overlap and high spectral density, which limit the applicability of 1D NMR for mixtures analysis. A particularly useful method in the case of aromatic compounds is maximum-quantum (MaxQ) NMR, based on multiple-quantum NMR [START_REF] Munowitz | [END_REF][5][6][START_REF] Norwood | Multiple quantum spectroscopy of liquid samples[END_REF][START_REF] Sinton | [END_REF]. MaxQ NMR relies on the encoding of multiple-quantum coherences. Specifically, when the highest-quantum coherence (the MaxQ) present in a given spin system is encoded, the corresponding peak in the indirect dimension reduces to a single line that resonates at a position given by the sum of the 1Q chemical shifts of the spins participating to the MaxQ. This simplifies drastically the multiple-quantum dimension, allowing a differentiated identification of the compounds in the mixture [9][10][11][12]. This technique has been successfully used to simplify crowded spectra of several kinds of mixtures. Other applications of multiple-quantum NMR include spin counting in MQ filtered COSY or 13 C detected INADEQUATE experiments [START_REF] Norwood | Multiple quantum spectroscopy of liquid samples[END_REF][13][14][15], and the identification of spin topologies [16] for spin state selection relying on heteronuclear couplings.

Multidimensional NMR methods such as MaxQ NMR are however, due to the presence of one or several indirect evolution dimensions, more time consuming and unsuitable for studies of dynamical processes and/or unstable samples, which require appropriate time resolution. Several strategies have been developed to overcome the time limitation of multidimensional NMR. Some of these, are based on a reduced inter-scan delay that can be optimized together with the radiofrequency (RF) excitation pulse angles [START_REF] Rouger | Fast n-Dimensional Data Acquisition Methods[END_REF][START_REF] Schanda | [END_REF], on non-uniform sampling (NUS) of the multidimensional data space coupled with non-Fourier signal processing methods [19][20][21], on Hadamard encoding [22 -23], and on covariance analysis [24][25]. Examples of applications of fast 2D NMR for reaction monitoring include the kinetic study of an organic reaction [26][27], the analysis of bacterial metabolism in situ [28] the monitoring of a phosphorylation biochemical reaction [29]. NUS, in conjunction with Recursive Multi-Dimensional Decomposition (R-MDD) data processing, has been combined with MaxQ NMR for an accelerated acquisition [11]. The most significant acceleration of 2D NMR experiments is obtained with the concept of "ultrafast" 2D NMR, which relies on spatial encoding of the indirect dimension and yields a complete data set in a single scan. UF 2D NMR has been used for a large number of applications [30], including real-time reaction monitoring [31][32][33], and so far it has been applied so far only for the encoding of coherence orders of up to two. [34][35] In this article, we demonstrate the ultrafast (UF), singlescan acquisition of multiple-quantum NMR spectra, using spatial encoding of the multiple-quantum coherences of coherence orders of up to five. We show how the resulting method can be used for the maximum-quantum analysis of a model mixture of aromatic compounds, and also for reaction monitoring, with significantly reduced experiment durations. The analysis is supported by numerical spin simulations, which also help to assign the MaxQ spectra. The resulting methods will be useful for the analysis of mixtures containing a variety of structurally similar aromatic compounds, such as polyphenol, flavanols and secoiridoids [12].

Institut de Chimie des Substances Naturelles, CNRS UPR2301, Univ.Paris Sud, Université Paris-Saclay. 1, avenue de la Terrasse, 91198 Gif-sur-Yvette,France.

Theory

The UF2DNMR approach was designed by Frydman and co-workers [36][37][38][39], and has already been applied to a variety of NMR pulse sequences, such as COSY, TOCSY and HSQC for the study of complex mixtures with significantly reduced experimental times. [30] The NMR pulse sequences for ultrafast multiple-quantum (UFMQ) NMR spectroscopy, used in this work, are shown in Fig. 1. The general setting up of UF2DNMR pulse sequences consists in the replacement of the evolution period (𝑡 ! ) of a conventional pulse sequence by a spatial encoding scheme, based on the combination of bipolar gradients (encoding gradients, 𝐺 " ) and pulses whose frequencies are swept linearly in time -also known as chirp pulses. As the conventional MQ NMR sequences, widely described in the literature [START_REF] Munowitz | [END_REF][5][6][START_REF] Norwood | Multiple quantum spectroscopy of liquid samples[END_REF][START_REF] Sinton | [END_REF], the UF sequences contain a spin-echo block (Fig. 1), in which the second 90 o pulse is used to generate MQ coherences, of even order when applied on the x-axis and of odd order when applied on the y-axis (assuming a first 90° pulse along x). The mixing pulse, indicated as flip angle 𝛽 , is used to convert MQ coherences into single quantum. Coherence selection gradients that flank the mixing pulse are used to select the coherence order during the evolution period. Sequence A and B shown in Fig. 1 differ by the use of a refocusing block used to add additional time to let anti-phase terms evolve into in-phase terms, which can lead to an improved signal-to-noise ratio, as explained below.

The difference between UF and conventional NMR consists in the spatial partitioning of the sample into a set of slices in which independent experiments are performed in parallel instead of sequentially. This approach creates a position-dependent evolution time of the form, 𝑡 ! (𝑧) = 𝐶𝑧, where C is a constant that depends on the pulse sequence and z is the position along the longitudinal axis. UF experiments described in this work are performed using a constant time (CT) scheme [31], to let spins spend the same amount of time in the transverse plane regardless of their position in the sample. The purpose of the gradients, applied along the z-axis, is to create a position-dependent off-resonance frequency, while the purpose of the first chirp is to rotate spins into the x-axis sequentially in space and time. Consider a multiple-quantum coherence of the form

∏ 𝐿 # $ % #&!
, the overall phase shift acquired by the MQ, at the end of the first chirp pulse, is given by the sum of the phase shift for each single quantum coherence, and can be described by Eq. 1.

Eq. 1 where

is the spin phase before the application of the chirp pulse, p is the coherence order, is the sweep rate, is the chemical shift offsets involved.

Z0 is a z-independent term that is not considered here (all the spectra are processed in magnitude mode). The phase acquired by the MQ contains a desirable linear part in z, but also unwanted quadratic terms proportional to z 2 . In order to eliminate the quadratic term, a second chirp is applied with identical duration, sweep rate and gradient amplitude but with opposite sign of the gradient. After the second chirp, the phase shifts of the MQ is given by Eq. 2:

Eq. 2

The expression in Eq. 2 comes from the second term of Eq. 1, it has a prefactor of four rather than two, as in Eq. 1, and is negative due to the presence of the second chirp pulse. Eq. 2 can be rewritten, normalizing to the sample length such that the coefficient of the quadratic phase in Eq. 1 becomes equal to the product of the sweep rate and the duration of the chirp that is proportional to its bandwidth. Therefore, writing the sample length as:

and then incorporating all the terms in a constant equal to:

, Eq. 2 can be reduced to Eq. 3:

Eq. 3

B) AQ A) AQ 1 H G z G x,y G e G e G p G a G a T a T a L g 1 H G z G x,y T e G e G e G p T a T a L g G a G a 1 1 T e ϕ (π ) (z) = -ϕ 0 (z) + p γG e ( ) 2 R ⎛ ⎝ ⎜ ⎜ ⎜ ⎞ ⎠ ⎟ ⎟ ⎟ z 2 + 2γG e T (π ) Ω i i=1 p ∑ BW z + Z 0 ϕ (π ) (z) = 0 R = BW T e Ω i ϕ (π -π ) (z) = ϕ 0 (z) - 4γ G e T (π ) Ω i i=1 p ∑ BW z L z = BW γ G e C = 4T e L z ϕ (π -π ) (z) = ϕ 0 (z) -Cz Ω i i=1 p ∑
Eq. 3 has the desired form, which is linear in z and in the sum of the chemical shifts, with a proportionality constant C that depends on the sequence parameters. The quadratic and linear phase shifts acquired by the MQ coherences after the first chirp (given by Eq. 1) and after spatial encoding block (given by Eq. 3) were verified using spin dynamics simulations performed using Fokker-Planck theory in the Spinach software. [40,41] As expected, a good agreement between analytical and numerical phase shifts was observed (Fig. S1 in ESI).

After the spatial encoding block, the phase of the MQ coherence can be described by a helix around the z-axis, with contributions from different z values interfering destructively. With the mixing pulse, this positiondependent phase is transferred to observable singlequantum coherence. The application of a readout gradient then results in the formation of echoes, at a position that reflects the initial helical winding, and hence the encoded multiple-quantum chemical-shift. In order to unfold both the indirect (multiple-quantum) and direct (single-quantum) dimensions, MRI-inspired echo-planar spectroscopic imaging (EPSI) acquisition is used, based on a train of bipolar gradients (𝐺 ' ) with identical amplitude and duration repeated a number of times, 𝐿 ( . A pre-phasing gradient, 𝐺 % , is used before acquisition to shift the spectrum in the MQ dimension. The signal is then rearranged into a 2D matrix, and Fourier transformed along the direct dimension before magnitude calculation.

Experimental and theoretical section

Sample preparation.

The model aromatic mixture (Fig. 2) studied in this work was prepared by dissolving six compounds: caffeic, ferulic and vanillic acids (MaxQ equal to 3) naphthalene and anthracene (MaxQ equal to 4) and phenol (MaxQ equal to 5) in DMSO-d6, to make a solution about 150 mM of each compound.

UF MQ NMR was also used for reaction monitoring, with the example of a inverse electron-demand aza-Diels-Alder reaction, reported by Masson and co-workers [42]. This concerns the reaction of the N-phenyl imine, with (E)benzyl (penta-1,3-dien-1-yl)carbamate as dienophile, catalyzed by a racemic BINOL-phosphoric acid, affording the corresponding tetrahydroquinoline. The reaction was performed by adding benzyl N-[(1E)-prop-1-en-1-yl]carbamate (the dienophile, 39.33 mg, 0.21 mmol, 1.05 equivalent) and a catalyst (1.98 mg, 5 μmol, 2.8 %mol) to a solution of N-benzylideneaniline (imine, 36.61 mg, 0.20 mmol, 1.0 equivalent) in 0.5 mL of CDCl3, at room temperature. The mixture was then stirred for few seconds and then poured into an NMR tube before reaction monitoring.

NMR spectroscopy

Experiments on the model mixture were performed at a nominal temperature of 298 K using a Bruker 600 MHz NMR spectrometer operating at a 1 H Larmor frequency of 600.13 MHz (AVANCE III console) equipped with a roomtemperature triple-axis gradient high-resolution probe (TXI) capable of generating z gradients fields up to 65 G/cm and orthogonal gradients up to 50 G/cm.

For the UF experiments, the amplitude of the encoding gradients was set equal to 0.78 G/cm in the UF 3Q experiments, equal to 0.65 G/cm in the UF 4Q experiments and equal to 0.26 G/cm in the UF 5Q experiments, with a chirp pulse of 12 kHz sweep width and duration 𝑇 " /2, was kept constant and equal to 15 ms. The amplitude of the encoding gradients was decreased in order to adapt the spectral width in the indirect dimension. The amplitude of the acquisition gradients was set equal to 26 G/cm in all the UF experiments, their duration was set equal to 428 μs, and the number of loops was set equal to 80, resulting in an acquisition time of 72 ms. The coherence selection gradients around the mixing pulse (with 𝛽 kept constant and equal to 90 o ) were determined in according to the G2 = p x G1 rule, values of the G1 and G2 gradients were set in according to the coherence order to select. For these sequences, a more efficient de-phasing of unwanted coherences was obtained by placing pairs of orthogonal gradient pulses around the second chirp pulse and the refocusing pulse with length equal to 1 ms and amplitude equal to 10 G/cm and 35 G/cm, respectively. For the UF experiments, the time that elapses between the excitation pulse and the end of acquisition is of less than 1 second. This duration is sufficient to encode the complete 2D information, and for single-scan experiments started at thermal equilibrium, it corresponds to the complete experimental duration. The total duration of the conventional MQ experiments was of about 10 minutes. For the UF experiments, the time that elapses between the excitation pulse and the end of acquisition is of less than 1 second. This duration is sufficient to encode the complete 2D information, and for single-scan experiments started at thermal equilibrium, it corresponds to the complete experimental duration. When multiple consecutive experiments were recorded (e.g. for build-up curves or reaction monitoring) a conservative relaxation delay of 10 s was used to avoid any hardware problem, resulting in a duration of about 10 s for each UF2DNMR experiment.

For both the UF and conventional experiments, the evolution time was also set equal to 30 ms; the acquisition time was set equal to 72 ms in the UF experiments, and 200 ms, in the conventional experiments. The processing of the conventional MQ experiment was performed using either the full FID or the first chunk of the FID with length equal to 72 ms. All the experiments were acquired in one single scan per increment.

A signal to noise (SNR) comparison between UF and conventional MQ NMR experiments, was performed on the model aromatic mixture with the same experimental conditions as those described above, but using the same total of scans for the conventional and UF experiment, resulting in the same total experiment time.

The cycloaddition reaction was monitored using both the same room-temperature triple-axis gradient probe (TXI) and a single axis cryoprobe CP TCI600 H-C/N, capable of generating z gradients fields up to 53.5 G/cm, using a Bruker NMR spectrometer operating at a 1 H Larmor frequency of 600.33 MHz (AVANCE III console). Parameters in the experiment performed using the TXI, were set as the following: the amplitude of the encoding gradients was set equal 0.72 G/cm with a chirp pulse of 12 kHz sweep width and duration 𝑇 " /2 , kept constant and equal to 15 ms. Parameters in the experiment performed using the single axis cryoprobe, were set as the following: the amplitude of the encoding gradients was set equal to 0.37 G/cm with a chirp pulse of 9 kHz sweep width and duration 𝑇 " /2 , kept constant and equal to 15 ms. The amplitude of the of the acquisition gradients was set equal to 27 G/cm in all the UF experiments, their duration was set equal to 428 μs. The number of loops was set equal to 80. The remaining parameters were the same as those used for the model mixture. The number of scans in the UF experiments, performed to monitor the Diels-Alder cycloaddition reaction, was set equal to 8. UF experiments were acquired every 2 minutes; the total duration of each experiment was equal to 1 minute and 22 seconds.

Apodization of the conventional dimensions was performed using a sine bell function, while in the UF dimension Gaussian apodisation in the spatial domain was used. Simulated and experimental spectra are represented with a reduced chemical shift scale, for the indirect dimension, given by , where are the 1Q chemical shifts participating to that specific MQ and p is the coherence order of the MQ experiment.

Simulations

All the simulations were performed using the Spinach library, [40][41] the code developed for simulations and analysis will be publicly available from the version 2.3 and later.

Results and Discussion

The potential of UF 2D MQ NMR for the acquisition of MaxQ spectra of aromatic mixtures and for reaction monitoring is illustrated here. In the first example, UF MQ NMR is applied to a stable model mixture and comparison between UF and conventional MQ NMR spectra is carried out showing comparable signals are encoded in the two experiments. In the second example, a time series of UF 4Q NMR spectra are acquired at different stages of the Diels-Alder cycloaddition reaction.

UF MaxQ NMR analysis of an aromatic mixture

The chemical structures of the molecules of the aromatic mixture are shown in Fig. 2. Fig. 3 shows the 1D NMR spectrum of the aromatic mixture studied in this work, showing the signal overlap that can be solved using 2D NMR. Figure 4 shows 2D NMR spectra acquired for the model mixture of aromatic compounds. The UF experiments were carried out with the sequence shown in Fig. 1B, and the conventional ones also included a spin-echo delay between mixing and detection, with values of the 𝜏 and 𝜏′ delays chosen according to the strategy described below. Note that the conventional experiments are processed here with an acquisition time that matches that of the UF ones equal to 72 ms, to compare the effect of the encoding mode only. Fig. S2.1 shows 3Q, 4Q and 5Q conventional NMR spectra processed with using the full FID with length equal to 200 ms, characterized by better resolution.

Fig. 4.

Comparison between UF (top array) and conventional (bottom array) MQ NMR spectra of aromatic mixture studied in this work. Conventional spectra were processed using a contour level fifty times the root-mean-square (rms) of the noise, while UF spectra were processed using a contour level three times the rms of the noise.

The full assignment of chemical shifts in both the 1Q and MQ dimensions for the correlations observed in the simulated and experimental spectra are reported in Tables S2 2) were performed to support the interpretation of the experimental spectra. A numerical code for the calculation of multiple-quantum chemical shifts was used for identification and assignment of the specific coherence orders, accelerating and simplifying the assignment for aromatic mixtures. Most of the peaks observed in the conventional spectra were observed also in the UF spectra, confirming that multiplequantum coherences can be encoded spatially for coherence orders of up to 5 at least. In this case, spatial encoding reduces the experiment duration from several minutes to less than one second. Such speed however comes with a well-documented sensitivity penalty [38,45], due to the increased acquisition bandwidth in UF2DNMR. In the UF 3Q spectrum we did not observe 3Q arising from weak couplings between protons within the ring and the acrylic functional groups of the caffeic and ferulic acids, represented by operators: (6.90 ppm), (6.93 ppm) and (7.18 ppm) belonging to the caffeic acid, and operators: (7.02 ppm), (7.08 ppm) and (7.31 ppm), belonging to the ferulic acid. The sensitivity of the UF experiments can be improved to some extent by signal averaging. For example, averaging 16 scans gives a sensitivity increase of 4, while maintaining a speed advantage over the conventional experiment; in the present case however this is not sufficient to recover the missing peaks. Improved sensitivity would also be obtained with the use of a cryogenically cooled probe, with the caveat that triple-axis gradients are less frequently available.

In the MaxQ approach, MQ NMR spectra are analyzed to identify correlations corresponding to complete spin systems. Three clear 3MaxQ(s), arising from caffeic, ferulic and vanillic acid, were observed in the 3Q NMR spectra, as well as two 4MaxQ(s) from naphthalene and anthracene in the 4Q spectra, and one 5MaxQ from the phenol in the 5Q NMR spectra, the experimental chemical shifts of the MQ in the indirect

L 3 + L 4α + L 4β + L 1 + L 4α + L 4β + L 1 + L 3 + L 4β + L 3 + L 4α + L 4β + L 1 + L 4α + L 4β + L 1 + L 3 + L 4β + dimension
, reported in the Table S2.2, matched those calculated, reported in the Table S2.3. However, not all the possible correlation peaks predicted were observed in the experimental data.

Choice of experimental parameters

The acquisition of the spectra shown in Fig. 4 and7, obtained using the pulse sequence shown in Fig. 1B, required the optimization of the multiple-quantum build-up time 2𝜏 and of a refocusing delay 2𝜏 ! between the mixing pulse and acquisition.

For UF2DNMR experiments carried out on high-resolution solution-state NMR hardware, the duration of the train of bipolar gradient is limited by the modest robustness of the gradient coil and amplifier. As a result, acquisition blocks of up to about 100 ms are typically used. If the acquisition is started just after the mixing pulse, the duration may not be enough for anti-phase single-quantum coherences to evolve into observable terms.

For this reason, a spin-echo block ( 𝜏 -𝜋 -𝜏 ) is inserted between the mixing pulse and the acquisition period.

The parameters 𝜏 and 𝜏 ! were optimised using the sequences A (without the refocusing period) and B (with the refocusing period) shown in Fig. 1. Fig. 5 shows data obtained from UF experiments performed using these sequences as well as equivalent conventional ones: the average behaviour of the peak volumes arising from MQ coherences belonging to phenol and naphtalene, is plotted as function of 𝜏 or 𝜏 ! (the full set of curves is shown in. Fig. S2.3). Sequence A was used to determine the MQ build up times, by running a set of experiments with different 𝜏 delays. The value of 𝜏 corresponding to the highest peak volume, was then kept fixed in the sequence B, and a new set of experiments were performed with different 𝜏 ! delays in order to determine the time required to let the anti-phase terms to evolve into in-phase terms. Note that no 5MaxQ in the UF spectrum from the sequence without the refocusing block was observed. (a-c), evolution of the peak volume (normalized to the highest peak volume observed in each trend) of phenol and naphthalene observed in conventional and UF 3Q, 4Q and 5Q NMR spectra obtained using the sequence A, as function of the 𝜏 delay that was changed from 20 ms to 300 ms. (d-f), evolution of the peak volume of the phenol and naphthalene in conventional and UF 3Q, 4Q and 5Q NMR spectra, as function of the 𝜏 ! delay that was changed from 20 ms to 300 ms, the length of the 𝜏 delay was kept fixed at the values shown in the title. Plot with the dotted lines represent data obtained from a FID (originally 800 ms long) truncated in nine chucks of 72 ms.

The data obtained from conventional and UF experiments showed comparable maxima and trends. The plots in Figs. 5ac show three clear maxima for all the MQ(s), in the range between 60 ms and 100 ms, centred about 200 ms and at 300 ms. Choosing points corresponding to maxima (at 200 ms in the 3Q experiments, at 80 ms in the 4Q experiments and at 100 ms in the 5Q experiments), a new set of experiments were performed using the sequence B keeping 𝜏 fixed at these values and with 𝜏 ! changing from 20 ms to 300 ms, as shown in Figs. 5d-f. From this data, we concluded that in order to acquire UF MQ spectra with of good quality, as that obtained in the conventional ones, build up times ranging between 80 ms -200 ms, and a delay (that can be introduced by a refocusing block or by a pre-acquisition delay) of about 60 ms -100 ms before the acquisition, have to be applied. 3Q spectra showed in Fig. 4 (and Fig. 7 for the UF 4Q NMR experiments) were acquired using sequence B with 𝜏 equal to 200 ms and 𝜏 ! equal to 180 ms, 4Q spectra were obtained with 𝜏 equal to 80 ms and 𝜏 ! equal to 60 ms, 5Q spectra were obtained with the 𝜏 delay equal to 100 ms and 𝜏 ! equal to 60 ms, corresponding to maxima observed in plots showed in Fig. 5.

In order to illustrate the role of the refocusing delay, a complementary curve was obtained by processing data obtained with conventional MQ NMR pulse sequence (without spin-echo between mixing and acquisition) with an acquisition time (𝑡 ) ) of 800 ms, but using a data chunk of 72 ms separated from the mixing pulse. The evolution of the peak volume obtained in the first nine chunks (Figs. 5d-f, dotted lines), matches that of the experiments using the refocusing delay. In this work the refocusing delay did not serve the purpose of pure-absorption processing of the data [43], which is in most cases not feasible for spatially encoded 2D spectra, but to add an additional time in the pulse sequence in order to allow the conversion of the anti-phase terms to in-phase term, increasing the intensity of the signal in the spectra.

Sensitivity of UF MQ NMR

While it provides a significant acceleration of multidimensional experiments, spatial encoding also comes with a sensitivity penalty [38,[44][45]. Besides the reduction in signal due to the acquisition of a single scan, UF2DNMR experiments have reduced sensitivity per square root of measurement time, due to the increased noise level that comes with the use of a large acquisition bandwidth to cover the gradient-induced frequency dispersion. This effect can be characterised by comparing the signal-to-noise ratio (SNR) of, on the one hand, conventional experiments acquired with N1 increments and a single scan per increment, and, on the other hand, UF experiments acquired with N1 signal-averaged scans. SNR comparisons show that the UF version, as expected, has, in the direct dimension, a sensitivity penalty in the 5-25 range. The spread of SNR ratios is dues in part to the fact that the UF experiment is here implemented in constant time mode, which results in additional J-modulation of peak intensities. Interestingly, the SNR ratio is less unfavourable for UF spectra in the indirect dimension, because of significant t1 noise in the conventional experiments, while UF2DNMR spectra are essentially free of t1 noise [44], SNR measurements for a selection of peaks is shown in Table S2.4-2.6.

UF MQ NMR applied to reaction monitoring

UF2DNMR has been shown to be useful to monitor chemical reaction at short reaction time and with increased time resolution [46]. UF MQ NMR could complement the set of available UF pulse sequences, especially for aromatic compounds. is illustrated here with the monitoring of a catalysed cycloaddition reaction with UF 4Q NMR experiments. The reaction scheme of the studied inverse electron-demand aza-Diels-Alder reaction is shown in Fig. 6, which a variation of MaxQ from the reagents (MaxQ equal to 5) to the product a cyclohexene derivative with a very well-defined 4Q arising from protons 8, 9, 10 and 11. The 1D spectra of the initial reaction mixture and final cyclohexene derivative compound, as well as the assignment of the signals are shown in Fig. S3.1 and Table S3.1. Fig. 7 shows a selection of spectra from a time-series acquired during the reaction, which was carried out in an NMR tube, using either a room-temperature probe equipped with triple-axis gradients, or Comparing the data obtained with two different probes highlights the relative merits of the two setups. As expected, the spectra acquired with a cryoprobe have a higher signal-to-noise ratio. For example, the 4Q correlation of the two phenyl groups of the product, at 7.40 ppm, were already visible after 5 minutes after the addition of the dienophile and the catalyst, while they become visible after 7 minutes only in the experiments performed with the triple-axis gradient probe. On the other hand, the use of orthogonal gradients for coherence selection with the triple-axis gradient probe results in much cleaner spectra, so that a cryoprobe equipped with triple-axis gradients would be ideal for this type of experiments.

Conclusions

In summary, we have demonstrated the ultrafast acquisition of maximum quantum (MaxQ) spectra in a single scan, with performance comparable to those observed in the conventional experiments, and proposed an experimental strategy to determine the best experimental conditions with an optimal compromise between sensitivity and resolution, as well as a theoretical approach to quickly identify correlation peaks that can simplify the spectral analysis. The proposed UF MaxQ approach could be useful for the analysis of stable mixtures and for reaction monitoring that contain and /or involve structurally similar aromatic compounds.

Fig. 1 .

 1 Fig. 1. Pulse sequences for (A) UF MQ without refocusing period. (B) UF MQ with refocusing period.

Fig. 2 .

 2 Fig. 2. Chemical structure of the six compounds used in this work, were: (A) caffeic acid, (B) ferulic acid, (C) vanillic acid, (D) anthracene, (E) naphthalene and (F) phenol.

Fig. 3 :

 3 Fig. 3: 1D NMR spectrum of the aromatic mixture studied in this work, the colour code and numbering are referring to structures shown in Fig. 2.

Fig. 5 .

 5 Fig. 5.(a-c), evolution of the peak volume (normalized to the highest peak volume observed in each trend) of phenol and naphthalene observed in conventional and UF 3Q, 4Q and 5Q NMR spectra obtained using the sequence A, as function of the 𝜏 delay that was changed from 20 ms to 300 ms. (d-f), evolution of the peak volume of the phenol and naphthalene in conventional and UF 3Q, 4Q and 5Q NMR spectra, as function of the 𝜏 ! delay that was changed from 20 ms to 300 ms, the length of the 𝜏 delay was kept fixed at the values shown in the title. Plot with the dotted lines represent data obtained from a FID (originally 800 ms long) truncated in nine chucks of 72 ms.

Fig. 6 .

 6 Fig. 6. Inverse electron-demand aza-Diels-Alder reaction catalysed by a racemic BINOL-phosphoric acid.

  with a single-axis gradient. The 4Q spectra of the diene (before the addition of the dienophile and the catalyst) and of the final mixture are also shown. The conventional 4Q NMR spectra of the reaction mixture and of the final compound are shown in Fig.S3.2.

Fig. 7 :

 7 Fig. 7: UF 4Q NMR monitoring of a catalysed cycloaddition reaction, with (a-d) a room-temperature probe equipped with the triple-axis gradient probe, (a'-d') a cryoprobe with the single-axis gradient, UF 4Q NMR spectra were acquired at different stage of the reaction. a) imine compound before the addition of the catalyst and the dienophile, b) reaction mixture 5 minutes and 22 seconds after the addition of the dienophile and the catalyst (4 minutes required for locking and shimming, plus the experimental time of 1 minute and 22 seconds), c) reaction mixture 7 minutes and 22 seconds after the addition of the dienophile and the catalyst, d) reaction mixture at the end of the reaction. The spectra were processed using contour levels at 3 times the rms of the noise, the colour code of the operators was established in according to chemical structure shown in Fig. 6. Spectra obtained with the triple-axis and single-axis probe had different spectra width in the UF dimension due to the difference in the amplitude of the encoding gradients, this figure is showing only the central region of the full spectra.Signals belonging to the imine compound, the dienophile and the final cyclohexene compound can be assigned. In the first UF 4Q NMR spectum (Fig.7a), four intense signals arising from the 4Q of the imine compound ( at 7.32 ppm, at 7.36 ppm, at 7.63 ppm,

9

 9 Ultrafast acquisition of multiple quantum spectra of an aromatic mixture in one second Maria Grazia Concilio, Corentin Jacquemmoz, Dina Boyarskaya, Géraldine Masson and Jean-Nicolas Dumez* Page No. 1 -Page No. Ultrafast maximum quantum NMR spectroscopy for the analysis of aromatic mixtures

Acknowledgements

This research was supported by the Agence Nationale de la Recherche (ANR-16-CE29-0012).