Olivier Pringault D'

Dr Patricia Bonin

Dr Au

Lapeyrouse Saint

Alexander L Jaffe

Maxime Fuster

Marie C Schoelmerich

Lin-Xing Chen

Jonathan Colombet

Hermine Billard

Télesphore Sime-Ngando

Jillian F Banfield

.L-1) Chlorophyceae Cryptophyceae Cyanobacteria

Keywords: Aster Like Nanoparticles Biomimetic Mineral-Organic Particles Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaea

Tout d'abord un grand merci au Dr Claire Geslin et au Dr

Table des Figures et Tableaux

 ............................................................................... ......................................................................................................................................................... ...................................................................................................................................................... Figure 11: Schematic overview of the specific and major ecological roles of femtoplankton entities mentioned in this review. ......................................................................................................................................................... ...................................................................................................................................................... . ..................................................................................................................................................................... Figure 22: (A-C), Electromicrographs documenting a putative interaction between aster-like nanoparticles and microbial cells. ................................................................................................................................................ Figure 23: Sampling site locations and distribution of ALNs in different aquatic environments along the watershed of Loire River (France). ............................................................................................................... . ........................................................................................................................................................................ ................................................................. .............................................................................................................................................................................. .............................................................................................................................................................................. .............................................................................................................................................................. .............................................................................................................................................................................. ALNs. .............................................................................................. . .......................................................................................................................................... . .......................................................................................................................................................... Table 4: Pearson correlation between Aster Like Nanoparticles and the environmental variables in the 3 lakes. ..................................................................................................................................................................... Table 5: Significant Spearman correlation coefficients between the presence of ALNs and the presence of microbial OTUs. ...................................................................................................................................................

Figure 21:(A) Distribution of aster-like nanoparticles and bacteria abundances in 16 selected stations of a tropical coastal ecosystem (Ha Long Bay-Vietnam), and (B) analyses of correlations (Spearman's productmoment correlation coefficient) between ALNs and environmental parameters which compile all sampling points

Figure 27: Principal Component Analysis of individuals (sampling points) in function of lakes (A) or seasons (B)

Figure 30: Transmission electron micrographs of different morphotypes of aster-like nanoparticles (ALNs

Figure 38 : Images d'ALNs en microscopie électronique à transmission (A,B) ou en microscopie à force atomique (C,D) détaillant la structure des

Table 1: Comparison of morphologies, some main constitutional elements and development strategies of femtoplankton entities

Table 2: Physicochemical characteristics of the lakewater on

Table 3: Mean ± SD of physico-chemical and biological characteristics according to the lakes (A) or the seasons (B)

Résumé

Face au changement global et notamment à l'augmentation de la température des eaux de surface [START_REF] Whitehead Pg | A review of the potential impacts of climate change on surface water quality[END_REF], il est devenu indispensable de comprendre et d'anticiper l'évolution des écosystèmes aquatiques. Le bon fonctionnement et l'évolution de ces écosystèmes ont toujours été intimement liés au fonctionnement du compartiment biologique et notamment microbien [START_REF] Lalli | Biological Oceanography: An Introduction[END_REF]. Les avancées technologiques des dernières décennies ont permis de mettre en évidence un véritable réseau d'interactions microbiennes [START_REF] Pomeroy | The Microbial Loop[END_REF], intégrant une diversité jusqu'alors insoupçonnée d'entités submicrométriques pouvant avoir une importance fonctionnelle majeure [START_REF] Mostajir | LES RÉSEAUX TROPHIQUES MICROBIENS DES MILIEUX AQUATIQUES ET TERRESTRES. Presses Universitaires de Pau et des Pays de l'Adour 10. Sime-Ngando T[END_REF]. Pour comprendre le fonctionnement global des écosystèmes aquatiques, il semble donc nécessaire de concentrer des efforts de recherche sur les plus petites fractions de taille, notamment sur les particules nanoplanctoniques appartenant au femtoplancton jusqu'alors sous-considérées (< 0.2 µm ou 200 nm).

Dans ce contexte, la découverte d'une nouvelle catégorie de particules organiques appartenant au femtoplancton, nommées « Aster Like Nanoparticles » (ALNs) (Colombet et al., 2019), soulève de nombreuses questions et notamment celle de leur importance fonctionnelle au sein des écosystèmes aquatiques. L'objectif principal de cette thèse est donc d'approfondir nos connaissances sur les fonctionnalités des ALNs, en se focalisant particulièrement sur l'étude écologique de ces entités afin de pouvoir, à terme, expliquer leur présence et appréhender leurs interactions avec leur environnement physico-chimique et microbien. Pour cela, différentes échelles d'intégration seront considérées : de l'échelle écosystémique à l'échelle expérimentale, en conditions contrôlées.

Nos résultats ont, dans un premier temps, permis de mettre en évidence la présence des ALNs dans un large spectre d'habitats aux caractéristiques différentes [START_REF] Fuster | Trophic conditions influence widespread distribution of Aster-Like nanoparticles within aquatic environments[END_REF]. Ces résultats ont permis de prouver l'ubiquité des ALNs, capables de se développer dans des environnements physico-chimiques variés. Une étude complémentaire a permis de dresser la dynamique temporelle des ALNs dans différents écosystèmes aquatiques, suggérant que les ALNs sont un acteur majeur à intégrer dans les modèles de successions écologiques [START_REF] Fuster | Occurrence and Seasonal Dynamics of ALNs in Freshwater Lakes Are Influenced by Their Biological Environment[END_REF]. Cette étude, menée dans trois lacs du Puy-de-Dôme, a permis de démontrer l'importance des paramètres biologiques dans la distribution des ALNs, et notamment l'importance potentielle des procaryotes. Finalement, des études en microcosmes ont permis de confirmer l'importance des procaryotes, avec des résultats montrant un développement jusqu'à 20 fois plus important des ALNs en présence d'une forte concentration de procaryotes. De façon générale, nos résultats ont démontré l'importance des ALNs en tant que nouveaux acteurs dans les écosystèmes aquatiques, d'une part par leur dynamique écosystémique marquée et, d'autre part, par leurs interactions avec les procaryotes, principaux régulateurs des flux de matière et d'énergie. Les ALNs sont donc de nouvelles entités planctoniques qu'il faudra désormais prendre en compte dans l'étude des écosystèmes aquatiques. Enfin, l'ensemble de nos résultats soulève des perspectives de recherche sur la nature et l'écologie des ALNs et leur place dans les schémas évolutifs du monde organique.

Abstract

With global change and especially the increase of surface water temperature [START_REF] Whitehead Pg | A review of the potential impacts of climate change on surface water quality[END_REF], it has become essential to understand and anticipate the evolution of aquatic ecosystems. The proper functioning and evolution of these ecosystems have always been linked to the functioning of the biological compartment, and especially the microbial compartment [START_REF] Lalli | Biological Oceanography: An Introduction[END_REF]. Over the last few decades, technological advances have revealed a complex network of microbial interactions [START_REF] Pomeroy | The Microbial Loop[END_REF], including a previously unsuspected diversity of sub-micrometric entities that may have major functional importance [START_REF] Mostajir | LES RÉSEAUX TROPHIQUES MICROBIENS DES MILIEUX AQUATIQUES ET TERRESTRES. Presses Universitaires de Pau et des Pays de l'Adour 10. Sime-Ngando T[END_REF]. To understand the global functioning of aquatic ecosystems, it therefore seems necessary to focus research on the smallest size fractions, especially on the previously underconsidered nanoplanktonic particles belonging to femtoplankton (< 0.2 µm or 200 nm).

The discovery of a new type of organic particles belonging to femtoplankton, named "Aster Like Nanoparticles" (ALNs) (Colombet et al., 2019), raises many questions, especially about their functional importance in aquatic ecosystems. The principal objective of this thesis is therefore to deepen our knowledge on the functionalities of ALNs, focusing especially on the ecological study of these entities to be able, in the future, to explain their presence and understand their interactions with their physico-chemical and microbial environment. To this, different scales of integration will be considered: from the ecosystemic to the experimental scale, under controlled conditions.

Our results allowed us to demonstrate the presence of ALNs in a wide range of habitats with different characteristics [START_REF] Fuster | Trophic conditions influence widespread distribution of Aster-Like nanoparticles within aquatic environments[END_REF]. These results proved the ubiquity of ALNs, which can develop in various physico-chemical environments. A complementary study has shown the temporal dynamics of ALNs in different aquatic ecosystems, suggesting that ALNs are a major player to be integrated in models of ecological succession [START_REF] Fuster | Occurrence and Seasonal Dynamics of ALNs in Freshwater Lakes Are Influenced by Their Biological Environment[END_REF]. This study, performed in three lakes of the Puy-de-Dôme, demonstrated the importance of biological parameters in the distribution of ALNs, and the potential importance of prokaryotes. Eventually, microcosm studies confirmed the importance of prokaryotes, with results showing a development of up to 20 times more ALNs in the presence of a high prokaryotes concentration. Altogether, our results showed the importance of ALNs as new actors in aquatic ecosystems by their strong ecosystemic dynamics and by their interactions with prokaryotes, the main regulators of matter and energy flows. ALNs are therefore new planktonic entities that should be considered in the study of aquatic ecosystems. All our results raise research perspectives on the nature and ecology of ALNs and their position in the evolutionary patterns of the organic world. [11] Il est désormais avéré qu'un changement climatique d'origine anthropique est inévitable. Dans ce contexte de changement global, l'un des impacts est l'augmentation moyenne de la température des eaux de surface, entrainant une modification de l'équilibre chimique et biologique des écosystèmes aquatiques [1]. Prédire les changements de ces écosystèmes afin d'anticiper leurs impacts est donc devenu un défi majeur pour la communauté scientifique. Pour cela, il est nécessaire de comprendre leur fonctionnement, notamment en étudiant (i)

Les flux de matière et d'énergie transitant par ces écosystèmes.

(ii) La diversité des entités et leurs activités biochimiques, régulateurs biologiques de ces flux.

À l'origine, le fonctionnement des écosystèmes et notamment les interactions entre les différents microorganismes et les flux associés étaient appréhendés de manière simplifiée [2].

Les premiers modèles de chaînes trophiques aquatiques étaient donc structurés autour de deux concepts différenciés [2] :

(i) La chaine trophique des brouteurs (reposant sur l'assimilation photosynthétique des producteurs primaires -phytoplancton-, consommé -broutage-par le zooplancton, lui-même consommé par les poissons).

(ii) Le recyclage de la matière organique (provenant des déchets produits par la chaine trophique des brouteurs) par les procaryotes, notamment les bactéries hétérotrophes.

Dû aux limitations techniques, ce concept de chaînes trophiques dissociées ne prenait en compte qu'une part minime de la diversité des organismes aquatiques, excluant notamment les entités sub-micrométriques et les métabolismes et interactions biologiques potentiels associés. La diversité de ces entités s'est par la suite montrée beaucoup plus importante que ce que l'on croyait [3,[START_REF] Joshi | Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files[END_REF], contribuant de manière tout aussi importante aux flux de matière et d'énergies de la chaîne trophique que les groupes identifiés initialement [5]. L'importance quantitative et fonctionnelle de cette nouvelle diversité biologique, auparavant non considérée, a donc conduit à une reconsidération des modèles d'organisation trophique des écosystèmes aquatiques.

Aujourd'hui, nous sommes passés d'une simple chaîne trophique à un véritable réseau complexe d'interactions, intégrant cette nouvelle diversité aux flux de matière et d'énergie à travers les concepts de boucle microbienne [6,7], virale et de réseaux trophiques microbiens [8][9][START_REF] Chaumeil | GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF] (Figure 1). D'après [16] La boucle microbienne est connectée de manière directe et indirecte au réseau trophique classique, via les processus de prédation, parasitisme, excrétion, recyclage des éléments nutritifs, etc… [12] (Figure 1). La mise en évidence d'une diversité sub-micrométrique importante a permis d'améliorer les modélisations de flux qui, jusqu'ici, n'expliquaient qu'en partie les transferts énergétiques et de biomasse [13,14]. Les modélisations actuelles font donc une part de plus en plus importante aux entités de petite taille dans les écosystèmes aquatiques (i.e. nano, pico et femtoplancton) [9,15], lesquelles ont jusqu'à maintenant été sous considérées [16]. L'intégration de toutes les composantes du plancton, y compris celles de plus petite taille, semble donc essentielle dans la compréhension du fonctionnement des écosystèmes. Le terme plancton a été introduit pour la première fois par Hensen (1887), pour définir tout organisme vivant en suspension dans l'eau, ayant un pouvoir locomoteur réduit. Le plancton a d'abord été divisé en grands groupes fonctionnels en fonction de leurs modes trophiques (e.g. producteurs primaires, consommateurs primaires, etc…), mais des raisons pratiques liées à leur étude ont conduit à la création d'une classification par taille où différentes modes trophiques sont confondus [17] (Figure 2).

Si les fractions de tailles supérieures sont aujourd'hui largement considérées, les fractions de plus petites tailles ont été ignorées ou sous-estimées durant des décennies, notamment à cause de limitations technologiques. Pour comprendre le fonctionnement global des écosystèmes aquatiques, il semble donc important de concentrer des efforts de recherche sur les plus petites fractions de taille, notamment sur les particules nanoplanctoniques appartenant au femtoplancton (< 0.2 µm ou 200 nm).

Le développement des nouvelles méthodes analytiques, notamment en microscopie, a permis d'améliorer nos connaissances sur les particules nanométriques vivantes ou non (e.g. les particules femtoplanctoniques : 2 -200 nm). Ces techniques ont permis de mettre en évidence une diversité insoupçonnée, les milieux aquatiques étant des réservoirs importants d'entités femtoplanctoniques jusqu'alors négligées. Le femtoplancton n'est donc pas uniquement composé de virus, comme considéré durant des décennies, mais aussi de nombreux autres types de particules. La diversité de ces nanoparticules peut être classée selon un gradient progressif de complexité, allant d'entités minéralo-organiques à des entités biotiques [16] (Figure 3). D'après [16].

Les progrès scientifiques ont donc permis d'identifier différentes entités femtoplanctoniques :

• Les particules minéralo-organiques biomimétiques (BMOPs), dérivées de processus physico-chimiques pouvant associer des minéraux et des molécules d'origine organique [18] (Figure 3 A-B).

• Les vésicules extracellulaires (EVs) (Figure 3 C-D). Les EVs sont universellement produites par les membres de toutes les branches de l'arbre de la vie [19,20] ; ces vésicules peuvent avoir des fonctions biologiques ou écosystémiques potentiellement importantes [16,21].

• Les virus ou particules d'allure virale (VLPs) (Figure 3 E-F). Les virus ont longtemps été considérés comme la seule composante du femtoplancton. II s'agit d'entités biologiques acellulaires, incapables de se reproduire sans leurs cellules hôtes. Ayant un génome constitué d'ADN ou d'ARN, les virus se trouvent partout où la vie cellulaire est présente ; ils sont très abondants en milieu aquatique et représentent un grand réservoir de biodiversité sur terre [START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF].

• Les nanobactéries ou nanoarchées (plus petits procaryotes décrits à ce jour). Parmi ces nanoprocaryotes, la découverte des CPR (Candidate Phyla Radiation) et DPANN (acronyme des cinq premiers phyla, « Candidatus Diapherotrites », « Candidatus Parvarchaeota », « Candidatus Aenigmarchaeota », Nanoarchaeota et « Candidatus Nanohaloarchaeota ») a généré de nouvelles connaissances concernant la place des procaryotes dans l'arbre de la vie (Figure 3 G-H) [23].

La découverte de toutes ces entités a largement complexifié la compréhension de la fraction femtoplanctonique, impliquant une reconsidération de la diversité et de l'importance écologique du femtoplancton. À travers le spectre de leurs activités et de leurs hôtes potentiels, les entités femtoplanctoniques ont la capacité d'interagir avec tous les composants du plancton. Étant donné leur forte concentration, le femtoplancton peut jouer un rôle majeur dans la circulation, la disponibilité et le transfert de matière et d'énergie dans l'environnement [18]. Leurs interactions avec les autres entités influencent et peuvent contrôler la structure des communautés microbiennes, avec un impact direct ou indirect sur des cycles majeurs tel que le cycle du carbone [24][25][START_REF] Weitz | Quantitative Viral Ecology: Dynamics of Viruses and Their Microbial Hosts[END_REF].

La diversité méconnue et l'abondance de toutes ces entités ont donc nécessairement un impact sur la circulation des éléments et les cycles biogéochimiques dans les écosystèmes aquatiques.

Ces nanoparticules représentent encore aujourd'hui une source potentielle de nouvelles Tout comme les autres entités femtoplanctoniques, les ALNs sont des interactants potentiels des procaryotes [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Ajouté à leur capacité de développement et de colonisation du milieu avec des abondances pouvant atteindre 10 8 particules.mL -1 , ces ALNs seraient des acteurs méconnus dans le fonctionnement des écosystèmes aquatiques [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

Aujourd'hui, la compréhension de l'évolution des écosystèmes aquatiques est un défi majeur, notamment face au changement global. La découverte des ALNs soulève de nombreuses questions sur leurs rôles potentiels dans les cycles d'éléments conservés régissant le fonctionnement des écosystèmes. Comprendre ce fonctionnement nécessite donc une meilleure appréhension des entités nanométriques tel que le femtoplancton. L'objectif principal de cette thèse vise à approfondir nos connaissances sur les ALNs. Cet objectif est particulièrement centré sur l'étude écologique de ces entités, en lien avec leurs rôles potentiels dans les écosystèmes aquatiques.

Suite à l'état de l'art, le corps du manuscrit s'articulera autour des objectifs de la thèse visant à explorer l'écologie des ALNs afin de pouvoir, à terme, expliquer leur présence, appréhender leurs interactions et leurs rôles dans les écosystèmes aquatiques. Pour cela, différentes échelles d'intégration seront considérées : de l'échelle écosystémique à l'échelle expérimentale, en conditions plus ou moins contrôlées.

(i) Le chapitre 1 a pour objectif spécifique de déterminer les conditions préférentielles de développement des ALNs. Pour ce faire nous avons réalisé une étude géographique sur le bassin versant de la Loire, afin de déterminer la distribution des ALNs dans différents écosystèmes aquatiques.

(ii) Le chapitre 2 permettra de vérifier les facteurs putatifs de contrôle des ALNs identifiés dans le chapitre 1, en étudiant leur trophodynamique saisonnière dans 3 écosystèmes lacustres.

(iii) Le chapitre 3 s'intéressera aux interactions potentielles que les ALNs peuvent avoir avec les autres communautés présentes dans l'écosystème, abordées via des expériences en conditions contrôlées. Ces études expérimentales viseront à valider les hypothèses retenues lors des suivis écosystémiques précédents.

Pour finir, un dernier chapitre viendra conclure les travaux réalisés durant cette thèse. L'objectif de ce chapitre sera de mener une analyse intégrative des résultats obtenus, afin de faire ressortir les éléments marquants permettant de mieux comprendre l'écologie des ALNs. Cela permettra également de dresser de nouvelles perspectives de recherche, sources de réflexions pour généraliser les rôles potentiels des ALNs dans le fonctionnement des écosystèmes aquatiques.

ÉTAT DE L'ART / DÉCOUVERTE DES ALNs

Le femtoplancton est devenu en quelques années un compartiment essentiel dans la

Le compartiment femtoplanctonique : source de nouvelles connaissances en biologie et en écologie

Femtoplankton: What's New?

Jonathan COLOMBET 1 , Maxime FUSTER 1 , Hermine BILLARD 1 , Télesphore SIME-NGANDO

Abstract

Since the discovery of high abundances of virus-like particles in aquatic environment, emergence of new analytical methods in microscopy and molecular biology has allowed significant advances in the characterization of the femtoplankton, i.e., floating entities filterable on a 0.2 µm pore size filter. The successive evidence in the last decade (2010-2020) of high abundances of biomimetic mineral-organic particles, extracellular vesicles, CPR/DPANN (Candidate phyla radiation/Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota and Nanohaloarchaeota), and very recently of aster-like nanoparticles (ALNs), show that aquatic ecosystems form a huge reservoir of unidentified and overlooked femtoplankton entities. The purpose of this review is to highlight this unsuspected diversity. Herein, we focus on the origin, composition, and the ecological potentials of organic femtoplankton entities.

Particular emphasis is given to the most recently discovered ALNs. All the entities described are displayed in an evolutionary context along a continuum of complexity, from minerals to cell-like living entities.

Introduction

Victor Hensen first introduced the term "plankton" in 1887 to define all organisms that live in suspension in water and have limited locomotion power to maintain their position against currents. Plankton was first divided into broad functional groups according to their trophic levels but practical reasons related to their study has led to a classification by size classes [17].

Thus, Sieburth classified plankton into size ranges covering eight orders of magnitude from femto-(0.02-0.2 µm) to mega-plankton (>20 cm) [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF] (Figure 2).

While the largest size fraction has proved to be very diversified, with the occurrence of various phylogenetic groups, the smallest one, i.e., femtoplankton, has long been considered to be exclusively composed of virus-like particles (VLPs) [9,[START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF]. Over the last two decades, technical advances in molecular and microscopic sciences have revealed an unexpected and underestimated diversity of femtoplankton entities other than viruses, including, for example, various tiny prokaryotes CPR (Candidate phyla radiation), DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota and Nanohaloarchaeota) [23] and, more recently, intriguing aster-like nanoparticles (ALNs) that we have reported in various aquatic systems [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

These discoveries lead to a necessary reconsideration of the femtoplankton compartment in terms of diversity and associated ecological potentials. We refer here to "femtoplankton entities" as those that (i) are totally or partially organic, (ii) can be filterable on a 0.2 µm pore size filter, (iii) are bounded by an outer membrane, "membrane-like" or wall structure and (iv)

have the ability to multiply or divide independently or not. Fully inorganic or non-biotic nanoparticles (from 1 to 100 nm) and molecular colloids (from 1 to 1000 nm) populating aquatic systems have been the subject of excellent reviews and will not be discussed here [START_REF] Hochella | Nanoscience and technology: the next revolution in the Earth sciences[END_REF][START_REF] Santschi | Marine colloids, agents of the self-cleansing capacity of aquatic systems: Historical perspective and new discoveries[END_REF]. In addition, miniaturized prokaryotes and Candidatus Pelagibacter ubique that are on the border between femto-and nanoplankton are also excluded from this review [START_REF] Duda | Ultramicrobacteria: Formation of the concept and contribution of ultramicrobacteria to biology[END_REF][START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF][START_REF] Morris | SAR11 clade dominates ocean surface bacterioplankton communities[END_REF][START_REF] Rappé | Cultivation of the ubiquitous SAR11 marine bacterioplankton clade[END_REF].

This review focuses on the diversity of femtoentities in aquatic ecosystems, with an emphasis on the origin and composition of their different representatives and the associated ecological potentials. The femtoplankton entities treated in this review are presented in an evolutionary context, along a gradient of progressive increase in complexity, ranging from mineral-organic entities (biomimetic mineral-organic particles/nanobes) to fully biotic entities (VLPs-i.e., viruses, subviral, agents and gene transfer agents-extracellular vesicles and prokaryotes).

Particular attention is given to the recently discovered aster-like nanoparticles [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

From Mineral to Biotic Entities: A Path Toward the Living

Being?

Biomimetic Mineral-Organic Particles and Nanobes

The discovery and characterization of new femtoplankton entities collides with the concept of the origin and emergence of a cell life form. Two major theories ("The RNA world" vs. "The metabolism-first") and two approaches ("top-down biology" vs. "bottom-up chemistry") have historically competed over the research of the starting point of life on the primitive Earth and the primordial stages of life evolution [START_REF] Dyson | Origins of life[END_REF][START_REF] Gilbert | Origin of life: The RNA world[END_REF][START_REF] Ikehara | Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach)[END_REF][START_REF] Oparin | Introductory Address[END_REF][39][START_REF] Preiner | The Future of Origin of Life Research: Bridging Decades-Old Divisions[END_REF][START_REF] Shapiro | A Replicator Was Not Involved in the Origin of Life[END_REF][START_REF] Woese | The universal ancestor[END_REF]. Many scenarios to explain the emergence of the first cell life form arise from these lines of research and from the possible location where life appeared (e.g., submarine hydrothermal vents, pumice rafts, volcanic-hosted splash pools, subaerial geysers, etc., reviewed in [START_REF] Dass | Stochastic Prebiotic Chemistry within Realistic Geological Systems[END_REF][START_REF] Westall | A Hydrothermal-Sedimentary Context for the Origin of Life[END_REF]). However, at present, there is no experimental evidence of a consensus scenario (discussed in [START_REF] Preiner | The Future of Origin of Life Research: Bridging Decades-Old Divisions[END_REF][START_REF] Camprubí | The Emergence of Life[END_REF][START_REF] Forterre | The origin of modern terrestrial life[END_REF][47] and references herein). A recurring feature in the evolutionary process that could lead to the first life form is the gradual increase in complexity from inorganic nanoparticles to the emergence of the cell. Baum [START_REF] Baum | Selection and the Origin of Cells[END_REF] resumed that the cell could find its origin with the creation of chemical consortia adsorbed on mineral surfaces. The selection processes would eventually give rise to limited entities reproducing independently, such as cells.

Biomimetic mineral-organic particles (BMOPs), including the majority of controversial "nanobes" also known as "nanobacteria", "nanobacteria" or "calcifying nanoparticles" [18,[START_REF] Barr | Detection of biofilm formation and nanobacteria under long-term cell culture conditions in serum samples of cattle, goats, cats, and dogs[END_REF][START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF][START_REF] Cisar | An alternative interpretation of nanobacteria-induced biomineralization[END_REF][START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Jones | Amorphous calcium carbonate associated with biofilms in hot spring deposits[END_REF][54][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Yaghobee | What are the nanobacteria?[END_REF], could be considered as a first step in complexification leading to the genesis of a cell type structure, known as a protocell. The formation of the majority of BMOPs/nanobes could be the result of physico-chemical processes (e.g., aggregation) that are entirely abiotic, or

Figure 5: Transmission electron micrographs of biomimetic mineral-organic-(BMOPs) and/or nanobe-like particles (A-H) and vesicle-like particles (I-S).

Arrows indicate the target particles when the samples are heterogeneous. (A,B,N-S) scale bar: 100 nm, (C-H,I-M) scale bar: 500 nm.).

combinations of minerals and molecules derived from biological entities [18,[START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF]54].

Nevertheless, these entities present intriguing features. They have the potential to generate mineral-organic amalgams that are able to replicate themselves via cell-like processes, such as symmetrical fission and they have the ability to mimic various life forms (e.g., coccoid, amoeboid, ovoid, filamentous, etc.), such as microscopic fungi (Actinomycetes) and prokaryotes [START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Martel | Purported nanobacteria in human blood as calcium carbonate nanoparticles[END_REF][START_REF] Mckay | Search for past life on Mars: possible relic biogenic activity in martian meteorite ALH84001[END_REF][59]. However, their tiny size (between 20 and 1000 nm in diameter, like those in Figure 5 A-H) results, in most cases, in volumes largely under the theoretical minimal cell volume (TMCV, i.e., 0.008 µm3) required to house nucleic acids and the associated biosynthetic machinery required for a self-sufficient form of life [18,[START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Folk | In defense of nannobacteria[END_REF].

The origin and characteristics of some of these biomimetic amalgams, mainly those known as "nanobes", remain poorly understood.

The composition of these aggregates of minerals and organic particles is representative of the environment in which they evolved, including human and cow blood, terrestrial minerals, extraterrestrial meteorites, and aquatic environments [18,[START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF][START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Mckay | Search for past life on Mars: possible relic biogenic activity in martian meteorite ALH84001[END_REF][START_REF] Akernan | Scanning Electron Microscopy of Nanobacteria -Novel Biofilm Producing Organisms in Blood[END_REF][START_REF] Kajander | Nanobacteria from blood: the smallest culturable autonomously replicating agent on Earth[END_REF][START_REF] Folk | Nannobacteria and the precipitation of carbonate in unusual environments[END_REF]. Since these entities are ubiquitous, we speculate that their diversity is likely at least as great as the number of possible mineral-organic combinations in the environment and is similar or greater than the known biological diversity of the past and contemporary living world.

Carbon, oxygen, nitrogen, calcium, phosphorus, silicon, iron, sodium, magnesium, manganese, fluorine, aluminum, barium, sulfur, zinc, potassium, terbium, chlorine and cobalt are examples of elements that may be included in BMOP and nanobe composition [18,[START_REF] Christian | Nanoparticles: structure, properties, preparation and behaviour in environmental media[END_REF]. This nonexhaustive list may combine mineral phases dominated by several compounds (e.g., calcium and iron sulfates, silicon and aluminum oxides, sodium carbonate, iron sulfide and hydroxides containing iron, manganese, aluminum) with organic phases of complex composition (e.g., humic materials, peptides, proteins, lipids, peptidoglycans, polysaccharides) [18,[START_REF] Christian | Nanoparticles: structure, properties, preparation and behaviour in environmental media[END_REF] and references herein). It is interesting to note that BMOPs from human samples can include a wide range of proteins with complex biological functions, such as coagulation factors, calcification inhibitors, complement proteins, protease inhibitors, or lipid carriers [START_REF] Martel | Comprehensive proteomic analysis of mineral nanoparticles derived from human body fluids and analyzed by liquid chromatography-tandem mass spectrometry[END_REF]. The presence of nucleic acids in BMOPs and nanobes remains a controversial issue. Some authors have reported positive detection of nucleic acid using various markers [54,[START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF]. Raoult et al.[54] suggested that BMOPs and nanobes do not contain nucleic acid and that this positive detection could be the result of the labeling of contaminating nucleic acids trapped on the target particle. These results strongly suggest that environmental BMOPs and nanobes are potential carriers of genetic information and associated biological functions. It is therefore very important to strengthen the research efforts on their origin, composition, diversity, and ecological potentials through their interactions with biotic and abiotic environments.

Many authors, in agreement with the origin, composition and the theoretical formation pattern of BMOPs and nanobes, have classified them as non-living forms [18,[START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF]54,[START_REF] Martel | Purported nanobacteria in human blood as calcium carbonate nanoparticles[END_REF]. However, some controversial "nanobes" remain mysterious and further work is needed to clearly elucidate their exact nature and to understand the potential role of BMOPs and nanobes in the evolution of life [START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Yaghobee | What are the nanobacteria?[END_REF][START_REF] Folk | Nannobacteria and the precipitation of carbonate in unusual environments[END_REF]. Indeed, if they are not living entities, BMOPs and nanobes can be considered as an evolutionary step towards cell formation through the formation of mineralorganic complexes. Their composition and organization into cell type structures (including a membrane mimicking the cell wall, [START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF]) could be consistent with the beginning of the compartmentalization process known as one of the critical steps in the genesis of earlier free or symbiotic cell forms.

Extracellular Vesicles

The progressive increase in complexity of bio-mineral complexes at cell emergence requires a critical step where a boundary occurs and separates the living cell system from its environment [START_REF] Oparin | Introductory Address[END_REF][START_REF] Chen | From Self-Assembled Vesicles to Protocells[END_REF]67]. The compartmentalization of the primordial soup (i.e., the process that allowed the isolation and creation of a physico-chemical and thermodynamic environment suitable for the synthesis of bio-macromolecules) into vesicles would have favored the emergence of primitive life forms [START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]. These authors also suggested that membrane vesicles could have a role in early cell evolution and may have helped shape the nature of LUCA, our Last Universal Common

Ancestor. Thus, lipid vesicles may have been the first protocells to concentrate RNA before the appearance of ribocells, ancestors of RNA-based cells, that preceded LUCA [START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]. Beside this evolutionary theory, there is no doubt that extracellular vesicles (EVs) represent the smallest cell-like entities surrounded by a lipid structure.

The biology of EVs has been widely documented over the last decade, mainly in terms of their origin, composition, diversity and biological purposes (see references in [19,[START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF]). Scientists reported that EV production is a universal and conserved process that occurs in all branches of the tree of life: bacteria, archaea and eukaryotes [20,25]. EVs are diverse in origin and composition, and there is little consensus on their classification [START_REF] Gould | As we wait: coping with an imperfect nomenclature for extracellular vesicles[END_REF]. Bacterial vesicles are represented by extracellular vesicles (20-250 nm) or outer membrane vesicles (20-230 nm) while archaea produce membrane vesicles (50-230 nm). Eukaryotic EVs can be grouped into three main groups: microvesicles (50-1000 nm), exosomes (30-150 nm) and apoptotic bodies (500-2000 nm) [START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF][START_REF] El Andaloussi | Extracellular vesicles: biology and emerging therapeutic opportunities[END_REF]. With the exception of apoptotic vesicles and large microvesicles, the other EVs are spherical nanoparticles [20,21,[START_REF] Koning | Cryo-electron tomography analysis of membrane vesicles from Acinetobacter baumannii ATCC19606T[END_REF][73][START_REF] Pérez-Cruz | Outer-inner membrane vesicles naturally secreted by gram-negative pathogenic bacteria[END_REF]. These particles could therefore be found in plankton where they can be confused with other nanoparticles (Figure 5 I-S). Since all living cells on earth are probably capable of producing vesicles, we assume that their diversity could be as great as that of their parent cells.

Bacterial vesicles are formed by budding of the cytoplasmic, outer and outer-inner membrane.

The composition of their membrane and lumen is therefore reminiscent of the membrane, periplasm and cytoplasm of their producer cells. For example, EVs may contain soluble proteins, membrane proteins, lipoproteins, phospholipids and glycolipids from the donor cells membrane. All of these molecules are involved in essential cell membrane functions, such as substances transfer, cell adhesion, ion conductivity, cell signaling, binding surface for several extracellular structure, etc. [19,20,[START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF][START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF]. They also carry elements of the cytoplasm of the producing cells, such as toxins, DNA, RNA, immunomodulatory compounds, communication factors, adhesins, adenosine triphosphate (ATP), enzymes involved in the degradation of peptidoglycans or antibiotics, virulence factors (anthrolysin, coagulases, lipase), etc. [19,[START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF] and references therein). The quality and quantity of molecular loads differ greatly from one EV to another. For example, in the marine environment, Biller et al. [START_REF] Biller | Membrane vesicles in sea water: heterogeneous DNA content and implications for viral abundance estimates[END_REF] demonstrated that the size and quantity of DNA varied between different bacterial taxa and that only a small proportion of EVs contain DNA.

Knowledge about the vesicles produced by archaea is less extensive and still in its infancy compared to bacteria. In aquatic environments, the models studied (mainly Sulfolobus and Thermococcales) show that archaea EVs are membrane vesicles produced by cytoplasmic membrane. The biology of these models, in terms of origin, composition, diversity and biological purpose, is detailed in [19]. As with bacteria, the composition of archaea vesicles is inherited from their producing cell. For example, membrane vesicles produced by Sulfolobus or Thermococcus species harbor S-layer proteins and the oligopeptide-binding protein OppA obtained from parental cells [START_REF] Prangishvili | Sulfolobicins, specific proteinaceous toxins produced by strains of the extremely thermophilic archaeal genus Sulfolobus[END_REF][START_REF] Soler | Virus-like vesicles and extracellular DNA produced by hyperthermophilic archaea of the order Thermococcales[END_REF][78][START_REF] Ellen | Proteomic analysis of secreted membrane vesicles of archaeal Sulfolobus species reveals the presence of endosome sorting complex components[END_REF]. The EVs of three Sulfolobus species carry various proteins identified as having potential implications in cell division (ESCRT, Vps4), adhesion, migration, homing, pattern formation and signal transduction (vWA), as well as in signaling, endocytosis (flotillin), cyanure detoxification (thiosulfate sulphur transferase) and antimicrobial processes (sulfolobicin) [19,[START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]. EVs produced by Thermococcus species are often associated with genomic DNA or RNA [START_REF] Soler | Virus-like vesicles and extracellular DNA produced by hyperthermophilic archaea of the order Thermococcales[END_REF]78,[START_REF] Choi | Proteomics of extracellular vesicles: Exosomes and ectosomes[END_REF]. Recently, Erdmann et al. [START_REF] Erdmann | A plasmid from an Antarctic haloarchaeon uses specialized membrane vesicles to disseminate and infect plasmid-free cells[END_REF] described a new type of EV containing plasmid in a psychrophilic halophilic archaea Halorubrum lacusprofundi.

The origin and composition of eukaryotic vesicles (i.e., exosomes and microvesicles) are well documented (see reviews in [19,[START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF]). Gill et al. [19] mentioned that the release of EVs in the environment is characteristic, and probably conserved, in all eukaryotic cell types (i.e., animals, plants, protists and fungi), including single and multicellular organisms. As such, they may be present in all types of environments, including aquatic systems. However, most studies to date have been conducted in animals, mainly in terrestrial mammalian models such as mice and humans [START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF]. Exosomes are formed through the endocytic pathway from the "outward" budding of the late endosomal membrane [START_REF] Harding | Receptor-mediated endocytosis of transferrin and recycling of the transferrin receptor in rat reticulocytes[END_REF][START_REF] Pan | Fate of the transferrin receptor during maturation of sheep reticulocytes in vitro: Selective externalization of the receptor[END_REF]. They can accumulate in multivesicular bodies during the endosomal pathway and can be released into the environment after fusion with the plasma membrane [20,[START_REF] Yáñez-Mó | Biological properties of extracellular vesicles and their physiological functions[END_REF][START_REF] Bebelman | Biogenesis and function of extracellular vesicles in cancer[END_REF][START_REF] Simons | Exosomes--vesicular carriers for intercellular communication[END_REF][START_REF] Théry | Membrane vesicles as conveyors of immune responses[END_REF]. Microvesicle EVs are formed from direct outward budding or pinching of the cell's plasma membrane [START_REF] Muralidharan-Chari | Microvesicles: mediators of extracellular communication during cancer progression[END_REF]. In some cases, they are released from tubular structures that are extensions of the plasma membrane [START_REF] Rilla | Hyaluronan production enhances shedding of plasma membranederived microvesicles[END_REF]90]. Exosomes and microvesicles are formed by packaging the cytoplasmic contents in membrane-bound vesicles and have been shown to carry all types of cellular components. Extensive reviews on cargo molecules and their functions have already been provided [19,[START_REF] Doyle | Overview of Extracellular Vesicles, Their Origin, Composition, Purpose, and Methods for Exosome Isolation and Analysis[END_REF][START_REF] Villarroya-Beltri | Sorting it out: Regulation of exosome loading[END_REF]. For example, microvesicles can contain proteins involved in cell adhesion, motility, activation and proliferation (tetraspanins and associated proteins). Other cargo proteins can also be present, such as those fundamental in pathogen recognition (immunoglobulins), cytoskeletal properties (tubulin and actin), vesicular trafficking (Rab GTPase proteins, annexins, stomatin, prohibitin, flotillin) or cell division (ESCRT-related proteins), etc. In addition, many lipids, including sphingomyelin, cholesterol, ganglioside GM3, desaturated lipids, phosphatidylserine and ceramide are also intravesicular components of eukaryotic EVs, as well as genetic materials [START_REF] Subra | Exosome lipidomics unravels lipid sorting at the level of multivesicular bodies[END_REF][93][94][95][START_REF] Skotland | An emerging focus on lipids in extracellular vesicles[END_REF]. These include a large amount of mRNA and sRNA, single-stranded DNA, mitochondrial DNA, plasmid DNA and double-stranded DNA [START_REF] Valadi | Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells[END_REF][START_REF] Balaj | Tumour microvesicles contain retrotransposon elements and amplified oncogene sequences[END_REF][START_REF] Guescini | C2C12 myoblasts release micro-vesicles containing mtDNA and proteins involved in signal transduction[END_REF][100][101].

Overall, EV composition varies greatly depending on the phylogenetic position, lifestyle and physiological state of the parental cells, as well as prevailing environmental conditions (reviewed in [102]). They represent a huge reservoir of biomolecules and are essential vectors in the aquatic environment. Protein and nucleic acid contents mainly derived from parental cells but also from their viruses and other symbionts [19,[START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]103]. These authors suggested many potential interactions between viruses and EVs, in both evolutionary and physiological contexts. Gill and Forterre [68] proposed the existence of ribovirocells, derived from lipid vesicles, which evolved into virocells at the origin of viruses. EVs can be used as decoys against viral attack but virus-infected cells also produce EVs that enhance viral infection (reviewed in [19]). Improving our knowledge of the biology and ecology of EVs is essential for understanding the origin of viruses [104,105].

Viruses and Gene Transfer Agents

Viruses

The genesis of EVs is an example of biological compartmentalization based on lipid arrangements and boundaries. Biological compartmentalization may also result from protein or protein-lipid arrangements and boundaries which are characteristics of encapsidated and enveloped viruses. The origin of viruses is widely debated. Three main hypotheses have been formulated, namely the progressive (or escape) hypothesis, the regressive (or reduction)

hypothesis and the virus-first hypothesis. Krupovic and Koonin [106] defined these hypotheses as follows. The progressive hypothesis postulates that viruses evolved independently in different domains of life from cellular genes that embraced selfish replication and became infectious. The regression hypothesis submits that viruses are degenerated cells that have succumbed to obligatory intracellular parasitism and in the process, have shed many functional systems that are ubiquitous and essential in cellular life forms, particularly the translation apparatus. Finally, the virus-first hypothesis, also known as the primordial virus world hypothesis, views viruses (or virus-like genetic elements) as intermediaries between prebiotic chemical systems and cellular life and therefore postulates that virus-like entities are derived from the precellular world. These hypotheses are well discussed in [107]. In addition to the possible co-evolution between viruses and EVs [108], it is clear that the complexity of these particles increases from vesicles to viruses, to living cells. In the virus-first hypothesis, Koonin

[109] suggested that capsid is a primitive form that may have paved the way for the formation of the extant complex membranes of modern cells. This author mentioned that viral particles could have served as a "laboratory" to test molecular devices that were then incorporated into the membranes of emerging cells. Gill and Forterre [START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF] proposed that viruses may have existed prior to the appearance of the first cell and that they could be descendants of lipid vesicles through the formation of ribovirocells, prior to the emergence of RNA virions.

Viruses are acellular biological entities (Figure 6) unable to reproduce without their cell hosts.

They have a genome consisting of DNA or RNA that could be double-stranded or singlestranded, linear or circular, segmented or unsegmented.

The genome is encapsulated in a protein coat called a capsid (with exception of Endornaviridae, Hypoviridae, Narnaviridae), which in specific cases can be enveloped by lipid membranes. All types of life forms, from prokaryotes (bacteria and archaea) to eukaryotes (animals and plants), can be infected by one or more viruses [110][111][112][113]. The diversity of viruses is therefore probably at least as great as that of their susceptible hosts [114]. Viruses have been classified according to a combination of different criteria: type (RNA or DNA) and form (single-or double-stranded; circular or linear) of the nucleic acids; the different ways in which they produce mRNA; morphology of viral particle; host type; and presence/absence of an envelope ([115, 116] and references herein). Thus, seven groups, organized into taxonomic levels, have been delineated: genera, 68 subgenera and 6590 species [123]. Note also the existence in femtoplankton of subviral agents which are not classified in the same way as viruses [123,[126][127][128]. These subviral agents are composed of three varieties: satellite viruses, viroids and prions (widely defined and described in [123,126]). They mainly infect plants, fungi, and/or vertebrates.

Satellite viruses are subviral agents morphologically indistinguishable from ordinary viral particles lacking genes capable of encoding functions necessary for replication. Thus, for their multiplication, they depend on the co-infection of a host cell with a helper virus. Viroids are small, circular, single-stranded, non-protein-coding RNAs that replicate autonomously when inoculated into higher plants. Prions are infectious protein particles devoid of nucleic acids. [146] argued that the characteristics of giant viruses, distinct from those of small phages and partially analogous to those of symbiotic bacteria, blur the distinctions between life and non-life. Finally, although there is no consensus on the scenario explaining the origin of viruses and their living or nonliving nature, it is now accepted that they have been involved in the genesis and/or the evolution of cellular life forms.

Gene Transfer Agents (GTAs)

While viruses are implicated in cellular genesis and/or evolution, some of them have been suspected of drifting into gene transfer agents (GTAs), in a process that has been conceptualized

as "prophage domestication" [154][155][156]. Briefly, GTAs arise though deletion and recombination processes that place the structural and DNA-packaging genes of prophage under the control of cellular regulators [157]. GTAs are suspected to be actively maintained by natural selection acting on benefits they confer [157]. GTAs are defined as tailed phage-like particles (with structural similarities to established phage morphotypes such as siphoviruses and podoviruses) that contain a random fragment of the genome of the producer cell genome [158,159]. Their capsid sizes vary from 30 to 80 nm and they contain 4-14 kbp of DNA packaged in a protein capsid shell [160][161][162][163][164][165][166]. The stages of GTA production show similarities with those of lysogenic infection from specific attachment to the release of GTAs into the extracellular environment via lysis of the producer cell [167][168][169]. However, unlike the prophage genes, the genes encoding GTAs are not excised from the genome of the host cell. GTAs are not replicative.

The amount of DNA it contains is insufficient to encode the protein components of the particle itself. Therefore, a GTA particle does not necessarily contain genes encoding GTA and cannot transfer a complete set of GTA structural genes to a recipient cell. This is distinct from a generalized transducer phage, for which usually only an occasional particle contains host genes,

and

CPR / DPANN

The tree of life gives a primordial role to prokaryotes in phylogenetic evolution. The recent discovery of CPR (Candidate Phyla Radiation) and DPANN (acronym of the first five phyla, "Candidatus Diapherotrites", "Candidatus Parvarchaeota", "Candidatus Aenigmarchaeota", Nanoarchaeota and "Candidatus Nanohaloarchaeota") has generated new knowledge concerning the place of prokaryotes in the evolutionary processes of life. These entities have the general characteristics of prokaryotes but present original peculiarities (volume close to the theoretical minimal cell volume, i.e., 0.008 µm 3 , genome and reduced metabolic capacities consistent with a symbiotic lifestyle, and cellular components, e.g., ribosome, of unusual composition) which make them atypical prokaryotes and potentially the smallest known life form [23]. The evolutionary origins of the CPR and DPANN radiations in the two domains of bacteria and archaea, respectively, are still pending because the exact phylogenetic position of some of these entities in the tree of life is uncertain and controversial [23,181,182]. The hypothesis that some of these entities may have appeared during a dramatic but heterogeneous Arrows indicate the target particles when the samples are heterogeneous. Scale bar: 500 nm.

episode of genome reduction, or may have originated from a protogenote community and coevolved with other prokaryotes, has recently emerged [182]. Considering the latter hypothesis and in a cell-centered view of life, CPR and DPANN could represent the smallest and simplest life form known from the last universal common ancestor (LUCA) and/or protogenotes [23,183,184]. These minimalist living entities could thus bridge the gap and establish the continuum between non-cellular but compartmentalized nano-entities (vesicles and viruses) and more complex cellular life forms.

Genome analyses and rare observations indicate that CPR and DPANN have the smallest genomes and cell size in the cellular world ([23] and references herein) (Figure 7). For example, the first member of Nanoarchaeota, N. equitans, is characterized by small cells, only 400 nm in diameter (volume = 0.0335 µm 3 ), and codes for one of the smallest known archaeal genomes (0.49 Mb) [185,186].

Slightly larger genomes (0.64-1.08 Mb) of other ultra-small archaea (Parvarchaeota and Micrarchaeota) with cell volumes as low as 0.009 µm 3 , have since been discovered [187][188][189],

as well as some nanosized Nanohaloarchaea (0.1-0.8 µm) [START_REF] Rilla | Chapter Five -Hyaluronan-Coated Extracellular Vesicles-A Novel Link Between Hyaluronan and Cancer[END_REF][191][192][193]. Reduced genome and cell size are also characteristics of many groups of CPR bacteria. For example, a reduced genome of less than 0.694 Mb has been recorded for the candidate population OD1 [START_REF] Record | Exosomes as new vesicular lipid transporters involved in cell-cell communication and various pathophysiologies[END_REF], with a few ultra-small bacteria of the shortest length (less than 179 nm) and an assumed minimal volume close to 0.004 µm 3 [195]. Most of the CPR is filterable onto 0.2 µm filter ( [23] and references herein). Some CPR and DPANN species are characterized by sparse meta bolisms, with limited catabolic and anabolic capacities, consistent with a symbiotic lifestyle ([23, 181, 182] and references herein). These authors pointed out that CPR and DPANN entities are not monolithic in terms of metabolism but rather harbor a diversity of metabolic capacities, consistent with a range of lifestyles ranging from obligatory symbionts or putative parasites to free-living mode, depending on their degrees of dependence on other organisms (prokaryotes or eukaryotes).

The characteristics of CPR and DPANN call into question the fact that they are cellular life forms. Unlike vesicles and viruses, their ability to code genetic systems for cell division and to transform energy and carbon compounds, coupled with the existence of easily recognizable ribosomes (often of unusual composition), clearly distinguish them as cellular living organisms [23]. They therefore represent a substantial part of the diversity of bacteria and archaea domain. The CPR seems to be a monophyletic radiation with at least 74 phylum-level lineages while DPANN encompasses at least 10 different lineages [23,181]. In addition to terrestrial and animal microbiomes, these organisms were found in many aquatic environments, including acidic, alkaline, and hypersaline habitats, freshwater, and marine ecosystems ( [23] and references herein).

Although these ubiquitous and diverse entities are recognized as the smallest known life form, the lack of an autonomous development in some of them opens a new path at the root of the tree of life to a group of organisms that are unable to reproduce by themselves. Finally, Lannes et al. [196] mentioned that CPR and DPANN superphyla may not be the only prokaryotes found in femtoplankton and they anticipated the discovery of new autotrophic aquatic nano-organisms with the development of single cell genomics.

Something New in the Femtoplankton

Over the past decade, the discovery of BMOPs, EVs and CPR/DPANN (see above) has significantly increased the complexity of the femtoplankton environmental fraction previously considered to be composed primarily of viruses [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF]. This perception, discussed here, has been recently enriched by the discovery of mysterious aster-like nanoparticles (ALNs, Figure 8).

These new femtoplankton particles, whose origin is unknown, do not belong to any previously defined environmental entities (see [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]). Selected-area electron diffraction of ALNs revealed an amorphous structure, mainly composed of carbon, oxygen, calcium and nitrogen. Trace amounts of potassium were also identified in association with the particles.

ALNs are presumably formed of organic components [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. ALNs are original pleomorphic nanoparticles (Figure 8) exhibiting puzzling aster-like shapes with arm-like outgrowths protruding from a central core. Three dominant morphotypes emerged based on the size and number of arms (4-, 11-and 20-armed forms). Some appeared endowed with a singular budlike appendix that seemed to arise from the center of symmetry of the particle. The sagittal sections of the arms reveal a tubular appearance, with an area of electron light surrounded by a wall-like structure. Their average length ranges from 110 to over 439 nm, with volumetric estimates of less than 0.0014 µm 3 . Despite positive nucleic acid labelling, the presence of nucleic acids in ALNs remains to be proven [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. The hypothesis of a support of heredity is supported by the occurrence of the same ALN morphotypes regardless of the environmental context and the recurrent radial symmetry of the particles, which might reflect a developmental relationship between the morphotypes [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

We supplemented these unusual and original descriptive characteristics with development studies of ALNs in vitro and in situ. These include sensitivity to biocidal treatments, changes in ALN abundance in the absence of potential host cells, marked seasonal dynamics and developmental processes of ALNs that confirm their originality and question their origin [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

We have also shown that ALNs are ubiquitous entities capable of maintaining themselves in most continental and coastal aquatic environments (lakes, rivers, marshes, estuarine area) [197].

The positive correlation between prokaryotic abundance and ALN recorded between all environments considered in this study, and the close physical contact between ALNs and prokaryotes displayed in [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF], suggest a potential link between prokaryotes and ALNs. Future work is required to elucidate the origin, composition and ecology of these entities, until now unclassified, and their place in the evolution of life.

Overall, the discovery of ALNs, following that of diverse and ubiquitous BMOPs/nanobes, EVs, and femtoplankton prokaryotes, suggests that femtoplankton could host novel types of other ultra-small particles that could provide new insights into biodiversity and the functioning of the aquatic environment. The main characteristics of the femtoplankton entities and their organizational complexity are summarized and schematized in Table 1 andFigure 9.

This overlooked richness represents an unexpected windfall for understanding the evolutionary processes leading from minerals to the emergence of life on the earth (Figure 10). Indeed, femtoplankton entities can be placed in the context of prebiotic evolution by marking out the potential pathway to the cellular and viral world. In the early evolutionary stages, based on the hypothesis of a prebiotic peptide/RNA world developed in [198], BMOPs/nanobes, as potential supports (inside or fixed outside) of prebiotic organic chemistry, could have paved the way for the formation of primitive elements (organic molecules). The evolution of a procell towards the first protocell could have been achieved after encapsulation and compartmentalization of the primitive elements into fatty acids vesicles prior to evolution by unregulated and error-prone way division, depending on environmental conditions [START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]199]. The complexification of the Early stages of evolution leading to a procell are based on the hypothesis of a prebiotic peptide/RNA world developed in [198]. In these early stages biomimetic mineral-organic particles (BMOPs)/nanobes, as a potential support (inside or fixed outside) of prebiotic organic chemistry, could have paved the way for the formation of organic molecules. The evolution of a procell toward the first protocell can be achieved after encapsulation and compartmentalization of the primitive elements into fatty acid vesicles prior to evolution by unregulated and error-prone way division, depending on environmental conditions [START_REF] Gill | Origin of life: LUCA and extracellular membrane vesicles (EMVs)[END_REF]199]. Complexification of biochemical (metabolic) and replicative systems, as well as membrane/cell walls, during the protocell stages has led to divisions that are more independent of environmental conditions [199] and to the initiation of the cellular and viral world [111]. The emergence of Candidate Phyla Radiation/Diapherotrites Parvarchaeota Aenigmarchaeota Nanoarchaeota Nanohaloarchaeota (CPR/DPANN) from protocell or prokaryotic communities is adapted from [182].

biochemical (metabolic) and replicative systems, as well as of the membrane/cell walls, during the following protocell stages would have led to divisions more independent of environmental conditions and to the initiation of the cellular and viral world [111,199]. CPR/DPANN emerged from late protocell stages or from prokaryotic communities as suggested in [182].

Quantitative and Functional Significances of Femtoplankton

One of the peculiarities of femtoplankton entities is their widespread distribution. The femtoplankton is present in all possible aquatic ecosystems. Viruses, vesicles and gene transfer agents as symbionts of prokaryotes are everywhere; they thrive from hot springs to polar glaciers, from acidic to alkaline environments, from freshwater to hypersaline systems [19,20,25,110,[138][139][140][141][142][143][144][145]176] and associated references). CPR/DPANN have also been listed in a wide variety of environments [23]. BMOPs/nanobes have been found in marine water and in some extreme environments [18,[START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Folk | Nannobacteria and the precipitation of carbonate in unusual environments[END_REF]. ALNs, although data are still sparse, appear to be salinity-tolerant and colonize a wide variety of freshwater ecosystems [197]. Each environment has its own unique diversity of femtoplankton entities. Some types or species are endemic or specific to a given ecosystem under given conditions, others are more tolerant of variations in the environment and are widely distributed. The endemicity and transbiome invasion (e.g., marine-freshwater) of viruses and some femtoplankton prokaryotes are discussed in [200].

Movements or transfers from one ecosystem to another have been demonstrated for ALNs or viruses, for example, which can move along a watershed or through atmospheric systems [198,201,202]. Thus, femtoplankton entities are certainly the most diversified and widespread in the biological world. Capturing their diversity and specific abundance and comparisons between ecosystems is a challenge. By their diversity and composition, femtoplankton entities represent a huge reservoir of mineral and organic molecules. This reservoir makes them an essential player in the circulation, availability and transfer of elements affecting the biogeochemistry of their environment. The catabolic or anabolic metabolisms expressed in some of them or the potential symbiotic lifestyle in others, mean that these femtoplankton entities are not only an essential driving force in the diversification of aquatic organisms, but are also a significant driving force in the flow of matter and energy circulating in aquatic ecosystems. The following section reviews the quantitative and functional importance of the femtoplankton compartment according to their origin and composition as described above.

Quantitative Importance

Many efforts have been made to estimate the diversity of BMOPs/nanobes, EVs, GTAs and CPR/DPANN in the aquatic environment (see above). Nevertheless, estimates of their quantitative importance are still very rare. Although Wu et al. [18] mentioned that seawater contains a relatively high particle-seeding potential, to our knowledge, no data on the abundance of BMOPs or nanobes in the aquatic environment is available. Little more information is available for EVs. In a rare field study, Biller et al. [24] suggested that EV concentrations range from 10 5 to 10 6 vesicles per mL of sea water. To our knowledge, there are no data available about the abundance of GTAs in aquatic ecosystems. Genomic or proteomic studies of CPR and DPANN are increasingly documented, leading to a better consideration of their wide diversity [203][204][205]. However, to our knowledge there are no reports of their density in water neither as episymbionts (attached to a cell) nor as free-living elements. In a specific study, we reported significant amounts of ALNs in contrasted aquatic ecosystems [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. These ubiquitous entities fluctuate spatially and temporally, with values ranging from undetectable to 9.0 ± 0.5 × 10 7 particles•mL -1 [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. As for other femtoplankton entities, the assessment of their quantitative importance requires a strong consideration in future work. Conversely, the quantitative importance of viruses has been widely documented and reviewed [110,139,140,[206][207][208]. More than 10 30 viruses can exist in aquatic environments at any given time [139].

Their abundances vary spatially and temporally up to estimates exceeding 10 Soler et al. [212] suggested that EVs could outnumber true viral particles in some aquatic environments and Colombet et al. [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] reported that ALNs can account for up to 40% of virioplankton counted by transmission electron microscopy.

There is an evident lack of data on the relative quantification of the recently discovered and overlooked femtoplankton components, both temporally and spatially. A combination of electronic microscopy and nucleic acid-based methods is needed to reveal the relative contribution of each of the femtoplankton categories [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. In the future, such a consideration appears to be fundamental in deciphering the global importance of femtoplankton in the functioning of aquatic ecosystems and the related biogeochemical cycles.

Potential Ecological Importance

Estimating the overall functional importance of femtoplankton is a challenge for the future.

This requires considering not only the diversity and quantity but also the biological/physiological state (composition, lifestyle, activity, etc.) of each of its representatives and the environmental contexts. A first approach is to speculate on the specific potential significance of each of the femtoplankton entities.

BMOPs/Nanobes

These entities are overlooked in aquatic systems and very little data are available on their putative ecological importance. Like all femtoplankton entities, BMOP/nanobe biomass may play a crucial role in the circulation, availability and transfer of matter in the environment [18].

The assumed ecological significance of these entities could be inferred from biomedical sciences. Yaghobee et al. [START_REF] Yaghobee | What are the nanobacteria?[END_REF] reported several roles for some of these entities in calcificationrelated human diseases. Breitschwerdt et al. [213] and Barr et al. [49] reported their occurrence in terrestrial mammals. It is therefore very likely that the BMOPs/nanobes can play an important role in the health of marine animals, which by inference suggests an ecological role in the environment. Çiftçioglu and Kajander [214] reported interactions (endocytosis) with cultured mammalian cells involving potential cytotoxicity. Such interactions with microbes in the environment could have a great implication for the receptor cell biology, although these are hypothetical and remain to be fully explored.

Extracellular Vesicles

A little more information about the ecological significance of vesicles in aquatic systems is available. Gill et al. [19] reported that EVs, as carriers of various molecular cargoes from cell to cell, can modify cellular physiology (stress response, intercellular competition, pathogenicity and detoxification) and can play important roles in all types of intercellular interactions. They can be involved in the quorum sensing, acclimatization to nutrient limitation, morphological plasticity and trapping of toxins and antibiotics [25]. Additionally, EVs as carriers of genetic information between cells have been proposed as a novel vehicle for horizontal gene transfers (HGT), in addition to the well-known related mechanisms of transformation, transduction and conjugation [START_REF] Erdmann | A plasmid from an Antarctic haloarchaeon uses specialized membrane vesicles to disseminate and infect plasmid-free cells[END_REF]215]. As a result, they can significantly modify the gene pool and associated metabolic capacities of their receptors. Interactions between EVs and viruses have also been documented [19,216]. EVs have the potential to regulate host-virus dynamics [216]. Some

EVs can propagate the viral genome or plasmids [108]. EVs can sometimes act as decoys to limit viral infection, while viruses can manipulate the production of EVs from infected cells to their own advantage [217,218]. As consequence, several ecological roles can be inferred for EVs, including their influence on ecology and community structure, the trophic-level interactions and their impact on the carbon cycle [21,24,25,. Nevertheless, as with

BMOPs/nanobes, these potential roles are largely derived from biomedical sciences and remain to be extensively explored in natural environments.

Viruses and Gene Transfer Agents

Microbial ecologists have devoted more effort into understanding the functional importance of viruses in aquatic environments [START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF][START_REF] Weitz | Quantitative Viral Ecology: Dynamics of Viruses and Their Microbial Hosts[END_REF]110,112,121,139,140,197,210,[219][220][221][222][223]. These studies reported that viruses are major components of the aquatic food web, not only as parasites that can lead to cell death, but also as a powerful weapon able to manipulate the life histories, evolution and ecology of their hosts.

Suttle [139] reported that every second, approximately 10 23 viral infections occur in the ocean.

These infections are a major source of mortality, and cause disease in a wide range of organisms, from shrimp to whales. Through them, viruses contribute to both top-down and bottom-up control of the microbial community [START_REF] Weitz | Quantitative Viral Ecology: Dynamics of Viruses and Their Microbial Hosts[END_REF]. Viruses directly influence the abundance of aquatic communities. Lytic viruses may account for up to 50% of bacterial mortality in the pelagic ecosystems and can abruptly terminate eukaryote algae blooms [218,[224][225][226][227]. Bossart and Duignan [112] noted that viral infections also have major effects on the health of marine mammals, including neoplasia, epizootics and zoonoses. As a major source of mortality, lytic viral infections considerably affect biogeochemical cycles. The fate of matter produced by lysis can follow a different pathway, from direct remineralization/regeneration by the microbial loop, which can support a higher microbial biomass, to export by aggregation and sedimentation [110,219,228,229]. Viral infection can alter cell stoichiometry and uptake rates [220,230]. Zimmerman et al. [223] discussed how metabolic reprogramming of host cells during lytic viral infection alters the nutrient cycle and ocean exports of carbon. They reported that viral infection transforms host metabolism through metabolic genes encoded by the virus, whose functions appear to alleviate energy and biosynthetic limitation in viral production. They emphasized the importance of the physiological state of the host cell and environmental conditions in the regulation of these processes.

Viruses are also important drivers of microbial diversity [110,231,232]. Two concepts can explain this power: the "antagonistic coevolution" (arms race) and "killing the winner". In the concept of "antagonistic coevolution", hosts and viruses coevolve in order to escape lethal infections for the hosts, a situation that can make surrounding hosts resistant to viruses [233].

In the "killing the winner" model, viral predation of temporarily abundant and specific hosts can weaken the between-host competition for resources and promote the coexistence of host diversity by allowing the growth of non-abundant or rare host species [231,[234][235][236]. Viruses affect also the diversification and physiology of aquatic hosts through horizontal transfers of genetic materials [237,238]. One example is the transfer of photosynthesis genes between viruses and their hosts Prochlorococcus

CPR/DPANN and Other Femtoplankton Prokaryotes

The main ecological implications of the femtoplankton entities described above are related to their composition (BMOPs/nanobes, vesicles, viruses), their ability to transport and transfer various molecules and genetic material (EVs, viruses, GTAs) and/or their "parasitic" lifestyles (viruses) which can modulate the physiology and ecology of receptor cells (prokaryotes or eukaryotes). Until now, CPR/DPANN and other ultra-small prokaryotes are the only femtoplankton entities capable of metabolic activity. Although description of their potential metabolic activities is still in its infancy, this could profoundly impact biogeochemical cycles in the aquatic environment.

Castelle et al. [23,243] and Anantharaman et al. [244] have demonstrated that members of CPR and DPANN superphyla have genetic supports able of encoding molecules involved in numerous autotrophic or heterotrophic reactions. For example, some CPR and DPANN have Rubisco type II/III genes, while others have gene-encoding enzymes involved in the carbon, nitrogen, sulfur and hydrogen cycles [244,245]. Nevertheless, most CPR/DPANN lack parts of the central metabolic pathways, including nucleotides, amino acids and lipid biosynthesis and require a host to complete their life cycle [23,169,209,246]. Achievement of the metabolic potential of episymbiotic CPR/DPANN is therefore dependent on the presence and availability of their hosts. The corollary of these interactions is the potential impact on the activities and metabolic capacities of the organisms on which they depend [23]. On a larger scale, Anantharam et al.

[244] revealed evidence of extensive interconnection between the metabolisms of coexisting community members. These interrelationships are likely necessary to complete many biogeochemical pathways. This does not exclude the notion that some CPR/DPANN seem to have the genetic potential to be free-living, with aerobic and/or fermentative heterotrophic behavior [23,246]. These discoveries are complemented by Lannes et al. [196] who have demonstrated that ultra-small marine prokaryotes, not necessarily CPR or DPANN, collectively harbor the genes required for the complex metabolism in carbon fixation, which could significantly increase their potential involvement in biogeochemical cycles. Lannes et al. [196] then anticipated that the discovery of new autotrophic marine nanoorganisms with novel metabolic capacities is not impossible.

The potential ecological importance of CPR/DPANN, or other ultra-small prokaryotes is currently known through metagenomic and proteomic analyses or co-cultures of rare species.

Therefore, their ability to express their genetic potential and to manipulate the metabolic potential of their hosts (symbiont, presumed new parasites) remains to be explored under contrasted environmental conditions, in order to estimate the overlooked ecological significance of these ultra-small prokaryotes.

ALNs

The ecological role of the ALNs is currently unknown but could be potentially important. The total biomass of ALNs during bloom periods is likely to mobilize circulating mineral and organic nutrients to the detriment (competition?) of other microbial communities in aquatic ecosystems. For example, ALNs could be of great significance in the homeostasis of Ca in aquatic systems due to their high calcium composition. In addition, direct interplay with bacteria could significantly influence energy and matter flows mediated by prokaryote compartment [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. The composition and activity of ALNs and interactions with the prokaryotic compartment remain to be confirmed and clarified to better understand the potential ecological role of ALNs. Clearly, these entities are new actors in the matter and energy flows circulating in aquatic systems which will have to be considered in future work.

Overall, recent evidence of numerous, diverse and ubiquitous, metabolically active (femtoplankton prokaryotes) or not (BMOPs/nanobes, EV), femtoentities as well as mysterious ALNs, implies a deep reconsideration of the diversity and ecological significance of femtoplankton. Historically considered through viral activity alone, this ecological significance may be greater than previously considered. Figure 11 reviewed the ecological potentials of femtoplankton representatives in the environment.

The overlooked diversity and the associated biomass of all these entities necessarily have a deep impact on the circulation of conservative elements and the related biogeochemical cycling.

Through the spectrum of their activities and potential hosts, femtoplankton entities have the ability to interact with all components of plankton. Femtoplankton maintains a privileged relationship with pico-and nanoplankton by not only being a parasite (e.g., viral lysis [139]), but also a food source (e.g., protozoan grazing [247]), a development factor (e.g., symbiosis

with CPR/DPANN [23,244]) or evolution promotors (e.g., HGT via virus [237,238], EVs [START_REF] Erdmann | A plasmid from an Antarctic haloarchaeon uses specialized membrane vesicles to disseminate and infect plasmid-free cells[END_REF]215], GTAs [242]). Femtoplankton models both the phenotype and genotype of their interacting hosts and thus could significantly impact the biodiversity and ecological functions of all the components of plankton.

The autonomous realization of metabolic pathways by free-living femtoplankton entities (i.e., femtoplankton prokaryotes) could also significantly expand the ecological importance of femtoplankton in geochemical cycles.

Finally, taken together, femtoplankton entities represent a powerful engineering weapon able to deeply affect biodiversity and matter and energy flows circulating in aquatic environments.

Nevertheless, most of the potential effects of femtoplankton remain to be explored. Their estimation needs to consider not only the diversity and biology of their representatives, but also their ability to interact with other biological elements and to express their activities in environmental contexts.

Conclusions

This review highlights that the femtoplankton compartment hosts a huge diversity of unidentified and overlooked entities at the frontiers of our knowledge. From an evolutionary point of view, this source of new diversity could be essential to a better understanding of the processes leading from the mineral-organic phase to a cell-like living entity. Femtoplankton could present all the stages presumably involved in the life initiation. Moreover, it could be crucial in many ecological processes. It represents a powerful engineering weapon capable of profoundly affecting biodiversity and matter and energy flows circulating in aquatic environments. Finally, this review highlights the need to deepen our knowledge of this still largely unknown compartment.

Découverte de nouvelles entités femtoplanctoniques : les Aster-Like Nanoparticles

Abstract

This study reports the discovery of Aster-Like Nanoparticles (ALNs) in pelagic environments.

ALNs are pleomorphic, with three dominant morphotypes which do not fit into any previously defined environmental entities [i.e., ultramicro-prokaryotes, controversed nanobes, and nonliving particles (biomimetic mineralo-organic particles, natural nanoparticles or viruses)] of similar size. Elemental composition and selected-area electron diffraction patterns suggested that the organic nature of ALNs may prevail over the possibility of crystal structures. Likewise, recorded changes in ALN numbers in the absence of cells are at odds with an affiliation to until now described viral particles. ALN abundances showed marked seasonal dynamics in the lakewater, with maximal values (up to 9.0 ± 0.5 × 107 particles•mL-1) reaching eight times those obtained for prokaryotes, and representing up to about 40% of the abundances of viruslike particles. We conclude that (i) aquatic ecosystems are reservoirs of novel, abundant, and dynamic aster-like nanoparticles, (ii) not all virus-like particles observed in aquatic systems are necessarily viruses, and (iii) there may be several types of other ultra-small particles in natural waters that are currently unknown but potentially ecologically important.

Introduction

Recent advances in environmental and nanoparticle sciences have helped to reveal an unexpected diversity of living and non-living femto-entities (0.02-0.2 μm as defined for femtoplankton by [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF]) in the environment. Previously considered to be mainly composed of viruses [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF], the successive discovery in significant abundance, and in various environments, of mysterious nanobes [START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Mckay | Search for past life on Mars: possible relic biogenic activity in martian meteorite ALH84001[END_REF]59], extracellular vesicles (EVs) [START_REF] Biller | Membrane vesicles in sea water: heterogeneous DNA content and implications for viral abundance estimates[END_REF]212], ultramicroprokaryotes [23,[START_REF] Duda | Ultramicrobacteria: Formation of the concept and contribution of ultramicrobacteria to biology[END_REF][START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF]203,204,248,249] and biomimetic mineralo-organic particles (BMOPs) [18], has significantly increased the complexity within the environmental fraction of femto-entities.

Contrary to viruses or EVs, controversed nanobes, some of which could be affiliable to BMOPs, and ultramicro-prokaryotes, including recently discovered CPR (Candidate Phyla Radiation)

and DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaea), have the ability to develop outside a host [18,[START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF]54,[START_REF] Martel | Purported nanobacteria in human blood as calcium carbonate nanoparticles[END_REF]250]. Nanobes exhibit diverse morphotypes: coccoid, amiboid, ovoid or filamentous shapes [START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Mckay | Search for past life on Mars: possible relic biogenic activity in martian meteorite ALH84001[END_REF]59].

Among them, only ultramicro-prokaryotes are clearly affiliated to living organisms according to the volumetric criteria advanced by the National Research Council (1999) [251], i.e., the theoretical minimal cell volume (TMCV) sufficient to house nucleic acids and the associated biosynthetic machinery is at 0.008 μm3. Though these new entities were described in natural environments, relatively little is known about their ecological significance. Available data however suggests a significant impact on the biogeochemical cycles. EVs are potentially involved in cell communication, competition and survival of bacteria [252]. Interactions between ultramicro-prokaryotes and other micro-organisms communities may shape natural microbiome function [23]. Likewise, BMOPs incorporate trace elements and proteins suggesting that these entities may play a role in the circulation and availability of minerals and organic molecules in the environment [18]. Characterizing the femtoplankton biomass and the diversity of its representatives seems crucial to our understanding of the functioning of aquatic ecosystems.

In this study, we report the discovery of abundant and seasonally-fluctuating populations of "Aster-Like Nanoparticles" (ALNs) in a freshwater lake of Massif Central (France), with volumes lower than TMCV. ALNs display typical and unique morphological features. Physicalchemical aspects, pleomorphism, flow cytometry and growth analyses of ALNs are presented and compared to distinctive features of living or not-living particles of similar size. Preliminary attempts to evidence DNA-based heredity support are reported.

Materials and Methods

Study sites and Sample Collection

Samples were collected at the surface of an artificial and highly eutrophic freshwater lake (surface area 1.2 ha, maximum depth 2.5 m) near Neuville in the French Massif Central (45°44'24"N; 3°27'39"E; 465 m altitude). Part of the samples were immediately fixed with 1%

(v/v) formaldehyde and stored at 4°C until analysis (see below). Unfixed samples were transported at 4°C to the laboratory and treated within two h (see below). In situ dynamics of ALNs were monitored in 11 fixed samples collected between November 2016 and January 2018. Table 2 lists the physical-chemical characteristics of the water analyzed once, in February 2017.

Detection of ALNs was also conducted on surface microlayer samples of 16 selected geographical stations (namely HL1 to HL16) from the Ha Long Bay (Vietnam). Details on these samples and their environment were provided in a previous work [253]. ALNs were quantified on electronic microscopy grids prepared as mentioned below.

ALN, Prokaryote, and Virus-Like Particle (VLP) Counts and Imaging

ALNs in fixed samples were collected by centrifugation at 15,000 g for 20 min at 14°C directly onto 400-mesh electron microscopy copper grids covered with carbon-coated Formvar film (Pelanne Instruments, Toulouse, France). Particles were over-contrasted using uranyl salts as described elsewhere [254]. ALNs were counted by transmission electron microscopy (TEM) using a Jeol 1200EX microscope (JEOL, Akishima, Tokyo, Japan) at 80 kV and x50,000 magnification. Grids were scanned before counting to check that ALNs were randomly

Experimental Design

Enrichment and Culture of ALNs

The sample with the highest density of ALNs collected on March 15th 2017 was used for enrichment and culture of ALNs. Within two h after sampling, 20 L of raw lake water was filtered through a 25-μm-pore-size nylon mesh and filtrates were immediately concentrated by tangential-flow ultrafiltration using a Kross-Flow system (Spectrum, Breda, The Netherlands) equipped with a 0.2-μm cut-off cartridge. Aliquots of this concentrated 0.2 μm-25 μm fraction

were sequentially centrifuged at 8,000 g, 10,000 g (pellets discarded) then 12,000 g for 20 min each time at 14°C. ALNs contained in the supernatant of this last run were cultivated at 4°C in the dark with a regular supply of culture medium. To obtain this culture medium, ultra-filtrate <0.2 μm of the initial lake sample was filtered through a 30 KDa cut-off cartridge and autoclaved. Figure 12 shows ALN cultures obtained through this procedure compared to the raw samples. The pellet obtained at 12,000 g was suspended in distilled/deionized sterile water (DDW), centrifuged at 10,000 g, and the supernatant was directly frozen to-20°C for microscopic and flow cytometry analyses of Enriched-ALNs (E-ALNs). Detailed procedure of experimental design and analyses is provided in supplementary materials (Figure S1).

Growth Monitoring

As state above, ALN cultures were enriched by sequential centrifugations at 8,000 g, 10,000 g (pellets discarded) then 12,000 g for 20 min each time at 14°C. For growth monitoring, this was followed by successive filtrations of the highest-speed supernatant through 0.45-μm and 0.2-μm filters (Sartorius, Göttingen, Germany) to obtain ALN-enriched but prokaryote-free medium. This filtrate (<0.2-μm) was diluted 10-folds in the culture medium (see above) and incubated in triplicate over a 36-day period at 4°C in the dark, then 12 uneven subsamples were taken and formaldehyde-fixed before counts. Absence of prokaryotes at the start and end of the growth monitoring period was checked by flow cytometry, transmission electron microscopy and plate count agar spreading incubated at 4°C and 20°C during 4 weeks.

Susceptibility to Chemical or Physical Agents

To address the question of the living nature of the ALNs we examined their susceptibility to various chemical (lysozyme, antibiotics) or physical (heat) agents. Lysozyme is an antimicrobial enzyme that destructs Gram + bacteria cell wall by peptidoglycan hydrolysis

[257] and which can also act against viruses [258,259]. Antibiotics treatments used in this study are all known to block replication processes of bacteria DNA or protein synthesis [260,261].

Novobiocin is principally active against Gram+ bacteria, gentamycin against Gram-bacteria and norfloxacin has a broad-spectrum bactericidal action. Heat shock above 85°C was used owing to the irreversible physiological damage caused by this treatment to biological entities

[262].
Prokaryote-free ALN fractions prepared as described under the 'growth monitoring' section were separately treated with 2 mg/mL lysosyme (1 h at room temperature), submitted to heatshock (1 h at 90°C) or supplemented with antibiotics (50 μg/mL norfloxacin in sterile DDW;

10 μg/mL gentamycin in sterile DDW or 250 μg/mL novobiocin in sterile DDW) (all chemicals from Sigma-Aldrich, Saint-Quentin-Fallavier, France). Treated samples were incubated for 20 days in the dark at 4°C. To test the efficiencies of these biocide treatments, we used two treated "control fractions": ALN-free bacteria cultures isolated from lake Neuville and grown on the same culture medium as ALNs, and 0.2 μm filtered ALN-free but ultrafiltration-enriched VLP water lake. This second control fraction was obtained from Lake Pavin where ALNs are undetectable over the year. Biocide effects of treatments were determined by direct comparison of treated vs. untreated samples at day 20. ALN, prokaryote and femtoplanktonic communities were performed on formaldehyde-fixed samples at the end of the incubations as previously described. All tests were carried out in triplicates.

Cryo-Transmission Electron Microscopy (Cryo-TEM) Specimen Preparation and Imaging

For cryo-TEM, 3 μL of unfixed suspensions containing ALNs were deposited onto glowdischarged Lacey Carbon 200-mesh grids and loaded into the thermostatic chamber of a Leica EM-GP automatic plunge freezer, set at 20°C, and 95% humidity. Excess solution was blotted for 1" with a Whatman filter paper No. 1, and the grid was immediately flash-frozen in liquid ethane cooled at-185°C. Specimens were then transferred onto a Gatan 626 cryo-holder, and cryo-TEM was carried out on a Jeol 2100 microscope, equipped with a LaB6 cathode and operating at 200 kV, under low-dose conditions. Images were acquired using SerialEM software

[263], with defocus ranging of 1,000 nm, on a Gatan US4000 CCD camera. This device was placed at the end of a GIF Quantum energy filter (Gatan Inc., Pleasanton, CA), operated in zeroenergy-loss mode, with a slit width of 25 eV. Images were recorded at a magnification corresponding to the calibrated pixel size of 1.80Å or 0.89Å.

Scanning Electron Microscopy (SEM) Specimen Preparation and Imaging

Genomic Analyses

Nucleic Acids Extraction and Amplification

Genomic DNA was extracted from unfixed suspensions containing ALNs obtained as described in the section "Growth monitoring". The sample was harvested by centrifugation at 12,000 g for 20 min at 14°C. The pellet was resuspended in 500 μl of sterile DDW and mixed with 600 mL of saturated phenol (pH 8.0). Then, two cycles of freezing in a liquid nitrogen bath (15 min) and thawing in a 100°C water bath (5 min) were conducted. The sample was mixed with 750 μL of chloroform and centrifuged at 14,000 g for 20 min at 4°C. Thereafter, the aqueous layer was transferred to another fresh 1.5 mL microtube and mixed with same volume of cold absolute ethanol and 3 M sodium acetate. The nucleic acid pellet obtained by centrifugation at 14,000 g for 20 min at 4°C was washed twice with ice-cold 70% ethanol and pelleted again.

The pellet was resuspended in 50 μL of deionized water. Total extracted DNA was randomly amplified by Whole Genome Amplification (WGA) with GenomiPhi V2 kit (GE Healthcare, Chicago, Illinois, USA).

Library Preparation and Sequencing

Single-molecule Real-time long reads sequencing was performed with a PacBio Sequel Sequencer (Pacific Biosciences, Menlo Park, CA, USA). The SMRTBell library was prepared using a DNA Template Prep Kit 1.0, following the "procedure and checklist for greater than 10 kb template using AMPure PB beads" protocol. Genomic DNA(1,7 ug) was slightly sheared using a Covaris g-Tube (Covaris, UK) generating DNA fragments of approximately 20 kb. A

Fragment Analyzer (Agilent Technologies, Santa Clara, CA, USA) assay was used to assess the fragment size distribution. Sheared genomic DNA was carried into the first enzymatic reaction to remove single-stranded overhangs followed by treatment with repair enzymes to repair any damages that may be present on the DNA backbone. A blunt-end ligation reaction followed by exonuclease treatment was conducted to generate the SMRT Bell template. Two

AMPure PB beads 0.45X purifications, and one at 0.4X were used to obtain the final library.

The SMRTBell library was quality inspected and quantified on a Fragment Analyzer (Agilent

Sequence Assembly and Annotation

The 1,930,845 raw PacBio reads (4.1 Kb in average) were assembled using the SMRT Analysis software and the Hierarchical Genome Assembly Process (HGAP) workflow [264]. This procedure includes pre-assembly error correction, assembly and polishing. The circular nature of HGAP derived contigs was assessed via the dot-plotting tool Gepard [265] and circular genome sequences were derived through an alignment approach and manual curation. The 5,162 corrected long reads (12.6 Kb in average) produced after the pre-assembly error correction process were utilized to determine the coverage of each contig using BLASTn (threshold of 90% on the identity percent) [266]. These corrected reads and contigs were

Results

Morphological Analyses

The ALN shape corresponds to arm-like segments which extend radially from a unique core structure. Three dominant morphotypes emerged on the basis of size and number of arms. The first morphotype displayed 4 to 10 arms connected to a delta-shaped tail with a mean length of 110 ± 18 nm and an average volume of 0.000055 μm3 (Figures 13A-F).

The second morphotype consisted of forms with 11-arms that were consistently observed within the ALN population (Figures 13G-K). They were clearly distinct from the first morphotype by their length (333 ± 28 nm) and volume (mean value: 0.00057 μm3). Some appeared endowed with a singular bud-like appendix that seemed to arise from the center of symmetry of the particle. This appendix is thicker and slightly longer than the radial arms (Figures 13I-K).

Finally, the third ALN morphotype corresponds to a sub-population that was composed of 20 arms (Figures 13L-P). These 20-armed forms constituted the lengthiest (439 ± 39 nm) and the most voluminous (0.0014 μm3) ALNs identified in our samples. Their arms displayed characteristic tapered shapes, were frequently associated by pairs (Figure 13P), and there was no indication for supernumerary outgrowths as seen in other ALN morphotypes.

Standard, scanning, and cryo-transmission electron microscopy (cryo-TEM) indicated that the arms of ALN particles project from a central core (Figures 14A-D). This core displayed high and homogeneous electron density, while the arms showed differential contrasts depending on the plane of the section. Arms appeared as hollow structures when viewed in sagittal sections (Figure 14C). Cryo-TEM of whole specimens allowed direct comparison between the central core, the radial arms and the supernumerary appendix of the 11-armed morphotypes (Figure

Elementary Analysis

Energy-filtered transmission electron microscopy and electron energy loss spectroscopy (EELS) analyses performed on entire ALNs indicated that these nanoparticles were mostly composed of carbon, oxygen, calcium and nitrogen (Figures 15 A,B). Trace amounts of potassium were also identified in association with the particles. EELS spectra at the C K-edge and Ca L2,3-edges of ALNs were significantly different from those of Ca-carbonates used as reference (Figure 15C) as they did not show a peak at 290 eV indicative of 1s → π* electronic transitions in carbonates and a much lower Ca/C ratio. Likewise, selected-area electron diffraction of ALNs revealed an amorphous structure (K.B. personal communication).

Elemental composition and selected-area electron diffraction patterns thus suggest that ALNs are presumably formed of organic components, indicating that their organic nature may prevail over the possibility of mineral structures.

Flow Cytometry Analysis

Flow cytometry (FC) analyses were performed on enriched-ALNs fraction (E-ALNs, see Materials and methods) composed of 96% ALNs and 4% of VLPs (Figure 12B) ascertained by TEM observation and counting.

No fluorescence signal was obtained using lipophilic markers FM4-64 or PKH26. Different nucleic acid dyes were tested, including DAPI, PI, SYBR Green I, SYBR Gold. While labeling with DAPI (a weakly permeant AT selective dye) and PI (impermeant nucleic acid intercalating dye) were unsuccessful, the SYBR dyes (permeant cyanine dyes), which are more sensitive compounds with high penetrating capacities, allowed to separate distinctive populations from E-ALN samples. As shown in Figure 16A, three populations termed P1, P2, and P3 were reproducibly split on the basis of SYBR Green I signal intensity and side scatter. Because ALNs were shown to be thermo-sensitive, heating was omitted in the protocol used for SYBR labeling. TEM indicated ALNs with familiar shapes in all sorted gates excepted in P4 gate that exclusively contained beads used as a control for sorting quality control (Figure 16B). Absence of ALNs in P4 indicated a non-random but differential sorting of the nanoparticles using the selected sorting gates. This was confirmed by TEM analyses of ALNs from the three sorting gates (Figure 16B). The sub-population from P3 gate provided the strongest SYBR signal, and consisted of large ALN morphotypes, i.e., 20-armed, budding 11-armed, and 11-armed morphotypes.

The smaller ALNs (4-10 armed forms) were mostly concentrated in gates P1 and P2 together with virus-like particles and similar-sized particles of undetermined nature (VLPs).

Interference between ALNs and VLPs in FC particle quantification was evaluated using thermo-sensitivity property of ALNs compared to VLPs. This was achieved through comparative analysis of E-ALNs and a VLP community used as an ALN-free control, submitted

or not to heating (Figure 16C). Heat induced a significant increase of counted VLPs in P2 (from 4.8 ± 0.7 to 8.2 ± 1.1 × 106 mL-1) and P3 (from 1.7 ± 0.2 to 2.0 ± 0.3 × 106 mL-1)

populations sorted from the ALN-free control. Heating of P2 and P3 sorted from E-ALNs resulted in the opposite effect, i.e., a decrease in number of recorded events (P2: from 5.8 ± 0.6 to 4.2 ± 0.4 × 106 mL-1; P3: from 1.8 ± 0.2 to 0.9 ± 0.1 × 106 mL-1).

Overall, ALNs are positively labeled with SYBR nucleic acid dyes and interfere with VLPs quantification when using fluorescence based methods.

Nucleic Acid Detection

Detection of nucleic acid was performed on fraction composed of >99% ALNs and <1% of VLPs ascertained by TEM and obtained as described in section 'growth monitoring'.

No reads or contigs were similar to a prokaryotic 16S rRNA sequence. All the 233 contigs were shorter than 6 Kb except one contig of 11,258 bp. Almost all contigs could be unambigously affiliated to small single-stranded DNA viruses, 213 being affiliated to the Microviridae family and 16 to CRESS DNA viruses (circular Rep-encoding ssDNA viruses) (Figure 17). Each piece of the pie corresponds to a contig and its size is proportional to the number of reads that were associated to this contig. Two contigs had no similarity to Uniprot proteins and one contig was similar to a bacterial DNA-directed DNA polymerase (49.5 amino acid identity on 94 residues), but these contigs were all very short (1,300, 115, and 290 bp, respectively). Although the largest contig of 11,258 bp had no obvious affiliation, its characteristics are similar to known viruses that infect prokaryotes: (i) short genes (23 protein Lysozyme treatment leaded to a rise of prokaryotes (58%) suggesting that this ALN-free fraction was mostly composed of Gramspecies. The complete loss of ALN-free femtoplanktonic communities (99%) showed the strong antiviral activity of this enzyme [258,259]. As expected prokaryotic "control fraction" displayed drastic loss in response to heat, norfloxacin, gentamicin and novobiocin (100%, 100%, 57%, 41%, respectively) (Figure 18).

Clearly, ALNs are susceptible to the life-inhibiting treatments. It seems also worth noting that responses to the treatments differed depending on the morphotypes. For example, 11-armed morphotypes proved much more resilient than others, while the 4-10-armed appeared more sensitive to the treatments.

In vitro Monitoring

ALN population fluctuates over a 36-day period in prokaryote-free medium (PFM) at 4°C (Figure 19). A transient rise of abundance was evident from day 0 to day 1 (multiplication factor MF = 3.6). The population then appeared relatively stable from day 1 to day 15 before a marked decrease up to day 20, preceding a second rise period from day 20 to day 29 (MF = 3.3), then a second decline phase up to day 36. All these fluctuations with time were statistically significant (Figure 19). Quantification of ALN morphotypes in PFM revealed that 4-10-armed

Ecosystemic Monitoring

Analysis of natural samples collected over a 13-month period in an eutrophic lake of the French Massif Central revealed high ALN abundances characterized by marked seasonal fluctuations (Figure 20).

The maximal density reached a value of 9.0 ± 0.5 × 10 7 mL -1 (March 15th 2017). ALN abundances were up to 8-fold higher than those obtained for FC-counted prokaryotes and represented up to 39% of the total FC-counted VLPs in corresponding samples. ALN abundances increased with season from autumn to spring (MF = 60). Prokaryote abundances fluctuated slowly from 0.8 ± 0.1 to 2.1 ± 0.4 × 10 7 mL -1 , while VLPs ranged from 2.0 ± 0.2 to 48.4 ± 1.5 × 10 7 particles mL -1 . For both communities, highest values were recorded in spring and in autumn, respectively (Figure S2). ALN abundance was not correlated to those of prokaryotes or VLPs.

At the morphotype level, we observed a high dominance of 11-armed forms which averaged 79 ± 16% of the total abundance over the 13-month sampling period (Figure 20). The 4-10 and 20-armed forms appeared in much smaller proportions (mean values = 10 ± 11% and 11 ± 11%, respectively). Proportions of these two forms were inversely correlated with those of 11-armed forms over time (Spearman's r = -0.77 and r = -0.73, respectively, p < 0.05). Proportions of budding 11-armed forms and 11-armed forms devoid of bud-like appendix were also negatively correlated to each other (Spearman's r = -0.91, p < 0.01). Budding forms accounted for the highest proportions at the onset and throughout the increasing phase of total ALNs, but then disappeared with the decline in the total ALN abundance. ALNs were exclusively composed of 11-armed morphotypes a few months after their population was stabilized at its lowest level.

Detection of ALNs conducted on surface microlayer of 16 selected geographical stations (namely HL1 to HL16) from Ha Long Bay (Vietnam) show a high spatial heterogeneity with values ranging from undetectable to 3.4 × 10 4 mL -1 (Figure 21A). The dynamics of ALNs and bacteria were significantly correlated (Spearman's r = 0.81, p< 0.01, Figure 21B). No reliable correlation could be established between ALNs and physico-chemical variables (Figure 21B).

ALNs show seasonal and ecosystemic fluctuations probably induced by environmental parameters. Proportions of each recorded morphotype shift according to seasonal dynamics.

Discussion

ALNs Are Original Pleomorphic Nanoparticles

Here we report the discovery of 'Aster-Like Nanoparticles' (ALNs) in lakewater. These pleomorphic entities, exhibit puzzling aster-like shapes with arm-like processes that project from a central core (Figure 14). All morphotypes exhibit shapes that distinguish ALNs from previously established groups of nanoparticles, including ultramicro-prokaryotes [23,[START_REF] Duda | Ultramicrobacteria: Formation of the concept and contribution of ultramicrobacteria to biology[END_REF][START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF],

controversed nanobes [START_REF] Folk | SEM imaging of bacteria and nannobacteria in carbonate sediments and rocks[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF][START_REF] Yaghobee | What are the nanobacteria?[END_REF]59,270], biomimetic mineralo-organic particles (BMOPs) [18], viruses [271] or extracellular vesicles (EVs) [START_REF] Biller | Membrane vesicles in sea water: heterogeneous DNA content and implications for viral abundance estimates[END_REF]212]. Their mean length ranges from 110 ± 18 nm (4-10-armed morphotype) to 439 ± 39 nm (20-armed morphotype). Volumetric estimates of all ALN types indicated values (averaging 0.000055 μm3, 0.00057 μm3, and 0.0014 μm3 for 4-10, 11, and 20-armed morphotypes respectively) that were significantly lower compared to the smallest known prokaryotes [START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF] and to the Theoretical Minimal Cell Volume (TMCV). Nanobes, BMOPs, viruses (excepted giant viruses) and EVs are the sole examples of entities comparable to ALNs in terms of numerical volume. The composition (mostly carbon, oxygen, calcium and nitrogen with trace amounts of potassium) and the amorphous structure revealed by electronic microscopy (Figure 15) point out that ALN are possible organic particles [START_REF] Benzerara | Nanobacteria-like calcite single crystals at the surface of the Tataouine meteorite[END_REF][START_REF] Uwins | Novel nano-organisms from Australian sandstones[END_REF], or at least that their organic content may prevailed over their mineral composition known from mineral forming nanobes [272], BMOPs or "natural nanoparticles" [18,273], partly or totally composed of minerals.

ALN volumes were largely under the theoretical minimal cell volume (TMCV) required to house nucleic acids and the associated biosynthetic machinery required for a self-sufficient form of life [251]. Use of the TMCV established there is 20 years ago to define compatibility with living nature must be however considered with caution. Indeed, recent advances in microbiology and virology have revealed existence of nanosized prokaryotes with biovolumes close to the TMCV. Giant viruses were reported as well. Genomic analysis of nanosized prokaryotes revealed a limited sub-cellular organization coupled with a significant reduction of biosynthetic and energy conservation pathways [23,[START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF]. Meanwhile, exceptionally large viruses were discovered that contain DNA encoding proteins involved in mRNA translation [274,275]. These discoveries have reopened the debate on the origin and the definition of life.

In the absence of scientific consensus on what the TMCV should be exactly, it would be perhaps premature to make the conclusion that ALNs cannot be living particles with the only criteria being their exceptionally small size. Various experimental approaches were developed to address this issue (see below).

The ability of ALNs to develop in the absence of cells (Figure 19) provides additional entry points to discuss the nature of these particles compared to viruses or extracellular vesicles (EVs). It seems worthwhile to underline, at this point, that host-independent morphogenesis is quite unusual in viral world or for EVs, although extracellular morphological plasticity has been reported for ATV viruses (Acidianius Two-tailed Virus) that infect archaeons living in particularly harsh aquatic environments [276,277]. ALN morphotype fluctuations that happen in the absence of cells seem at odds with a viral nature of ALNs if viewed as gradual assembly/disassembly processes within a single particle having a pleomorphic lifestyle.

However, the alternative, i.e., convergence of otherwise unrelated nanoparticles, toward an "aster-shaped" morphology must also be considered. In this case, morphotype fluctuations could merely reflect survival capabilities of unrelated particles in the absence of cells. Clearly, further studies are required to elucidate morphotype fluctuations related to the exact nature of ALNs.

Sensitivity to a wide range of antibiotics was used as a critical point to establish the non-living nature of biomimetic particles [54]. The abundance of ALNs was dramatically affected by biocide agents (norfloxacin, novobiocin, lysozyme or heat shock) (Figure 18). These results subsequent TEM analysis of the sorted ALNs provided preliminary insights in this topic. The cytometry step was assessed using permeant cyanine SYBR dyes. These stains preferentially bind to double-stranded DNA, but can also stain single-stranded DNA and RNA with variable efficiency. TEM analyses of sorted fractions showed that SYBR Green I and side scatter signal intensities were morphotype-dependent and allowed to establish a positive correlation between the complexity of morphotypes and the intensity of fluorescence emitted by the particles (Figure 16). Assuming that FC-detected SYBR-staining is indicative for the presence of nucleic acids encased in the nanoparticle (core structure?), highly enriched ALN cultures (0.2 μm filtered) appeared as suitable material from which putative DNA could be directly extracted and characterized at the molecular level. Whole genome sequencing was then developed using the same DNA template. 16S rRNA genes have not been identified as part of the 233 contigs assembled through this approach (Figure 17). Assuming that DNA extraction and amplification were efficient, our data suggests that ALNs lack a detectable genomic features and translation machinery of prokaryotes. The great majority of contigs delivered by whole genome analysis were affiliated to the microviridae, a family of bacteriophages with a single-stranded DNA genome. However, microviridae contigs must be viewed as assemblies of sequence fragments from remnants of viral populations initially comprised in the lake water sample. According to these results, we were not able to demonstrate the presence of nucleic acids in ALNs. Extraction and non-specific amplification efficiencies of nucleic acids are strongly linked to the nature of the particle. Development of a specific protocol to purified ALN enriched-cultures will be a critical point as soon as the exact nature of ALNs will be determined.

could
Overall, our data on the atypical morphology, the reduced biovolume, the suspected dominant organic nature, the sensibility to biocide treatments, and the ability to develop in the absence of cells indicate than ALNs are new femto-entities which, at the moment, cannot be classified in any known category of femto-entities previously described in environmental samples.

Ecological Significance of ALNs

Our discovery of ALNs and the existence of other ultra-small non-viral particles raise the ecological question of the accuracy of the "VLP" (i.e., virus-like-particles) fraction in aquatic ecosystems. Commonly used to designate free-occurring viruses, the acronym VLP is also synonymous of "known and yet unknown viral aquatic particles" especially as standardized FC methodologies include heat-driven procedures particularly efficient for detection of viral particles that are, otherwise, refractory or weakly responsive to SYBR-staining [256].

Interference between ALNs and VLPs in FC particle quantification and successful sorting of largest morphotypes (Figure 16), indicate that ALNs must be viewed as atypical nanoparticles comprised in the VLP fraction. Events recorded from ALNs may lead to overestimate the viral load when analyzing viromes in aquatic ecosystems by counting SYBR-stained particles which is the methodology currently used for optimal detection of viruses by flow cytometry [110].

Experimental bias generated by overlapping of fluorescent signals produced by viruses and by other types of nanoparticles encompassed within the viral population was previously assessed in the case of EVs which constitute regular components of VLP fractions in natural environment [START_REF] Soler | Virus-like vesicles and extracellular DNA produced by hyperthermophilic archaea of the order Thermococcales[END_REF]211,212]. Comparative studies between ecological groups comprising viral communities should therefore be interpreted with caution when pleomorphic nanoparticles such as ALNs occur in samples, notably when seasonal variations favor temporary bloom or predominance of one ALN morphotype over others.

Ecological significance of ALNs was approached by in situ seasonal and ecosystemic analyses.

Seasonal analyses in a French eutrophic lake revealed a marked seasonal dynamic in ALN abundances from 8.0 ± 3.8 × 10 4 to 9.0 ± 0.5 × 10 7 mL -1 (Figure 20) and suggest a tight control of the environmental parameters on ALNs. Relative proportions of each morphotype shifted concomitant to fluctuations in total ALN abundance. 11-armed form appeared the alone form in condition of the lowest density of ALNs, suggesting that this peculiar form could be more resistant to adverse environmental factors than others forms. Inverted correlation between 11armed forms and the others forms, also noted when ALNs were maintained for 36 days in prokaryote-free lake water (in laboratory condition) suggests that these forms may be of importance in maintaining a permanent pool of ALNs in lake water and in promoting propagation of the nanoparticles when growth conditions become more favorable. This assumption is only possible assuming that pleomorphism arises from inter-conversion between morphotypes. The idea that morphotypes described in this study all develop from the same "stem entity" is not demonstrated and remains a fundamental question to be addressed in the medium compared to in situ analyses (multiplication factor of 3.6 in cell-free medium compared to 60 in French Lake). These data suggests that microbial communities may help promoting the nanoparticle dynamics. Interestingly, more detailed observations of microbial communities collected from eutrophic lakes revealed arm-mediated contacts between ALNs and bacteria (Figure 22). The role of microbial communities in the control of ALNs and the functional significance of the observed contacts between ALNs and bacteria are still unclear.

Further ecological studies of these puzzling nanoparticles should be placed in the context of ecosystemic relationships between ALNs and prokaryotes as well as between ALNs and other biological or physic-chemical components.

Seasonal and spatial dynamics are a characteristic of aquatic microbial communities which regulate energy and matter flows in aquatic systems [110,279]. To our knowledge, long-term ongoing researches on the ecology and population dynamics of nanobes or non-living particles are currently lacking. This precludes any comparison with our ALN studies. Nevertheless, our observations clearly raise the question of the ecological importance of ALNs in the functioning of aquatic ecosystems. Although reduced on a unit scale, the biomass of total ALNs during bloom periods is likely to mobilize circulating mineral and organic nutrients at the expense (competition?) of other microbial communities of aquatic ecosystems. In addition, direct interplay with bacteria (Figure 22) could significantly influence the energy and material flows mediated by the prokaryotic compartments.

Conclusion

This study shows, for the first time, that aquatic ecosystems may contain abundant and dynamic nanoparticles of a novel type with ecological potentialities, especially in meso-and eutrophic waters which are predilection sites for ALN detection. Tough the question of the living or nonliving nature of ALNs remains unresolved at this time, their original features re-open the debate on the minimal cell volume for a self-sufficient form of life. Experiments are in progress to explore the exact nature of ALNs and identify biotic and abiotic factors involved in regulation of their dynamics in microcosm and environmental conditions. In this context, an upcoming challenge will be to obtain mass cultures of ALN particles grown in VLP-, EV-and prokaryotefree medium. Clearly, we have describe novel types of environmental nanoparticles that, as the most ecological outcome, emphasize that not all virus-like particles observed in aquatic systems are necessarily viruses and that there may be several types of other ultra-small particles in natural waters that are currently unknown but potentially ecologically important. This study was supported by the CYSTEM platform UCA-PARTNER (University of Clermont Auvergne UCA), Clermont-Ferrand, France) and the Microorganisms: Genome and Environment laboratory (LMGE, UMR6023 CNRS-UCA, Clermont-Ferrand, France). This work also benefitted from the assistance of the Multiscale Electron imaging platform (METi) at the CBI (Toulouse, France), from the Technological Center for Microstructures (CTμ) (Villeurbanne, France) and from the GENTYANE Sequencing Platform (Clermont-Ferrand, France). The authors thank the UCA Centre Imagerie Cellulaire Santé (UCA, Clermont-Ferrand) for help with microscopy intercalibration. We thank Anne Catherine Lehours (LMGE) and Guillaume Borrel (BECM, Institut Pasteur, Paris, France) for helpful comments and discussions on the manuscript and Matthieu Legendre (IGS, UMR7256 Aix Marseille Université-CNRS, Marseille, France) for his assistance with the assembly of the sequence data. We also thank the two reviewers for their comments and suggestions which greatly increased the quality of this manuscript.

Supplemental materials

Conclusions

La découverte des ALNs, de nouvelles particules femtoplanctoniques aux caractéristiques inédites, suscite de nombreuses interrogations sur leur nature, leur écologie ainsi que leur rôle fonctionnel dans l'environnement.

Trophic Conditions Influence Widespread Distribution of

Aster-Like Nanoparticles Within Aquatic Environments

Maxime Fuster Publié dans Microbial Ecology -Juin 2020 doi: 10.1007/s00248-020-01541-6

Abstract

Aster-like nanoparticles (ALNs) are newly described femto-entities. Their ecology (e.g., geographic distribution, spatial dynamic, preferences, forcing factors) is still unknown. Here, we report that these entities, which have largely been ignored until now, can develop or maintain themselves in most aquatic environments in the Loire River catchment, France. We observed a significant influence of the trophic state on ALN ecological distributions. A positive relationship between prokaryotic abundance and ALN (r2 = 0.72, p < 0.01) has been identified, but its exact nature remains to be clarified. Combined with their ubiquitous distribution and high abundances (up to 7.9 × 106 ALNs mL-1) recorded in our samples, this probably makes ALNs an overlooked functional component in aquatic ecosystems.

Note

The discovery of the importance of extracellular vesicles [212], bacteria CPR (Candidate Phyla Radiation), archaea DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaea) [START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF]246], and "biomimetic mineralo-organic particles" [18] permitted to reconsider the diver-sity and ecological role of the femtoplankton, hitherto confined to the sole viruses, some < 0.2 μm filterable prokaryotes [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF]. The recent discovery of "aster like nanoparticles" (ALNs) in pelagic aquatic environments showed that the femtoplankton still hosts many unknown and undervalued entities [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. In a previous, unprecedented study on these entities, the authors have shown that ALNs are amorphous starshaped entities suspected to be organic in nature (composed mainly of carbon, oxygen, calcium and nitrogen with traces of potassium). Pleomorphic, these entities present three main morphotypes, with 4, 11, and 20 arms, and a reduced biovolume, lower than of the smallest known prokaryote. These original characteristics, combined with their sensitivity to biocidal treatments and their ability to grow in the absence of cells, raise questions about their exact nature and origin [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Their high seasonal abundances (up to 9.0 ± 0.5 × 10 7 entities•mL -1 ), in the range of virus-like particles, may exceed those of prokaryotes by up to about one order of magnitude [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Added to obser-vations of phenotypic close contact with prokaryotes [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF],

such numerical abundance levels probably make ALNs a significant actor in the functioning of aquatic systems. For example, its calcium composition [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] could have a significant impact on calcium homeostasis of aquatic environments. Without yet knowing their full biological Except for the first findings obtained from lake samples [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF], we still lack information on the ecological distribution and spatiotemporal dynamics of ALNs, in relation to the potential environmental forcing factors.

Results acquired in this second study demonstrate that ALNs are overlooked femto-entities, widely distributed, and that their dynamics are controlled by trophic status, in particular by the biological environment. Identification and quantification of ALNs and of their morphological variants are described in Colombet and collaborators [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Twenty-five study sites distributed over the Loire River catchment (France) were selected to represent different aquatic systems (rivers, canal, marshes, lakes, mudflat, and coastal ocean) as well as longitudinal gradient from the source to the estuary (Figure 23-A).

Sampling sites were classified into three trophic states according to all abiotic and biotic parameters measured in situ. Further details on the methodology used are provided in the supplementary text and data. ALNs have the ability to colonize different aquatic environments: lakes, rivers, marshes, coastal oceanic waters, except source areas, and altitude lakes (Figure 23). They were found in environments with contrasting physicochemical (e.g., conductivity, oxygen, nutrients) and biological (e.g., virus, prokaryotes, algae) characteristics (Supplementary Table S1). This defines them as tolerant and ubiquitous entities capable of maintaining themselves in the majority of con-tinental and coastal aquatic environments. The abundances of ALNs recorded (1.1 × 10 7 ± 0.17 × 10 7 ALNs mL -1 ) indicate preferential development in plain lakes, marshes, Loire estu-ary, and in lesser extent within free-flowing river channels (Figure 23-B,C). Detection of ALNs has also been mentioned in the tropical estuarine system of Ha Long Bay (Vietnam) and in the Saloum River in Senegal, thus

broadening the habitat preferences and potential distribution of these entities [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. However, sampling of these studies was sporadic, and these conclusions must be weighted by the high seasonal or even daily fluctuations of ALNs recorded previously [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. The sampling period, i.e., spring, was based on the results obtained from the unique study on seasonal monitoring of ALNs in a eutrophic lake [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. We recognize the need of additional data on the seasonal variability of ALNs in different aquatic envi-ronments in order to optimize sampling periods. 2,3,[START_REF] Joshi | Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files[END_REF], medium (state 2 = sites 5,6,8,11,14,15,16,18,19,20,24,25), and high (state 3 = sites 7,9,[START_REF] Chaumeil | GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF]12,13,17,21,[START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF]23) trophic levels of the different aquatic en-vironments. b Correlation analysis (Spearman's test, p < 0.01) between the different physical-chemical and biological parameters of the different sampling points. T°C temperature, O2 dissolved oxygen, P total organic phosphorus, N total organic nitrogen, C total organic carbon a b

The presence of ALNs in the coastal ocean samples raises questions about their potential for development in the marine environment and their possible transfer from continental waters to the oceans. We suggest that the gradual and significant increase of ALN abundance (undetectable to 8.8 × 10 5 ALNs.mL -1 ) from the source to the estuary (Figure 23-B) can be explained through the ALN down-stream transfer along the river continuum, as observed for other entities or pollutants [283][284][285]. The occurrence of 11-budding-arm forms in the downstream area suggests that ALNs could be transported from the upstream catchment to more favorable conditions for their development down-stream. The occurrence of the different forms of ALN in-dicates dominance of 20-arm forms (69% of total ALNs) in marshes, while 11-arm forms dominate in lakes and rivers (38% and 47% of total ALNs, respectively; Figure 23-C).

Environmental conditions probably select and/or favor the development of one type in respect to another, through a process that remains unexplained and which could either reflect the gradual development from one form to another or the occurrence and development of rather independent forms. In order to better understand spatial distributions of ALNs, future investigations will have to demonstrate if a form of resistance distinct from forms of propagation able to develop over time (i.e., assuming distinct growth stages of the same organism) [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] exists.

These observations also point to the hypothesis that ALNs could be present in all aquatic environments but are selected by environmental factors (Baas Becking hypothesis) [286]. Such

an assumption is supported by the capacity of ALNs to develop in unrelated biomes, from temperate regions separat-ed by hundreds of kilometers as in our study, to tropical regions [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

According to the parameters recorded, we reported a significant influence of the trophic state on ecological distributions of ALNs (Figure 24-A) with a significant increase from undetectable ALNs.mL -1 in the environments classified in the first trophic state, to 2.2 × 10

ALNs.mL -1 in those classified in the third trophic state [287]. In this study, the trophic state was estimated according to the Trophic State Index, a reference method for the classification of aquatic environments [288].

Therefore, we suggest that ALNs, in addition to certain microbial components such as phytoplankton communities [289] may serve as a putative indicator of trophic conditions of aquatic environments. Whatever the aquatic system consid-ered, it seems that biological features prevail over physico-chemical ones in the regulation of the distribution and abun-dances of ALNs (Figure 24-B). The major correlative factor identified is the abundance of prokaryotes (r 2 = 0.72, p < 0.01; Figure 24-B). A significant statistical correlation and the observation of direct physical contact between prokaryotes and ALNs [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] suggest an interaction between these two components. Previous study showed that ALNs can grow without a potential host [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]; however, the presence of prokaryotes could promote their development through mechanisms that remain un-known [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Therefore, future investigations are needed to elucidate the nature of this mutual relationship which, perhaps, could be related to either bottom-up resource-driven or to top-down host-symbiont interactions.

Our findings reinforced the hypothesis of the biological origin of ALNs [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] and the hypothesis that ALNs are ubiquitous and widespread within continental freshwaters and coastal brackish waters. The estimation of the ecological importance of femtoplanktonic entities depends closely on their abundance and functions. This is demonstrated for viruses [140,290], extracellular vesicles, ultramicro-prokaryotes [START_REF] Ghuneim | Nano-Sized and Filterable Bacteria and Archaea: Biodiversity and Function[END_REF]246], and suspected for non-biological entities such as "biomimetic mineralo-organic particles" [18]. The average abundances of 9.9 × 10 5 and 7.9 × 10 6 we recorded respectively in plain lakes and marshes area (see Figure 23-A

Supplemental materials

Materials and methods

Study sites and sample collection

Samples were collected at the surface (0-40cm) of 25 aquatic environments from February to May 2019, distributed along the Loire River watershed (France, see locations and characteristics in Figure 1 and supplementary Tables S1 andS2): in the sampling day and immediately treated to the laboratory (see below).

8

Abiotic parameters measurements

Temperature (°Celsius), conductivity (µSiemens.cm -1 ) and dissolved oxygen content (mg.L -1 )

were measured in situ with a submersible probe (ProOdo YSI, Yellow Springs, Ohio, USA).

pH was measured on an unfixed sample in the laboratory (Thermo Scientific, Orion Star A111, Waltham, MA). Total organic nitrogen, chlorides and organic phosphorus (mg.L -1 ) were analyzed by UV-VIS spectrophotometry whereas total organic calcium was determined by ion chromatography and total organic carbon was determined by IR spectrophotometry after persulfate oxidation, on unfixed samples.

Biotic parameters measurements

Planktonic communities measurement: Chlorophyceae, cyanobacteria, Cryptophyceae and diatoms biomass was inferred from in situ measurement of chlorophyll a, phycoerythrin and phycocyanin (μg.L -1 ) using a submersible spectrofluorometric probe (BBE FluoroProbe) (Moldaenke GmbH, DE). The description of phytoplankton content was supplemented with the 1), ALNs detection and quantification of all sites were realized from 60 fold concentrated water. This was obtained by tangential-flow ultrafiltration of 40 L of raw water, previously filtered through a 25-µm-pore-size nylon mesh, using a Kross-Flow system (Spectrum, Breda, The Netherlands) equipped with a 0.2-µm cut-off cartridge. Aliquot of the concentrated 0.2 µm-25 µm fraction was immediately fixed with 1% (v/v) formaldehyde and stored at 4°C for ALNs counts. The microbial concentration of the concentrated fraction was determined by flow cytometry as described above. Most loaded samples were then diluted after concentration to prepare the microscopy grids. This dilution factor was calculated for each sample to obtain an equal load of prokaryotes on each grid. The sample with the lowest prokaryotic concentration after concentration was considered standard. The concentration factor and dilution were experimentally tested and chosen to promote clear discrimination between the ALNs and all entities present on the grid. Fixed-concentrated sample were centrifuged at 18,000 g for 20 min at 14°C directly onto 400-mesh electron microscopy copper grids covered with carbon-coated Formvar film (Pelanne Instruments, Toulouse, France). Collected particles were overcontrasted using uranyl salts as described here [254]. Ratio of ALNs/prokaryotes was determined by transmission electron microscopy (TEM) using a Jeol 1200EX microscope (JEOL, Akishima, Tokyo, Japan) at 80 kV and x50,000 magnifications [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. For all samples, 300 prokaryotes were counted (i.e. a minimum of 6 transects randomly distributed on the grid), in triplicate to ensure robust statistical processing of the data. At the same time, we also counted the number of ALNs present on these transects to determine this ratio. Entities with membrane folds and non-homogeneous shapes, characteristic of large extracellular vesicles (i.e.

microvesicles and some apoptotic vesicles), were excluded from the prokaryotic count.

Concentration of

Determination of trophic status of sampled aquatic environments

The classification in 3 different trophic states is done using the TSI (Trophic State Index) defined by Carlson in 1977 [288] and recommended by the OECD [292]. As the Secchi value was not applicable on all samples (river sample), we used an average TSI inferred from Average TSI = (TSI-P + TSI-Chla)/2

Our samples were then categorized as follow : sites 1, 2, 3, 4 in trophic state 1 (low), sites 5, 6, 8, 11, 14, 15, 16, 18, 19, 20 ,24, 25 in trophic state 2 (moderate) and sites 7, 9, 10, 12, 13 ,17, 21, 22, 23 in trophic state 3 (high) (see Table S1).

Correlation analyzes

Differences between the trophic states were assessed using a U test. Potential relationships between variables were tested with a Spearman test then visualized through a correlogram using the "Hmisc" package. All tests were performed under RStudio (R Core Team version 3.2.2, 2015).

Conclusions

Les

Occurrence and seasonal dynamics of ALNs in freshwater lakes are influenced by their biological environment

Maxime Fuster 1 , Hermine Billard 1 , Gisèle Bronner 1 ,Télesphore Sime-Ngando 1 , Jonathan Colombet ALNs.mL -1 ), with characteristic peaks in spring. We recorded correlation between ALNs and some prokaryotic phyla suggesting a broad and non-specific relationship. From their seasonal dynamics and potential link with prokaryotes, we conclude that ALNs represent an important ecological actor in the functioning of aquatic ecosystems

Introduction

The ecological importance of planktonic communities closely depends on their diversity and the associated spatio-temporal dynamics, in response to environmental changes. In the past, the ecological importance of picoplankton (0.2-2 µm) [15,300] and nanoplankton (2-20 µm) [301, 302] making up the bulk of the so-called microbial loop has been studied extensively. Their roles in the flow of energy and matter on a global scale has become evident [12]. Highlighting the importance of viruses resulted in the inclusion of femtoplankton (< 0.2 µm) in ecological models [219,225,303]. Viruses have long been considered as the main, if not the only, compartment of femtoplankton, mainly because of their interactions within the microbial loop where they shunt microbial particles into dissolved matter, i.e. the 'viral shunt' [START_REF] Jmcn | Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions 1[END_REF]230].

However, in the recent years, the discovery of an unsuspected diversity of femtoplankton Extracellular Vesicles (EVs), and Aster Like Nanoparticles (ALNs), leads to a necessary reconsideration of the ecological role of femtoplankton compartment, at least through the study of the diversity and dynamics of their representatives (Colombet et al.,[16]). Attempts to evaluate the quantitative and qualitative importance of CPR / DPANN [203,204], BMOPs [18],

EVs [24] underscores this necessity. Likewise, pioneering reports on ALNs also showed that these entities might have important ecological functions [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197]. ALNs are original aster-like entities composed of C, O, Ca, N, K with distinct morphotypes depending on the number of arms (4, 11 and 20 arms) present and their budding (Figure 25). Their size (on average from 110 to 430 nm) and volume (less than 1.4x10 -3 µm 3 ) lower than the minimum required for life expression (Theoretical Minimal Cell Volume, i.e. 0.008 µm 3 ) [251], together with their organic nature, their sensitivity to different biocidal treatments, and their capacity to change their numbers in the absence of potential hosts [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF], question their exact nature. The presence of nucleic acids remains to be proven [16,[START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

However, (i) their ability to colonize different continental and coastal aquatic environments according to their trophic status [197], (ii) their capabilities to produce bloom situations, with abundance peaks reaching up to 9.0 ± 0.5 × 10 7 ALNs.mL -1 [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF], and (iii) their putative functional interactions with prokaryotes [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197] strongly suggest that they are potentially significant actors in the flow of energy and matter transiting in aquatic systems. To understand the quantitative and functional importance of ALNs in the environment and their exact nature, it seems to be crucial to realize ecological studies integrating temporal variations of ALNs in various ecosystems considering possible environmental forcing parameters.

For this purpose, we monitored the in-situ dynamic of ALNs as well as the physico-chemical and biological parameters in three lakes of the Massif Central, France, during a one-year period.

Our results indicate that ALNs are new dynamic players in the ecology of aquatic systems, with potential links with microbial phyla.

Materials and methods

Study sites and sample collections

Samples were collected every month during one year Gervais and Lapeyrouse are eutrophic lakes with a significant human presence. Five liters of water was collected at the surface (0-40cm) of the deepest point of the lake, using a sampling bottle (5L-Niskin-type, Bionef, Fr). St. Gervais has the particularity of having been emptied

during November, December 2018 and January 2019 and returned to its maximum depth in December 2019. During the empty period, samples were taken from a permanent puddle at the center of the lake supplied by the upstream source flowing into the lake. Monitoring of the number of Aster Like Nanoparticles (ALNs) in this upstream source was performed during all the survey, in addition to the lake. Samples of virus-like particles (VLPs), prokaryotes and Aster Like Nanoparticles (ALNs) were fixed with 1% (v/v) formaldehyde and stored at 4 • C until counts within 4 hours following sampling. Samples of heterotrophic eukaryotes (HE) were fixed with 1% (v/v) formaldehyde and stored at -20 • C until counts.

Unfixed samples for analyses of phytoplanktonic communities, microbial diversity, nutrients concentrations and pH measurements were transported at 4°C and treated in the 4 hours following sampling.

Abiotic parameters measurements

Dissolved oxygen content (mg.L-1), temperature (°Celsius) and conductivity (µSiemens.cm-1)

were measured in-situ with a submersible probe (ProDSS YSI, Yellow Springs, Ohio, USA), while pH was measured in the laboratory (probe Thermo Scientific, Orion Star A111, Waltham, MA). Organic phosphorus, chlorides and total organic nitrogen were analyzed by UV-VIS spectrophotometry (NF ISO 15923-1). Total organic carbon was determined by IR spectrophotometry after persulfate oxidation (NF EN 1484) and total organic calcium, potassium, magnesium and sodium were determined by ion chromatography (NF EN ISO 14911). These standardized and normed measurements were carried out by an accredited institute (Eurofins, Saint-Etienne, France NF EN ISO/IEC 17025:2005 COFRAC 1-2091)

The nucleic acids were then precipitated with a mixture of glycogen 5mg.mL -1 , sodium acetate 3M and ethanol 100% overnight at -20°C. The DNA pellet was rinsed with ethanol (70%), dried and dissolved in the TE buffer. DNA was then purified using a commercial kit (NucleoSpin® gDNA Clean-up, Macherey-Nagel).

For archae, amplification of the V4-V6 region of the small subunit rDNA was amplified using the universal archae 519F and 1017R primers [305] (Tab s1). For bacteria, the V4-V5 region of the bacterial small subunit rDNA was amplified using the universal bacteria 515F and 928R primers [306] (Tab s1). In addition, the ITS region of fungi was amplified using common fungi primers ITS7f and ITS4r [307] (Tab s1). Each PCR was performed in a total volume of 50µL containing 1x final reaction buffer, 2 mM MgCl2, 0.2mM dNTP, 100 µg.mL -1 BSA, 0.2 µM of each primer, 0.025 U.µL -1 PROMEGA GoTaq HotsStart G2 and 5 µL of DNA. The different PCR programs are detailed in the supplemental (Tab s1). correlation analyses). Link between the log-transformed abundance of ALNs and prokaryotes was tested by linear regression using data obtained in the 3 lakes and those obtained from a previous study in Colombet et al.,[START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Cross effects of measured parameters were tested by the omega-square method ω2 [312].

Amplicon analysis and taxonomic affiliation

Results

Environmental parameters

Physico-chemical environment of the studied sites

Absolute values and seasonal variations in oxygen content, temperature and pH were characteristics of freshwater lakes in temperate regions. The three lakes showed similar average values (p > 0.05, Table 3-A) with marked statistical differences (p < 0.01) between seasons (Table 3-B). As expected, temperature was inversely correlated to oxygen (r 2 =-0.77, p < 0.01).

The summer and autumn warming periods of the lakes corresponded to oxygen depletion while the cold spring and winter periods corresponded to a rise in oxygenation of lake waters (Table 3-B). pH was stable during spring, summer and autumn and decreased significantly in winter (p < 0.01) (Table 3

-B).

The availability of mineral elements (K, Mg, Na, Ca) showed different distributions between lakes (Table 3-A). K and Mg had similar distributions with significant differences (p < 0.01) between the three lakes, with highest and lowest values recorded respectively in Fargettes and St. Gervais (Table3-A). Na concentration was significantly lower in Fargettes compared to St.

Gervais and Lapeyrouse (p < 0.01). Ca was significantly lower in St. Gervais compared to Fargettes and Lapeyrouse (p < 0.01) (Table 3

-A).

The main chemical factors that discriminated the three lakes appeared to be productivity indicators such as Phosphorus (P), Total Organic Carbon (TOC) or Total Nitrogen (TN). P, TOC and TN were significantly higher in Fargettes compared to Lapeyrouse while St. Gervais

Standing stocks of Viruses like particles, prokaryotes, phytoplankton and heterotrophic eukaryotes

The variations of biological environment (Viruses Like Particles (VLPs), prokaryotes, phytoplankton and heterotrophic eukaryotes (HE)) between lakes and seasons are listed in At the seasonal scale, no significant variations (p > 0.05) were recorded for the three lakes (Table 3-

Figure 27: Principal Component Analysis of individuals (sampling points) in function of lakes (A) or seasons (B).

Aster-Like Nanoparticles distribution

As for productivity indicators (P, TOC, TN) and prokaryotes concentrations, significant differences between ALN anbundances (p < 0.01) were recorded between lakes (Table 3-A).

As the above-mentioned parameters, the highest and lowest annual mean abundance of Aster Like Nanoparticles (ALNs) were recorded in lake Fargettes (6.12 ± 11.7 x10 5 ALNs.mL -1 ) and Lapeyrouse (0.83 ± 1.99 x10 5 ALNs.mL -1 ). St. Gervais had an intermediate average value (2.32 ± 2.60 x10 5 ALNs.mL -1 ) ( Linear regression (y = -3 + 1,2*x) was performed with data from the 3 lakes during the 12 months of sampling and data from Colombet et al., [13].

All parameters and ALNs were integrated in a principal component analysis (Figure 27). 54.1% of the variance is explained by the first 2 axes. This analysis showed a pronounced interlake variability, mainly due to the biological variables. Like the patterns of ALN abundance, Fargettes Lake was clearly distinguished from Lake Lapeyrouse with St. Gervais in intermediary (Figure 27-A). The summer/winter seasonal discrimination with spring and autumn in between is classic for temperate zone lake systems (Figure 27-B). The remarkable point of Fargettes in March stands out clearly from this analysis which coincides with the bloom of ALNs.

Interaction between Aster-like Nanoparticles and their environment

There was no significant correlation between ALNs and any of the measured physico-chemical parameters (Table 4). In contrast, significant correlations (p ≤ 0.05) were recorded between ALNs and their biotic environment, primarily with VLPs (r 2 = 0.47) and prokaryotes (r 2 = 0.32) (Table 4)

Linear regression of data including data obtained from a former study in lake Fargettes (Colombet et al.,[START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]), revealed a significant relation between ALNs and prokaryotes (Figure 28). The regression line linking number of ALNs as a function of number of prokaryotes appears highly significant (ALN concentration = -3 + 1.2 x prokaryotes concentration, R² = 0.43, ω 2 = 0.43, one way ANOVA (F (1,62) = 49.14, p < 0.001)) (Figure 28). As revealed by ω 2 = 0.43, one of the two parameters can explain 43 % of the distribution of the other (Figure 28).

No significant correlations were observed between ALNs and archaeal OTUs during the sampling period in the three lakes (Table 5). On the other hand, ALNs were significantly correlated (p < 0.01) with 5 bacterial phyla (Acidobacteria, Cyanobacteria, Firmicutes, Planctomycetes.

Discussion

Here we report the seasonal fluctuations of Aster Like Nanoparticles (ALNs) concentrations in 3 different lakes. These entities were first described in 2019 [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] and colonize different continental and coastal environments, reaching important concentrations in the order of 10 7

ALNs.mL -1 [197]. We recently demonstrated that their distribution could be influenced by the trophic state of the environment [197]. These pioneering works result in a partial understanding of the ecology of ALNs. Information on their spatial and seasonal dynamics in relation to their environment are crucial and could allow us to (i) reveal their environmental forcing factors, (ii)

understand their contribution to the flow of matter and energy and (iii) perhaps open a window on their exact nature. The seasonal variations of ALN abundances were similar in the three lakes which were in a restricted geographical area (French Massif Central) and were apparently driven more by differences in biological parameters. This is in agreement with our previous study [197] were ALNs increased in environments with high microbial density and nutrients content, such as Lake Fargettes. The study of the temporal dynamics of ALNs revealed a marked seasonality. The seasonal patterns of ALNs in the three lakes was relatively similar, with characteristic peaks in spring. The ALNs communities exhibited a rapid growth capacity with a high amplitude of abundance variations (from undetectable to 4.28 ± 0.74 x 10 6

ALNs.mL -1 between two consecutive time point in lake Fargettes for example). ALNs are therefore a rapid mobilization and sequestration factor of their constituent elements. Colombet and colleagues [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] showed that Ca is a preponderant constitutive element of ALNs. It is therefore very likely that ALNs have a key role in the aquatic Ca cycle. Considering the biomass dynamics of ALNs can therefore be fundamental in understanding the flow of elements through aquatic ecosystems, as has been demonstrated for viruses for example [303].

Seasonal variations in the form of bloom are a recurring pattern in aquatic microbial and viral communities [110,279,303,313]. All the models showing this kind of dynamics (free or symbiotic), have a prominent role in the functioning of the ecosystem. It is therefore undoubtedly that ALNs are intrinsic actors in the ecology of aquatic systems. However, the understanding of their ecology is intimately linked to the understanding of their control factors.

Different factors can explain temporal variations of microbial entities, including geographic and environmental factors [314], abiotic and biotic factors, bottom-up and top-down factors

[315], or the presence/absence of hosts for the life cycle such as for viruses [316]. The case of lake Saint Gervais, which was emptied for several weeks, makes it possible to specify here that the ALNs are aboriginal to the lake. Indeed, during the drying phase and until the peak of ALNs, we carried out regular sampling in the tributaries feeding the lake without ever detecting the presence of ALNs. The controlling factors of ALNs are thus intrinsic to the lake. No abiotic factors seem to have an impact on the variations of ALNs abundance in lake ecosystems.

It's interesting to note that with equal temperature between spring and fall, we recorded a significant development of ALNs in spring. The development of ALNs could therefore be more associated with the seasonal succession of biological communities forced by the interaction of physico-chemical environmental variables rather than with a single physico-chemical variable.

Among biotic factors measured, correlations with prokaryotes and VLPs were identified. We further explored these putative links to the microbial environment by integrating data previously acquired in Fargettes Lake [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. The linear regression model used allows us to highlight a strong link between ALNs and prokaryotes. The ω2 allowed us to estimate that 47 % of the variation in number of ALNs could be explained by the prokaryotes. These results support the observations described in Colombet et al., [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] where one can clearly distinguish a close physical interaction between ALNs and prokaryotes. These data raise the hypothesis that ALNs could have strong interactions with prokaryotes. One of the particularities of ALNs is their pleomorphism. Each form (see description in Colombet et al.,[START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]) has a particular seasonal dynamic (Fig 26-B). In the hypothesis that they are dependent on each other within a developmental cycle, it is likely that a partner, possibly prokaryotic, may intervene at certain stages and regulate the dynamics of the different forms. 11-arms forms could be a resistant form.

To identify more precisely which microbial communities may be involved in these interactions with ALNs, we analyzed the covariation of the presence of ALNs with those of the different bacterial, archaeal, and fungal phyla identified in the three lakes. ALNs appeared strongly positively correlated (r ² > 0,7, p < 0.05) with some fungal (Ascomycota and Chytridiomycota) and bacterial (Acidobacteria, Cyanobacteria, Firmicutes, Planctomycetes, Proteobacteria)

OTUs in lakes. Ascomycota is the most common fungal phylum in aquatic environments [317] and Chytridiomycota is a phylum with a huge implication in the regulation of aquatic organisms, especially influencing directly or indirectly the microbial loop [318,319]. Although we cannot rule out a direct relationship, it is more likely that fungi interact indirectly with ALNs via a third-party microbe. The positive correlations between ALNs and prokaryotes seem to target a large heterogeneity of bacterial phyla. Acidobacteria, Cyanobacteria, Firmicutes, Planctomycetes, and Proteobacteria represent most lake bacteria [320]. Thus, although we cannot formally infer a direct relationship, these data suggest that the spectrum of possible prokaryotic partners for ALNs may be broad and non-specific.

The data acquired here allow a better understanding of the ecology of ALNs, namely, a pronounced seasonal dynamic in the form of spring "bloom" that can be controlled by the

Conclusions

Les travaux associés à cette étude ont mis en évidence l'existence d'un pattern de développement basé sur une dynamique saisonnière des ALNs marquée dans les systèmes étudiés. Cette dynamique se manifeste par l'apparition de « blooms » printaniers, avec une grande amplitude de variation de concentrations (i.e. de non détectable à 4.28 x 10 6 ALNs.mL -

CHAPITRE 3 : INTERACTIONS ENTRE ALNs ET PROCARYOTES EN CONDITIONS CONTROLÉES

Les études précédentes de ce manuscrit ont permis de mieux appréhender la dynamique des ALNs dans les écosystèmes naturels. En effet, nous avons mis en évidence que leur présence dans un large spectre d'habitats ou que leur dynamique saisonnière, marquée par de fortes variations d'abondances, serait étroitement liée à celle des procaryotes.

Les procaryotes qui comprennent les bactéries et les archées, sont des acteurs essentiels des réseaux trophiques aquatiques. Retrouvés également dans la littérature sous le terme de bactérioplancton, ces derniers interviennent dans différents processus cruciaux des écosystèmes :

-Les bactéries autotrophes (i.e. cyanobactéries) jouent un rôle dans la production primaire [300,321].

-Les bactéries hétérotrophes sont impliquées dans la circulation de la matière minérale et organique dans les milieux aquatiques, notamment comme décomposeurs ou comme proies pour le zooplancton [9].

-Les archées, qui peuvent représenter jusqu'à 30% des procaryotes dans les zones euphotiques des écosystèmes lacustres [322], sont elles aussi impliquées dans différents processus biogéochimiques [323].

Les études écosystèmiques (c'est-à-dire à l'échelle des communautés naturelles) ayant suggéré des interactions potentielles entre les ALNs et les procaryotes, il nous a paru nécessaire d'aborder l'étude de ces interactions d'un point de vue expérimental, afin de mieux comprendre leur importance pour les communautés de procaryotes (e.g. impact sur la concentration, la diversité, le métabolisme…). Une partie des résultat de ce chapitre a fait l'objet d'une publication parue.

Interactions between concentration of prokaryotes and concentration of ALNs in in-vitro conditions

Maxime Fuster 1 , Hermine Billard 1 ,Télesphore Sime-Ngando 1 , Jonathan Colombet 11 Université Clermont Auvergne, CNRS, LMGE, Clermont-Ferrand F-63000, France

In preparation.

Introduction

In the past years, the discovery of extracellular vesicles, CPR (Candidate Phylum Radia) bacteria, DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaea), a,d biomimetic mineralo-organic particles, have highlighted the necessity of deepen our knowledge on femtoplanktonic compartment, considered for years to be composed only of viruses and few prokaryotic entities < 0.2 µm [16]. The discovery of the above entities has thus led to a reconsideration of the ecological importance of this compartment in the functioning of aquatic systems.

Moreover, the recent discovery of ALNs, i.e. the last of the discovered femtoplankton entities [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF], reinforces the hypothesis that femtoplankton remains today a reservoir of unknown entities with potential roles in aquatic ecosystems. ALNs are entities with a characteristic astershaped morphology. They are composed mainly of C, O, Ca, and present distinct morphotypes based on the number of arms of the entity [START_REF] Joshi | Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files[END_REF]11,20). These original characteristics, combined with their organic nature as well as their reduced bio-volume and their sensitivity to biocide treatments, raise many questions about their nature and origin. The few data accumulated on the ecology of these new particles have shown that they are distributed worldwide [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197] and closely associated with eutrophic environments [197]. Biological parameters seem to be the main forcing factor of their dynamics [324]. Correlative data obtained from these environmental studies have led to the hypothesis that prokaryotes may be a potential interactor involved in the regulation of their development. However, this speculation is purely empirical and needs to be verified and specified under controlled conditions.

In this work, we performed the first monitoring of ALNs under controlled prokaryotic conditions to evaluate the possible interactions between them. The results obtained indicate that the development of ALNs could be, at least partly, controlled by the development of a prokaryotic interactant. Our results support the hypotheses formulated in natural environmental studies, as for an interaction between ALNs and prokaryotic communities, that is stronger in nutrient-rich environments.

Materials and methods

Preparation of inocula

Consortia of different morphotypes of ALNs and prokaryotes derived from Lake Fargettes (a hyper eutrophic lake located in the French Massif Central; 45°44'24"N; 3°27'39"E; 465 m altitude; surface area 1.2 ha; maximum depth 2.5 m) were used for incubations. These consortia (ALNs length between 40 and 450nm) were selected, enriched and cultivated for a long-term (> 2 years at 4°C in dark condition) through tangential-flow ultrafiltration and differential centrifugation as described in Colombet et al. [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

ALNs contained in a 500 mL consortium aliquot that was filtered on 0.2 µm at low pressure (< 25 kPa) to remove prokaryotes (stericup, Millipore), were pelleted at 15,000 g for 45 min at 14°C and re-suspended in 30 mL of ultra-filtrate medium (UFsee supplementals for the preparation of the medium) leading to an inoculum A (i.e. containing ALNs and VLPs). (Figure 29). Other 500 mL aliquot, namely inoculum B (i.e. containing ALNs, VLPs and prokaryotes), were directly concentrated and resuspended in the same way without prior filtration (Figure 29).

Incubation and growth monitoring

Incubations 0.5 mL of each inoculum was amended with 19.5 mL of 4 different culture medium (with an increasing degree of nutrient enrichment, respectively UF, Minimum Medium (MM), Synura and BG-11 (see composition in supplemental Table S1)) in 50 mL sterile culture flask (Falcon® tissue culture flask) and incubated in triplicate at 6°C or 12°C in the dark.

3 different sampling points were realized (T0 / T1 = 7 months incubation / T2 = 13 months incubation). Each experimental sample (1.5 mL) was then immediately fixed with 2% final

30: Transmission electron micrographs of different morphotypes of aster-like nanoparticles (ALNs).

Scale bars = 100 nm. Crédits photos: J.colombetplateform CYSTEM concentration of formaldehyde. Before each sampling, the volumetric loss due to evaporation during the incubation period was compensated by adding an equivalent volume of medium.

ALNs, prokaryotes and VLPs counts

ALNs detection and quantification were realized by transmission electron microscopy (TEM) using a Jeol JEM 2100-Plus microscope (JEOL, Akishima, Tokyo, Japan) operating at 80 kV and x50,000 magnification as described in Colombet et al. [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. 5 different shapes were detected and counted. The 4 shapes described in Colombet et al. [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] (4-10 arms, 11 arms, 11 budding arms and 20 arms) and a new shape called X-shape (Figure 30).

Counts of ALNs were converted into ALNs per milliliter using a conversion factor deduced from control grids prepared with pre-determined concentrations of bacteria. Volume of the ALN particles was computed by considering the radial arms as cylinders and the central core as a sphere [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Counts of prokaryotes and Virus Like Particles were performed in triplicates by flow cytometry according to Brussaard [256] using a BD FACSAria Fusion SORP (BD Sciences, San Jose, CA) equipped with an air-cooled laser, delivering 50 mW at 488 nm with 502 longpass, and 530/30 bandpass filter set-up.

Diversity of bacterial communities

Nucleic acid extractions and amplifications

At the end of incubations, for each condition with the inoculum containing prokaryotes (i.e. inoculum B), triplicates were pooled, and bacterial microbial communities were collected on a 0.2 μm (Millipore) polycarbonate filter (until saturation, pressure < 25 kPa) and stored at -20°C until DNA extraction. The filters were covered with a lysing buffer (lysozyme 2 mg.mL -1 , SDS 0.5%, Proteinase K 100 μg. mL -1 and RNase A 8.33 μg. mL -1 in TE buffer pH 8) at 37°C for 90 minutes. A CTAB 10% / NaCl 5M solution was added, and the samples were incubated at 65°C for 30 minutes. The nucleic acids were extracted with phenol-chloroform-isoamyl alcohol (25:24:1) ; the aqueous phase containing the nucleic acids was recovered and purified by adding chloroform-isoamyl alcohol (24:1). The nucleic acids were then precipitated with a mixture of glycogen 5mg.mL -1 , sodium acetate 3M and ethanol 100% overnight at -20°C. The DNA pellet was rinsed with ethanol (70%), dried and dissolved in the TE buffer. DNA was then purified using a commercial kit (NucleoSpin® gDNA Clean-up, Macherey-Nagel). The V4-V5 region of the bacterial small subunit rDNA was amplified using the universal bacteria 515F and 928R primers [306] (Table S2). PCR was performed in a total volume of 50μL containing 1x final reaction buffer, 2 mM MgCl2, 0.2mM dNTP, 100 μg.mL -1 BSA, 0.2 μM of each primer, 0.025 U.μL -1 PROMEGA GoTaq HotsStart G2 and 5 μL of DNA. PCR programs is detailed in the supplemental (Table S2).

Amplicon analysis and taxonomic affiliation

Bacterial sequencing data were processed with the PANAM2 pipeline [308]. Briefly, sequence reads were assembled with Vsearch [309], excluding reads < 200pb, with ambiguous bases (N) or having mismatch in the forward/reverse primer. Demultiplexed amplicons were clustered into OTUs using Vsearch at a 95% id threshold. Representative sequence of OTUs were compared against the SILVA SSURef 115 database restricted to sequences with length > 1,200 pb, quality score > 75% and a pintail value > 50.

Data Analysis

The differences in ALNs concentrations depending on the culture media and the inocula were tested with the Kruskal-Wallis test. Concentration variations within the same condition were tested with Dunn test. The evolution of prokaryotic concentrations within the same condition were tested by a Wilcoxon test. The changes in the different ALNs forms in culture media were tested using a Chi 2 test.

Results

Starting conditions of growing media

At the starting incubation time (T0), no significant effect of inoculum (p > 0.05) or medium (p > 0.05) were observed on ALNs concentration (mean ALNs in inoculum A = 2.3 x 10 4 mL -1 , inoculum B = 2.6 x 10 4 mL -1 ). The proportions of the different forms of ALNs were distributed in a similar way whatever the culture medium or the starting inoculum (mean 70% of 4-10 arms, 15% of 11 arms, 10% of 11 budding arms and 5% of 20 arms). Conversely, we observed a statistical difference between prokaryotes concentration (p < 0.01) in inoculum A (mean = 3.6E+03) and inoculum B (mean = 5.7E+04). Inocula A and B were characterized by ratio of ALNs / Prokaryotes / VLPs of 10/2/1 and 10/16/2 respectively.

Figure 32: Monitoring of the concentration of prokaryotes (A) in inoculum B over time, function medium culture.

* indicate significant temporal differences between prokaryotes concentration in a same condition (Wilcoxon test, p < .05).

Dynamic of Aster-Like Nanoparticles, prokaryotes and VLPs-Bacteria Ratio in the different experimental conditions

The temporal dynamic of Aster Like Nanoparticles and prokaryotes corresponding to the different culture inocula and media are presented in Figure 31 and Figure 32 respectively. We recorded statistically significant effects of the inoculum (Kruskal-Wallis, 2 (2) = 15.8, p < .001, n = 96) and a significant effect of the culture medium (Kruskal-Wallis, 2 (2) = 28.9, p < .001, n = 96) on the increase in the concentration of ALNs (Figure 31).

The number of ALNs in culture media supplemented with inoculum A was statistically stable over time (p > 0.05), except in Synura medium at T1 in which we can record a 20x augmentation, from 4.03 x 10 3 ALNs.mL -1 to 8.55 x 10 4 ALNs.mL -1 (p < 0.05) (Figure 31). Conversely, we observed significant increase in the concentration of ALNs over time in all the media with ALNs and prokaryotes (inoculum B) (p < 0.05), except in the minimum medium (Figure 31). The maximum rise of concentration was observed in BG11 medium and inoculum B with a multiplication factor between T1/T0 = 51 from 8.92 x 10 3 ALNs.mL -1 to 4.56 x 10 5 ALNs.mL -1 . Multiplication factor between T0 and T1 in UF and synura media are respectively equal to 29 (from 8.26 x 10 3 ALNs.mL -1 to 2.36 x 10 5 ALNs.mL -1 ) and 23 (from 1.21E x 10 4

ALNs.mL -1 to 2.8 x 10 5 ALNs.mL -1 ALNs.mL -1 ) .

The variation of the prokaryote concentration obviously depended on the starting inoculum, whether filtered or not (Figure 32). The concentration of prokaryotes in inoculum A remained below 9.56 x 10 4 cell.mL -1 (low level of concentration, at detection limits). On the opposite, the prokaryotic concentration in inoculum B increased significantly throughout the incubation period (Figure 32), to reach a maximum of 2.71 x 10 7 cell.mL -1 . In the BG11 (highly nutrient enriched medium) at T2, we noticed a high difference in prokaryote abundances between the inoculum A and B, respectively at 7.29 x 10 3 cells.mL -1 and 2.31 x 10 7 cells.mL -1 .

The VBR, used as a proxy for viral infection, remained below 0.5 under conditions where the development of prokaryotes was observed. This demonstrates the tiny influence of VLPs on the growth of prokaryotes.

Variation of different ALNs morphotypes over time

The dynamics of different ALNs morphotypes in each monitored condition are shown in Figure 33. We report, for the first time, the appearance of an undescribed form of ALNs. This one presents a X-shape with 4 main arms symmetrically distributed from the central core. The mean diameter of this form is 47.6  9 µm for an average volume of 1.12E-04 µm 3 which is inferior in diameter to the smallest form of ALNs (110  18 µm) reported until now (Figure 30).

A significant change in the distribution of forms according to the inoculum was observed at T2=1 ( 2 = 15, df = 4, p < .01) and T3 ( 2 = 11, df = 4, p < .05) (Figure 33). We also observed a significant effect of the culture medium, whatever the inoculum or incubation time ( 2 = 53, df = 12, p < .01) (Figure 33).

We recorded changes in the communities of ALNs at T1. The forms 11 budding and 20 arms disappeared in the media incubated with inoculum A, except for the highly enriched BG11. In this, we noticed the remarkable appearance of new forms X-shape (60% 4-10 arms, 19% 11 arms, 3% of 11 budding and 20 arms, 15% of the X form) (Figure 33). Forms at T1 in the inoculum B was significantly different. 11 budding and 20 arms forms disappeared only in UF medium (87% 4-10 arms, 13% 11 arms) (Figure 33). We recorded a development of new xshape form in the synura (8%) and BG11 (2%) media.

At T2, the 20-arm and X forms were no longer detected in inoculum A (Figure 33). In contrast to T1, we detected the presence of 11 budding arms form in UF, MM, synura and BG11 (respectively 8, 4, 9 and 1%) (Figure 33). With inoculum B at T2, and contrary to T1, the 4 initially described forms of ALNs (4-10 arms, 11 arms, 11 budding arms and 20 arms) were present in all culture media. The X-form remained detectable only in the BG11 medium (14%) (Figure 33).

For inoculum A, a significant diminution of the volume of ALNs was observed between T0 (mean = 1.4 x 10 -4 µm 3 ) and T2 (mean = 0.82 x 10 -4 µm 3 ) (p < 0.05). For inoculum B, although no significant differences (p > 0.05) were observed, the mean volume of ALNs in T0 (mean = 0.87 x 10 -4 µm 3 ) was inferior to that recorded in T2 (mean = 1.1 x 10 -4 µm 3 ). No significant differences were observed between inoculum A and inoculum B at T0 and T2 (p > 0.05). Other class with total abundance < 0.5% = Erysipelotrichi, Coriobacteriia, Acidimicrobiia, Lentisphaeria, Spirochaetes, Chlorobia, Fusobacteriia, Rubrobacteria, Thermomicrobia, Deinococci, Anaerolineae, Acidobacteria, Phycisphaerae, Thermoleophilia, Bacteroidia.

Composition of prokaryotes communities

The final compositions of the bacterial communities of prokaryote enriched-inoculum B, in the different culture media are presented in Figure 34. We observe an increase in the observed richness index with an increase in the richness of the medium (UF index = 62, MM = 73, Synura = 76), except for BG11 (index = 66) (Figure 32-A, 34).

In UF medium (lowest nutrient environment, supp Table 1), bacteria were mainly distributed among the 3 following classes of proteobacteria: Alphaproteobacteria (35%), Betaproteobacteria (15%) and Deltaproteobacteria (35%) (Figure 34). In the other media the Alphaproteobacteria shown a strong decrease in their proportion to the benefit of Actinobacteria (60, 40 and 40% respectively). The increasing enrichment in nutrients (from MM to BG11, with synura as intermediate) benefits to the development of Cytophaga, Planctomycetes and Other classes (mean 7%, 8% and 5% respectively) at the expense of Proteobacteria.

Discussion and conclusion

In this study, we monitored the temporal changes in ALNs abundances under prokaryotic controlled in-vitro conditions. We used inocula from a culture originating from Fargettes Lake, in which the diversity and dynamic of ALNs and of their environment were previously documented [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197,324]. The conditions of preparation and incubation of the culture and inocula (see materials and methods) allowed a selection/enrichment of the different morphotypes of ALNs (Figure 33) simultaneously with the depletion of viruses (VBR = 2.07 and 0.08 for inoculum A and B respectively at t0) and the elimination of the accompanying eukaryotic microbial communities. This strategy allows a direct linkage of ALNs and accompanying prokaryotes. A VBR (proxy of viral infection) lower than 1 during the whole incubation period in prokaryotes enriched incubations confirms that the only dynamic entities in our incubations are ALNs and prokaryotes.

The strong multiplication of ALNs recorded in the conditions enriched in prokaryotes (inoculum B: factors of the multiplication of ALNs of 29, 23 and 41 respectively in UF, Synura and nutrient enriched BG11 media) compared to prokaryotes depleted conditions (inoculum A: no significant factors of the multiplication of ALNs in UF and BG11 media, factor of 20 in Synura) indicates a close interaction between them. These experimental observations confirm those previously suggested in environmental surveys [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197,324] and reinforces the presumption that ALNs are a new player in aquatic ecosystems. This has already been demonstrated for other femto-planktonic communities, such as viruses or CPRs and DPANNs (discussed in Colombet et al. [16]).

One of the peculiarities of ALNs is their pleomorphism. Described in Colombet et al. [27], 4 majority forms were previously identified, based on the number of arms and the presence of a bud. Experiments led in this study revealed the apparition of a new form during incubation period. This X shape is smaller in terms of size (47.58  9 µm) and volume (mean 1.12 x10 -4 µm 3 ) than those previously described. Add to the significant modification of the relative abundance of the different forms according to the culture medium and initial inoculum, these observations support the hypothesis of an interconversion of form during a putative development cycle. Occurrence of new X shape form, 20 arms and 11 budding arms in the richest culture medium or when we have a high concentration of prokaryotes also postulates for the intervention of prokaryotes in the realization of this cycle.

To understand the ALNs-prokaryotes interaction, we analyzed the bacterial composition of the media at the end of incubation. We have highlighted an overall increase in the observed richness with the increase in the availability of nutrients in the culture media. Like previous study, we can't infer a direct relationship between a specific phylum of prokaryotes and ALNs.

On the opposite, ALNs seems to have a broad and non-specific spectrum of prokaryotic partners. However, an interaction with prokaryotes could have a direct impact on matter and energy fluxes, particularly in the degradation of organic matter.

The data acquired here confirm the hypothesis of an interaction between ALNs and prokaryotic communities. The exact nature of this interaction (neutralism, parasitism, mutualism...) remains to be determined. Further studies on the impact of ALNs on prokaryotic communities in natural environments would allow us to:

(i)
Better understand the forcing factors governing their distribution and therefore to better understand their presence in ecosystems.

(ii) Formulate hypotheses as to their contribution to the flow of materials and energies of food webs.

(iii) Establish hypotheses about their exact nature

ALNs are therefore new players to be considered in the functioning of aquatic ecosystems, which should henceforth be taken into account in studies on femtoplankton and its impact in aquatic environments.

Supplemental materials

Medium

• Mix 1 mL of 1, 2, 3, 4, 5, 6, / 0.5 mL of 7 / 10 mL of 9 filtered on 0.2 μm filter • Add distilled water • Autoclaved • Add 0.5 mL 8 filtered on 0.2 μm filter

Commercial medium

Table S2: Primers used for the amplification and their PCR programs.

Bacteria Archae Fungi

Forward primer

515f- GTGYCAGCMGCCGCGGTA 519f-CAGCMGCCGCGGTAA its7f- GTGARTCATCGAATCTTTG Reverse Primer 928r- CCCCGYCAATTCMTTTRAGT 1017r- GGCCATGCACCWCCTCTC its4r- TCCTCCGCTTATTGATATGC Program 95°c 3mn ------x32------ 98°c 20s 65°c 40s 72°c 30s ----------------- 72°c. 10mn 95°c 3mn ------x32------ 98°c 20s 68°c 30s 72°c 30s ----------------- 72°c. 5mn 95°c 3mn ------x32------ 98°c 20s 57°c 30s 72°c 30s ----------------- 72°c. 5mn

Abstract

Microbial communities in lakes can profoundly impact biogeochemical processes through their individual activities and collective interactions. However, the complexity of these communities poses challenges, particularly for studying rare organisms such as Candidate Phyla Radiation bacteria (CPR) and enigmatic entities such as aster-like nanoparticles (ALNs). Here, a reactor was inoculated with water from Lake Fargettes, France, and maintained under dark conditions at 4°C for 31 months and enriched for ALNs, diverse Planctomycetes, and CPR bacteria. We reconstructed draft genomes and predicted metabolic traits for 12 diverse Planctomycetes and 9 CPR bacteria, some of which are likely representatives of undescribed families or genera.

One CPR genome representing the little-studied lineage "Candidatus Peribacter" was curated to completion (1.239 Mbp) and unexpectedly encodes the full gluconeogenesis pathway.

Metatranscriptomic data indicate that some planctomycetes and CPR bacteria were active under the culture conditions, accounting for ∼30% and ∼1% of RNA reads mapping to the genome set, respectively. We also reconstructed genomes and obtained transmission electron microscope images for numerous viruses, including one with a >300-kbp genome and several predicted to infect Planctomycetes. Together, our analyses suggest that freshwater Planctomycetes are central players in a subsystem that includes ALNs, symbiotic CPR bacteria, and viruses.

Note

Laboratory incubations of natural microbial communities can aid in the study of member organisms and their networks of interaction. This is particularly important for understudied lineages for which key elements of basic biology are still emerging. Using genomics and microscopy, we found that members of the bacterial lineage Planctomycetes may be central players in a subset of a freshwater lake microbiome that includes other bacteria, archaea, viruses, and mysterious entities, called aster-like nanoparticles (ALNs), whose origin is unknown. Our results help constrain the possible origins of ALNs and provide insight into possible interactions within a complex lake ecosystem.

Freshwater lakes host diverse microbial communities that likely control ecosystem biogeochemistry [325,326]. Here, we established a laboratory culture based on an inoculum from Lake Fargettes, France, a site chosen as part of a parallel study of enigmatic aster-like nanoparticles (ALNs) [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197]. ALNs are enigmatic, organic, femtoplankton entities that exhibit bloom-like behavior in various freshwater and coastal environments [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197]. In this experiment, microscopy showed that the proportion of ALNs increased substantially during incubation, from 26% to 36% of imaged objects (see Table S1). To seek clues to the origins of ALNs and the organisms that they might associate with, and to better understand the lake ecosystem overall, we studied the culture using a combination of metagenomics, metatranscriptomics, and microscopy. In doing so, we recovered draft genomes for abundant and transcriptionally active Planctomycetes as well as CPR bacteria, phages, and eukaryotic viruses. Overall, we provide clues to associations and potential interactions among microbial groups in a lake ecosystem. Concentrate from the 0.2-μm to 25-μm size fraction of the highly eutrophic Lake Fargettes, France, was incubated at 4°C in the dark with filtered and sterilized lake water (<20 kDa). The incubation was performed under dark conditions to favor heterotrophic organisms associated with ALNs instead of phototrophic eukaryotes. After 31 months, DNA and RNA were extracted for metagenomic and transcriptomic analyses. DNA reads were assembled and the scaffolds profiled to identify ribosomal protein S3 (rpS3). Profiling using the predicted rpS3 protein sequences revealed that the enrichment was bacterially dominated, although several members of the Thaumarchaeota were present (Figure 35-A; see also Table S2). The most abundant organisms overall were Planctomycetes (∼27% of overall rpS3 coverage), including the most abundant singular organism (Figure 35 and Table S2). CPR bacteria were 5 of the top 25 most abundant organism groups (∼9% overall rpS3 coverage; Figure 35 and Table S2). Compared to baseline abundances in Lake Fargettes, these results indicated enrichment of these groups, particularly CPR bacteria, which were barely detectable in the lake (<1% relative abundance; Figure 35-B and Table S3).

Where possible, scaffolds were assigned to genome bins that ranged in quality from draft to nearly complete. The 48 genomes captured most of the phylogenetic diversity (76% of the most abundant rpS3 genes; Figure 35-A and Tables S2 andS4); 12 genomes represent phylogenetically diverse Planctomycetes, including several from the Planctomycetes and Phycisphaeraeclasses (see Fig. S1 and Table S4). Metabolic reconstructions suggested that the Planctomycetes are primarily heterotrophs with the potential to oxidize nitrite or reduce nitrate in three cases (Figure 35-E ). We also recovered 9 genomes of CPR bacteria, 8 of which were classified as "Candidatus Parcubacteria" (Figure S1). The "Candidatus Parcubacteria" genomes encoded minimal metabolic capacities, consistent with symbiotic lifestyles [23]. However, several had a phylogenetically distinct nirK gene that may play a role in denitrification or energy conservation [327] (Figure 35-E). Read mapping from a metatranscriptome collected contemporaneously with the metagenome suggested that some Planctomycetes and, to a lesser extent, CPR bacteria were actively transcribing under the culture conditions, with Planctomycetes and CPR accounting for about 27% and 1%, respectively, of RNA reads stringently mapping to the nonredundant set of genomes (Figure 35-D and Table S4). However, only a small proportion of total RNA reads (201,809 reads, or ∼0.2% of the total) mapped stringently to the genome set and passed filtering for non-mRNAs. The ninth draft CPR genome was for a member of the undersampled CPR lineage "Candidatus Peribacteria." We manually curated the original bin of 6 fragments into a single fragment that was circularized by a small, unbinned contig, and all scaffolding errors and local misassemblies were fixed (see Figure S2). The newly reported, fully curated 1,239,242-bp genome shares ∼89% similarity in its 16S rRNA gene and is largely syntenous with a closely related "Candidatus Peribacteria" genome from Rifle, Colorado [328], supporting the accuracy of both assemblies (see Figure S3). Unlike the Rifle genomes, this peribacter likely cannot synthesize purines de novo. Other notable differences include the presence of vacuolar-type H + /Na + -transporting ATPase complex and the lack of genes for biosynthesis of mevalonate.

Based on biosynthetic deficiencies, we conclude that this bacterium probably relies on other organisms for many building block but to a lesser extent than the "Candidatus Parcubacteria."

Supporting this idea, we observed that the peribacter genome encodes all gluconeogenesis enzymes, including fructose-1,6-bisphosphatase I, which was not found in the "Candidatus Parcubacteria" genomes (Figure 35-E)

We reconstructed 12 phage sequences and 5 phage-like sequences, including 3 circularized genomes exceeding 100 kbp and 2 incomplete phage/phage-like fragments of >300 kbp (see and Bacteroidetes (Figure 36 and Table S5).

We also reconstructed large fragments of 17 eukaryotic viruses. Based on the phylogenetic placement of the major capsid protein and homologs of the poxvirus late transcription factor VLTF3, some viruses belonged to Iridoviridae (Betairidoviridae), extended Mimiviridae, Phycodnaviridae, and Pitho-like viruses (see Figure S4 and S5 and Table S5). Other viruses could only be classified at the superclade level, including those within a potentially novel Phycodnaviridae, Asfarviridae, Megavirales (PAM) clade, or did not contain either marker protein (see Figure S4 andS5). Interestingly, we detected very little transcription of genes from phage or eukaryotic viruses (mean coverage, ≪1×), suggesting that they were not actively replicating in the incubated community (see Table S5). The lack of eukaryotes in the enrichment suggests that some of these particles have derived from the inoculum and persisted for over 2 years.

Imaging of incubation community

We imaged a diversity of cellular, cellular-like, and noncellular particles, as well as many ALNs, using transmission electron microscopy (TEM) (Figure 36 and Figure S6). Based on the presence of the extracellular holdfast [330,331], we infer that the cell imaged in Figure 36 is likely a member of the Planctomycetes, with at least two attached distinct types of viruslike particles (VLPs). This finding is consistent with the high abundance of Planctomycetes in the enrichment as well as multiple phages predicted to infect them (∼18 to 100× coverage). We also imaged numerous tailed phages (see Fig. S6), including one with a 145-nm-diameter capsid and 214-nm tail (Figure 36, ph). This large capsid size is consistent with those of jumbo phages with genomes in the 300-kbp range [329], two of which were reconstructed here (see Table S5). Despite these observations, TEM image counts suggested that the overall proportion of tailed phages decreased from 26% to less than 1% of imaged objects over the course of the incubation (see Table S1).

Discussion and conclusion

Planctomycetes are globally distributed across freshwater ecosystems, where they are thought to play important roles in nitrogen and carbon cycling [332,333]. Our analyses expand genomic sampling for these organisms, and coenrichment suggests that they interact with CPR bacteria.

Although we cannot establish a direct association between Planctomycetes and CPR bacteria from the current data, reported lifestyles for other CPR suggest that they are host cell-attached, at least at sometimes [334]. Furthermore, the enrichment contains a similar level of diversity of both Planctomycetes and CPR, raising the possibility of species-specific associations (see

Figure S1

). As episymbionts, CPR would almost certainly influence the physiology of Planctomycetes cells, either via mutualistic interactions or parasitism, and, thus, the biogeochemical cycles that Planctomycetes mediate. The approach used in the current study could guide future coisolation of CPR bacteria of the "Candidatus Parcubacteria" and "Candidatus Peribacteria" lineages to test this hypothesis.

Like CPR bacteria, phages clearly impact their hosts and, thus, ecosystem structure and performance. It is intriguing that phages were maintained over the long incubation period, as they are often lost from laboratory cultures [335]. A subset of the phages clearly infect Planctomycetes, the diversity of which may have enabled their sustained replication One motivation of our study was to seek clues to the origin of ALNs, and it is also intriguing to find them coenriched with Planctomycetes and CPR bacteria. Their defined morphologies suggest that they develop under genetic control; however, the genetic system responsible for producing ALNs remains unknown. We found no evidence for nucleic acid sequences from completely unknown organisms or mobile genetic elements or were not able to extract them with the methods used here. Thus, one possible interpretation is that ALNs originate from cooccurring bacteria and that Planctomycetes and CPR should be among candidates for further study.

Materials and methods can be found in the supplemental material. 465 m altitude). Lake water was collected on March 15, 2017 when the highest density of ALNs was recorded in 2017 (9.0 ± 0.5 × 10 7 ALNs•mL -1 ). Information about this sample is provided in Colombet et al. 2019 [1]. Within two hours after sampling, 100 L of raw lake water was filtered through a 25-μm-pore-size nylon mesh. Microbial communities were enriched by tangential-flow ultrafiltration using a Kross-Flow system (Spectrum, Breda, The Netherlands) equipped with a 0.2-μm cut-off cartridge. Aliquots (600 mL) of this concentrated 0.2 μm-25μm fraction were sequentially centrifuged at 8,000 g, 10,000 g (pellets discarded) then 12,000 g for 20 minutes each time at 14°C. Microbial communities contained in the final supernatant were cultivated for an initial period of 6 months at 4°C in the dark (to favor the development of prokaryotic communities associated with ALNs, instead of phototrophic eukaryotic communities) . The physico-chemical parameters of the starting sample are listed in Table S6.

After 6 months, the selected microbial community was enriched by centrifugation at 6000 g for 20 minutes at 14°C and the pellet (in liquid phase) incubated 25 more months at 4°C in the dark. At the end of the incubation, the medium was sonicated using Elmasonic S30 (Elma, Germany) and microbial communities were pelleted by centrifugation at 6000 g for 20 minutes at 14°C. The pellet suspended in distilled deionized water was used for nucleic acid extraction and amplification.

DNA and RNA extractions were performed using the RNA x DNA from soil kit (740143, Macherey-Nagel, Germany). The RNA sample was treated with Turbo DNA-free Kit (Invitrogen, Massachusetts, USA). The concentration of the samples was checked using a Qubit fluorometer (Invitrogen, Massachusetts, USA).

TEM imaging of enrichment communities

Microbial communities were imaged at T0 and T31 to visualize their evolution, using a JEOL JEM 2100-Plus microscope (JEOL, Akishima, Tokyo, Japan) operating at 80 kV and 40,000x magnification. For each sample, 10 images were randomly captured in order to have a significant representation of microbial communities. We then defined the percentage of different observed phenotypes as a proportion of the total observed communities (Table S1).

Monthly microbial community profiling at Lake Fargettes

Samples were collected every month for 1 year (10/2018 to 09/2019) from the depth interval of 0-40 cm of lake Fargettes. For each sample, microbial communities were collected on a 0.2 µm (Millipore) polycarbonate filter (until saturation, pressure < 25 kPa) and stored at -20°C until DNA extraction. The filters were covered with a lysing buffer (lysozyme 2 mg.mL-1 SDS 0.5%, Proteinase K 100 µg.mL-1 and RNase A 8.33 µg.mL-1 in TE buffer pH 8 at 37°C for 90 minutes. A CTAB 10% / NaCl 5M solution was added, and the samples were incubated at 65°C for 30 minutes. The nucleic acids were extracted with phenol-chloroform-isoamyl alcohol (25:24:1) the aqueous phase containing the nucleic acids was recovered and purified by adding chloroform-isoamyl alcohol (24:1). The nucleic acids were then precipitated with a mixture of glycogen 5mg/mL-1, sodium acetate 3M and ethanol 100% overnight at -20°C. The DNA pellet was rinsed with ethanol (70%), dried and dissolved in TE buffer. The DNA was purified with NucleoSpin® gDNA Clean-up (Macherey-Nagel).

Table S5. Particle composition in the starting and final incubation samples as determined by cell counts.

Table S6. Physico-chemical parameters associated with the starting sample.

Figure S1. Phylogenetic placement of Planctomycetes (left panel) and CPR bacteria (right panel) genomes reconstructed in this study (indicated by red dots at branch tips).

Scale bar represents the average number of substitutions per site. Black dots at interior nodes indicate ultrafast bootstrap support >=95%. The amplification of the V4-V5 region of the bacterial small subunit rDNA was performed using the universal bacteria 515F (GTGYCAGCMGCCGCGGTA) and 928R (CCCCGCYAATTCMTTTRAGT) primers modified with barcodes. PCR was performed in a total volume of 50 µL containing 1x final green reaction buffer, 2 mM final MgCl2, 0.2mM final dNTP, 100 µg.mL -1 final BSA,0.2 µM final of primers, 0.025 U.µL -1 final PROMEGA GoTaq HotsStart G2 and 5 µL of sample DNA.

To process the bacterial sequencing data (Illumina Miseq©, 2*250 bp), we used the FROGS pipeline [2]. After the clean-up procedure, sequences were assembled and clustered into OTUs with a similarity threshold of 95%. The representative sequences of each OTU were affiliated by similarity using the SILVA_132_16s database.

Metagenomic/metatranscriptomic sequencing, binning, and marker gene analysis

Library preparation and sequencing of extracted DNA and RNA was performed at the Vincent J. Coates Genomics Sequencing Laboratory and Functional Genomics Laboratory at U.C. Berkeley. Extracted RNA was treated with the QiaSeq FastSelect kit to deplete rRNA. Samples were sequenced on a NovaSeq 6000 with 150 bp, paired-end reads. DNA and RNA were sequenced to a depth of ~10 Gbp and 25 million read pairs, respectively. Quality filtering and assembly of DNA reads, as well as binning of assembled scaffolds and genome annotation followed the workflow outlined in [3]. Briefly, metagenomic reads were trimmed using Sickle [START_REF] Joshi | Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files[END_REF] and subsequently assembled using MEGAHIT (v. 1.2.9) [5]. Gene calls were made with Prodigal ('meta' mode) [6] and genes were annotated with USEARCH [7] against several protein databases. Finally, scaffolds were binned both manually, using GC content, coverage, and phylogenetic profile, as well as in an automated fashion using MetaBAT2 [8]. The highest quality bins were chosen from the set of manual and automated bins using DASTool [9].

Genomes were classified at the phylum or class level based on the majority taxonomic affiliation of member contigs, and supplemented with BLAST searches of ribosomal proteins where necessary. Additionally, genome classification according to the GTDB scheme was assigned by running GTDB-tk with default parameters [START_REF] Chaumeil | GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF].

For the marker gene analysis (Fig. 1ac), we computed the mean coverage of scaffolds encoding a ribosomal protein S3 (rpS3) gene using bowtie2. Phylum-level taxonomic affiliation of these scaffolds was manually curated based on consensus gene-level taxonomy, binning information, and BLAST searches of protein sequence, where necessary.

Quality filtering and genome curation for bacteria and archaea

Genomic bins were profiled for single copy genes using CheckM. For CPR bacteria, a custom workflow was used with a set of 43 marker genes sensitive to lineage-specific losses of ribosomal proteins in this group. We filtered all bins to those ≥ 70% completeness and ≤10% contamination and removed redundancy in the set at the species level using dRep (95% ANI) [11]. Retained genomic bins were manually 'polished' by removing contigs that were outliers in terms of GC content and coverage. Contigs with aberrant or ambiguous consensus taxonomy were manually expected if ≥ 5 kbp or automatically removed if <5 kbp. For the Peribacteria genome (LakeFargettes_0920_ALND_PER-ii_52_24), additional manual genome curation was performed. This involved fixing local scaffolding errors and extending the six original contigs using unplaced paired reads. The extended contigs were then joined based on end overlaps and paired read support. This resulted in two contigs, the larger of which was circularized and the other contained the 16S rRNA gene. Based on identification of a sequence within the larger contig that was also present at the end of the smaller contig, the larger contig was broken and joined to the smaller contig. This produced a single linear fragment. We used BLAST against the metagenome of the sample to identify a 4 kbp fragment that perfectly aligned to the ends of the linear fragment, circularizing the genome. The circularization overlap was trimmed and paired read support was verified by visualization throughout the entire final genome. Finally, the start position was adjusted based on the cumulative GC skew (Fig. S2). Genes/proteins were then re-predicted for the curated genome using Prodigal (single) [6].

We selected one of a set of near-identical complete Peribacteria genomes (SAMN03842449) from a previous publication [12] for comparison to the newly curated genome. Full genomes and 16S rRNA sequences were aligned in Geneious (Mauve plugin and MAFFT aligner, respectively).

Phylogenomic and gene content analyses for CPR bacteria and Planctomycetes

For analyses of gene content, we focused on a subset of 21 genomes from the CPR bacteria and Planctomycetes. Gene/protein predictions were re-computed for this subset using Prodigal (single mode). Predicted protein sequences were annotated using kofamscan and resulting HMM hits were preliminarily filtered to those with e < 1x10 -6 for use in downstream phylogenetic and metabolic analyses.

First, proteins annotated as rpS3 (K02982) were extracted and combined with reference sequences drawn either from NCBI (Planctomycetes) or a previous publication [13] on CPR phylogeny as well as a balanced sampling of other bacterial phyla as an outgroup. Each sequence set was aligned using mafft (auto) [14] and the resulting alignment was trimmed using trimal (gt 0.1) [15]. Maximum-likelihood trees were inferred using iqtree (-m TEST -safe -st AA -bb 1500 -nt AUTO -ntmax 20) [16] and subsequently visualized/annotated using iTOL [17].

For analyses of metabolism, we stringently filtered the kofamscan results, requiring that protein hits attain a score equal to or greater than the model specific thresholds for each KO. Results were then passed to KEGGDecoder [18] for visualization. For CRISPR-Cas analyses, we employed a custom script that first identifies repeat regions on scaffolds using PILER-CR [19] with default parameters, then detects Cas protein using the TIGRFAM HMM database [20] using hmmsearch [21] within 10 kbp (both upstream and downstream) of each identified repeat region. If at least one Cas protein was detected for a given repeat region, the spacer sequences from the adjacent CRISPR locus and also the paired reads and unplaced paired reads were extracted to identify spacer targets. Target identification was performed by blastn-short with an

Figure S5. Maximum likelihood (ML) single-protein tree of VLTF3-like protein from putative eukaryotic virus genomes.

The tree is rooted between the PAM and the MAPI putative superclades (see: doi.org/10.1073/pnas.1912006116).

e-value threshold of 1x10 -3 . Hits were further filtered to those in which the spacer and targeted sequence were aligned over ≥90% of the spacer length and with no more than 2 mismatches.

Viral genome identification and analysis

Viral genomes were identified through taxonomic profiling and identification of key viral structural proteins. While most recovered viral genomes were single-contig, in some cases multiple contigs of putative viral origin were binned together on the basis of GC content, coverage, and scaffold overlap. Viral genomes were tentatively classified as bacteriophage or eukaryotic viruses based on taxonomic profiling. Completeness and quality information for single-contig viruses was estimated using CheckV [START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF].

To establish phylogenetic affiliation of bacteriophages, we gathered curated sets of reference sequences for viral terminase and major capsid protein (MCP) from RefSeq. Reference sets were filtered to those sequences with sequence lengths 1±0.5 times the median and subsequently de-replicated at 95% identity using usearch (-cluster_fast, -id 0.95) [7]. Proteins for the newly identified phage genomes were predicted using Prodigal (meta mode). Terminase and MCP sequences were identified using BLAST (-evalue 1e-20) against a database built from the reference set. Sequences were concatenated with those of the reference set and aligned using MAFFT (--reorder --auto). Alignments were trimmed using trimal (-gt 0.2) and maximum likelihood trees were inferred using IQtree (-m TEST -st AA, version 1.6.12). Trees were decorated using taxonomic information for RefSeq sequences and putative lineages were assigned to newly identified phage genomes based on tree placement.

Host prediction for phages was performed using a combination of CRISPR-Cas targeting (described above) and taxonomic profiling. Briefly, for phylogenetic profiling, phage proteins were compared against UniRef100 using a custom DIAMOND database (diamond blastp) [23]. Hits were filtered to those with 70% or greater coverage of the query sequence and an e-value less than or equal to 1x10 -10 . We retrieved taxonomic affiliation for above-threshold hits and computed the percentage of genes on each phage with highest similarity to various bacterial lineages. If the bacterial lineage with the most hits among phage genes reached a percentage ≥ 3x that of the next highest lineage, it was assigned as the putative phage host. This method was previously shown to be consistent with host prediction via CRISPR-Cas targeting [24].

To infer the taxonomy of the 17 putative viruses of eukaryotes, all proteins were profiled against the Pfam database. 17 major capsid proteins (PF16903|PF04451) from 11 eukaryotic virus bins and 8 VLTF3-like proteins (PF04947) from 8 bins served as markers. If there were multiple major capsid proteins per bin, the protein with the highest PFAM score was selected. The marker proteins were aligned with a reference dataset of capsid or VLTF3-like proteins from Nucleo-Cytoplasmic Large DNA Viruses [25] and 48 additional capsid proteins retrieved from NCBI (Extended Data File 1-2). The sequences were aligned, trimmed and the phylogenetic tree was constructed as described above. Finally, viruses were taxonomically classified based on phylogenetic placement.

Les ALNs : un nouvel acteur du femtoplancton

Dans un contexte de changement global, et notamment du réchauffement des eaux de surfaces, il est plus que jamais nécessaire de comprendre le fonctionnement des réseaux trophiques aquatiques dans leur globalité, afin de mieux anticiper l'impact de ces changements [1]. Cela passe par la compréhension des flux biogéochimiques et de leurs équilibres, étroitement associés à l'activité d'entités biologiques de tailles variées. Les progrès scientifiques de ces dernières décennies ont permis la mise en évidence d'une importante diversité de microorganismes et de leur rôles fonctionnels dans les flux de matière et d'énergie, avec notamment l'intégration du concept de boucle microbienne dans les réseaux trophiques [6,7].

Si les fractions de tailles supérieures (macro et microplancton) sont aujourd'hui largement étudiées, les fractions les plus petites (nano et femtoplancton) ont longtemps été délaissées, dû notamment aux limitations technologiques. La mise en évidence d'une importante diversité dans ces dernières fractions, grâce notamment aux progrès technologiques, remet en question la compréhension des flux de matière et d'énergie qui passent par les écosystèmes aquatiques [18,[24][25][START_REF] Weitz | Quantitative Viral Ecology: Dynamics of Viruses and Their Microbial Hosts[END_REF].

La compréhension de l'évolution des écosystèmes aquatiques passe nécessairement par une meilleure appréhension du fonctionnement des entités femtoplanctoniques, qui sont à la base de l'organisation trophique de ces écosystèmes. Comme discuté dans Colombet et al. [16], les organismes femtoplanctoniques peuvent être classés le long d'un gradient de complexification, allant d'entités minéral-organiques jusqu'aux entités entièrement organiques. Les entités femtoplanctoniques sont aux frontières de la définition actuelle du vivant. L'étude de ce compartiment, au-delà de son rôle dans les écosystèmes aquatiques, pourrait permettre de comprendre les processus qui ont mené à la compartimentalisation cellulaire et ceux qui ont mené à l'apparition de métabolismes cellulaires.

Les écosystèmes aquatiques sont des réservoirs de nouvelles entités nanométriques, sources de nouvelles connaissances écologiques. L'étude du femtoplancton pourrait aussi être un point clé dans la compréhension des limites du vivant et de l'apparition de la vie. La découverte récente de nouvelles femtoparticules, et notamment les ALNs [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] dans les écosystèmes aquatiques soulève la question de leur importance dans ces écosystèmes. Historiquement considérée à travers la seule activité virale, l'importance écologique de toutes les entités nanométriques, y compris les ALNs nouvellement découverts, est sans doute plus grande qu'on ne l'avait pensée auparavant. La diversité méconnue et l'abondance de toutes ces entités ont nécessairement un impact sur la circulation des éléments conservés qui sont à la base des cycles biogéochimiques.

La plupart des effets potentiels du femtoplancton reste donc à explorer, en tenant compte de la diversité des différentes entités qui la composent, mais aussi de leur capacité à interagir avec d'autres entités à l'échelle de l'écosystème.

Cette thèse s'est effectuée dans le cadre de cette découverte, en prenant en compte les apects écologiques, notamment l'importance quantitative, la dynamique et le rôle fonctionnel des ALNs dans les écosystèmes.

La découverte des ALNs soulève de nombreuses questions sur leur nature et leurs potentiels rôles dans l'environnement. Dans un premier temps, il était important de caractériser ces entités, afin de définir leur nature. Les travaux préliminaires à cette thèse ont permis une caractérisation partielle de ces entités. Colombet et collaborateurs [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] ont montré que les ALNs par leur morphologie, leur composition chimique (i.e. C, O, Ca, N et K), leur structure amorphe et leur susceptibilté à des traitements physico-chimiques étaient de nouvelles particules biocompatibles.

La nature des ALNs, couplée à l'observation de contacts étroits avec des cellules (Figure 22) [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] suggère une interaction forte avec d'autres organismes dans les écosystèmes [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. Les études portant sur l'interaction entre certaines entités femtoplanctoniques comme les CPR et DPANN ou les virus et leurs hôtes ont démontré un rôle important de ces interactions dans la structure et le fonctionnement des écosystèmes [START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF]23,219,223]. Au même titre que ces entités, les ALNs pourraient donc jouer un rôle dans les écosystèmes. Leur capacité à se maintenir in-vitro en absence d'hôtes, réduite en comparaison des valeurs retrouvées in-situ [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF] laisse suggérer différents rôles pour ces différentes formes. Dans tous les cas, négliger l'existence des ALNs et leurs impacts potentiels dans l'environnement, conduira nécessairement à une compréhension partielle des flux de matière et d'énergie dans les écosystèmes.

La découverte des ALNs souligne donc la nécessité d'étudier non seulement les ALNs mais aussi plus en détail l'ensemble du compartiment femtoplanctonique.

Écologie des ALNs et importance putative

Comprendre l'importance quantitative et fonctionnelle d'entités aquatiques telles que les ALNs passe nécessairement par une appréhension de leur écologie. Cela sous-entend d'étudier leur habitat, leur distribution ainsi que leur trophodynamique dans les milieux naturels, afin de comprendre les facteurs de forçage qui régissent leur importance écologique.

L'étude géographique menée dans Fuster et al. [197] à l'échelle du bassin-versant de la Loire a permis de mettre en évidence la présence des ALNs dans un large spectre d'habitats aux caractéristiques hydrologiques différentes (i.e. lacs, rivières, vasières, marais, eaux côtières, canaux). Ces résultats ont permis de prouver l'ubiquité des ALNs, capable de se développer dans des environnements physico-chimiques variés. L'étude menée dans Fuster et al. [324] complète les résultats ponctuels obtenus précédemment [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]197], puisqu'elle dresse la femtoplanctoniques [19,110,139,243], font des ALNs des acteurs pouvant avoir un impact sur les autres communautés microbiennes. Nos résultats ont donc démontré l'importance des ALNs en tant que nouveaux acteurs dans les écosystèmes aquatiques, qu'il faudra désormais prendre en compte dans l'étude de ces écosystèmes.

Les études en milieu naturel nous ont permis de mettre en avant les facteurs potentiels de forçage pouvant expliquer la distribution des ALNs, notamment un lien étroit avec les communautés de procaryotes. Les études en conditions controlées ont permis de confirmer notamment cyanobactériens [336]. La modélisation pourrait donc être un outil puissant pour prédire les variations de la quantité d'ALNs dans l'environnement.

Des résultats annexes de ma thèse, sur le suivi sur le long-terme des ALNs (suivi in-situ depuis maintenant plus de 5 ans) semblent indiquer que la concentration en procaryotes pourrait être utilisée comme un éventuel proxy (R 2 =0,36, p < 0.01) (Figure 37), même si ces derniers ne sont pas la seule variable à prendre en compte.

Les résultats du chapitre 3 quant à eux indiquent que la disponibilité en nutriments dans le milieu pourrait aussi jouer un rôle important. Le développement d'un modèle prédictif nécessite donc de suivre la variation de nombreux paramètres in-situ, sur plusieurs années, pour pouvoir obtenir un modèle robuste et fiable.

Etude de l'écologie fonctionnelle des ALNs

Les différentes expériences réalisées durant la thèse ont également permis de mettre en évidence des caractéristiques écologiques importantes des ALNs. La prochaine étape sera de déterminer la nature de leurs impacts sur les écosystèmes, et notamment sur les communautés procaryotes.

La microcalorimétrie, une technologie disponible au laboratoire, pourrait être envisagée pour :

Résumé

Face au changement global et notamment à l'augmentation de la température des eaux de surface [START_REF] Whitehead Pg | A review of the potential impacts of climate change on surface water quality[END_REF], il est devenu indispensable de comprendre et d'anticiper l'évolution des écosystèmes aquatiques. Le bon fonctionnement et l'évolution de ces écosystèmes ont toujours été intimement liés au fonctionnement du compartiment biologique et notamment microbien [START_REF] Lalli | Biological Oceanography: An Introduction[END_REF]. Les avancées technologiques des dernières décennies ont permis de mettre en évidence un véritable réseau d'interactions microbiennes [START_REF] Pomeroy | The Microbial Loop[END_REF], intégrant une diversité jusqu'alors insoupçonnée d'entités submicrométriques pouvant avoir une importance fonctionnelle majeure [START_REF] Mostajir | LES RÉSEAUX TROPHIQUES MICROBIENS DES MILIEUX AQUATIQUES ET TERRESTRES. Presses Universitaires de Pau et des Pays de l'Adour 10. Sime-Ngando T[END_REF].

Pour comprendre le fonctionnement global des écosystèmes aquatiques, il semble donc nécessaire de concentrer des efforts de recherche sur les plus petites fractions de taille, notamment sur les particules nanoplanctoniques appartenant au femtoplancton jusqu'alors sous-considérées (< 0.2 µm ou 200 nm).

Dans ce contexte, la découverte d'une nouvelle catégorie de particules organiques appartenant au femtoplancton, nommées « Aster Like Nanoparticles » (ALNs) (Colombet et al., 2019), soulève de nombreuses questions et notamment celle de leur importance fonctionnelle au sein des écosystèmes aquatiques. L'objectif principal de cette thèse est donc d'approfondir nos connaissances sur les fonctionnalités des ALNs, en se focalisant particulièrement sur l'étude écologique de ces entités afin de pouvoir, à terme, expliquer leur présence et appréhender leurs interactions avec leur environnement physico-chimique et microbien. Pour cela, différentes échelles d'intégration seront considérées : de l'échelle écosystémique à l'échelle expérimentale, en conditions contrôlées.

Nos résultats ont, dans un premier temps, permis de mettre en évidence la présence des ALNs dans un large spectre d'habitats aux caractéristiques différentes [START_REF] Fuster | Trophic conditions influence widespread distribution of Aster-Like nanoparticles within aquatic environments[END_REF]. Ces résultats ont permis de prouver l'ubiquité des ALNs, capables de se développer dans des environnements physico-chimiques variés. Une étude complémentaire a permis de dresser la dynamique temporelle des ALNs dans différents écosystèmes aquatiques, suggérant que les ALNs sont un acteur majeur à intégrer dans les modèles de successions écologiques [START_REF] Fuster | Occurrence and Seasonal Dynamics of ALNs in Freshwater Lakes Are Influenced by Their Biological Environment[END_REF]. Cette étude, menée dans trois lacs du Puy-de-Dôme, a permis de démontrer l'importance des paramètres biologiques dans la distribution des ALNs, et notamment l'importance potentielle des procaryotes. Finalement, des études en microcosmes ont permis de confirmer l'importance des procaryotes, avec des résultats montrant un développement jusqu'à 20 fois plus important des ALNs en présence d'une forte concentration de procaryotes. De façon générale, nos résultats ont démontré l'importance des ALNs en tant que nouveaux acteurs dans les écosystèmes aquatiques, d'une part par leur dynamique écosystémique marquée et, d'autre part, par leurs interactions avec les procaryotes, principaux régulateurs des flux de matière et d'énergie. Les ALNs sont donc de nouvelles entités planctoniques qu'il faudra désormais prendre en compte dans l'étude des écosystèmes aquatiques. Enfin, l'ensemble de nos résultats soulève des perspectives de recherche sur la nature et l'écologie des ALNs et leur place dans les schémas évolutifs du monde organique.

Figure 1 :

 1 Figure 1 : Concept simplifié de chaîne trophique aquatique. ...............................................................................

Figure 2 :

 2 Figure 2 : Représentation schématique des différentes classes de taille planctoniques.......................................

Figure 3 :

 3 Figure 3 : Images d'entités femtoplanctoniques en microscopie électronique à transmission. ...........................

Figure 4 :

 4 Figure 4 : Images d'Aster Like Nanoparticles en microscopie électronique en transmission. ............................

Figure 5 :

 5 Figure 5: Transmission electron micrographs of biomimetic mineral-organic-(BMOPs) and/or nanobe-like particles (A-H) and vesicle-like particles (I-S). ...................................................................................................

Figure 6 :

 6 Figure 6: Transmission electron micrographs of different morphotypes of virus-like particles (VLPs)...........

Figure 7 :

 7 Figure 7: Transmission electron micrographs of attached (A-Q) or free (R-T) femtoplankton-like prokaryotes. ............................................................................................................................................................

Figure 8 :

 8 Figure 8: Transmission electron micrographs of different morphotypes of aster-like nanoparticles. ..............

Figure 9 :

 9 Figure 9: Schematic overview of the main components and of organizational complexity (increase in complexity from left to right) of the femtoplankton entities mentioned in this review. ......................................

Figure 10 :

 10 Figure 10: Significance of femtoplankton entities in prebiotic evolution: a potential pathway to the cellular and viral world. ......................................................................................................................................................

Figure 12 :

 12 Figure 12: Electromicrographs showing heterogeneity of pelagic communities (A) in lakewater collected on March 15 th 2017 and ALN-enriched culture (B) obtained from this sampling...................................................

Figure 13 :

 13 Figure 13: Transmission electron microscopy (TEM) micrographs of different morphotypes of aster-like nanoparticles. .........................................................................................................................................................

Figure 14 :

 14 Figure 14: Electromicrographs of aster-like nanoparticles.................................................................................

Figure 15 :

 15 Figure 15: Energy-filtered transmission electron microscopy (EFTEM) (A) and electron energy loss spectroscopy (EELS) analyses (B,C) of aster-like nanoparticles.........................................................................

Figure 16 :

 16 Figure 16: Flow cytometry analysis of aster-like nanoparticle-enriched preparations (E-ALNs). ...................

Figure 17 :

 17 Figure 17: Taxonomic affiliation of the 233 contigs from ALN-enriched DNA templates. ..............................

Figure 18 :

 18 Figure 18: Sensitivity of the particles to heat, antibiotics or lysosyme treatments. ............................................

Figure 19 :

 19 Figure 19: Development monitoring of aster-like nanoparticles in prokaryote-free medium. ..........................

Figure 20 :

 20 Figure 20: Abundance of aster-like nanoparticles in situ (Neuville-France) and ratios (in %) of different morphotypes over a 15-month period....................................................................................................................

Figure 24 :

 24 Figure 24: Relationships between ALNs and physical-chemical and biological environment. .......................

Figure 25 :

 25 Figure 25: Transmission electron microscopy (TEM) micrographs of different morphotypes of aster-like nanoparticles (ALNs)...........................................................................................................................................

Figure 26 :

 26 Figure 26: Dynamics of Aster Like Nanoparticles concentrations (A) and their different forms (B). ...........

Figure 28 :

 28 Figure 28: Linear regression between ALNs concentration and concentration of prokaryotes. .....................

Figure 29 :

 29 Figure 29: Experimental design for the preparation of inoculums. .................................................................

Figure 31 :

 31 Figure 31: Monitoring of the concentration of ALNs over time, function of medium culture and inoculum. ..............................................................................................................................................................................

Figure 32 :

 32 Figure 32: Monitoring of the concentration of prokaryotes (A) in inoculum B over time, function medium culture. .................................................................................................................................................................

Figure 33 :

 33 Figure 33: Dynamic of ALNs different forms function of culture medium......................................................

Figure 34 :

 34 Figure 34: Bacterial composition of the incubations of inoculum B, according to the culture medium. .......

Figure 35 :

 35 Figure 35: Long-term incubation enriched for members of the Planctomycetes and CPR bacteria. ..............

Figure 36 :

 36 Figure 36: TEM imaging and viral genomics in the enrichment culture. ........................................................

Figure 37 :

 37 Figure 37 : Evolution de la concentration en ALNs et en procaryotes entre 2017 et 2021 dans le lac Fargettes...............................................................................................................................................................................

  February 2017...................................................

Figure 1 :

 1 Figure 1 : Concept simplifié de chaîne trophique aquatique. Cette représentation intègre les concepts de boucle microbienne et virale, jouant un rôle essentiel dans le transfert de matière et d'énergie. D'après[11]

Figure 2 :

 2 Figure 2 : Représentation schématique des différentes classes de taille planctoniques. D'après[16]

Figure 3 :

 3 Figure 3 : Images d'entités femtoplanctoniques en microscopie électronique à transmission.

Figure 4 :

 4 Figure 4 : Images d'Aster Like Nanoparticles en microscopie électronique en transmission. Ces images ont été obtenues lors d'observations d'échantillons issus de milieux naturels. Crédits photos : J.Colombetplateforme CYSTEM. Échelles = 100 nm

Figure 6 :

 6 Figure 6: Transmission electron micrographs of different morphotypes of virus-like particles (VLPs). (A) VLP embedded in a vesicle-like structure. (B) Tailless VLP. (C-N) Tailed VLPs representing phages like morphotypes. (O-U) Giant tailed VLPs. (V-Y) Archaea-like viruses. Scale bars = 100 nm, excepted notifications (O,S,R).

  (i) positive-stranded RNA viruses, (ii) negative-stranded RNA viruses, (iii) double-stranded (ds) RNA viruses, (iv) reverse-transcribing viruses with positive-stranded RNA genomes, (v) reverse-transcribing viruses with ds DNA genomes, (vi) single-stranded (ss) DNA viruses, and (vii) dsDNA viruses [117, 118]. With the development of high-throughput sequencing technologies [119-122], the International Committee on Taxonomy of Viruses (ICTV) has considerably simplified the classification criteria by allowing all viruses to be classified on the basis of genome-sequence information [123]. The classification based on genome-sequence information opens up a new way in the classification of viruses that are known only from metagenomic data [114, 124]. Although no universally shared sequences are conserved across the entire genome of the viral world, the genomic approach also allows to target the phylogeny of specific viruses harboring common genetic markers [125]. The taxonomic classification of viruses is constantly evolving. In March 2020, the ICTV has identified 4 realms, 9 kingdoms,

Figure 7 :

 7 Figure 7: Transmission electron micrographs of attached (A-Q) or free (R-T)femtoplankton-like prokaryotes.

Figure 8 :

 8 Figure 8: Transmission electron micrographs of different morphotypes of aster-like nanoparticles. (A-H) 4-10-armed forms. (I-M) 11-armed forms and their budding 11-armed variants (N-R) with elongated and swollen bud-like excrescences. (S-X) 20-armed forms. Scale bars = 100 nm.

Figure 9 :

 9 Figure 9: Schematic overview of the main components and of organizational complexity (increase in complexity from left to right) of the femtoplankton entities mentioned in this review.The question mark (?) represent uncertainty about the presence/absence of this compound in the target entity. The dotted line (--) means "Optional". GTAs = gene transfer agents, BMOPs = Biomimetic mineral-organic particles, ALNs = aster-like nanoparticles. Note that the tail (mainly an attribute of bacteriophages) is not present in all naked viruses.

Figure 10 :

 10 Figure 10: Significance of femtoplankton entities in prebiotic evolution: a potential pathway to the cellular and viral world.

  [239].Ramisetty and Sudhakari [240] underlined that the temperate prophages are one of the most significant drivers of bacterial genome evolution and sites of biogenesis of genetic information.Nasir et al. [238] noted that phage conversion during transduction alters host physiology with respect to metabolism, pathogenicity, and niche adaptation. Although lacking metabolic activities, viruses can profoundly affect geochemical cycles by modelling the diversity and activity of their potential hosts.GTAs are unusual vehicles for HGT, which appears to be an hybrid of bacteriophage transduction and natural transformation[170].McDaniel, et al. [241] reported frequencies of antibiotic gene transfer by GTAs in in situ marine microcosms that were orders of magnitude greater than any other known mechanism. The transferred genes can enhance fitness or resilience and have the potential to drive bacterial evolution and genome plasticity, including the spread of virulence and antimicrobial resistance genes[242]. The ecological significance of GTAs is probably underestimated because they are difficult to distinguish from viral particles.

Figure 11 :

 11 Figure 11: Schematic overview of the specific and major ecological roles of femtoplankton entities mentioned in this review. BMOPs = Biomimetic mineral-organic particles, ALNs = aster-like nanoparticles, CPR/DPANN = Candidate Phyla Radiation/Diapherotrites Parvarchaeota Aenigmarchaeota Nanoarchaeota Nanohaloarchaeota, GTAs = gene transfer agents, HGT = horizontal gene transfers.

Figure 12 :

 12 Figure 12: Electromicrographs showing heterogeneity of pelagic communities (A) in lakewater collected on March 15 th 2017 and ALN-enriched culture (B) obtained from this sampling. P, prokaryote; VLP, virus-like particle; A, ALNs. Scale bars = 100 nm.

A

  fixed suspension (1% (v/v) formaldehyde) containing ALNs was deposited by filtration on 0.2-μm-pore-size filters (Whatman, Maidstone, UK), post-fixed with 1% osmium tetroxide, rinsed, and dehydrated through increasing concentrations of ethanol and then of hexamethyldisilasane. Following Cu sputter coating, dry filters were observed and imaged using a Zeiss Merlin Compact SEM operating at 2, 3 or 5 kV (Zeiss, Oberkochen, Germany).Nucleic Acid Staining, Membrane Markers, and Flow Cytometry (FC)Analyses and Sorting of ALNsUnfixed suspensions containing ALNs were thawed at 4°C and diluted in 0.02-μm-filtered Tris EDTA buffer prior to FC analyses. Analyses were performed using four nucleic acid dyes [SYBR Green I (Invitrogen S7563, Paisley, UK), SYBR Gold (Invitrogen S11494), propidium iodide (PI) (Sigma-Aldrich P4864) and DAPI (Sigma-Aldrich 32670)] and two lipophilic membrane markers [FM4-64 (Molecular Probes T13320, Eugene, OR) and PKH26 (Sigma-Aldrich P9691)]. ALNs were i) stained at 80°C for 10 min with SYBR Green I or SYBR Gold as described in[256]; ii) pre-heated at 80°C for 10 min then stained with 10 μg•mL -1 PI or 1 μg•mL -1 DAPI for 10 min in the dark. Nucleic acids were also stained without heating. Staining with FM4-64 (5 μg•mL -1 ) and PKH26 (1/500 diluted from commercial solution) was carried out in the dark for 10 min at room temperature. All experimental conditions were reproduced in triplicates. Triplicates of 0.2 μm ALN-free filtrated water lake (i.e., enriched VLPs water from lake Pavin) and cultivated bacteria from lake Neuville were used for biological controls.Cytometric analysis was performed on a BD FACSAria Fusion SORP flow cytometer (BD Biosciences) equipped with a 70-μm nozzle. Laser and filter configuration was as follows:DAPI was excited by a 355-nm UV laser, fluorescence was collected with a 410 long pass (LP) and a 450/50 band pass (BP). SYBR Green I and SYBR Gold were excited at 488 nm and fluorescence was collected with a 502 LP and a 530/30 BP. PI and FM4-64 were excited at 561 nm and fluorescence was collected with a 600 LP and a 610/20 BP for PI, and with a 685 LP and a 710/50 BP for FM4-64. PKH26 was excited at 561 nm and fluorescence was collected with a 582/15 BP. Targeted particles were visualized on a "marker fluorescence vs. side scatter" dotplot. Data were acquired and processed using FACSDivA 8 software (BD Biosciences).Characterization of ALNs and VLPs from samples processed for cytometric analyses was carried out by TEM as previously described. Plots were compared with those of a similarlyprocessed VLPs community obtained from Lake Pavin (see site description in[254]) on October 24th 2017. FC sorting was performed on samples stained with SYBR Green I in unheated conditions for optimal preservation of ALNs morphology and reliable morphotype diagnosis. Commonly described "viral fractions"[256] were gated on SYBR Green I fluorescence and sorted out using the continuous "Purity" mode. 0.5-μm fluorescent beads (Polysciences, Warrington, PA) served as control sorted fraction. Particles from sorted gates were re-analyzed by FC and identified and counted by TEM.

  Technologies) and a Qubit fluorimeter with Qubit dsDNA HS reagent Assay kit (Life Technologies). A ready-to-sequence SMRTBell Polymerase Complex was created using a Binding Kit 2.1 (PacBio) and the primer V4, the diffusion loading protocol was used, according to the manufacturer's instructions. The PacBio Sequel instrument was programmed to load and sequenced the sample on PacBio SMRT cells v2.0 (Pacific Biosciences), acquiring one movie of 600 min per SMRTcell and generate 8 Gb of bases and an insert N50 at 7.75Kb.

Figure 13 :

 13 Figure 13: Transmission electron microscopy (TEM) micrographs of different morphotypes of aster-like nanoparticles. (A-F) 4-10-armed forms with some (A-D) presenting a few arms articulated around a deltashaped excrescence (arrows). (G-K) 11-armed forms and their budding 11-armed variants (I-K) with elongated and swollen bud-like excrescences (arrows). (L-P) 20-armed forms. Scale bars = 100 nm.

Figure 14 :

 14 Figure 14: Electromicrographs of aster-like nanoparticles. (A,B) Scanning electron microscopy (SEM) micrographs showing ALNs with multiple full-grown radial arms (A) or a mix of emerging (arrow) and full-grown arms (B). (C) TEM micrograph of an ultra-thin section of an ALN. Sagittal sections of arms reveal a tubular appearance with electron light area enclosed by a wall-like structure (arrows). (D,E) Cryo-TEM micrographs. (D) Radial arms display a similar mottled appearance. (E) Magnified view of the box selected from the previous image revealing circular substructures (arrow). Scale bars = 100 nm.

Figure 15 :

 15 Figure 15: Energy-filtered transmission electron microscopy (EFTEM) (A) and electron energy loss spectroscopy (EELS) analyses (B,C) of aster-like nanoparticles.(A) Zero-loss image and EFTEM C, O, and Ca maps of an ALN. Scale bar=200 nm. (B) EELS spectra of an ALN particle (blue) and formvar (red). Insert: close-up of the backgroundnormalized spectrum of an ALN particle at the N and O K-edges. (C) EELS spectra of a reference calcite crystal at the C K-edge and the Ca L2,3-edges. The relative intensities at the C K-edge and Ca L2,3 edges correlate with C/Ca atomic ratio.

Figure 16 :

 16 Figure 16: Flow cytometry analysis of aster-like nanoparticle-enriched preparations (E-ALNs).(A) Gating of three distinctive populations (P1, P2, P3) of SYBR Green-stained E-ALNs. Heating was omitted during the staining procedure, and beads (0.5 μm) were used as control fraction (P4). The gray area in scatter plot including in P1, P2, and P3 commonly represents VLP fractions (see[256]). A pie chart shows the relative proportions of ALNs morphotypes attested by TEM. (B) Distribution of ALNs morphotypes and beads in the four FACS-sorted fractions counted by TEM. (C) Cytometry counts of P1, P2, and P3 gated fractions compared to counts obtained when heating was included in the SYBR Green staining procedure, and to counts of particles in ALNs-free viral community stained in heat-driven conditions. Mean values from triplicate and standard errors are plotted. Significant representativeness of morphotypes in sorted populations (B) is indicated by symbols: ¤ (Fisher's exact test on a contingency table, p < 0.01). Significant differences between "non-heated" and "heated" conditions (C) are indicated by an symbol ¤ (Student T-test, p < 0.05).

Figure 17 :

 17 Figure 17: Taxonomic affiliation of the 233 contigs from ALN-enriched DNA templates.Each piece of the pie corresponds to a contig and its size is proportional to the number of reads that were associated to this contig.

Figure 18 :

 18 Figure 18: Sensitivity of the particles to heat, antibiotics or lysosyme treatments. Effects of treatments by heat, antibiotics and lysosyme were assessed compared to untreated controls at day 20. Results are expressed as the percentage of ALNs which have resisted to treatments and continued to develop compared to control after a 20-day incubation. ALN-free prokaryotic cultures and femtoplanktonic communities (0.2 μm filtrated water from an eutrophic lake) were used as controls. Mean values from triplicate and standard errors are plotted. Significant differences with control are indicated by symbol (T-test, p < 0.05).

Figure 19 :

 19 Figure 19: Development monitoring of aster-like nanoparticles in prokaryote-free medium.Temporal variations of ALNs abundances and ratios (in %) of different morphotypes over a 36day period. Mean values from triplicate and standard errors are plotted. Significant differences between ALNs abundance at t (n) and t (0) and between ALNs abundance at t (n) and t (n-1) are indicated by symbols ¤ and , respectively (T-test, p< 0.05).

Figure 20 :

 20 Figure 20: Abundance of aster-like nanoparticles in situ (Neuville-France) and ratios (in %) of different morphotypes over a 15-month period. Note the peak of abundance between late December 2017 and mid-March 2017 and the return to low-density populations within a few months. Mean values from triplicate and standard errors are plotted. Significant differences between ALNs abundance and the previous time are indicated by asterisks (Student T-test, p < 0.05).

and 11 -

 11 armed morphotypes fluctuate inversely over time (Figure19, Spearman's r = -0.86, p < 0.001). These fluctuations were positively (4-10-armed forms) or negatively(11-armed forms) correlated to total ALN population (Spearman's r = 0.66 and r = -0.82, respectively, p < 0.05).The proportion of the smallest ALN forms (predominant morphotype at day 0) increases concomitantly with total number of ALNs but decreases as the abundance of total ALNs returns to baseline (day 0, day 20, and day 36). Inversely, the proportion of 11-armed forms increases during phases of total ALN decline (days 20, day 36). Throughout the incubation period, we were not able to detect any prokaryotic cells using different approaches: flow cytometry, transmission electron microscopy, and plate count agar spreading.The above incubation monitoring show that the abundance of ALNs can change significantly over time in the absence of cellular entities, with different patterns registered in contrasted morphotype categories. The mechanisms under these changes remain unclear in the absence of a detectable genomic support.

Figure 21 :

 21 Figure 21:(A) Distribution of aster-like nanoparticles and bacteria abundances in 16 selected stations of a tropical coastal ecosystem (Ha Long Bay-Vietnam), and (B) analyses of correlations (Spearman's product-moment correlation coefficient) between ALNs and environmental parameters which compile all sampling points.All details on Ha Long Bay (Vietnam) environment are available from[253]. Level of significance: *p < 0.001. VA, viral abundance; BA, bacterial abundance; BP, bacterial production; FIC, frequency of infected cells; TEMP, temperature; SAL, salinity; Turb, turbidity; DOC, dissolved organic carbon; TPC, total particulate carbon; TPN, total particulate nitrogen in the bulk sample.

  suggest ALNs as self-sufficient forms of life. Differential responses of ALN morphotypes to the multiple damaging treatments should also be considered. 4-10-armed forms appeared more affected than the 11-armed forms, suggesting possibility of more resilient morphotypes within the population of nanoparticles. Comparisons of ALN responses to those of other populations used as controls did not however permit to draw more definite conclusions indicative of the living or non-living nature of these particles. More basically, the ability of ALN populations to persist in the absence of cells and the sensibility of the particles to biocide agents both raise the question of the existence of endogenous nucleic acids. Hypothesis of an heredity support is also supported by the reoccurrence of different ALN morphotypes whatever was the environmental context or season (see below) and the recurrent radial symmetry of the particles which might reflect a developmental relationship between morphotypes. Flow cytometry (FC) plotting and

  Figure 22: (A-C), Electromicrographs documenting a putative interaction between aster-like nanoparticles and microbial cells. (A'-C') are magnified views of sections indicated by arrows in (A-C). Note the close contact between arms of the ALNs and the microbial cells. Scale bars = 100 nm.

Supplementary figure 2 .

 2 Abundance of prokaryotes and virus like particles (VLPs) during in situ (Neuville-France) seasonal survey from November 2016 to January 2018 in an eutrophic freshwater lake near Neuville in the French Massif Central. Mean values from triplicate and standard errors are plotted.

  Leur polymorphisme atypique, couplé à un volume réduit, une nature organique suspectée, une sensibilité aux traitements biocides et une capacité à se développer en l'absence de cellules indiquent en effet que les ALNs sont de nouvelles femtoparticules qui, pour le moment, ne peuvent être classées dans aucune catégorie connue de femtoparticules précédemment décrites dans les échantillons environnementaux. Leur place le long de l'échelle évolutive, du minéral à la cellule vivante reste également à être déterminée.Au-delà des interrogations sur la nature exacte des ALNs, leur capacité de développement en conditions naturelles avec des densités pouvant atteindre 10 8 ALNs.mL -1 (ponctuellement 8 fois supérieur aux procaryotes), interroge sur leur écologie et leurs fonctions au sein des réseaux trophiques aquatiques. La question fondamentale de leur écologie reste ouverte et inexplorée. C'est donc sur ce principal défi que réside les objectifs des travaux présentés dans ce mémoire. Comment les ALNs, jusqu'à présent jamais décrites, émergent, se développent et évoluent dans les écosystèmes aquatiques ? Dans quels systèmes sont-elles capables d'évoluer et selon quelle dynamique ? Quels sont les facteurs de forçage régissant leur développement ? Les travaux présentés dans les chapitres suivants seront donc articulés autour de ces principaux axes de réflexion. CHAPITRE 1 : ÉTUDE DE LA VARIABILITÉ SPATIALE DES ALNs La détermination de l'écologie des ALNs représente un verrou fondamental à lever pour mieux comprendre leur importance quantitative et fonctionnelle dans les écosystèmes. Définir leur écologie passe avant tout par une prospective spatiale de leur distribution dans différents milieux ou habitats. L'habitat se définit comme un environnement physique délimité dans lequel l'entité étudiée présente une dynamique en lien avec les facteurs abiotiques et biotiques. En écologie aquatique, les habitats sont définis à différentes échelles, du micro-habitat (e.g. zone délimitée d'un cours d'eau) au macro-habitat (e.g. l'ensemble du système fluvial étudié) [280]. L'habitat est donc une notion complexe dûe à de nombreux facteurs intrinsèques tels que [281] : (i) L'échelle spatiale du milieu. (ii) L'abondance et la densité des entités. (iii) Les facteurs physico-chimiques du milieu. (iv) Les composantes biotiques présentes. Déterminer les différents habitats d'une entité va donc permettre de définir les facteurs de forçage pouvant influencer la présence ou l'absence de cette dernière [282]. Afin d'appréhender les conditions environnementales pouvant favoriser le développement des ALNs, une prospection à l'échelle géographique du bassin-versant de la Loire a été menée, intégrant des habitats aux conditions physico-chimiques et biologiques différentes. Cette étude a fait l'objet d'une publication parue.

Figure 23 :a

 23 Figure 23: Sampling site locations (1-25) and distribution of ALNs in different aquatic environments along the watershed of Loire River (France).

Figure 24 :

 24 Figure 24: Relationships between ALNs and physical-chemical and biological environment. a Comparison of the average (U test, p < 0.01) of ALNs according to the low (state 1 = sites 1,2, 3,[START_REF] Joshi | Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files[END_REF], medium (state 2 = sites5, 6, 8, 11, 14, 15, 16, 18, 19, 20, 24, 25), and high (state 3 = sites7, 9,[START_REF] Chaumeil | GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF] 12, 13, 17, 21,[START_REF] Nayfach | CheckV assesses the quality and completeness of metagenomeassembled viral genomes[END_REF] 23) trophic levels of the different aquatic en-vironments. b Correlation analysis (Spearman's test, p < 0.01) between the different physical-chemical and biological parameters of the different sampling points. T°C temperature, O2 dissolved oxygen, P total organic phosphorus, N total organic nitrogen, C total organic carbon

)

  are in the range of those of prokaryotes or viruses. The strong empirical relationship with prokaryotes and the regulation by their environment implies that ALNs are additional and so far ignored actors in aquatic ecosystems. Furthermore, to fully understand the ecological significance of ALNs in plankton dynamics, it is crucial to validate their biological nature. Table S1: Biological and physical-chemical features of the studied aquatic environments sampled from February to April 2019.

  ALNs per millilitre was obtained by multiplying ALNs/prokaryotes ratio by prokaryotes abundance (see schematic view of the used procedure in Fig S1)

Fig S1 :

 S1 Fig S1: Schematic view of the experimental strategy used to determine the abundances and the different ALNs morphotypes. Images of TEMs associated with the critical steps of sample preparation, showing a clear purification of the sample. Scale bars = 500 nm. TEM: Transmission Electron Microscopy. Additional technical details are available in supplementary materials.

  phosphorus and chlorophyll concentrations ([P] and [Chla] respectively): TSI -P = 14.42*Ln[P] + 4.15 (in µg.L-1) TSI -Chla = 30.6 + 9.81 Ln [Chla] (in µg.L-1)

Figure 25 :

 25 Figure 25: Transmission electron microscopy (TEM) micrographs of different morphotypes of aster-like nanoparticles (ALNs). A-C, 4-10 arms forms. D-F, 11 arms forms and their budding variants G-I. J-L 20 arms forms. Scale Bars = 100 nm

:

  Bacterial sequencing data were processed with the PANAM2 pipeline [308]. Briefly, sequence reads were assembled with Vsearch [309], excluding reads <200pb, with ambiguous calls (N) or having mismatch in the forward/reverse primer. Demultiplexed amplicons were clustered into OTUs using Vsearch at a 95% id threshold. Representative sequence of OTUs were compared against the SILVA SSURef 115 database restricted to sequences with length > 1,200 pb, quality score > 75% and a pintail value > 50. Archaea and Fungi sequencing data were analysed through the FROGs pipeline [310]. Sequence reads were assembled with Vsearch [309], excluding reads < 200pb, with ambiguous calls (N) or having mismatch in the forward/reverse primer. Demultiplexed amplicons were clustered into OTUs using Swarm [311] with distance (d) = 1. OTUs sequences were compared against the SILVA_132_16s database for archaea and Unite_Fungi_8,0 database for fungi. Data analysis Differences in physico-chemical and biological variables between seasons (Spring: March-May, Summer: June-August, Autumn: September-November, Winter: December-February) and lakes were tested by Kruskal-Wallis and Dunn tests. To investigate the potential proximity between our sampling points, function of lakes or seasons, principal component analysis (PCA) was used with the FactoMineR package. Potential relationships among all variables were tested

  B), excepted for HE. HE dynamic was significantly affected by seasons (p < 0.01) with a maximum number in autumns and minimal number in winter. Detailed lake-specific monthly variations for each biological parameter are presented in Figs s1-s2.Composition of communitiesMetabarcoding of bacterial, archaeal, and fungal communities revealed the predominance of the same phyla, whatever the lake and the season (Figs3). Bacterial communities in the three lakes were dominated by Proteobacteria (30%), Bacteroïdetes (15%) and unclassified bacteria (13%) (Figs3). Euryarchaeota (43%), Nanoarchaeota (40%) and Crenarchaeota (11%) were the major phyla for Archaea (Figs3). While the fungus community is dominated by unclassified fungi (40%), major known phyla correspond to Chytridiomycota (27%) and Basidiomycota (17%) (Figs3). The mean percentage of the relative abundance of these major phyla presents important temporal variations specific to each lake. For Lake Fargettes, we can notice a peak of Proteobacteria in March and April (More than 60% of total abundance), Bacteroidetes in May (50%) and the dominance of unclassified fungi in April (98%) (Figs3). In St. Gervais, Bacteroidetes (40%) increase in March, Euryarchaeota in February and April (50%), and Basidiomycota in December (90%) (Figs3). For Lapeyrouse lake, Bacteroidetes increase in

Figure 26 :

 26 Figure 26: Dynamics of Aster Like Nanoparticles concentrations (A) and their different forms (B). Total ALNs concentration in the 3 lakes during the 12 months of sampling (A). Dynamics of the different forms during this period (B)*. ND = No Detectable. * = data are obtained from mean of the 3 lakes

  4 x 10 5 to 7.0 x 10 5 for St. Gervais and from no detectable to 10 5 ALNs.mL -1 for Lapeyrouse) (Figure26-A), immediately followed by a decline in April in the three lakes. A second increasing phase was recorded from May until July, especially in St. Gervais.The mean distribution combined from the three lakes of different forms (Figure25) varied with time (Figure26-B). The 4-10 arms forms were recorded preferentially from October (15%) to November (27%) and showed highest values from March (45%) to July (35%) during and following the spring peaks of ALNs (Figure26-B). The 11 arms forms dominated the ALNs communities in October (71%), December (100%), January (87%), April (43%) and May (61%) mainly when the lowest concentrations of ALNs were recorded, whereas the 11 budding arms form dominated from June (53%) to September (63%) (Figure26-B). The 20 arms were detected from October (13%) to November (13%) and had highest values from February (35%) to April (15%) concomitantly with the spring peaks of ALNs (Figure26-B). During the ALN peaks of (March 2019), the contributions of the 4 different forms(4-10, 11, 11 budding and 20 arms) were at[START_REF] Camprubí | The Emergence of Life[END_REF] 25, 21 and 9%,. When the abundances of ALNs were particularly low, i.e., in December and January (Fig26-A), only the 11-arm form was represented, with absence or very low proportion of the budding form.

Figure 28 :

 28 Figure 28: Linear regression between ALNs concentration and concentration of prokaryotes.Linear regression (y = -3 + 1,2*x) was performed with data from the 3 lakes during the 12 months of sampling and data from Colombet et al.,[13].

  microbial and probably prokaryotic environment. The hypothesis that ALNs have strong interactions with prokaryotes is emerging but will have to be verified in the future as well as the possibility of a development cycle linking the different morphotypes. The functionality of ALNs is certain for the transfer of their constitutive elements within the microbial network but their role on other microbial components (neutrality, mutualism, parasitism...) remains to be determined. Through their dynamics, ALNs are undoubtedly new actors to consider in the functioning of aquatic ecosystems. More generally, our data highlight the seasonal importance of overlooked femtoplankton in aquatic ecosystems and their potential roles in the ecosystem functioning.

FigureFigure S3 .

 S3 Figure S2. Variation of different groups of nanophytoplanktonic communities (Chlorophyceae, Cryptophyceae, Cyanobacteria and Diatoms) in our 3 lakes over the 12-months sampling period.

Figure 29 :

 29 Figure 29: Experimental design for the preparation of inocula.

Figure

  Figure 30: Transmission electron micrographs of different morphotypes of aster-like nanoparticles (ALNs).Scale bars = 100 nm. Crédits photos: J.colombetplateform CYSTEM

Figure 31 :

 31 Figure 31: Monitoring of the concentration of ALNs over time, function of medium culture and inoculum. * indicate significant temporal difference between ALN concentration in a same condition (Dunn test, p < .05).

Figure 34 :

 34 Figure 34: Bacterial composition of the incubations of inoculum B, according to the culture medium.Other class with total abundance < 0.5% = Erysipelotrichi, Coriobacteriia, Acidimicrobiia, Lentisphaeria, Spirochaetes, Chlorobia, Fusobacteriia, Rubrobacteria, Thermomicrobia, Deinococci, Anaerolineae, Acidobacteria, Phycisphaerae, Thermoleophilia, Bacteroidia.

Figure 35 :

 35 Figure 35: Long-term incubation enriched for members of the Planctomycetes and CPR bacteria. (a) Rank abundance curve based on ribosomal protein S3 (rps3) coverage for organisms recovered at the end of incubation. Asterisks indicate marker genes that were binned into genomes. (b) Relative abundance of CPR bacteria and Planctomycetes during monthly sampling of Lake Fargettes based on 16S rRNA amplicon sequencing. Each point represents the relative abundance of CPR bacteria or Planctomycetes in a given month. (c) Overall community composition at the end of incubation, based on cumulative coverage of rpS3. Panel d displays the fraction of RNA reads from the end of incubation that could be mapped to genomes. (e) Sequence characteristics, metabolic predictions, and CRISPR-Cas loci information for genomes affiliated with the Planctomycetes and CPR bacteria. Cells with color fill indicate the fraction of key genes for each pathway (as defined by KEGGDecoder) that are present. X indicates genomes with CRISPR loci and if those loci contained spacers targeting at least one curated phage genome from the sampl

Figure 36 :

 36 Figure 36: TEM imaging and viral genomics in the enrichment culture.(A) Featured in this image is a cell inferred to be a Planctomycetes (pl) with a characteristic stalk and holdfast (h). Attached to the cell are four phage particles (v) (two different sizes; thus, likely different phages). Also visible is one large tailed jumbo phage (ph) that is 145 nm in diameter with a 214-nm tail as well as several aster-like nanoparticles (ALNs) (a). (B) Genome sizes and predicted hosts for phages and eukaryotic viruses.

Figure S2 .

 S2 Figure S2. Windowed and cumulative GC skew plot for the Peribacteria/PER-ii genome that was curated to completion.The peaked nature of cumulative GC skew, beginning at the origin and proceeding through the terminus, suggests that the genome assembly is accurate (seeChen et al., 2020Chen et al., doi:10.1101/gr.258640.119/gr.258640.119).

Figure S3 .

 S3 Figure S3. The newly reconstructed, curated Peribacteria genome (top sequence) is largely syntenous with a reference Peribacteria genome from Rifle, CO.Colored blocks indicate Locally Collinear Blocks as determined by the genome aligner Mauve.

Figure S4 .

 S4 Figure S4. Maximum likelihood (ML) single-protein tree of major capsid protein from putative eukaryotic virus genomes. The tree is rooted between the PAM and the MAPI putative superclades (see: doi.org/10.1073/pnas.1912006116).

Figure S6 .

 S6 Figure S6. Transmission electron micrographs of different phenotypes present in starting and final sample after 31 months of incubation.(a-q): starting sample / (A-R): final sample. VLPs: Virus Like Particles. CLPs: Cellular Like Particles. Scale bar: 500 nm (a, l, M, N, R), 200 nm (b, c, e, g-i, m-q, A, G, Q), 100 nm (d, f, j, k, B-F, H-L, O, P).

  dynamique temporelle des ALNs dans différents écosystèmes aquatiques. Cette étude dynamique menée dans 3 lacs du Puy-de-Dôme a permis de confirmer l'importance des paramètres biologiques dans la distribution des ALNs et, notamment, l'importance potentielle des procaryotes. Cette étude a également permis de mettre en évidence une dynamique saisonnière marquée des ALNs, avec une grande amplitude de variation des abondances d'une saison à l'autre, suggérant que les ALNs sont un acteur majeur à intégrer dans les modèles de successions écologiques.Ces résultats ont permis d'acquérir des informations sur l'écologie des ALNs et de soulever de nouvelles questions sur le rôle de ces entités dans les milieux aquatiques et notamment leur impact sur les autres communautés microbiennes. Leur forte concentration, pouvant être du même ordre que celle des procaryotes ou des VLPs, en font des entités pouvant impacter la biodiversité, l'activité et la structuration des communautés aquatiques. Les fortes variations de leurs abondances naturelles au cours du temps, sous forme de « blooms », en font également des entités pouvant jouer un rôle dans les flux de matière et d'énergie, notamment en mobilisant et en séquestrant des éléments constitutifs (e.g. rôle dans l'homéostasie du calcium dans les environnements aquatiques), comme cela a été suggéré pour d'autres entités comme les PMOBs par exemple[18]. La présence des mêmes formes d'ALNs quelque soit la nature du milieu ou sa localisation géographique suggère l'existence, dans la communauté naturelle des ALNs, d'un support d'hérédité constitutionnel ou associé à un symbionte qui permet d'aboutir aux mêmes conformations phénotypiques. Ces caractéristiques, décrites pour de nombreuses autres entités

  l'importance de ce lien corrélatif, avec des résultats montrant un développement jusqu'à 20 fois plus important des ALNs en présence d'une forte concentration de procaryotes. En outre, la mise en évidence d'une nouvelle forme d'ALNs dans nos cultures, forme par la suite observée occasionnellement dans l'environnement (données non montrées), soulève également de nombreuses questions sur les relations ontologiques entre les différentes formes d'ALNs et le rôle des procaryotes dans leur développement. La modification du ratio des différentes formes au cours du temps pourrait suggérer une interconnexion des formes, avec un lien entre procaryotes et ALNs plus poussé pour certaines formes que pour d'autres. Dans tous les cas, déterminer la nature exacte des ALNs et de leurs interactions avec les procaryotes représente un véritable défi pour les recherches futures sur les ALNs.Les expériences in-situ et en microcosmes ont permis de mettre en évidence l'importance des communautés procaryotes dans le développement des ALNs. L'utilisation de la modélisation pourrait donc permettre de prévoir la variation des concentrations en ALNs dans l'environnement. A titre d'exemple, la modélisation est utilisée dans la prédiction de blooms

Figure 37 :

 37 Figure 37 : Evolution de la concentration en ALNs et en procaryotes entre 2017 et 2021 dans le lac Fargettes.

  impact des ALNs sur le métabolisme des procaryotes et (ii) déterminer si les ALNs ont leur propre métabolisme. La microcalorimétrie est une approche déjà utilisée en écologie aquatique pour déterminer des modifications de métabolismes dans différentes classes de tailles planctoniques [337-341]. Un développement de méthode pour appliquer cette technique aux ALNs semble donc un moyen pertinent pour quantifier l'impact de ces entités sur les communautés procaryotes. Des approches par le marquage et le suivi d'incorporation d'éléments constitutifs des ALNs (i.e. C, Ca, N, O) pourraient être envisagées. Ce genre de méthode est utilisé classiquement en écologie aquatique pour estimer le rôle d'entités sur les flux énergétiques [342-344], et pourrait permettre d'estimer les flux potentiels transitant directement ou indirectement par les ALNs. L'utilisation de ces deux approches dans un premier temps pourrait donc nous permettre d'explorer les fonctions et les impacts potentiels des ALNs dans les environnements aquatiques.

Figure 38 :

 38 Figure 38 : Images d'ALNs en microscopie électronique à transmission (A,B) ou en microscopie à force atomique (C,D) détaillant la structure des ALNs. Les images A et B sont issues de Colombet et al. [27] et montrent la présence d'une sousstructure circulaire sur les bras des ALNs. La microscopie à force atomique d'ALNs (C-E) avec zoom (E) confirme l'existence d'éléments répartis de façon ordonée à la surface des ALNs. Barre d'échelle (A-B) = 100 nm. Images AFM David Albertini

  compréhension du fonctionnement des écosystèmes aquatiques. Si les progrès technologiques ont permis des avancées significatives dans l'exploration de sa diversité et de son rôle, cette fraction reste largement méconnue dans les écosystèmes aquatiques. Son étude est indubitablement une source de nouvelles connaissances tant sur les plans de la biologie, de l'évolution que de l'écologie. L'objectif de ce chapitre qui a fait l'objet de publications parues, est de faire un état de l'art des connaissances sur ce compartiment encore méconnu et d'introduire la découverte des ALNs. Nous aborderons dans ce chapitre la composante femtoplanctonique sous différents aspects : diversité, importances quantitatives et fonctionnelles, origine évolutive. Une attention particulière sera donnée au modèle d'étude de ces travaux de thèse, les ALNs. Leur découverte sera abordée ici en les plaçant dans le contexte de la diversité structurelle et fonctionnelle du femtoplancton.

Table 1 : Comparison of morphologies, some main constitutional elements and development strategies of femtoplankton entities. Viroids

 1

and prions composed only of RNA molecule and proteins respectively are not shown in the table. BMOPs = Biomimetic mineral-organic particles, ALNs = aster-like nanoparticles, CPR/DPANN = Candidate Phyla Radiation/Diapherotrites Parvarchaeota Aenigmarchaeota Nanoarchaeota Nanohaloarchaeota. ND = not determined. / = absence. + = presence.

Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics Jonathan

  Colombet1*, Hermine Billard1*, Bernard Viguès1*, Stéphanie Balor 2 , Christelle Boulé 3 , Lucie Geay 3 , Karim Benzerara 4 , Nicolas Menguy 4 , Guy Ilango 1 , Maxime Fuster 1 , François Enault 1 , Corinne Bardot 1 , Véronique Gautier 5 , Angia Sriram Pradeep Ram 1 and Télesphore Sime-Ngando 1

* These authors have contributed equally to this work 1 Université Clermont Auvergne, CNRS, Laboratoire Microorganismes:Génome, Environnement, Clermont-Ferrand F-63000, France 2 Université Paul Sabatier Toulouse III, CNRS, Plateforme de Microscopie électronique intégrative (METI), Centre de Biologie Intégrative (CBI), Toulouse F-31000, France 3 Université Claude Bernard Lyon 1, Centre Technologique des Microstructures (Ctμ), Villeurbanne F-69100, France 4 Sorbonne Universités, Université Pierre et Marie Curie Paris 06, Muséum National d'Histoire Naturelle, Institut de Recherche pour le Développement, CNRS, Institut de Minéralogie, de Physique des Matériaux, et de Cosmochimie, Paris F-75000, France 5 Université Clermont Auvergne, INRAE, UMR GDEC, Plateforme GENTYANE, Clermont-Ferrand F-63000, France Publié dans Frontiers in Microbiology -Octobre 2019 doi: 10.3389/fmicb.2019.02376

Supplementary figure 1. Detailed procedure of experimental design and analyses performed from a sample collected on March 15 th 2017 in a eutrophic freshwater lake near Neuville in the French Massif Central.

	EFTEM:	Energy-Filtered
	Transmission	Electron
	Microscopy; ALN: Aster Like
	Nanoparticles; EELS: Electron
	Energy Loss Spectroscopy;
	SEM:	Scanning	Electron
	Microscopy;	TEM
	Transmission	Electron
	Microscopy; DDW: Distilled
	Deionized Water.

  1 , Hermine Billard 1 , Marie Mandart 1 , Johannes Steiger 2 , Télesphore Sime-Ngando 1 ,

	Jonathan Colombet 1
	1 Université Clermont Auvergne, CNRS, LMGE, Clermont-Ferrand F-63000, France

2

Université Clermont Auvergne, CNRS, GEOLAB, Clermont-Ferrand F-63000, France

Table S2 . Typology, geographical characteristics and sampling dates of the studied aquatic environments sampled from February to April 2019.

 S2

	counts of nanophytoplankton and nanocyanobacteria populations, from unfixed samples, by
	flow cytometry as described elsewhere [291] using a BD FACS Calibur cytometer (BD
	Sciences, San Jose, CA) equipped with an air-cooled laser, delivering 15 mW at 488 nm with
	the standard filter set-up.
	Prokaryotes, virus-like particles (VLPs) and ALN counts: Counts of prokaryotes and VLPs from
	fixed samples were performed by flow cytometry as described elsewhere [291] using a BD
	FACS Calibur flow cytometer (BD Sciences, San Jose, CA) equipped with an air-cooled laser,
	delivering 15 mW at 488 nm with the standard filter set-up. Since the source area showed low
	microbial load for robust TEM (Transmission Electronic Count) counting (Table

  travaux menés dans cette étude montrent que les ALNs ont un large spectre d'habitats : rivières, lac, marais, vasière, eaux côtières. Leur présence est également rapportée en milieux 'étude exploratoire précédente a permis de mettre en évidence un lien étroit entre ALNs et statut trophique du milieu, avec des plus fortes abondances dans les milieux eutrophes. Cela indique que la présence des ALNs serait dépendante de la productivité de l'écosystème.

	marins (mer de chine [293] et mer d'Arabie -données non montrées-), ce qui en fait des Cependant, cette étude spatiale menée dans des milieux dispersés, intégrant une variabilité
	particules ubiquistes dont le développement, avec des concentrations atteignant celles des géographique, ne tient pas compte de la dynamique temporelle des ALNs.
	procaryotes ou des virus selon le milieu, pourrait impacter le fonctionnement de grandes masses Intégrer cette dimension temporelle permettra de mieux appréhender l'écologie des ALNs et
	d'eaux. Leur distribution est étroitement associée au statut trophique du milieu considéré. D'un une exploration des facteurs biologiques pouvant contrôler non seulement leur présence mais
	point de vue empirique, les conditions biologiques prévalent sur les paramètres physico-aussi leur développement. L'étude de la dynamique temporelle des ALNs dans un même milieu
	chimiques dans le contrôle de leur importance quantitative. Leur forte concentration, du même permettra également de mettre en lumière les interactions potentielles avec les différents
	ordre que celles des procaryotes ou des virus selon les milieux, ainsi que leur présence dans des facteurs biologiques et physico-chimiques du milieu. C'est pour atteindre cet objectif spécifique
	environnements aquatiques très variés, suggèrent une grande importance des ALNs dans le
	fonctionnement de ces écosystèmes.
	Ainsi, la phénologie et les successions écologiques des communautés microbiennes dans le
	temps régissent le fonctionnement des écosystèmes aquatiques. Cette étude menée dans 3
	écosystèmes lacustres vise à identifier un « pattern » temporel dans la dynamique des ALNs,
	en relation avec les communautés microbiennes pouvant potentiellement réguler cette
	dynamique.

Les conclusions de cette étude ouvrent de nouvelles perspectives et hypothèses de travail. Les prélèvements ponctuels ayant permis de mettre en évidence des facteurs de contrôle putatifs des ALNs, étudier la présence des ALNs dans un même milieu au cours du temps semble indispensable, afin de préciser et valider les facteurs de forçage de leur dynamique. CHAPITRE 2 : ÉTUDE IN-SITU DE LA VARIABILITÉ TEMPORELLE DES ALNs Lde la thèse que la présente étude, qui a fait l'objet d'une publication parue, a été conduite. La dynamique temporelle des organismes est un élément clé dans la structuration saisonnière des communautés, et plus largement dans le bon fonctionnement des écosystèmes. Les premières études, portant sur la succession de plantes et d'animaux dans des environnements variés ont démontré l'importance de cette saisonnalité dans l'équilibre et le bon fonctionnement des écosystèmes [294, 295]. Par la suite, les progrès technologiques et notamment en microscopie, cytométrie en flux ainsi que le séquençage haut-débit ont permis de mettre en évidence une telle importance chez les organismes planctoniques [296], et notamment les organismes procaryotes [297, 298] et les phages [110]. La variabilité de ces organismes, à différentes échelles de temps, impacte donc la structuration des communautés et plus largement les réseaux trophiques aquatiques [299].

Table 3 : Mean ± SD of physico-chemical and biological characteristics according to the lakes (A) or the seasons (B).

 3 by linear pair-wise correlations (Pearson correlation analyses). Potential relationships between the presence/absence of ALNs and OTUs were tested by pairwise correlations (Spearman

	(A)	Fargettes	St. Gervais	Lapeyrouse
	O2 ns (mg.L -1 )	8.46 ± 3.45	9.36 ± 3.02	9.86 ± 2.07
	Temperature ns (°C)	12.63 ± 7.13	12.79 ± 8.04	13.32 ± 7.72
	pH ns	7.54 ± 0.67	7.88 ± 0.83	7.53 ± 0.56
	K (mg.L -1 )	31.15 ± 5.53 a	2.78 ± 0.51 b	5.11 ± 0.49 c
	Mg (mg.L -1 )	4.84 ± 0.52 a	3.22 ± 1.13 b	4.23 ± 0.48 c
	Na (mg.L -1 )	8.98 ± 2.27 a	12.52 ± 1.29 b	13.04 ± 1.41 b
	Ca (mg.L -1 )	22.94 ± 2.44 a	17.61 ± 6.08 b	24.06 ± 2.75 a
	P (mg.L -1 )	0.23 ± 0.06 a	0.14 ± 0.12 ab	0.06 ± 0.02 b
	T.O.C. (mg.L -1 )	23.92 ± 4.34 a	10.78 ± 3.70 b	10.67 ± 1.05 b
	T.N. (mg.L -1 )	4.73 ± 2.65 a	3.13 ± 1.89 ab	1.75 ± 0.67 b
	VLP ns (VLPs.mL -1 )	1.31 ± 0.70 x10 8	1.08 ± 0.88 x 10 8	0.78 ± 0.66 x 10 8
	Prokaryotes (cells.mL -1 )	2.73 ± 1.77 x10 7 a	1.59 ± 0.92 x 10 7 a	0.39 ± 0.36 x 10 7 b
	Nanophytoplankton (µg.L -1 )	178.20 ± 98.80 a	106.27 ± 70.84 a	222.44 ± 13.13 b
	Picophytoplankton	4.62 ± 2.01 x 10 5 a	4.97 ± 6.43 x 10 5 a	0.76 ± 0.93 x 10 5 b
	(cells.mL -1 )
		2.34 ± 1.46 x10 4 a	2.08 ± 1.56 x10 4 ab	1.23 ± 0.77 x10 4 b
	Heterotrophic eukaryotes
	(cells.mL -1 )
	ALN (ALNs.mL -1 )	6.12 ± 11.7 x10 5 a	2.32 ± 2.60 x10 5 ab	0.83 ± 1.99 x10 5 b

Table 3 -

 3 A). At the seasonal scale, no significant variation (p > 0.05) was recorded for the three lakes in the availability of mineral elements, P, TOC and TN (Table3-B)

	(B)	Spring	Summer	Autumn	Winter
	O2 (mg.L -1 )	10.22 ± 2.80 bc	6.29 ± 1.31 a	8.46 ± 1.82 ac	11.94 ± 1.93 b
	Temperature (°C)	12.70 ± 3.18 a	22.39 ± 2.54 b	11.87 ± 6.68 a	4.70 ± 1.36 c
	pH	8.31 ± 0.44 a	7.69 ± 0.44 a	7.60 ± 0.83 ab	7.01 ± 0.29 b
	K ns (mg.L -1 )	11.75 ± 12.18	14.94 ± 16.23	13.97 ± 15.02	11.40 ± 11.84
	Mg ns (mg.L -1 )	3.97 ± 0.95	4.45 ± 0.87	4.37 ± 1.15	3.59 ± 0.96
	Na ns (mg.L -1 )	11.95 ± 2.75	12.54 ± 2.15	11.40 ± 2.43	10.16 ± 2.27
	Ca ns (mg.L -1 )	21.33 ± 4.08	23.78 ± 3.64	21.86 ± 5.42	19.18 ± 5.80
	P ns (mg.L -1 )	0.14 ± 0.12	0.16 ± 0.08	0.17 ± 0.13	0.11 ± 0.09
	T.O.C. ns (mg.L -1 )	14.34 ± 7.78	16.10 ± 6.56	17.44 ± 7.95	12.60 ± 6.21
	T.N. ns (mg.L -1 )	3.46 ± 3.28	2.61 ± 1.34	3.14 ± 1.95	3.59 ± 2.20
	VLP ns (VLPs.mL -1 )	0.88 ± 0.51 x 10 8	1.32 ± 0.87 x 10 8	1.07 ± 1.09 x10 8	0.95 ± 0.44 x 10 8
	Prokaryotes ns (cells.mL -1 )	2.09 ± 2.33 x 10 7	1.46 ± 1.10 x 10 7	1.33 ± 1.25 x10 7	1.39 ± 1.05 x 10 7
	Nanophytoplankton ns (µg.L -1 )	137.84 ± 138.11	103.03 ± 88.35	111.31 ± 78.03	56.79 ± 45.02
	Picophytoplankton ns (cells.mL -1 )	2.69 ± 2.77 x 10 5	5.32 ± 6.32 x 10 5	4.27 ± 4.58 x 10 5	1.54 ± 1.38 x 10 5
	Heterotrophic eukaryotes	1.80 ± 1.75 x 10 4	2.35 ± 0.91 x 10 4 ac 2.69 ± 1.20 x 10 4	0.69 ± 0.39 x 10 4 b
	(cells.mL -1 )	ab		c
	ALN (ALNs.mL -1 )	7.14 ± 13.30 x10 5	2.11 ± 2.16 x10 5 ab 1.72 ± 2.50 x10 5	1.39 ± 2.55 x10 5 b
		a		ab
	O 2 : Oxygen; K: Potassium; Mg: Magnesium; Na: Sodium; Ca: Calcium; P: Phosphorus; T.O.C.: Total
	Organic Carbon; T.N.: Total Nitrogen; VLP: Viral Like Particles; ALN: Aster Like Nanoparticles
	a,b,c indicate significant differences between lakes or seasons (Dunn test, p < 0.01)
	ns indicate no effect of lakes or seasons on this parameter. * = data are obtained from mean of the 3 lakes

Table 3 and

 3 Figs s1-s2. The average numbers of VLPs were similar for the three lakes (p > 0.05) (Table3-A). Prokaryote and HE numbers followed the spatio-temporal dynamic of the

productivity indicators (P, TOC and TN) with highest average recorded in Lake Fargettes compared to Lapeyrouse (p < 0.01) and no significant difference with lake St. Gervais (p > 0.05). Lapeyrouse had higher content in nanophytoplankton and lower content in picophytoplankton compared to Fargettes and St. Gervais (p < 0.01).

Table 3 -

 3 A). ALN dynamic was significantly affected by seasons (p < 0.01) with remarkable spring peaks in the three lakes, recorded in March 2019 (

Table 3 -

 3 B). In these lakes, ALN abundances fluctuated from undetectable to a low range from October 2018 to February 2019 before a strong increase towards the main peaks recorded in March 2019 (from no detectable to 10 6 for Fargettes, 2.

Table 4 : Pearson correlation between Aster Like Nanoparticles and the environmental variables in the 3 lakes.

 4

		O2	T°c	pH	K	Mg	Na	Ca	P	TOC	TN	VLP	Prok	NPP	PPP	HE
	ALN	-0.26 0.28 0.24	0.22 -0.01 -0.21	0	0.23	0.25	0.17	0.47*	0.32*	0.31	0.26	-0.01

Table 5 : Significant Spearman correlation coefficients between the presence of ALNs and the presence of microbial OTUs.

 5

	Kingdom	Phylum	Lake	R 2
		Acidobacteria	St. Gervais	0.85
			St. Gervais	0.71
		Cyanobacteria
			Lapeyrouse	0.71
	Bacteria	Firmicutes	Fargettes	0.82
		Planctomycetes	Fargettes	0.77
			Fargettes_1	0.77
		Proteobacteria	Fargettes _2	1
			St. Gervais	0.84
			Fargettes_1	0.77
		Ascomycota	Fargettes _2	0.77
			St. Gervais _1	0.85
	Fungi
			St. Gervais_2	0.85
		Chytridiomycota	Lapeyrouse	0.84
	Positive correlation analyses (Spearman's test, p < 0.01) between the presence of different OTUs (and
	their affiliations) and the presence of ALNs.
	_(x) = different OTU

Table S1 : Composition of culture medium used for incubations Ultra-Filtrat (UF) medium Minimum medium (MM) Synura medium BG-11 medium

 S1

	1/ Water from the lake filtered frontally on a	Stocks
	filtration tissue with a porosity of 20 μm	1/ K 2 HPO 4	160 g per L
	2/ Successive tangential filtration with a porosity of 0.65 μm, 0.20 μm and 20 kd.	2/ KH 2 PO 4 3/ MgSO 4 4/ NaCl	40 g per L 20 g per L 10 g per L
	3/ Ultrat filtrate autoclaved and stored in the dark at 4°C until use	5/CaCl 2 6/ Trisodium citrate 2H 2 O 7/FeSO 4	20 g per L 100 g per L 0.5 g per L
			8/ Oligoelements trace	9 g per L
			9/ Vitamines	0.101 g per L
	Stocks
	CaCl 2 2 H 2 O	36.8 g per L
	MgSO 4 7H 2 O	37 g per L
	NaHCO 3	12.6 g per L
	K 2 HPO 4 3H 2 O	5.7 g per L
	NaNO 3	85 g per L
	Na 2 SiO 3 5H 2 O	28.42 g per L
	Oligoelements trace	9 g per L
	Vitamines	0.101 g per L
	Soil extract	400 g per L

Medium

• Mix 10 mL of 1, 2, 3, 4, 5 and 0.5 mL of 8 • 929 mL distilled water • Autoclaved • Add 10 mL of 6, 7 and 0.5 mL of 9 filtered on 0.2 μm filter

Table S5 )

 S5 . Phylogenetic analyses of encoded terminase and capsid proteins suggested that the phages likely fall within the Caudovirales, which are known to include numerous tailed phages

	with large capsids [329]. Additionally, we used phage gene content and analyses of bacterial
	CRISPR	loci	to	infer	that	phages	infect Planctomycetes, Proteobacteria,

Table S1 . Taxonomic affiliation and coverage of ribosomal protein S3 marker genes used to survey microbial community composition in the enrichment sample.

 S1

	scaffold	bin	lineage	in_draft_genome	coverage
	LakeFargette_0920_ALND_scaffold_281956	LakeFargette_0920_ALND_Planctomycetes_64_91	Planctomycetes	VRAI	88,14
	LakeFargette_0920_ALND_scaffold_603991	LakeFargette_0920_ALND_Burkholderiales_70_71	Proteobacteria	VRAI	76,37
	LakeFargette_0920_ALND_scaffold_544059	LakeFargette_0920_ALND_Actinobacteria_63_63	Actinobacteria	VRAI	65,3
	LakeFargette_0920_ALND_scaffold_273213	LakeFargette_0920_ALND_Nitrosoarchaeum_limnia_33_41	Thaumarchaeota	VRAI	47,21
	LakeFargette_0920_ALND_scaffold_208593	LakeFargette_0920_ALND_Planctomycetes_66_46	Planctomycetes	VRAI	45,7
	LakeFargette_0920_ALND_scaffold_63232	LakeFargette_0920_ALND_Planctomycetia_59_40	Planctomycetes	FAUX	44,66
	LakeFargette_0920_ALND_scaffold_616036	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	40,64
	LakeFargette_0920_ALND_scaffold_58038	LakeFargette_0920_ALND_Planctomycetia_67_38	Planctomycetes	VRAI	39,53
	LakeFargette_0920_ALND_scaffold_24295	LakeFargette_0920_ALND_Actinobacteria_52_33	Actinobacteria	FAUX	37,85
	LakeFargette_0920_ALND_scaffold_721642	LakeFargette_0920_ALND_Nitrosoarchaeum_limnia_33_41	Thaumarchaeota	VRAI	36,13
	LakeFargette_0920_ALND_scaffold_8147	LakeFargette_0920_ALND_Planctomycetes_63_28	Planctomycetes	FAUX	31,14
	LakeFargette_0920_ALND_scaffold_401388	LakeFargette_0920_ALND_Bacteria_66_32	Lentisphaerae	VRAI	30,5
	LakeFargette_0920_ALND_scaffold_625734	LakeFargette_0920_ALND_Chloroflexi_53_29	Chloroflexi	VRAI	29,39
	LakeFargette_0920_ALND_scaffold_493788	LakeFargette_0920_ALND_Nomurabacteria_33_28	Candidate Phyla Radiation	VRAI	28,01
	LakeFargette_0920_ALND_scaffold_423256	LakeFargette_0920_ALND_Chthoniobacter_flavus_63_25	Verrucomicrobia	VRAI	25,54
	LakeFargette_0920_ALND_scaffold_768437	LakeFargette_0920_ALND_Verrucomicrobia_56_25	Verrucomicrobia	VRAI	25,05
	LakeFargette_0920_ALND_scaffold_51390	LakeFargette_0920_ALND_Betaproteobacteria_62_19	Proteobacteria	VRAI	24,1
	LakeFargette_0920_ALND_scaffold_894461	LakeFargette_0920_ALND_Parcubacteria_55_23	Candidate Phyla Radiation	VRAI	23,2
	LakeFargette_0920_ALND_scaffold_695414	LakeFargette_0920_ALND_PER-ii_52_24	Candidate Phyla Radiation	VRAI	22,9
	LakeFargette_0920_ALND_scaffold_272472	LakeFargette_0920_ALND_Parcubacteria_45_23	Candidate Phyla Radiation	VRAI	22,57
	LakeFargette_0920_ALND_scaffold_76017	LakeFargette_0920_ALND_Rhodocyclales_64_19	Proteobacteria	VRAI	22,14
	LakeFargette_0920_ALND_scaffold_13249	LakeFargette_0920_ALND_Planctomycetes_59_20	Planctomycetes	VRAI	21,64
	LakeFargette_0920_ALND_scaffold_186177	LakeFargette_0920_ALND_Planctomycetes_68_24	Planctomycetes	VRAI	21,52
	LakeFargette_0920_ALND_scaffold_491135	LakeFargette_0920_ALND_Parcubacteria_41_22	Candidate Phyla Radiation	VRAI	21,32
	LakeFargette_0920_ALND_scaffold_497873	LakeFargette_0920_ALND_Gemmatimonadetes_70_15	Gemmatimonadetes	VRAI	19,55
	LakeFargette_0920_ALND_scaffold_129779	LakeFargette_0920_ALND_Parvibaculum_lavamentivorans_63_19	Proteobacteria	VRAI	19,25
	LakeFargette_0920_ALND_scaffold_214369	LakeFargette_0920_ALND_Parvibaculum_lavamentivorans_63_19	Proteobacteria	VRAI	18,62
	LakeFargette_0920_ALND_scaffold_440048	LakeFargette_0920_ALND_Alphaproteobacteria_61_16	Proteobacteria	VRAI	18,2
	LakeFargette_0920_ALND_scaffold_123941	LakeFargette_0920_ALND_RBG_16_RIF_WS3X_69_13	RIF-WS3X	VRAI	17,81
	LakeFargette_0920_ALND_scaffold_596440	LakeFargette_0920_ALND_Planctomycetia_62_14	Planctomycetes	VRAI	15,99
	LakeFargette_0920_ALND_scaffold_89631	LakeFargette_0920_ALND_Planctomycetia_62_14	Planctomycetes	VRAI	15,89
	LakeFargette_0920_ALND_scaffold_8116	LakeFargette_0920_ALND_Acidobacteria_64_15	Acidobacteria	FAUX	15,88
	LakeFargette_0920_ALND_scaffold_265761	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	15,84
	LakeFargette_0920_ALND_scaffold_274210	LakeFargette_0920_ALND_Betaproteobacteria_49_15	Proteobacteria	VRAI	15,27
	LakeFargette_0920_ALND_scaffold_897265	LakeFargette_0920_ALND_Parvibaculum_lavamentivorans_58_9	Proteobacteria	FAUX	15,12
	LakeFargette_0920_ALND_scaffold_184246	LakeFargette_0920_ALND_Verrucomicrobia_58_12	Verrucomicrobia	VRAI	14,82
	LakeFargette_0920_ALND_scaffold_312775	LakeFargette_0920_ALND_Kaiserbacteria_55_14	Candidate Phyla Radiation	VRAI	14,64
	LakeFargette_0920_ALND_scaffold_1093151	LakeFargette_0920_ALND_Methylophilales_50_13	Proteobacteria	VRAI	13,76
	LakeFargette_0920_ALND_scaffold_118019	LakeFargette_0920_ALND_Parcubacteria_54_14	Candidate Phyla Radiation	VRAI	13,7
	LakeFargette_0920_ALND_scaffold_406568	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	12,83
	LakeFargette_0920_ALND_scaffold_372729	LakeFargette_0920_ALND_UNK	Ignavibacteria	FAUX	12,75
	LakeFargette_0920_ALND_scaffold_136658	LakeFargette_0920_ALND_Deltaproteobacteria_72_12	Proteobacteria	VRAI	12,51
	LakeFargette_0920_ALND_scaffold_231019	LakeFargette_0920_ALND_Bacteria_70_12	Planctomycetes	VRAI	12,46
	LakeFargette_0920_ALND_scaffold_1067166	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	12,39
	LakeFargette_0920_ALND_scaffold_680977	LakeFargette_0920_ALND_Planctomycetia_61_12	Planctomycetes	VRAI	12,22
	LakeFargette_0920_ALND_scaffold_132528	LakeFargette_0920_ALND_Parvibaculum_62_11	Proteobacteria	FAUX	12,18
	LakeFargette_0920_ALND_scaffold_143954	LakeFargette_0920_ALND_Nitrosoarchaeum_33_12	Thaumarchaeota	VRAI	11,97
	LakeFargette_0920_ALND_scaffold_744926	LakeFargette_0920_ALND_Nitrosoarchaeum_33_12	Thaumarchaeota	VRAI	11,74
	LakeFargette_0920_ALND_scaffold_461457	LakeFargette_0920_ALND_Alphaproteobacteria_62_11	Proteobacteria	FAUX	11,57
	LakeFargette_0920_ALND_scaffold_299947	LakeFargette_0920_ALND_Planctomycetes_60_11	Planctomycetes	VRAI	11,45
	LakeFargette_0920_ALND_scaffold_720996	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	10,97
	LakeFargette_0920_ALND_scaffold_515556	LakeFargette_0920_ALND_Planctomycetes_66_10	Planctomycetes	VRAI	10,6
	LakeFargette_0920_ALND_scaffold_848823	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	10,52
	LakeFargette_0920_ALND_scaffold_857978	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	10,45
	LakeFargette_0920_ALND_scaffold_331752	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	10,32
	LakeFargette_0920_ALND_scaffold_829436	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	10,32
	LakeFargette_0920_ALND_scaffold_186100	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	10,29
	LakeFargette_0920_ALND_scaffold_518171	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	10,27
	LakeFargette_0920_ALND_scaffold_621702	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	10,24
	LakeFargette_0920_ALND_scaffold_847323	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	10,17
	LakeFargette_0920_ALND_scaffold_1067717	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	9,98
	LakeFargette_0920_ALND_scaffold_980850	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	9,85
	LakeFargette_0920_ALND_scaffold_863729	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	9,78
	LakeFargette_0920_ALND_scaffold_57619	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	9,7
	LakeFargette_0920_ALND_scaffold_537840	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	9,57
	LakeFargette_0920_ALND_scaffold_75275	LakeFargette_0920_ALND_Haliangium_ochraceum_69_9	Proteobacteria	FAUX	9,56
	LakeFargette_0920_ALND_scaffold_867308	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	9,43
	LakeFargette_0920_ALND_scaffold_915891	LakeFargette_0920_ALND_UNK	Acidobacteria	FAUX	9,42
	LakeFargette_0920_ALND_scaffold_112286	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	9,27
	LakeFargette_0920_ALND_scaffold_515120	LakeFargette_0920_ALND_Spirochaetia_49_9	Spirochaetes	VRAI	9,25
	LakeFargette_0920_ALND_scaffold_366703	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	8,92
	LakeFargette_0920_ALND_scaffold_340692	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	8,86
	LakeFargette_0920_ALND_scaffold_785936	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	8,79
	LakeFargette_0920_ALND_scaffold_500109	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	8,68
	LakeFargette_0920_ALND_scaffold_984081	LakeFargette_0920_ALND_UNK	Gemmatimonadetes	FAUX	8,65
	LakeFargette_0920_ALND_scaffold_698987	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	8,52
	LakeFargette_0920_ALND_scaffold_82079	LakeFargette_0920_ALND_Chloroflexi_57_8	Chloroflexi	FAUX	8,47
	LakeFargette_0920_ALND_scaffold_792610	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	8,45
	LakeFargette_0920_ALND_scaffold_966786	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	8,28
	LakeFargette_0920_ALND_scaffold_861196	LakeFargette_0920_ALND_Actinobacteria_42_5	Actinobacteria	FAUX	8,26
	LakeFargette_0920_ALND_scaffold_1061080	LakeFargette_0920_ALND_Planctomycetales_59_8	Planctomycetes	VRAI	8,22
	LakeFargette_0920_ALND_scaffold_1108551	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	8,22
	LakeFargette_0920_ALND_scaffold_1097660	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	8,17
	LakeFargette_0920_ALND_scaffold_79971	LakeFargette_0920_ALND_Verrucomicrobia_57_8	Verrucomicrobia	VRAI	8,1
	LakeFargette_0920_ALND_scaffold_441425	LakeFargette_0920_ALND_Planctomycetes_58_8	Planctomycetes	VRAI	8,08
	LakeFargette_0920_ALND_scaffold_95241	LakeFargette_0920_ALND_Armatimonadetes_54_8	Armatimonadetes	VRAI	8,01
	LakeFargette_0920_ALND_scaffold_27400	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,98
	LakeFargette_0920_ALND_scaffold_217289	LakeFargette_0920_ALND_Parcubacteria_36_7	Candidate Phyla Radiation	VRAI	7,97
	LakeFargette_0920_ALND_scaffold_358504	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,92
	LakeFargette_0920_ALND_scaffold_1025004	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	7,86
	LakeFargette_0920_ALND_scaffold_147053	LakeFargette_0920_ALND_Bacteria_57_7	Proteobacteria	VRAI	7,85
	LakeFargette_0920_ALND_scaffold_618165	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,73
	LakeFargette_0920_ALND_scaffold_34747	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,72
	LakeFargette_0920_ALND_scaffold_23073	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,71
	LakeFargette_0920_ALND_scaffold_191264	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,71
	LakeFargette_0920_ALND_scaffold_878114	LakeFargette_0920_ALND_Elusimicrobia_65_5	Elusimicrobia	FAUX	7,67
	LakeFargette_0920_ALND_scaffold_821632	LakeFargette_0920_ALND_Parcubacteria_52_6	Candidate Phyla Radiation	FAUX	7,54
	LakeFargette_0920_ALND_scaffold_610682	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,47
	LakeFargette_0920_ALND_scaffold_131892	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,42
	LakeFargette_0920_ALND_scaffold_237264	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	7,41
	LakeFargette_0920_ALND_scaffold_236654	LakeFargette_0920_ALND_UNK	Candidate Phyla Radiation	FAUX	7,4
	LakeFargette_0920_ALND_scaffold_1028751	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,39
	LakeFargette_0920_ALND_scaffold_225644	LakeFargette_0920_ALND_Bacteroidetes_35_6	Bacteroidetes	VRAI	7,35
	LakeFargette_0920_ALND_scaffold_778924	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,3
	LakeFargette_0920_ALND_scaffold_222078	LakeFargette_0920_ALND_Nomurabacteria_36_7	Candidate Phyla Radiation	VRAI	7,29
	LakeFargette_0920_ALND_scaffold_223589	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,25
	LakeFargette_0920_ALND_scaffold_836706	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,24
	LakeFargette_0920_ALND_scaffold_797512	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,2
	LakeFargette_0920_ALND_scaffold_1058136	LakeFargette_0920_ALND_UNK	Chloroflexi	FAUX	7,17
	LakeFargette_0920_ALND_scaffold_309233	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	7,17
	LakeFargette_0920_ALND_scaffold_408613	LakeFargette_0920_ALND_UNK	Gemmatimonadetes	FAUX	7,15
	LakeFargette_0920_ALND_scaffold_679117	LakeFargette_0920_ALND_UNK	Chloroflexi	FAUX	7,09
	LakeFargette_0920_ALND_scaffold_435731	LakeFargette_0920_ALND_UNK	Gemmatimonadetes	FAUX	7,03
	LakeFargette_0920_ALND_scaffold_313467	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	7,03
	LakeFargette_0920_ALND_scaffold_174291	LakeFargette_0920_ALND_UNK	unknown	FAUX	7,02
	LakeFargette_0920_ALND_scaffold_559607	LakeFargette_0920_ALND_Leptospira_40_6	Spirochaetes	VRAI	6,97
	LakeFargette_0920_ALND_scaffold_344979	LakeFargette_0920_ALND_UNK	unknown	FAUX	6,7
	LakeFargette_0920_ALND_scaffold_861210	LakeFargette_0920_ALND_Actinobacteria_42_5	Actinobacteria	FAUX	6,68
	LakeFargette_0920_ALND_scaffold_1102982	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,64
	LakeFargette_0920_ALND_scaffold_92228	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,64
	LakeFargette_0920_ALND_scaffold_429158	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,41
	LakeFargette_0920_ALND_scaffold_1055040	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,34
	LakeFargette_0920_ALND_scaffold_712356	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	6,34
	LakeFargette_0920_ALND_scaffold_1052743	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,31
	LakeFargette_0920_ALND_scaffold_916344	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	6,21
	LakeFargette_0920_ALND_scaffold_924620	LakeFargette_0920_ALND_UNK	unknown	FAUX	6,17
	LakeFargette_0920_ALND_scaffold_28878	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	6,1
	LakeFargette_0920_ALND_scaffold_872568	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	6,1
	LakeFargette_0920_ALND_scaffold_344650	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,08
	LakeFargette_0920_ALND_scaffold_356858	LakeFargette_0920_ALND_Chloroflexi_68_6	Chloroflexi	FAUX	6,07
	LakeFargette_0920_ALND_scaffold_603014	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	6,04
	LakeFargette_0920_ALND_scaffold_1021972	LakeFargette_0920_ALND_UNK	Bacteroidetes	FAUX	5,91
	LakeFargette_0920_ALND_scaffold_122183	LakeFargette_0920_ALND_UNK	Candidate Phyla Radiation	FAUX	5,86
	LakeFargette_0920_ALND_scaffold_624629	LakeFargette_0920_ALND_Ignavibacteriales_43_5	Ignavibacteria	FAUX	5,85
	LakeFargette_0920_ALND_scaffold_458886	LakeFargette_0920_ALND_UNK	Bacteroidetes	FAUX	5,83
	LakeFargette_0920_ALND_scaffold_524793	LakeFargette_0920_ALND_Gammaproteobacteria_39_5	Proteobacteria	FAUX	5,83
	LakeFargette_0920_ALND_scaffold_458193	LakeFargette_0920_ALND_UNK	Actinobacteria	FAUX	5,82
	LakeFargette_0920_ALND_scaffold_204951	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	5,74
	LakeFargette_0920_ALND_scaffold_634250	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	5,71
	LakeFargette_0920_ALND_scaffold_606014	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	5,68
	LakeFargette_0920_ALND_scaffold_898784	LakeFargette_0920_ALND_UNK	Lentisphaerae	FAUX	5,66
	LakeFargette_0920_ALND_scaffold_1078232	LakeFargette_0920_ALND_UNK	Bacteroidetes	FAUX	5,62
	LakeFargette_0920_ALND_scaffold_777089	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	5,51
	LakeFargette_0920_ALND_scaffold_387256	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	5,5
	LakeFargette_0920_ALND_scaffold_1035013	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	5,5
	LakeFargette_0920_ALND_scaffold_653084	LakeFargette_0920_ALND_UNK	unknown	FAUX	5,47
	LakeFargette_0920_ALND_scaffold_1008936	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	5,39
	LakeFargette_0920_ALND_scaffold_199395	LakeFargette_0920_ALND_UNK	Chloroflexi	FAUX	5,36
	LakeFargette_0920_ALND_scaffold_993087	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	5,32
	LakeFargette_0920_ALND_scaffold_437057	LakeFargette_0920_ALND_UNK	Chloroflexi	FAUX	5,29
	LakeFargette_0920_ALND_scaffold_23882	LakeFargette_0920_ALND_UNK	Bdellovibrio	FAUX	5,24
	LakeFargette_0920_ALND_scaffold_941758	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	5,18
	LakeFargette_0920_ALND_scaffold_703634	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	5,17
	LakeFargette_0920_ALND_scaffold_84111	LakeFargette_0920_ALND_UNK	Candidate Phyla Radiation	FAUX	5,1
	LakeFargette_0920_ALND_scaffold_314964	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	5,05
	LakeFargette_0920_ALND_scaffold_4142	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	4,99
	LakeFargette_0920_ALND_scaffold_905352	LakeFargette_0920_ALND_UNK	unknown	FAUX	4,88
	LakeFargette_0920_ALND_scaffold_667746	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	4,76
	LakeFargette_0920_ALND_scaffold_466018	LakeFargette_0920_ALND_UNK	Planctomycetes	FAUX	4,71
	LakeFargette_0920_ALND_scaffold_688680	LakeFargette_0920_ALND_UNK	Chloroflexi	FAUX	4,52
	LakeFargette_0920_ALND_scaffold_610251	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	4,38
	LakeFargette_0920_ALND_scaffold_760013	LakeFargette_0920_ALND_UNK	unknown	FAUX	4,29
	LakeFargette_0920_ALND_scaffold_164266	LakeFargette_0920_ALND_Parcubacteria_34_5	Candidate Phyla Radiation	FAUX	4,22
	LakeFargette_0920_ALND_scaffold_449776	LakeFargette_0920_ALND_UNK	Candidate Phyla Radiation	FAUX	4,02
	LakeFargette_0920_ALND_scaffold_19460	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	3,69
	LakeFargette_0920_ALND_scaffold_455567	LakeFargette_0920_ALND_UNK	Verrucomicrobia	FAUX	3,45
	LakeFargette_0920_ALND_scaffold_87228	LakeFargette_0920_ALND_UNK	Proteobacteria	FAUX	3,29
	LakeFargette_0920_ALND_scaffold_538712	LakeFargette_0920_ALND_UNK	Bacteroidetes	FAUX	3,2

Table S2 . Relative abundance data during monthly sampling of Lake Fargettes ("prelim", based on amplicon sequencing) and at incubation end point ("end", based on metagenomic sequencing of ribosomal protein S3). Percent change between end point and preliminary average is also shown. Only lineages

 S2

	detected	by	both	sequencing	efforts	are	shown	here.

Table S3 . Characteristics of bacterial and archaeal genomes reconstructed in this study. Table S4. Characteristics of viral (phage and eukaryotic viruses) sequences reconstructed in this study. Abbreviations: mcp -major capsid protein, vltf3 -Poxvirus Late Transcription Factor.

 S3

	lineage				prelim_relative_abundance	end_relative_abundance	percent_change
	Planctomycetes					0,063892308		0,272084772	3,258490288
	Proteobacteria					0,340461538		0,243024664	-0,286190547
	Candidate Phyla Radiation				0,001776923		0,093725909	51,74618252
	Actinobacteria					0,016492308		0,087798011	4,323573425
	Verrucomicrobia					0,002846154		0,077431372	26,20561715
	Acidobacteria					0,011692308		0,036826707	2,149652585
	Chloroflexi					0,021438462		0,035126866	0,6384975
	Gemmatimonadetes				0,005346154		0,020292756	2,795767272
	Lentisphaerae					0,045869231		0,017314442	-0,622526001
	Bacteroidetes					0,235038462		0,013364106	-0,94314077
	Spirochaetes					0,010530769			0,0077666	-0,262485045
	Armatimonadetes						9,23E-05		0,003835417	40,55035122
	Elusimicrobia					0,010492308		0,003672615	-0,649970681
	bioproject	biosample	genome_name				genome_id	lineage	gtdbtk_classification bin_length_bp	num_scaffolds	checkm_completeness_percent checkm_redundancy_percent rna_read_count
	PRJNA757735	SAMN20994847	LakeFargette_0920_ALND_Actinobacteria_63_63		None		Actinobacteria	d__Bacteria;p__Actinobacteriota;c__Acidimicrobiia;o__Acidimicrobiales;f__Ilumatobacteraceae;g__UBA668;s__ 3206627 18 93,59 2,14	2734
	PRJNA757735	SAMN20994881	LakeFargette_0920_ALND_Mycobacterium_68_14		None		Actinobacteria	d__Bacteria;p__Actinobacteriota;c__Actinomycetia;o__Mycobacteriales;f__Mycobacteriaceae;g__Mycobacterium;s__ 2909805 462 90,26 5,05	854
	PRJNA757735	SAMN20994879	LakeFargette_0920_ALND_Alphaproteobacteria_58_11		None		Alphaproteobacteria d__Bacteria;p__Proteobacteria;c__Alphaproteobacteria;o__Micavibrionales;f__UBA2020;g__PALSA-926;s__ 2110177 87 96,16 2,2	1181
	PRJNA757735	SAMN20994877	LakeFargette_0920_ALND_Alphaproteobacteria_61_16		None		Alphaproteobacteria d__Bacteria;p__Proteobacteria;c__Alphaproteobacteria;o__Micropepsales;f__Micropepsaceae;g__SZUA-430;s__ 3485382 417 76,93 2,33	3993
	PRJNA757735	SAMN20994837	LakeFargette_0920_ALND_Parvibaculum_lavamentivorans_63_19	None		Alphaproteobacteria d__Bacteria;p__Proteobacteria;c__Alphaproteobacteria;o__Parvibaculales;f__Parvibaculaceae;g__Parvibaculum;s__ 3624273 53 95,16 9,28	10245
	PRJNA757735	SAMN20994865	LakeFargette_0920_ALND_Armatimonadetes_54_8		None		Armatimonadetes	d__Bacteria;p__Armatimonadota;c__Fimbriimonadia;o__Fimbriimonadales;f__Fimbriimonadaceae;g__UBA2391;s__ 3129870 282 93,98 2,78	2147
	PRJNA757735	SAMN20994874	LakeFargette_0920_ALND_Bacteroidetes_35_6		None		Bacteroidetes	d__Bacteria;p__Bacteroidota;c__Bacteroidia;o__AKYH767;f__2-12-FULL-35-15;g__2-12-FULL-35-15;s__ 3640609 793 82,7 1,92	3650
	PRJNA757735	SAMN20994864	LakeFargette_0920_ALND_Betaproteobacteria_49_15		None		Betaproteobacteria d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Burkholderiales;f__Gallionellaceae;g__Nitrotoga;s__ 2525574 172 89,87 2,2	89
	PRJNA757735	SAMN20994844	LakeFargette_0920_ALND_Betaproteobacteria_62_19		None		Betaproteobacteria d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Burkholderiales;f__SG8-41;g__PALSA-1004;s__ 3967837 704 85,33 4,7	5537
	PRJNA757735	SAMN20994843	LakeFargette_0920_ALND_Methylophilales_50_13		None		Betaproteobacteria d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Burkholderiales;f__Methylophilaceae;g__CAILHX01;s__ 1454965 104 78,34 0,36	2656
	PRJNA757735	SAMN20994867	LakeFargette_0920_ALND_Rhodocyclales_64_19		None		Betaproteobacteria d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Burkholderiales;f__Rhodocyclaceae;g__Sulfuritalea;s__ 2912685 567 86,6 4,23	1891
	PRJNA757735	SAMN20994836	LakeFargette_0920_ALND_Burkholderiales_70_71		None		Burkholderiales	d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Burkholderiales;f__Burkholderiaceae;g__Rhizobacter;s__ 5281630 30 97,2 3,42	27443
	PRJNA757735	SAMN20994838	LakeFargette_0920_ALND_Chloroflexi_53_29		None		Chloroflexi	d__Bacteria;p__Chloroflexota;c__Anaerolineae;o__Anaerolineales;f__EnvOPS12;g__OLB14;s__ 3869740 17 97,27	2	4273
	PRJNA757735	SAMN20994863	LakeFargette_0920_ALND_Kaiserbacteria_55_14		C6		CPR (Kaiserbacteria) d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__UBA2163;g__UBA10103;s__ 867436 43 97,6744186	0	349
	PRJNA757735	SAMN20994859	LakeFargette_0920_ALND_Nomurabacteria_33_28		C9		CPR (Nomurabacteria)d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__UBA9973;g__;s__ 691430 7 95,34883721	0	68
	PRJNA757735	SAMN20994869	LakeFargette_0920_ALND_Nomurabacteria_36_7		C8		CPR (Nomurabacteria)d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__UBA9973;g__UBA9973;s__ 527439 84 86,04651163	0	411
	PRJNA757735	SAMN20994842	LakeFargette_0920_ALND_PER-ii_52_24		C2		CPR (Peribacteria)	d__Bacteria;p__Patescibacteria;c__Gracilibacteria;o__Peribacterales;f__Peribacteraceae;g__;s__ 1239242 1 97,6744186	0	648
	PRJNA757735	SAMN20994873	LakeFargette_0920_ALND_Parcubacteria_36_7		C7		CPR (Nomurabacteria)d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__UBA9973;g__UBA8515;s__ 500334 102 86,04651163	0	32
	PRJNA757735	SAMN20994841	LakeFargette_0920_ALND_Parcubacteria_41_22		C4		CPR (Vogelbacteria) d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__XYD1-FULL-46-19;g__;s__ 689206 5 97,6744186	0	277
	PRJNA757735	SAMN20994840	LakeFargette_0920_ALND_Parcubacteria_45_23		C1		CPR (Andersenbacteria) d__Bacteria;p__Patescibacteria;c__Andersenbacteria;o__UBA10190;f__UBA10190;g__HO2-45-11b;s__ 913537 4 97,6744186	0	91
	PRJNA757735	SAMN20994855	LakeFargette_0920_ALND_Parcubacteria_54_14		C3		CPR (Uhrbacteria)	d__Bacteria;p__Patescibacteria;c__ABY1;o__SG8-24;f__2-12-FULL-60-25;g__CAIXDN01;s__ 1050475 23 97,6744186	0	30
	PRJNA757735	SAMN20994839	LakeFargette_0920_ALND_Parcubacteria_55_23		C5		CPR (Parcubacteria) d__Bacteria;p__Patescibacteria;c__Paceibacteria;o__UBA9983_A;f__UBA2163;g__;s__ 694997 5 97,6744186	0	168
	PRJNA757735	SAMN20994850	LakeFargette_0920_ALND_Bacteria_57_7		None		Deltaproteobacteria d__Bacteria;p__UBA10199;c__UBA10199;o__DSSB01;f__DSSB01;g__DSSB01;s__ 2607638 385 73,03	1,78	939
	PRJNA757735	SAMN20994871	LakeFargette_0920_ALND_Deltaproteobacteria_72_12		None		Deltaproteobacteria d__Bacteria;p__Myxococcota;c__Polyangia;o__Haliangiales;f__Haliangiaceae;g__;s__ 10778332 564 93,87	5,05	12702
	PRJNA757735	SAMN20994854	LakeFargette_0920_ALND_Gemmatimonadetes_70_15		None		Gemmatimonadetes d__Bacteria;p__Gemmatimonadota;c__Gemmatimonadetes;o__Gemmatimonadales;f__Gemmatimonadaceae;g__PNKF01;s__ 3081198 56 94,82 1,2 3775
	PRJNA757735	SAMN20994853	LakeFargette_0920_ALND_Bacteria_66_32		None		Lentisphaerae	d__Bacteria;p__Verrucomicrobiota;c__Kiritimatiellae;o__UBA8416;f__;g__;s__ 5430970 42	91,39	4,05	11418
	PRJNA757735	SAMN20994878	LakeFargette_0920_ALND_Nitrospirae_57_8		None		Nitrospirae	d__Bacteria;p__Nitrospirota;c__Nitrospiria;o__Nitrospirales;f__Nitrospiraceae;g__Palsa-1315;s__ 2366434 1019 82,56	7,07	2954
	PRJNA757735	SAMN20994849	LakeFargette_0920_ALND_Bacteria_70_12		P5		Planctomycetes	d__Bacteria;p__Planctomycetota;c__UBA1135;o__PLA2;f__;g__;s__ 5498985 184	88,57	2,27	5658
	PRJNA757735	SAMN20994875	LakeFargette_0920_ALND_Planctomycetales_59_8		P8		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Pirellulales;f__Pirellulaceae;g__SXOA01;s__ 5600513 924 85,02	8,22	963
	PRJNA757735	SAMN20994880	LakeFargette_0920_ALND_Planctomycetes_58_8		P6		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Gemmatales;f__Gemmataceae;g__;s__ 6322228 792 85,57	3,95	4253
	PRJNA757735	SAMN20994868	LakeFargette_0920_ALND_Planctomycetes_59_20		P10		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Pirellulales;f__UBA7805;g__;s__ 6576304 457 89,08	4,67	1652
	PRJNA757735	SAMN20994866	LakeFargette_0920_ALND_Planctomycetes_60_11		P7		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Gemmatales;f__Gemmataceae;g__Gemmata;s__ 9797810 293 95,05 4,65	9728
	PRJNA757735	SAMN20994851	LakeFargette_0920_ALND_Planctomycetes_64_91		P4		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Phycisphaerae;o__Phycisphaerales;f__SM1A02;g__SYAC01;s__ 2801258 8 98,48	0	5670
	PRJNA757735	SAMN20994862	LakeFargette_0920_ALND_Planctomycetes_66_10		P1		Planctomycetes	d__Bacteria;p__Planctomycetota;c__MHYJ01;o__WSZJ01;f__WSZJ01;g__WSZJ01;s__ 4573548 377 86,55	2,34	5812
	PRJNA757735	SAMN20994858	LakeFargette_0920_ALND_Planctomycetes_66_46		P3		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Phycisphaerae;o__Phycisphaerales;f__Phycisphaeraceae;g__;s__ 4373169 67 96,59	1,14	9384
	PRJNA757735	SAMN20994857	LakeFargette_0920_ALND_Planctomycetes_68_24		P2		Planctomycetes	d__Bacteria;p__Planctomycetota;c__UBA1135;o__UBA1135;f__GCA-002686595;g__;s__ 4738582 62 89,78	4,84	10152
	PRJNA757735	SAMN20994860	LakeFargette_0920_ALND_Planctomycetia_61_12		P11		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Pirellulales;f__PNKZ01;g__PNKZ01;s__ 7079622 167 96,13	1,15	805
	PRJNA757735	SAMN20994872	LakeFargette_0920_ALND_Planctomycetia_62_14		P9		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Pirellulales;f__UBA7805;g__;s__ 5853981 523 95,4	4,77	377
	PRJNA757735	SAMN20994848	LakeFargette_0920_ALND_Planctomycetia_67_38		P12		Planctomycetes	d__Bacteria;p__Planctomycetota;c__Planctomycetes;o__Pirellulales;f__UBA1268;g__QWPN01;s__ 4346575 144 96,55	4,13	295
	PRJNA757735	SAMN20994882	LakeFargette_0920_ALND_Leptospira_40_6		None		Spirochaetes	d__Bacteria;p__Spirochaetota;c__Leptospirae;o__Leptospirales;f__Leptospiraceae;g__;s__ 2990272 730 88,54	0,11	13285
	PRJNA757735	SAMN20994861	LakeFargette_0920_ALND_Spirochaetia_49_9		None		Spirochaetes	d__Bacteria;p__Spirochaetota;c__Leptospirae;o__Leptospirales;f__Leptonemataceae;g__;s__ 4488021 134 95,29	0,59	7955
	PRJNA757735	SAMN20994846	LakeFargette_0920_ALND_Nitrosoarchaeum_33_12		None		Thaumarchaeota	d__Archaea;p__Thermoproteota;c__Nitrososphaeria;o__Nitrososphaerales;f__Nitrosopumilaceae;g__Nitrosarchaeum;s__ 1288093 65 91,42 1,05	658
	PRJNA757735	SAMN20994835	LakeFargette_0920_ALND_Nitrosoarchaeum_limnia_33_41	None		Thaumarchaeota	d__Archaea;p__Thermoproteota;c__Nitrososphaeria;o__Nitrososphaerales;f__Nitrosopumilaceae;g__Nitrosarchaeum;s__ 1875056 26 99,03 1,46	20465
	PRJNA757735	SAMN20994852	LakeFargette_0920_ALND_Chthoniobacter_flavus_63_25	None		Verrucomicrobia	d__Bacteria;p__Verrucomicrobiota;c__Verrucomicrobiae;o__Chthoniobacterales;f__Chthoniobacteraceae;g__Chthoniobacter;s__ 5004242 37 97,86 1,38 1440
	PRJNA757735	SAMN20994856	LakeFargette_0920_ALND_Verrucomicrobia_56_25		None		Verrucomicrobia	d__Bacteria;p__Verrucomicrobiota;c__Verrucomicrobiae;o__Chthoniobacterales;f__UBA6821;g__UBA6821;s__ 2395852 32 97,3 1,35	26
	PRJNA757735	SAMN20994876	LakeFargette_0920_ALND_Verrucomicrobia_57_8		None		Verrucomicrobia	d__Bacteria;p__Verrucomicrobiota;c__Verrucomicrobiae;o__Verrucomicrobiales;f__Verrucomicrobiaceae;g__VFKE01;s__ 3049454 387 86,62 1,36	142
	PRJNA757735	SAMN20994870	LakeFargette_0920_ALND_Verrucomicrobia_58_12		None		Verrucomicrobia	d__Bacteria;p__Verrucomicrobiota;c__Verrucomicrobiae;o__Chthoniobacterales;f__UBA6821;g__UBA6821;s__ 1904895 392 85,66 9,29	110
	PRJNA757735	SAMN20994845	LakeFargette_0920_ALND_RBG_16_RIF_WS3X_69_13		None		WS3X	d__Bacteria;p__Eisenbacteria;c__RBG-16-71-46;o__RBG-16-71-46;f__RBG-16-71-46;g__CAIXRL01;s__ 2095941 513 82,77	3,4	2424
	virus_name			virus_id	bin_length_kbp	scaffold_number	checkv_quality	checkv_completeness_percent viral_lineage		marker_gene	predicted_host	prediction_method	rna_coverage_mean	rna_coverage_breadth
	LakeFargette_0920_ALND_Phaeocystis_Virus_25_19	V1	453,941	1	High-quality	97,1	Extended Mimiviridae		vltf3	unknown Eukaryota	None	0,002428431	0,001152132
	LakeFargette_0920_ALND-Phage-like-45-26		V2	365,116	1	Medium-quality	88,82	probable Caudovirales		mcp	Bacteroidetes	gene content	0,009258397	0,004483507
	LakeFargette_0920_ALND_Euk_Virus_uncertain_35_24	V3	328,689	3	None	None	Iridoviridae (Betairidoviridae)	mcp	unknown Eukaryota	None	0,004624679	0,002360894
	LakeFargette_0920_ALND_Phage_41_43		V4	318,533	1	Medium-quality	89,55	probable Caudovirales		mcp, terminase	unknown Bacteria	None	0,061799783	0,02814779
	LakeFargette_0920_ALND_Euk-Virus-like_43_13		V5	292,118	1	Low-quality	39,18	Phycodnaviridae		mcp	unknown Eukaryota	None	0,005281401	0,001749293
	LakeFargette_0920_ALND_Euk_Virus_23_53		V6	269,488	3	None	None	Iridoviridae (Betairidoviridae)	mcp	unknown Eukaryota	None	0,006493507	0,003083625
	LakeFargette_0920_ALND_Euk_Virus_60_22		V7	264,161	3	None	None	Pitho-like virus		vltf3	unknown Eukaryota	None	0,003723773	0,0014953
	LakeFargette_0920_Bacteroidetes_Phage_31_13		V8	244,156	1	Medium-quality	83,71	probable Caudovirales		mcp, terminase	unknown Bacteria	None	0,003549093	0,00295303
	LakeFargette_0920_ALND_Euk_Virus_30_90		V9	239,893	2	None	None	None		None	unknown Eukaryota	None	0,005534385	0,003155574
	LakeFargette_0920_ALND_Euk_virus_57_23		V10	222,082	1	Low-quality	40,78	PAM superclade		mcp	unknown Eukaryota	None	0,003703837	0,001864176
	LakeFargette_0920_ALND_Bacteroidetes_Phage_34_48	V11	210,042	2	None	None	None		None	unknown Bacteria	None	0,003642571	0,001318784
	LakeFargette_0920_ALND_Virus_51_31		V12	200,528	5	None	None	None		None	unknown Eukaryota	None	0,006532251	0,003296298
	LakeFargette_0920_ALND_Bacteroidetes_Phage_34_33	V13	199,985	1	Medium-quality	66,26	probable Caudovirales		mcp, terminase	unknown Bacteria	None	0,007621287	0,003885291
	LakeFargette_0920_ALND_Euk_Virus_28_48		V14	194,208	2	None	None	None		None	unknown Eukaryota	None	0,001670896	0,000978333
	LakeFargette_0920_ALND_Potentially_Complete_Phage_38_44	V15	184,249	1	Medium-quality	70,86	probable Caudovirales		terminase	unknown Bacteria	None	0,008647521	0,004526483
	LakeFargette_0920_Potentially_Complete_Phage-like-59_217	V16	161,51	1	Complete	100	None		None	Proteobacteria	gene content	0,24485002	0,07829236
	LakeFargette_0920_Euk_virus_35_23		V17	159,398	2	None	None	None		None	unknown Eukaryota	None	0,006976832	0,002691376
	LakeFargette_0920_ALND_Virus_31_91		V18	153,302	1	Low-quality	32,65	Iridoviridae (Betairidoviridae)	mcp	unknown Eukaryota	None	0,021109747	0,008786578
	LakeFargette_0920_ALND_Phage-like_42_13		V19	134,911	1	Low-quality	26,47	None		None	unknown Bacteria	None	0,001899659	0,00161588
	LakeFargette_0920_ALND_Virus_50_31		V20	125,625	1	Low-quality	26,89	novel clade in PAM superclade	mcp	unknown Eukaryota	None	0,004399283	0,002332338
	LakeFargette_0920_ALND_Virus_30_12		V21	124,125	2	None	None	None		None	unknown Eukaryota	None	0,028645266	0,00248137
	LakeFargette_0920_ALND_Phage-like_AC_TGA_55_18	V22	113,056	1	Not-determined	None	None		None	Planctomycetes	gene content	0,028909003	0,006518893
	LakeFargette_0920_ALND_Virus_28_14		V23	106,566	1	Low-quality	32,63	MAPI superclade		mcp, vltf3	unknown Eukaryota	None	0,002086153	0,00090085
	LakeFargette_0920_ALND_Putative_Phage_57_26		V24	105,432	1	Complete	100	None		None	unknown Bacteria	None	0,008538972	0,004363002
	LakeFargette_0920_ALND_Potentially_Complete_Phage_67_101	V25	105,294	1	Complete	100	probable Caudovirales (Siphoviridae)	mcp, terminase	unknown Bacteria	None	0,0626379	0,035889983
	LakeFargette_0920_ALND_Virus_28_46		V26	100,712	1	Low-quality	21,58	Extended Mimiviridae		mcp, vltf3	unknown Eukaryota	None	0,000626479	0,000625546
	LakeFargette_0920_ALND_Phage-like_60_19		V27	79,26	1	Low-quality	35,25	None		None	unknown Bacteria	None	0,010163064	0,006156952
	LakeFargette_0920_ALND_Phage_44_31		V28	78,461	1	High-quality	100	probable Caudovirales (Siphoviridae)	terminase	Planctomycetes	crispr targeting	0,19995914	0,07282599
	LakeFargette_0920_ALND_Phage_34_28		V29	78,261	1	None	None	probable Caudovirales		mcp, terminase	unknown Bacteria	None	0,004096734	0,004088882
	LakeFargette_0920_ALND_Virus_42_12		V30	67,091	1	Low-quality	14,36	novel clade in PAM superclade	mcp	unknown Eukaryota	None	0,00061248	0,00061111
	LakeFargette_0920_ALND_Virus_49_30		V31	60,882	1	Low-quality	13,03	Extended Mimiviridae		mcp, vltf3	unknown Eukaryota	None	0,001745373	0,001084064
	LakeFargette_0920_ALND_Phage-like_59_11		V32	54,736	1	Complete	100	probable Caudovirales (Podoviridae)	terminase	Proteobacteria	gene content	0,005349357	0,002667349
	LakeFargette_0920_ALND_Likely_Planctomycete_Phage_53_37	V33	42,71	1	Medium-quality	51,4	None		None	Planctomycetes	gene content	0,004605263	0,002317958
	LakeFargette_0920_ALND_Phage_50_35		V34	39,638	1	Medium-quality	62,59	None		None	unknown Bacteria	None	0	0

Table 2: Physicochemical characteristics of the lakewater on February 2017.

November December

La première étape dans ce travail (déjà mis en place en parallèle de ma thèse) est le développement d'une méthode de purification des ALNs issus du milieu naturel. Des résultats d'approches moléculaires ont déjà été abordés dansColombet et al.,[START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF]. La microscopie électronique à transmission (Figure38-Aet B) et la microscopie à force atomique couplée à de la spectrométrie (Figure 38 C-E) ont permis de mettre en évidence une structure organisée et des molécules à la surface des ALNs. Ces résultats confirment que l'identification de ces molécules semble une étape complémentaire et importante dans l'appréhension de l'origine des ALNs et de leur rôle dans les environnements aquatiques. En se basant sur les résultats obtenus durant cette thèse, les perspectives du point de vue écologique sont celles qui pourraient permettre d'améliorer la compréhension du rôle des ALNs dans l'environnement. Ces perspectives et un travail sur la nature exacte des ALNs seront nécessaires pour, à terme, anticiper leurs dynamique et et leur impact dans des environnements en constante évolution.

Remerciements

Acknowledgments

Thank you to the anonymous reviewers for their numerous helpful suggestions.

Acknowledgments

Acknowledgments

This study benefited from equipment and technical assistance of CYSTEM platform UCA-PARTNER (University of Clermont Auvergne UCA), Clermont-Ferrand, France) and the Laboratoire Microorganismes: Genome et Environment (LMGE, UMR6023 CNRS-UCA, Clermont-Ferrand, France). The authors thanks Thomas Ruiz (LMGE) for helpful comments and discussions on the manuscript.

ACKNOWLEDGMENTS

We thank Alex Crits-Christoph, Adair Borges, Rohan Sachdeva, and Yue Clare Lou for informatics support and helpful discussions. We also thank Plateforme CYSTEM-UCA PARTNER (Clermont-Ferrand, France) for their technical support and expertise, the Innovative Genomics Institute, and the Vincent J. Coates Genomics Sequencing Laboratory at UC Berkeley. M.F., H.B., J.C., and T.S.-N. performed sample collection, incubation experiments, and microscopy. A.L.J., L.-X.C., M.C.S., and J.F.B. performed metagenomics and sequence analysis, and J.F.B carried out the manual genome curation. All authors contributed to project design and manuscript writing. J.F.B. is a founder of Metagenomi. The other authors declare no competing interests.

Funding M.F. was supported by a PhD fellowship from the CPER 2015-2020 SYMBIOSE challenge program (French Ministry of Research, UCA, CNRS, INRA, Auvergne-Rhône-Alpes Region, FEDER). This review is a contribution to the "Nanopoulpes" project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program Origins, 2020 edition. This research was also financed by the French government IDEX-ISITE initiative . Funding FE was supported by the EUed Horizon 2020 Framework Programme for Research and Innovation (Virus-X, project no. 685778). This study is a contribution to the C NO LIMIT project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program X-life, 2018 edition. Funding for sampling at Halong Bay was obtained through the French-Vietnamese Hubert Curien Partnership (Contract No. 23971TK) and the Ministry of Science and Technology of Vietnam (Contract No. 46/2012/HD-NDT). Funding Information This study was supported by the CYSTEM platform UCA-PARTNER (University of Clermont Auvergne UCA), Clermont-Ferrand, France) and the Laboratory Microorganisms: Genome and Environment (LMGE, UMR6023 CNRS-UCA, Clermont-Ferrand, France). MF was supported by a PhD fellowship from the CPER 2015-2020 SYMBIOSE challenge program (French Ministry of Research, UCA, CNRS, INRA, Auvergne-Rhône-Alpes Region, FEDER). This study is a contribution to the "C NO LIMIT" project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program X-life, 2018 edition. This research was also financed by the French government IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25). Funding Information MF was supported by a PhD fellowship from the CPER 2015-2020 SYMBIOSE challenge program (French Ministry of Research, UCA, CNRS, INRA, Auvergne-Rhône-Alpes Region, FEDER). This study is a contribution to the "C NO LIMIT" project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program X-life, 2018 edition. This study is a contribution to the "NANOPOULPE'' project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program Origines, 2020. This research was also financed by the French government IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25).

Figure 33: Dynamic of ALNs different forms function of culture medium. This dynamic was followed through time by differentiating the 2 starting inocula. UF=Ultra Filtrate. MM= Minimal Medium. Funding was provided by the Innovative Genomics Institute at UC Berkeley, the Chan Zuckerberg Biohub, and a Moore Foundation grant 71785. M.F. was supported by a Ph.D. fellowship from the CPER 2015-2020 SYMBIOSE challenge program (French Ministry of Research, UCA, CNRS, INRA, Auvergne-Rhône-Alpes Region, FEDER). M.C.S. was supported by a DFG fellowship. This study is a contribution to the "C NO LIMIT" project funded by the Interdisciplinary Mission of the French National Center of Scientific Research (CNRS) Program X-life, 2018 edition. This research was also financed by the French government IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25).

Supplemental materials

In vitro incubation, selection, and sequencing of microbial communities associated with ALNs

Lake Fargettes is an artificial and highly eutrophic freshwater lake (surface area 1.2 ha, maximum depth 2.5 m) near Neuville in the French Massif Central (45°44'24"N; 3°27'39"E;

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Data availability

Read data and draft genomes from this study are available through NCBI at PRJNA757735. Genome accession information for the 48 bacterial and archaeal genomes is also listed in Table S3 at https://zenodo.org/record/5362898#.YiuiRBPML5Y. Custom codes for the described analyses are also available on GitHub (github.com/alexanderjaffe/aln-enrichment). All supplementary figures, tables, extended data files, and genomes (including phage/viral genomes) are also available through Zenodo (https://doi.org/10.5281/zenodo.5362897).

Conflicts of Interest

The authors declare no conflict of interest Author Contributions JC and HB performed the experiments and the flow cytometric analyses. JC performed the transmission electron microscopy analyses. SB performed the cryo-transmission electron microscopy analysis. ChB and LG performed the scanning electron microscopy analysis. KB and NM performed the EFTEM and EELS analyses. JC, GI, MF, and AP analyzed samples from Ha Long Bay. FE, CoB, and VG realized genomic analyses. JC, HB, TS-N, and BV designed the research and wrote the manuscript. All authors have read, commented, and approved the final version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author's Contribution

MF, HB, MM, JC designed the study and analyzed data. All authors wrote the manuscript, contributed critically and gave final approval for publication.

Conflict of Interest

The authors declare that they have no conflict of interest.

Biotic parameters measurements

Phytoplanktonic communities

The biomasses of different groups of the Nanophytoplankton (i.e. Chlorophyceae, cyanobacteria, Cryptophyceae and diatoms) were inferred from in situ measurements of chlorophyll a, phycoerythrin and phycocyanin (μg.L-1) using a submersible spectrofluorometric probe (BBE FluoroProbe, Moldaenke GmbH, DE). Counts of picophytoplankton populations were determined by flow cytometry as described elsewhere [19] using a BD FACSCalibur (BD Sciences, San Jose, CA) equipped with an air-cooled laser, delivering 15 mW at 488 nm with the standard filter set-up.

VLP, Prokaryote, Heterotrophic eukaryote and ALN counts

Counts of VLPs, prokaryotes and heterotrophic eukaryotes (HE) were performed in triplicates by flow cytometry according to Brussaard [256] and Christaki et al.,[304] respectively using a BD FACSAria Fusion SORP (BD Sciences, San Jose, CA) equipped with an air-cooled laser, delivering 50 mW at 488 nm with 502 longpass, and 530/30 bandpass filter set-up. ALN (and their different forms) detection and quantification were realized by transmission electron microscopy (TEM) using a Jeol JEM 2100-Plus microscope (JEOL, Akishima, Tokyo, Japan) operating at 80 kV and x50,000 magnifications as described in Colombet et al., [START_REF] Colombet | Discovery of High Abundances of Aster-Like Nanoparticles in Pelagic Environments: Characterization and Dynamics[END_REF].

ALN/prokaryote ratios were determined in triplicate following uranyl salt contrasting of particles centrifuged at 18,000xg; 20 min; 14°C directly onto 400-mesh electron microscopy copper grids covered with carbon-coated Formvar film (Pelanne Instruments, Toulouse, France). The number of ALN results from the multiplication of this ratio-fold by prokaryote concentration obtained by cytometry.

Diversity of microbial communities

Nucleic acid extractions and amplifications : For each unfixed sample, microbial communities were collected on a 0.2 µm (Millipore) polycarbonate filter (until saturation, pressure < 25 kPa) and stored at -20°C until DNA extraction. The filters were covered with a lysing buffer (lysozyme 2 mg.mL -1 , SDS 0.5%, Proteinase K 100 µg.mL -1 and RNase A 8.33 µg.mL -1 in TE buffer pH 8) at 37°C for 90 minutes. A CTAB 10% / NaCl 5M solution was added, and the samples were incubated at 65°C for 30 minutes. The nucleic acids were extracted with phenolchloroform-isoamyl alcohol (25:24:1) ; the aqueous phase containing the nucleic acids was recovered and purified by adding chloroform-isoamyl alcohol (24:1).

Author's contribution MF, HB and JC designed and performed the experiments. MF and GB analyze genomic datas. MF, HB, GB, TSN and JC wrote the manuscript. All authors have read, commented, and approved the final version of the manuscript.

Conflicts of interest:

The authors declare that they have no conflict of interest.

Supplemental materials

Table S1: Primers used for the amplification and their PCR programs.

Bacteria

Archae Fungi

Forward primer

Transcriptome analysis

RNA reads were subjected to the same quality filtering pipeline referenced for DNA reads above and were subsequently mapped to the quality-filtered, de-replicated set of bacterial and archaeal genomes using bowtie2. To remove remnant rRNA and other non-mRNAs, we computed per-gene mapped read counts using pysam and removed those > 100 times the median non-zero per-gene read count for each genome. This process filtered about ~60 anomalously high-coverage ORFs, many of which corresponded to 16S rRNA or tRNA regions on scaffolds.

Read counts were then aggregated by phylum-level lineage. RNA reads were also mapped against the set of curated viral genomes described above. Mean coverage and coverage breadth were computed using CoverM (genome mode, --min-read-percent-identity 0.95 --min-coveredfraction 0).

DISCUSSION ET CONCLUSIONS GÉNÉRALES, PERSPECTIVES