Biology subjects

Chaffron, S.

Publications and source records attributed to Chaffron, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Codon usage bias maps ocean microbiome adaptation to temperature-nutrients regimes

Microbial communities underpin ocean productivity and biogeochemistry, but their functional adaptation to environmental gradients remains poorly understood. Codon usage bias (CUB), a marker of translational efficiency, constrains growth rate potential, yet its role in functional adaptation across natural communities is underexplored. By analysing 589 metagenome-derived microbial communities from the global ocean, we demonstrate that CUB in 320 metabolism-related gene groups capture genomic adaptation to distinct temperature and nutrient concentrations. We identified four adaptation signatures shaped by distinct temperature-nutrient regimes, revealing how microbes optimize protein synthesis in their ecological niche. This genome-centric approach deepens our understanding of functional adaptation in uncultured marine microbes and provides a framework to inform ocean biogeochemical models and predict microbial responses to climate-driven changes.

microbiology↗

bioRxiv2026

Satellite-gene abundance fusion reveals global hotspots of ocean ecosystem services

The Ocean sustains planetary health through climate regulation, biodiversity, and essential ecosystem services. Plankton underpins these processes by driving primary production, sustaining food webs, and mediating carbon sequestration. Yet the spatial organization of plankton-based ecosystem services remains poorly understood. The High Seas Treaty and the 30% Ocean protection target by 2030 create an urgent need for science-based guidance for global ocean governance. Here, we aim to identify key planktonic areas associated with functional diversity, net primary productivity, and carbon export globally. We used machine learning to integrate omics-derived plankton functions and satellite observations with diversity metric and ecosystem services. Leveraging metagenomic data, we identified molecular functions strongly linked to ecosystem functioning and project their global distributions across seasons. We reveal putative hotspots of functional diversity, net primary productivity, and carbon export. Our analysis pinpoints areas where all three indicators converge synchronously, predominantly along oceanographic structures such as polar fronts and principal current systems. By relying on satellite data as core input, our approach captures the temporal variability of these hotspots, providing a global, dynamic protocol for projections of plankton-based ecosystem services. These findings establish a foundation for developing integrative conservation tools based on ecosystem functioning and inform adaptive management under climate change.

ecology↗

bioRxiv2026

No-take marine reserves promote oligotrophic reef bacterioplankton communities across the Great Barrier Reef

Australias Great Barrier Reef is a biodiversity hotspot critical to ocean health, yet it faces increasing threats from climate change and localised impacts requiring effective conservation and management action. Rezoning of the Great Barrier Reef Marine Park in 2004 expanded No-Take Marine Reserves (NTMRs) to restrict extractive activities like fishing and collecting, creating one of the largest networks of marine reserves globally. Benefits like increased biomass of fisheries-targeted species and improved coral community health metrics have been reported, though the effects of zoning on water chemistry and seawater microbiology remain unexplored. Using data from the Great Barrier Reef Microbial Genomics Database, we investigated the structure of seawater microbiomes on 48 offshore reefs within NTMRs and fished reefs. A supervised classification method (MINT sPLS-DA) identified 350 indicator species that predict zoning with [~]71% accuracy (range 58-85%). Microbial communities broadly reflected reef states, with NTMR zones enriched in streamlined microbial oligotrophs (Pelagibacter and SAR86) correlating with higher cover of hard coral, crustose coralline algae, and herbivore fish abundance under lower nutrient conditions. By contrast, fished reefs harbored opportunists (Flavobacteriales, especially UA16, and Pseudomonadales) associating with elevated nutrients and turf algae cover. Co-occurrence networks revealed stronger competitive interactions in fished reefs, where nutrient-responsive taxa may outcompete other microbes, underscoring the need to investigate how these shifts influence reef nutrient cycling and function. Our findings reveal ecosystem-wide effects of marine zoning beyond fish protection, with distinct seawater microbiomes between fished reefs and NTMRs, which will help build decision tools for more targeted reef health monitoring assessments.

microbiology↗

bioRxiv2026

Multi-omics uncovers nutrient stress-driven interactions in the Prymnesium parvum holobiont, with vitamin B12 limitation highlighting mutualism.

Microalgal-bacterial interactions are central to nutrient cycling and ecosystem functioning in marine habitats, yet the mechanisms structuring these associations under defined nutrient constraints remain poorly resolved. Using a synthetic 15-member bacterial community (SynCom) and controlled nitrogen (N), phosphorus (P), and vitamin B12 limitation, we investigated how nutrient scarcity shapes the physiology, metabolism, and transcriptional activity of the harmful alga Prymnesium parvum and its associated microbiota. Under N- and P-limitation, the SynCom had minimal impact on algal growth despite nutrient-dependent shifts in toxin production and metabolite profiles. In contrast, B12-limitation triggered a strong mutualistic interaction in which the SynCom enabled a three-fold increase in algal biomass and drove restructuring of intracellular and extracellular metabolomes, including the accumulation of ectoine and membrane-associated lipids and the depletion of thiamine-like and stress-associated metabolites. Metabarcoding revealed stable community composition but enrichment of B12-producing taxa under B12-limited conditions, while metatranscriptomics uncovered functional divergence among SynCom members. Bacteria segregated into specialized B12- or N-responsive strains and metabolically plastic generalists sustaining broad transcriptional activity across all nutrient regimes. B12 producers (Marinovum algicola, Roseobacter sp., Halomonas sp.) upregulated cobalamin biosynthesis exclusively under B12 limitation, whereas several dependent taxa induced B12 transport and B12-requiring enzymes, indicating active vitamin exchange within the holobiont. P. parvum displayed nutrient-specific transcriptional programs, with B12-limited co-cultures shifting toward growth-associated gene expression despite constitutive expression of the B12-dependent metH gene. These results demonstrate that vitamin auxotrophy acts as a key metabolic lever reorganizing holobiont function, driving reciprocal benefits and reprogramming algal-bacterial metabolism in our synthetic system.

microbiology↗

bioRxiv2025

MIMEco: Multi-objective metabolic modeling to predict and explain pairwise interactions

Genome-scale metabolic models (GEMs) provide a mechanistic framework for quantitatively exploring an organisms physiology and its interactions with the environment. However, their use in microbial community modeling has been limited since it usually relies on community-wide objective functions or the integration of community abundance data. Nevertheless, predicting microbial interactions is crucial for understanding ecosystem dynamics, and thus requires dedicated methods. Here, we introduce MIMEco (Metabolic Interaction Modeling in Ecosystems), an open-source Python package that predicts pairwise microbial interactions through multi-objective optimization. MIMEco does not require abundance data, provides a user-friendly workflow, and predicts interaction types, strengths, and exchanged metabolites directly from Pareto fronts. In this study, MIMEco is validated by replicating experimental results of an in vitro co-culture of two auxotrophic Escherichia coli strains. By combining mechanistic inference with usability, MIMEco makes metabolic interaction modeling accessible to non-specialists while remaining flexible for experts, establishing a versatile platform for advancing metabolic ecology across biomedical and environmental fields. IMPORTANCEDeciphering microbial interactions through in vitro experiments is often costly and limited in scope, while existing bioinformatics tools can be complex to use or limited by actual sample data. MIMEco offers an open-source and user-friendly multi-objective framework for predicting and quantifying pairwise microbial ecosystem interactions and nutrient exchanges. We demonstrate its reliability by replicating a well-characterized laboratory experiment, showing that MIMEco can accurately reflects real biological behavior. This tool improves the communitys ability to explore and understand metabolic interaction mechanisms underpinning microbial ecosystems.

bioinformatics↗

bioRxiv2025

Genomics-based quantitative biogeography of marine plankton

Marine plankton are key drivers of ocean productivity and global carbon cycling, yet their quantitative biogeography remains poorly characterized. Environmental genomic datasets are inherently compositional, restricting analyses to relative abundances and limiting their integration into ecological and biogeochemical models. Here we combine DNA mass measurements, filtered seawater volumes, and metagenomic relative abundances to generate absolute estimates of cell concentrations and carbon biomass of plankton across the global ocean. Leveraging thousands of samples, this approach provides quantitative estimates for hundreds of eukaryotic and thousands of prokaryotic environmental genomes, unveiling ecological associations not captured by compositional data. Using the psbO marker gene, we reconstruct quantitative biogeographies of photosynthetic lineages and, through global-scale modeling, project their distributions to generate quantitative maps of phytoplankton communities across the worlds ocean. By bridging genomic data with biogeochemical metrics, this study provides novel resources for integrating plankton at genomic resolution into next-generation biogeochemical models.

genomics↗

bioRxiv2025

Ecological processes shaping marine microbial assemblages diverge between equatorial and temperate time-series

Marine microbial communities are structured by a complex interplay of deterministic and stochastic processes, yet how these vary across latitudes remains poorly understood. Most long-term microbial observatories are restricted to temperate regions, limiting our ability to assess latitudinal contrasts in microbial dynamics. Here, we compare coastal microbial communities from two contrasting marine time-series stations using standardized molecular protocols: a new tropical site in the Equatorial Atlantic (EAMO, 6{degrees}S) and a well-studied temperate site in the Mediterranean Sea (BBMO, 41{degrees}N). Monthly 16S and 18S rRNA gene sequencing of two size-fractions (0.22-3 {micro}m and >3 {micro}m) over 41 months (from April 2013 to August 2016) revealed marked differences in taxonomic composition, temporal variability, and ecological assembly processes. Temperate communities exhibited strong seasonal turnover, higher beta-diversity, and tighter coupling with environmental variables such as temperature and daylength. In contrast, tropical communities were compositionally more stable and more governed by biotic factors and stochastic processes such as historical contingency and ecological drift. These patterns were consistent across taxonomic domains and size-fractions, though selection was generally stronger in prokaryotes and the smallest size-fraction. Co-occurrence networks at the temperate site were more densely connected and environmentally responsive compared to tropical networks, where stochastic processes and putative biological interactions gain prominence. This study highlights the importance of integrating observatories from underrepresented latitudes into global microbial monitoring efforts, particularly as climate change alters the amplitude and frequency of environmental drivers across the ocean.

ecology↗

bioRxiv2025

MicrobioRel: A Set of Datasets for Microbiome Relation Extraction

Biomedical knowledge curation relies on a variety of Natural Language Processing tasks, including biomedical entity recognition and document-level relation extraction. With the growing size and capabilities of Language Models, effectively deploying them in specific and specialised domains remains a persistent challenge, highlighting the need for high-quality, domain-adapted datasets. In this work, we present MicrobioRel, a corpus of two datasets to study the relations between biological entities in the gut microbiome. The first dataset, MicrobioRel-cur, is a document-level labelled corpus, corresponding to paragraphs from journal articles that were manually annotated with different types of relations between biomedical concepts in the gut microbiome domain. We describe its creation process, annotation guidelines, and key statistics. On this dataset, we evaluated different architectures for relation extraction and identify PubMedBERT as the most effective model for this task. We also created a second dataset, MicrobioRel-pred, by generating relation predictions on other journal articles using the fine-tuned PubMedBERT model. We demonstrate its potential to extract meaningful interactions. The MicrobioRel is a crucial resource for advancing tasks like automatic knowledge extraction in specialised domains such as the gut microbiome, facilitating hypothesis generation and supporting scientific discovery.

bioinformatics↗

bioRxiv2025

Diatoms vs dinoflagellates: a temporal network analysis of bloom impacts on diversity and phytoplankton community structure in French coastal waters

Understanding phytoplankton community responses to bloom events is essential as these have major implications for biogeochemical cycles, marine food webs, but can also be harmful to ecosystems, the economy, and public health. Diatoms and dinoflagellates are the two most common bloom-forming classes, with distinct ecologies and bloom dynamics. Using time series from a long-term phytoplankton monitoring survey (REPHY) of French coastal waters analysed with ecological association networks and diversity metrics, we investigated how blooms of diatoms and dinoflagellates affect diversity and community structure within phytoplankton communities. We highlight distinct responses: an increase in species richness during diatom blooms and a decrease during dinoflagellate blooms. However, both bloom types resulted in a decrease in alpha diversity indices. Temporal association networks modularity and association strength were also differently impacted between both bloom types. However, high-level association types and composition in association networks remain stable, suggesting an important role of their proportions in ecosystem functioning and resilience. We propose several hypotheses for these findings based on known ecological and biological processes, that remain to be tested individually in dedicated studies. Our work underlines the importance of distinguishing the different types of blooms and studying the role of interactions between phytoplankton for a better understanding of their dynamics.

ecology↗

bioRxiv2025

Co-occurrence drives horizontal gene transfer among marine prokaryotes

Understanding the drivers and consequences of horizontal gene transfer (HGT) is a key goal of microbial evolution research. Although co-occurring taxa have long been appreciated to undergo HGT more often, this association is confounded with other factors, most notably their phylogenetic relatedness. To disentangle these factors, we analyzed 15,339 marine prokaryotic genomes (mainly bacteria) and their distribution in the global ocean. We identified HGT events across these genomes and enrichments for functions previously shown to be prone to HGT. By mapping metagenomic reads from 1,862 ocean samples to these genomes, we also identified co-occurrence patterns and environmental associations. Although we observed an expected negative association between HGT rates and phylogenetic distance, we only detected an association between co-occurrence and phylogenetic distance for closely related taxa. This observation refines the previously reported trend to closely related taxa, rather than a consistent pattern across all taxonomic levels, at least here within marine environments. In addition, we identified a significant association between co-occurrence and HGT, which remains even after controlling for phylogenetic distance and measured environmental variables. In a subset of samples with extended environmental data, we identified higher HGT levels associated with particle-attached bacteria and associations of varying directions with specific environmental variables, such as chlorophyll a and photosynthetically available radiation. Overall, our findings demonstrate the significant influence of ecological associations in shaping marine bacterial evolution through HGT.

evolutionary biology↗

bioRxiv2024

Patterns and drivers of diatom diversity and abundance in the global ocean

Diatoms constitute one of the most diverse and ecologically important phytoplankton groups, yet their large-scale diversity patterns and drivers of abundance are unclear due to limited observations. Here, we utilize Tara Oceans molecular and morphological data, spanning pole to pole, to describe marine diatom diversity, abundance, and environmental adaptation and acclimation strategies. The dominance of diatoms among phytoplankton in terms of relative abundance and diversity was confirmed, and the most prevalent genera were Chaetoceros, Thalassiosira, Actinocyclus and Pseudo-nitzschia. We defined 25 distinct diatom communities with varying environmental preferences illustrative of different life strategies. The Arctic Ocean stands out as a diatom hotspot with 6 of the diatom communities being exclusive to it. Light harvesting and photoprotection were among the cellular functions in which natural diatom populations invested the bulk of their transcriptional efforts. This comprehensive study sheds light on marine diatom distributions, offering insights to assess impacts of global change and oceanic anthropogenic impacts.

ecology↗

bioRxiv2023

Community metabolic modeling of host-microbiota interactions through multi-objective optimization

The human gut microbiota comprises various microorganisms engaged in intricate interactions among themselves and with the host, affecting its health. While advancements in omics technologies have led to the inference of clear associations between microbiome composition and health conditions, we usually lack a causal and mechanistic understanding of these associations. For modeling mechanisms driving the interactions, we simulated the organisms metabolism using in silico Genome-Scale Metabolic Models (GEMs). We used multi-objective optimization to predict and explain metabolic interactions among gut microbes and an intestinal epithelial cell. We developed a score integrating model simulation results to predict the type (competition, neutralism, mutualism) and quantify the interaction between several organisms. This framework uncovered a potential cross-feeding for choline, explaining the predicted mutualism between Lactobacillus rhamnosus GG and the epithelial cell. Finally, we analyzed a five-organism ecosystem, revealing that a minimal microbiota can favor the epithelial cells maintenance.

systems biology↗

bioRxiv2023

Genome-scale community modelling reveals conserved metabolic cross-feedings in epipelagic bacterioplankton communities

Marine microorganisms form complex communities of interacting organisms that influence central ecosystem functions in the ocean such as primary production and nutrient cycling. Identifying the mechanisms controlling their assembly and activities is a major challenge in microbial ecology. Here, we integrated Tara Oceans meta-omics data to predict genome-scale community interactions within prokaryotic assemblages in the euphotic ocean. A global genome-resolved co-activity network revealed a significant number of inter-lineage associations across large phylogenetic distances. Identified co-active communities included species displaying smaller genomes but encoding a higher potential for quorum sensing, biofilm formation, and secondary metabolism. Community metabolic modelling revealed a higher potential for interaction within co-active communities and pointed towards conserved metabolic cross-feedings, in particular of specific amino acids and group B vitamins. Our integrated ecological and metabolic modelling approach indicates genome streamlining and metabolic auxotrophies as central joint mechanisms shaping bacterioplankton community assembly in the surface global ocean.

ecology↗

bioRxiv2023

PhotoEukStein: Towards an omics-based definition of unicellular eukaryote phototrophs functional traits via metabolic modelling

Defining biological functional traits for unicellular organisms relies on comprehending the set and combination of the biochemical reactions their genomes encode for. This network of biochemical reactions defines the metabolic strategy organisms and communities use. Understanding the functional traits of unicellular organisms involves studying the combination of biochemical reactions encoded in their genomes. These reactions determine the metabolic strategy that organisms and communities use to grow in a specific environment. While prokaryotes have been extensively studied for their metabolic networks, eukaryotes have lagged behind due to the complexity of their genomes and the need for a better understanding of their metabolism. We have created PhotoEukstein, a meta-metabolic model for unicellular phototrophic eukaryotes. This meta-model enables quick and automated derivation of Genome-Scale Metabolic models directly from genomes. We have used it to analyse 533 environmental genomes and marine eukaryotic unicellular plankton transcriptomes. These models can help predict functional traits that cannot be purely deducted from taxonomic information or the listing of metabolic reactions encoded by the genome. They provide the opportunity to build connections with Earth System Models to pinpoint environmental parameters to capture specific functional traits.

systems biology↗

bioRxiv2023

Loss of the benthic life stage in Medusozoa and colonization of the open ocean

In marine environments, life cycle strategies strongly impact species dispersal and their ability to colonize new habitats. Pelagic medusozoans (jellyfish and siphonophores) exhibit various reproductive strategies, variations of meroplanktonic and holoplanktonic life cycles. In the ancestral meroplanktonic life cycle, a benthic polyp stage alternates with a pelagic medusa stage. During the course of evolution, some medusozoans lost their benthic stage, leading to a holoplanktonic life cycle. The ecological consequences of these losses have not been addressed at global scale. Here, integrating metabarcoding and environmental data from Tara Oceans into a phylogenetic framework, we show that each convergent transition toward a holoplanktonic life cycle is associated with a more offshore distribution compared to meroplanktonic medusozoans. Our analyses showed that holoplanktonic medusozoans are more globally distributed and relatively more abundant than meroplanktonic medusozoans, although they are less diversified and occupy a more peripheral position in a global plankton community interactome. This suggests that holoplanktonic medusozoans have acquired a greater tolerance to biotic and abiotic conditions. Overall, our results demonstrate the relationship between medusozoan life cycles, distribution, and biotic interactions, suggesting that the loss of the benthic stage promoted colonization of the open ocean.

evolutionary biology↗

bioRxiv2023

Genomic adaptation of giant viruses in polar oceans

Despite being perennially frigid, polar oceans form an ecosystem hosting high and unique biodiversity. Various organisms show different adaptative strategies in this habitat, but how viruses adapt to this environment is largely unknown. Viruses of phyla Nucleocytoviricota and Mirusviricota are groups of eukaryote-infecting large and giant DNA viruses with genomes encoding a variety of functions. Here, by leveraging the Global Ocean Eukaryotic Viral database, we investigate the biogeography and functional repertoire of these viruses at a global scale. We first confirm the existence of an ecological barrier that clearly separates polar and nonpolar viral communities, and demonstrate that temperature drives dramatic changes in the virus-host network at the polar/nonpolar boundary. Ancestral niche reconstruction suggests that adaptation of these viruses to polar conditions has occurred repeatedly over the course of evolution, with polar-adapted viruses in the modern ocean being scattered across their phylogeny. Numerous viral genes are specifically associated with polar adaptation, although most of their homologues are not identified as polar-adaptive genes in eukaryotes. These results suggest that giant viruses adapt to cold environments by changing their functional repertoire, and this viral evolutionary strategy is independent of the polar adaptation of their hosts.

microbiology↗

bioRxiv2022

Global observation of plankton communities from space

Satellite remote sensing from space is a powerful way to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here we present an approach to identify representative communities from a global plankton network that included both zooplankton and phytoplankton and using global satellite observations to predict their biogeography. Six representative plankton communities were identified from a global co-occurrence network inferred using a novel rDNA 18S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to train a model that predicted these representative communities from satellite data. The model showed an overall 67% accuracy in the prediction of the representative communities. The prediction based on 17 satellite-derived parameters showed better performance than based only on temperature and/or the concentration of chlorophyll a. The trained model allowed to predict the global spatiotemporal distribution of communities over 19-years. Our model exhibited strong seasonal changes in the community compositions in the subarctic-subtropical boundary regions, which were consistent with previous field observations. This network-oriented approach can easily be extended to more comprehensive models including prokaryotes as well as viruses.

ecology↗

bioRxiv2022

Combined in vivo and in situ genome-resolved metagenomics reveals novel symbiotic nitrogen fixing interactions between non-cyanobacterial diazotrophs and microalgae

BackgroundNon-cyanobacteria diazotrophs (NCDs) were shown to dominate in surface waters shifting the long-held paradigm of cyanobacteria dominance and raising fundamental questions on how these putative heterotrophic bacteria thrive in sunlit oceans. The absence of laboratory cultures of these bacteria significantly limits our ability to understand their behavior in natural environments and, consequently, their contribution to the marine nitrogen cycle. ResultsHere, we used a multidisciplinary approach and report an unprecedented finding in the diatom Phaeodactylum tricornutum (Pt) of NCDs in the phycosphere or the pelagic community sustaining its survival in the absence of bioavailable nitrogen. We sequenced the bacterial metacommunity associated with Pt and assembled several bacterial genomes, identifying multiple NCDs from the Rhizobiales order, including Bradyrhizobium, Mesorhizobium, Georhizobium and Methylobacterium. We demonstrated the nitrogen-fixing ability of PtNCDs through in silico identification of nitrogen fixation genes, or by using PCR, acetylene reduction, or 15N incorporation. We showed the wide occurrence of this type of interactions with the isolation of NCDs from other microalgae, their identification in the environment, and their predicted associations with photosynthetic microalgae. ConclusionsOur study underscores the importance of microalgae interactions with NCDs to permit and support nitrogen fixation. This work provides a unique model Pt-NCDs to study the ecology of this interaction advancing our understanding of the key drivers of global marine nitrogen fixation.

microbiology↗