ISME Communications

Microbial plankton play fundamental roles in biogeochemical cycles, driving nutrient cycling that influences the global climate and supports life on Earth. Picoplankton are the smallest and most abundant planktonic organisms. The distribution and ecology of these organisms is determined by environmental factors and their biogeography is largely shaped by basin-scale patterns of physicochemical composition of ocean waters. The increased availability of high-throughput sequencing data of microbial communities has enabled the description of how the global oceans are partitioned into distinct microbial biogeographical provinces. However, the key attributes associated with such provinces are still unclear. Here we present a model of picoplankton biogeography based on 1454 metagenomes from multiple sampling consortia, resulting in the largest integrated surface ocean metagenome analysis to date. We identify ten distinct groups based on metagenomic dissimilarity, divided into three categories: polar (Arctic and Antarctic), temperate (coastal temperate, temperate/subtropical transition, oceanic temperate, Mediterranean-like) and tropical (tropical low nutrient, tropical high nutrient, subtropical oceanic gyres). Using machine learning and omics data integration techniques, we predict province areas across the surface oceans and describe their environmental, taxonomical, and functional features. We quantify the relationship between environmental factors and each biogeographical province, identify their main representative taxa and the importance of carbon degradation and antimicrobial resistance pathways in functional community composition, and discuss implications for establishing a model for global picoplankton biogeography.

The bathypelagic ocean (1000-4000 m depth) is the largest aquatic biome on Earth but it is still largely unexplored. Due to its prevalent low dissolved organic carbon concentrations, most of the prokaryotic metabolic activity is assumed to be associated to particles. The role of free-living prokaryotes has thus been mostly ignored, except that of some chemolithoautotrophic lineages. Here we used a global bathypelagic survey of size-fractionated metagenomic and 16S (genes and transcripts) data and performed a differential abundance analysis to explore the functional traits of the different prokaryotic life-strategies, their contribution to the active microbiome, and the role that the quality of the dissolved organic matter (DOM) plays in driving this contribution. We found that free-living prokaryotes have limited capacity to uplift their metabolism in response to environmental changes and display comparatively lower growth rates than particle associated prokaryotes, but are responsible for the synthesis of vitamins in the bathypelagic. Furthermore, their contribution to the active prokaryotic microbiome increased towards waters depleted of labile DOM, which represented a large fraction of the tropical and subtropical ocean sampled stations. This points to a relevant yet overlooked role of free-living prokaryotes in DOM cycling in the vast bathypelagic desert.

The surface ocean exhibits strong vertical gradients in light, nutrients, and temperature, shaping the phytoplankton distribution which often defines a deep chlorophyll maximum (DCM). Aerobic anoxygenic phototrophic (AAP) bacteria inhabit the euphotic zone, with their abundances following the chlorophyll a variability. While AAP bacterial communities are known to differ across regions with contrasting environmental conditions, their vertical distribution remains poorly understood. We hypothesized that the diversity and community structure of AAP bacteria would vary across the vertical gradient, in relation to changes in environmental variables and following the DCM profile. To test this hypothesis, we studied the composition of AAP communities at different depths along the DCM structure in the South and Central Atlantic Ocean, by means of amplicon sequencing of the pufM gene. The results show significant differences in richness, community structure, and taxonomic composition of samples from different layers of the DCM, highlighting the dependance of AAP bacteria on its structure. Remarkably, the use of primers with broad phylogenetic coverage enabled the recovery of several phylogroups previously detected only through metagenomics. We show that they represent a significant fraction of marine AAP communities, provide clues on their ecological preferences, and confirm their association with the family Candidatus Luxescamonaceae, with genomic potential for carbon fixation.

Myxococcota are globally distributed bacteria renowned for their remarkable ecological and biotechnological significance due to their complex lifestyles, social behaviour, and secondary metabolite production. Despite their ubiquity in diverse environments, including soil, marine, and extreme habitats, their diversity and ecological roles remain underexplored. Here, we utilized the Microflora Danica dataset, encompassing >10,000 metagenomes and >400 rRNA gene datasets from various environments in Denmark, to investigate the distribution, diversity, and metabolic potential of Myxococcota. We show that Myxococcota are ubiquitous but strongly structured by environment, with soil-associated lineages enriched in predatory and multicellular development traits, whereas aquatic-associated taxa exhibit alternative lifestyles, including anaerobic metabolism and phototrophy. Comparative genomic analysis reveals widespread potential for secondary metabolite production, hydrocarbon degradation, and organohalide transformation, alongside diverse contribution to carbon and nutrient cycling. Together, these findings redefine Myxococcota as a functionally diverse and ecologically differentiated phylum, extending beyond canonical predation and multicellularity, and underscore their promise as large reservoir of unexplored functional potential for biotechnological applications in drug discovery and environmental remediation.

Hydrocarbons are vital for energy production and lead to serious environmental issues due to pollution. Microorganisms largely drive the production and degradation of hydrocarbons, yet little is known about viral contributions to hydrocarbon degradation. Here we identified 786 viral contigs from IMG/VR(v4), encoding five aerobic (alkB, ladA, almA, ndoB and dszC) and three anaerobic (bssA, ebdA and abcA) hydrocarbon-degrading genes (HDGs). vOTUs encoding HDGs span 26 distinct viral families, including 249 are mainly associated with host-associated environment and 463 are derived from aquatic habitat, respectively, implying that these viruses are broadly engaged in hydrocarbon-degradation processes across the entire biosphere. alkB (35%) and almA (28%) was tended to be encoded by Schizomimiviridae, bssA was tended to be encoded by T5-like bacteriophages (29%) and SPO1-like bacteriophages (22%), suggesting that the carriage of HDGs by viruses exhibits taxonomic specificity. With respect to host associations, Pseudomonadota and Bacillota constitute the two main potential host lineages, associated with 268 and 71 vOTUs, respectively. The profiling of ecological footprint reveals that viruses contribute a total of up to 30% gene abundance and 32% transcribing activity to hydrocarbon degradation in the global ocean. This study systematically revealed the distribution, diversity, virus-host correlation and activity of virus-encoded HDGs, underscoring the significant role of viruses in hydrocarbon metabolism on a global scale.

Viruses shape microbial community structures, impacting metabolic pathways and influencing biogeochemical cycles. Despite their importance, the influence of biotic and abiotic factors on viral community structures across environmental gradients in soil is relatively unknown compared to their prokaryotic hosts. While soil pH strongly influences microbial community structure, it is unclear whether there is a similar influence on soil virus communities. In this study, prokaryotic and viral communities were characterized in soils sampled from the extremes of a long-term pH-manipulated soil gradient (pH 4.5 and 7.5), and viral populations were compared to those in a variety of soil ecosystems ranging in pH (4.0 - 7.5). Prokaryotic and viral community structure were significantly influenced by soil pH at the local scale. Of 1,910 viral operational taxonomic units (vOTUs), 99% were restricted to pH 4.5 or 7.5 soil only. These were compared in gene sharing networks of populations from six other European and North American soil systems. A selection of viral clusters from acidic and neutral pH soils were more associated with those from the local gradient pH 4.5 or 7.5 soils, respectively. Results indicate that as with prokaryotes, soil pH is a factor structuring viral communities at the local and global scale.

The coupling between ocean and atmosphere across the strong seasonal gradients in the Arctic is poorly understood. Here, we explored the microbial and glycobiological connectivity between the sea surface microlayer (SML), the underlying seawater (ULW), snow, and aerosol particles in Kongsfjorden (Svalbard, 79{degrees}N) during autumn and spring. The marked overlap between marine and atmospheric microbiomes illustrates considerable sea-air transfer, linked to seasonally distinct environmental communities. For instance, Polaribacter and Formosa were aerosolized during the spring bloom, compared to Colwellia in autumn. Air-mass trajectories and microbial source tracking revealed a greater marine contribution in autumn, whereas spring aerosols were shaped by stronger winds and the cryosphere. Aerosol particles nonetheless contained numerous unique taxa, including Actinobacteria likely originating from terrestrial sources. Linking bacterial, microeukaryotic, carbohydrate, and meteorological dynamics established an overarching perspective across seasons and habitats, identifying four distinct ecosystem states. Genome-sequenced bacterial model isolates, representing key environmental populations, encode adaptive traits such as carotenoid and ectoine biosynthesis, supporting survival in the SML and atmospheric transfer. Comparison with time-series records from the nearby Fram Strait revealed that many aerosolized bacteria are consistent microbiome components; with implications for ecology and biogeochemistry across the wider Arctic.

The keystone species concept suggests that certain members of an ecological community, despite their low abundance, exert disproportionately large effects on species diversity and composition. In microbial ecology, experimental validation of this concept is limited due to significant technical challenges associated with selective species manipulation. Here, we tested this concept within a soil microbial food web by selectively suppressing a protist predator using phototoxicity induced by excessive excitation light during fluorescence microscopy within a microfluidic soil chip system. We targeted a Hypotrichia ciliate taxon--presumed primarily bacterivorous under our experimental conditions--and combined microscopy with metabarcoding of multiple microbial trophic levels to evaluate the effects of this suppression on microbial community abundance, diversity, and composition. Over the 20-day incubation, the chip system supported complex communities of bacteria, fungi, and protists. Following Hypotrichia suppression, two distinct ecological responses were observed: first, an increase in flagellate abundance that was consistent with mesopredator release and accompanied a significant rise in overall protist diversity; second, a convergence in protist community composition, indicative of biotic homogenization. Surprisingly, bacterial community abundance, richness, and composition remained unaffected, likely due to compensatory predation by increased numbers of bacterivorous flagellates. In contrast, fungal diversity decreased following Hypotrichia suppression, presumably resulting from the altered protist communities that favored facultative fungal consumers. Collectively, these findings provide direct experimental evidence that low-abundance microbial predators can function as keystone species, modulating predator community composition and diversity and having cascading effects on lower trophic levels within the brown microbial food web.

Marine viruses are key players of ocean biogeochemistry, profoundly influencing microbial community ecology and evolution. Despite their importance, few studies have explored the temporal dynamics of viral genome abundances in marine environments. Viral dynamics are complex, influenced by multiple factors such as host population dynamics and environmental conditions. To disentangle the complexity of viral communities, we developed an unsupervised machine learning framework to classify viral genomes into "chronotypes" based on temporal abundance patterns. Analysing an inter-seasonal monthly time-series of surface viral metagenomes from the Western English Channel, we identified chronotypes and compared their functional and evolutionary profiles. Results revealed a consistent annual cycle with steep compositional changes from winter to summer and steadier transitions from summer to winter. Seasonal chronotypes were enriched in potential auxiliary metabolic genes like ferrochelatases and 2OG-Fe(II) oxygenases compared to non-seasonal types. Chronotypes clustered into four groups based on their correlation profiles with environmental parameters, primarily driven by temperature and nutrients. Viral genomes exhibited a rapid turnover of polymorphisms, akin to Red Queen dynamics. However, within seasonal chronotypes, some sequences exhibited annual polymorphism recurrence, which declined over a 16-month period, suggesting that a fraction of the seasonal viral populations evolve more slowly. Classification into chronotypes revealed viral genomic signatures linked to temporal patterns, likely reflecting metabolic adaptations to environmental fluctuations and host dynamics. This novel framework enables the identification of long-term trends in viral composition, environmental influences on genomic structure, and potential viral interactions.

BackgroundBacteria of the Candidate Phyla Radiation (CPR), constituting about 25% of the bacterial biodiversity, are characterized by small cell size and patchy genomes without complete key metabolic pathways, suggesting a symbiotic lifestyle. Gracilibacteria (BD1-5), which are part of the CPR branch, possess alternate coded genomes and have not yet been cultivated. However, besides genomic evidence, little is known about the lifestyle of Gracilibacteria, their temporal dynamics, and activity in natural ecosystems, particularly in groundwater, where they were initially been genomically resolved. Therefore, we here aimed to investigate Gracilibacteria activity in situ and to discern expressed genes involved in their lifestyle, using the metaproteogenome of Gracilibacteria as a function of time in the cold-water geyser Wallender Born in the Volcanic Eifel region in Germany. ResultsWe coupled genome-resolved metagenomics and metaproteomics to investigate a cold-water geyser microbial community enriched in Gracilibacteria across a 12-day time-series. Groundwater was collected and sequentially filtered to fraction CPR and other bacteria. Based on 670 Gbps of metagenomic data, 1129 different ribosomal protein S3 marker genes and 751 high-quality genomes (123 population genomes after dereplication), we identified dominant bacteria belonging to Galionellales and Gracilibacteria along with keystone microbes, which were low in genomic abundance but substantially contributing to proteomic abundance. Seven high-quality Gracilibacteria genomes showed typical limitations, such as limited amino acid or nucleotide synthesis, in their central metabolism but no co-occurrence with potential hosts. The genomes of these Gracilibacteria encoded for a high number of proteins related to a symbiotic or even predatory lifestyle, e.g., type IV and type II secretion system subunits and features related to cell-cell interactions and cell motility, which were also detected on protein level. ConclusionsCoupling metagenomics to metaproteomics enabled us to identify microbial keystone taxa in a high-CO2 aquifer, and to reveal microbial dynamics of Gracilibacteria. We posit that Gracilibacteria might be successful microbial predators in this ecosystem, potentially aiding in population control of this highly perturbed microbial geyser community from the deep biosphere.

Understanding how microbial populations respond to disturbances represents a major goal for microbial ecology. While several theories have been advanced to explain microbial community compositional changes in response to disturbances, appropriate data to test these theories is scarce, especially when considering the challenges to define rare vs. abundant taxa and generalists vs. specialists, a prerequisite for testing the theories. Here, we define these two key concepts by employing the patterns of coverage of a (target) genome by a metagenome to define rare populations, and by borrowing concepts from macroecology, the proportional similarity index (PS index), to define generalists. Using these concepts, we found that coastal microbial communities are resilient to major perturbations such as tropical cyclones and (uncommon) cold or warm weather events snaps-in part-due to the response of rare populations, providing support for the insurance hypothesis (i.e., the rare biosphere has the buffering capacity to mitigate the effects of disturbances). Generalists appear to contribute proportionally more than specialists to community adaptation to perturbations like warming, supporting the disturbance-specialization hypothesis, i.e., disturbance favors generalists. Taken together, our results advance understanding of the mechanisms governing microbial populations dynamics under changing environmental conditions and have potential applications for ecosystem management.

Microbial cultivation remains essential for understanding the physiology, ecology, and biotechnological potential of environmental microbes, yet conventional plate-based methods (CPM) recover only a minute fraction of the environmental microbiome. Polar regions, particularly Arctic soils, represent unique reservoirs of "microbial dark matter" that remain challenging to cultivate, owing to oligotrophic conditions, low temperatures and freeze-thaw cycles that impose severe physiological constraints on microbial growth. Here, we report the first systematic application of microfluidic droplet technology (MDT) to Arctic active-layer soil microbiota and benchmark its performance against CPM using identical starting cell numbers, R2A medium, and incubation at 15{degrees}C. MDT achieved 6.5- to 8.1-fold higher recovery rates than CPM and improved isolation throughput by >180-fold. Near-full-length 16S rRNA gene sequencing (PacBio) revealed that MDT recovered significantly higher taxonomic richness across all taxonomic levels, with 256 genera detected in the high-cell-input group (DropAS_H) versus 211 in the corresponding plate group (PlateAS_H). Notably, MDT yielded a more even community distribution, significantly reducing the dominance of fast-growing copiotrophs such as Pseudomonas and Flavobacterium. Moreover, approximately 50% of sequences from MDT were affiliated with potential novel species (<98.46% identity to type strains), and 27% with potential novel genera (<95% identity). Strain verification by Sanger sequencing confirmed 12 of 17 isolates as candidate novel species, among which one strain represented a potential novel genus within Devosiaceae. This study demonstrates that MDT is a powerful platform for accessing the uncultured majority of polar soil microbiota and establishes a pipeline for high-throughput isolation of novel cold-adapted bacteria. IMPORTANCEArctic soils harbor a vast reservoir of microbial diversity that remains largely inaccessible due to the extreme oligotrophic conditions and low temperatures characteristic of polar environments, leading to slow growth rates and extended lag phases in most microbes. Conventional plate-based methods (CPM) inherently favor fast-growing copiotrophs while suppressing rare or slow-growing lineages. Here we demonstrate that microfluidic droplet technology (MDT) overcomes these fundamental constraints, representing its first systematic application to polar microbiology. By physically isolating individual cells into nanoliter-scale bioreactors, MDT mitigates interspecific competition, thereby releasing slow-growing and oligotrophic taxa that are otherwise outcompeted in bulk cultures. The water-in-oil emulsion format further enables extended low-temperature incubation without evaporative loss or airborne fungal contamination, issues that frequently compromise long-term plate-based cultivation of Arctic samples. Relative to CPM, MDT increased recovery rates by >6-fold and isolation throughput by >180-fold, while markedly enhanced both taxonomic richness and evenness. Exclusively recovered by MDT, the oligotrophic genus Caulobacter and numerous cold-adapted genera underscore that MDT accesses physiologically distinct fractions of the cryospheric microbiome. Furthermore, the integration of near-full-length 16S rRNA gene sequencing with MDT cultivation assessment provided substantially improved phylogenetic resolution for species-level identification and novel taxon delineation. Collectively, these findings establish MDT as a transformative platform for cryospheric culturomics, accelerating the construction of comprehensive polar strain collections essential for understanding cold-adaptation mechanisms and exploiting the biotechnological potential of Earths frozen microbiomes.

BackgroundBrazilian sponges of the genus Metania (phylum Porifera) are filter-feeding organisms from freshwater ecosystems. Here, we explored viral communities of Metania sp., their functional role in the sponge and how they differ from those in surrounding water. ResultsWe identified 1163 viral operational taxonomic units (vOTUs) from sponge tissue and adjacent water, with 555 vOTUs shared across habitats. Viral diversity was higher in sponges than in water, and community composition differed significantly (PERMANOVA, p = 0.037). Sponge-associated vOTUs exhibited broad phylogenetic diversity, including deep-branching and unclassified clades, and several exclusively sponge-associated Caudoviricetes. Virus-host predictions revealed 173 interactions, largely with sponge-associated bacteria, supported by CRISPR spacer matches, variant formation in multiple vOTUs across sponge individuals, and a high prevalence of microbial defence systems, particularly restriction-modification, abortive infection, and CRISPR-Cas pathways. Functionally, viral communities carried diverse auxiliary viral genes, including those involved in amino acid and central carbon metabolism, carbohydrate degradation, fatty acid biosynthesis, stress responses (e.g., metacaspase-1), and sulphur cycling. Nine sponge-associated vOTUs encoded carbonic anhydrase (CA), and phylogenomic as well as structural analyses showed strong conservation of CA active sites between sponge viruses, bacterial symbionts, and the sponge host. Protein-level homology searches revealed broad biogeographic distribution of viral CA homologs across global ocean microbiomes, despite limited nucleotide similarity, highlighting deep functional conservation. ConclusionsThese findings reveal a phylogenetically diverse and functionally rich viral community associated with freshwater Metania sp., characterized by extensive host interactions, diverse defence mechanisms, and auxiliary metabolic capacities. The structural conservation and widespread distribution of viral carbonic anhydrase genes further suggest ecologically significant roles in carbon transformation within freshwater sponges and potentially across aquatic ecosystems.

Linking bacteriophages (phages) to their hosts remains a fundamental challenge to understanding microbial ecology, viral evolution, and horizontal gene transfer. Although phages are the most abundant biological entities on Earth, the majority of them remain uncharacterized due to the lack of efficient host-linking approaches. Traditional methods, such as plaque assays, have significant limitations as they depend on visible lysis and therefore fail to detect phages that do not form plaques. Conversely, shotgun metagenomics can recover viral genomes directly from environmental samples; however, it cannot directly link phages to their bacterial hosts. In this study, we addressed this limitation by tackling the critical question of "who infects whom?" through the development of a novel, culture-independent approach that utilises an anucleate bacterial minicells-based platform to enrich for phages capable of infecting a target bacterial host. To validate our approach, purified Escherichia coli minicells were exposed to a concentrated viral fraction derived from sewage samples. Genomic DNA from phages that successfully infected and interacted with the E. coli minicells was isolated, amplified, and sequenced. Metagenomic analysis revealed a distinct E. coli-specific virome, including several putatively novel phage species and genera. This platform effectively bridges the gap between culture-dependent and metagenomic methods, providing a scalable, host-targeted tool for identifying phage-host pairs. Our approach also opens new opportunities for studying phage-host interaction networks in complex microbial ecosystems and enhances our ability to investigate viral diversity, host specificity, and the ecological roles of phages in natural environments.

Blooming microalgae (phytoplankton) release diverse organic molecules that fuel the marine pools of dissolved and particulate organic matter. A highly specialized community of heterotrophic bacteria rapidly remineralizes substantial parts of this organic matter in the sun-lit upper ocean. In particular, microalgae produce large quantities of various organosulfur compounds that can serve as carbon and sulfur sources for bacteria. Here, we report on the analyses of a time series of previously generated 30 long-read metagenomes, 30 corresponding deeply sequenced short-read metatranscriptomes and 15 metaproteomes from 0.2-3 {micro}m size fractions that we sampled in 2020 during a biphasic phytoplankton bloom in the German Bight (Southern North Sea). We analyzed the assembled contigs as well as 70 bacterial metagenome-assembled genomes that recruited the highest transcript numbers with respect to the utilization of methyl sulfur compounds (dimethylsulfoniopropionate (DMSP), dimethyl sulfide (DMS), dimethyl sulfone (DMSO2)), C3-sulfonates (2,3-dihydroxypropane-1-sulfonate (DHPS), 3-sulfolactate, 3-sulfopyruvate) and 2-aminoethanesulfonic acid (taurine). We observed a pronounced resource partitioning among bacterial clades that utilize distinct organosulfur compounds, which may explain successions of these clades during the studied bloom. Alphaproteobacteria were the most active and degraded a variety of organosulfonates via various metabolic routes. However, we also found previously underreported roles of members of the Bacteroidota and Gammaproteobacteria as efficient degraders of DMSP, DMS, and DMSO2. One striking observation was a strong preference for DMSP cleavage in Bacteroidota as opposed to DMSP demethylation in Alphaproteobacteria and indications for a particular proficiency for taurine utilization in Ilumatobacter_A and Acidimicrobiia. ImportanceSulfur-containing low-molecular-weight algal metabolites play an important role in overall marine carbon and sulfur fluxes. This study highlights that such compounds may play a crucial role in governing the succession of distinct bacterioplankton clades in response to phytoplankton blooms in coastal shelf areas of the temperate zone, such as the German Bight of the North Sea. While Alphaproteobacteria are the most versatile and competitive degraders of dissolved organosulfur compounds during such blooms, this study repositions clades previously thought to play only a more limited role in dissolved organosulfur metabolism in situ, such as Gammaproteobacteria, Bacteroidota, and Acidimicrobiia, as crucial contributors to the remineralization of organosulfur compounds in the upper ocean. This study also highlights the high level of interconnectedness of bacterial carbon and sulfur cycling during phytoplankton blooms.

Temperature and light play a crucial role in regulating phytoplankton blooms in the Ocean. To assess the importance of these two parameters experimentally, microcosms were conducted on seven picoplankton communities (<3 m) sampled in December, March, June and September 2015 and 2016 in the North Western Mediterranean Sea. Each community was exposed to 4 realistic seasonal conditions (December, March, June and September). Metabarcoding was used to investigate the eukaryotic diversity in the 56 microcosms experiments in parallel to high-frequency monitoring of environmental diversity in the sea. The three major lineages identified were the Stramenopiles, Alveolata and Archaeplastida. Overall, the five-day incubations were not sufficient to reshape the initial microbial communities completely. The microcosm outcome was strongly influenced by the dynamics of phytoplankton starting communities. In pre-bloom conditions, phytoplanktonic species were the most sensitive to temperature and light conditions. During a bloom, species belonging to diatoms or Chlorodendrophyceae usually did not respond to light and temperature in microcosms and continued to bloom independently of the applied seasonal condition. Together, these results suggest that light and temperature seasonal conditions play a crucial role in regulating phytoplankton dynamics in pre-bloom conditions and biotic interactions may be preponderant in bloom and post-bloom conditions.

At methane seeps worldwide, syntrophic anaerobic methane-oxidizing archaea and sulfate-reducing bacteria (ANME-SRB) promote carbonate precipitation and rock formation, acting as methane and carbon sink. While maintenance of active anaerobic oxidation of methane (AOM) within seep carbonates has been documented, the ANME-SRB reactivity to methane exposure remains uncertain. Surface-associated microbes may metabolize AOM-derived sulfide, maintain carbonate anoxia, and contribute to carbonate dissolution and higher trophic levels; however, these microbial communities are poorly described thus far. Here we provide new insights into microbial diversity, metabolic potential, activity, and resiliency within and on Southern Californian methane seep carbonates, by combining 16S rRNA and metagenomic sequencing, laboratory incubations, and BONCAT-FISH. Ca. Methanophaga (ANME-1) dominated the carbonate interiors across different seepage activities, based on sequencing, while the dominant SRB was Ca. Desulfaltia, potentially a new ANME partner. BONCAT-FISH revealed differences in ANME-1 cell activity, suggesting cell dormancy or DNA preservation at less active seep sites. Carbonate incubations from low activity seeps ([&ge;]24 months) showed an exponential AOM reactivation (44-day doubling time), suggesting seep carbonates remain potential methane sinks over dynamic seepage conditions. The surface-associated communities were distinct from the carbonate interior and other seep habitats, and highly heterogeneous. Surface ANME-SRB biofilms and sulfide-oxidizing bacterial mats were associated with high and intermediate AOM carbonates, potentially influencing carbonate precipitation/dissolution. Carbonate surfaces shared diverse aerobic methanotrophs with invertebrates, potentially serving as pool for animal epibionts. Besides particulate methane monooxygenases from aerobic methanotrophs, we found divergent forms including within a Methylophagaceae (GCA-002733105) MAG suggesting a new function within Methylophagaceae.

Understanding how microbial communities respond to disturbance remains a fundamental question in ecology, with broad implications for biodiversity, ecosystem function, and biotechnology. Trait-based approaches offer general rules to predict community responses by linking ecological strategies to measurable traits. While life-history strategy frameworks such as the competitor-ruderal-stress-tolerant (CSR) model are well established in plant and animal ecology, their application to microbial communities has been limited. Here, we experimentally tested how microbial communities shift across a gradient of disturbance frequency in replicated bioreactors treating synthetic wastewater. We applied six conditions by doubling the organic loading rate at different frequencies, from undisturbed to press disturbance, and monitored changes over 42 days using genome-resolved metagenomics, 16S rRNA gene sequencing, biomass quantification, and effluent chemistry. By integrating ordination, network analysis, and machine learning, we identified emergent community-level life-history strategies that aligned with increasing disturbance. These strategies were reflected in functional trade-offs, shifts in community composition, and genomic trait distributions. A simulation-based approach was used to generate a CSR classification of metagenome-assembled genomes, which was consistent with patterns observed in other microbial ecosystems. Our results demonstrate that life-history frameworks can capture predictable dynamics in microbial communities across disturbance regimes. This strategy provides a unifying tool for linking microbial structure, function, and traits across scales, helping to reconcile ecological theory with microbial resource management. More broadly, our findings support the integration of classical ecological theory with microbial genomics to uncover the trait-based principles that govern microbiome function and stability in both natural and engineered ecosystems.

Modern agriculture faces the dual challenge of increasing food production while reducing reliance on synthetic inputs that degrade soil ecosystems and compromise long-term sustainability. Algal biomasses have emerged as promising biostimulants, yet their capacity to selectively modulate soil microbiomes and plant growth-promoting bacterial (PGPB) functions remains poorly understood. Here, we evaluated 17 phylogenetically and biochemically diverse macro- and microalgal extracts to determine their effects on soil microbial communities, bacterial functional traits, and tomato (Solanum lycopersicum) performance. Algal supplementation selectively restructured microbial communities without disrupting overall diversity, promoting taxa associated with plant-beneficial functions, including Bacillus, Pseudomonas, and Actinobacteria. In soil microcosms, specific treatments increased culturable bacterial abundance by up to [~]200-fold relative to the initial soil. Functional assays revealed strong extract- and strain-dependent responses. Siderophore production and ACC-associated activity were the most consistently stimulated traits, whereas auxin production, biofilm formation, and proline synthesis showed more variable or context-dependent responses. Notably, Ulva sp. (AP11.2) enhanced siderophore production across the majority of isolates, with over four-fold increases in individual strains, while Arthrospira-derived extracts (NG4.1, N14.1) consistently promoted bacterial growth across multiple taxa. In contrast, extracts such as Nannochloropsis sp. (NG6.1) and Tetraselmis sp. (NG5.1) induced more selective or inhibitory responses, highlighting extract-dependent functional trade-offs. Integration of biochemical and biological datasets identified fatty acid composition as a key axis associated with microbial functional responses, whereas volatile organic compound profiles showed weaker and less consistent associations. These microbiome and functional shifts translated into improved plant performance, with algal treatments increasing tomato growth and reducing mortality by approximately 20% under non-sterile soil conditions characterized by pathogen-associated pressure. Together, these findings demonstrate that algal extracts act as selective modulators of soil microbiomes, enhancing specific bacterial functions and improving plant performance in a context-dependent manner. This work provides a mechanistic framework for the development of targeted algal-based biostimulants aimed at reducing agrochemical inputs and advancing microbiome-informed agriculture.

The functions of microbial communities, including substrate conversion and pathogen suppression, arise not as a simple sum of individual species capabilities but through complex interspecies interactions. Understanding how such functions arise from individual species and their interactions remains a major challenge, limiting efforts to rationally understand microbial roles in both natural and engineered ecosystems. Because current holistic (meta-omics) and reductionist (isolation- or single-cell-based) approaches struggle to capture these emergent microbial community functions, this study explores an intermediate strategy: analyzing simple sub-community combinations to enable a bottom-up understanding of community-level functions. To examine the validity of this approach, we used a nine-member synthetic microbial community capable of degrading the environmental pollutant aniline, and systematically generated a dataset of 256 sub-community combinations and their associated functions. Analyses using random forest models revealed that the sub-community combinations of just three to four species enabled the quantitative prediction of functions in larger communities (5-9-member; Pearsons r = 0.78-0.80). Prediction performance remained robust even with limited sub-community data, suggesting applicability to more diverse microbial communities where exhaustive sub-community observation is infeasible. Moreover, interpreting models trained on these simple sub-community combinations enabled the identification of key species and interspecies interactions that strongly influence the overall community function. These findings provide a methodological framework for mechanistically dissecting complex microbial community functions through sub-community-based analysis.