Tiny ocean plankton (picoplankton) are fundamental for the functioning of the biosphere, but the ecological mechanisms shaping their biogeography are partially understood. Comprehending whether these microorganisms are structured by niche vs. neutral processes is highly relevant in the context of global change. The ecological drivers structuring picoplankton communities differ between prokaryotes and minute eukaryotes (picoeukaryotes) in the global surface ocean: while prokaryotic communities are shaped by a balanced combination of dispersal, selection, and drift, picoeukaryotic communities are mainly shaped by dispersal limitation. Yet, whether or not the relative importance of these processes in structuring picoplankton varies as we dive into the deep ocean was unknown. Here we investigate the mechanisms structuring picoplanktonic communities inhabiting different ocean depths. We analyzed 451 samples from the tropical and subtropical global ocean and the Mediterranean Sea covering the epi- (0-200m), meso- (200-1,000m), and bathypelagic (1,000-4,000m) depth zones. We found that selection decreased with depth possibly due to lower habitat heterogeneity. In turn, dispersal limitation increased with depth, possibly due to dispersal barriers such as water masses and bottom topography. Picoplankton β-diversity positively correlated with environmental heterogeneity and water mass variability in both the open-ocean and the Mediterranean Sea. However, this relationship tended to be weaker for picoeukaryotes than for prokaryotes. Community patterns were generally more pronounced in the Mediterranean Sea, probably because of its substantial cross-basin environmental heterogeneity and deep-water isolation. Altogether, we found that different combinations of ecological mechanisms shape the biogeography of the smallest members of the ocean microbiome across ocean depths.

Background Ocean microbes constitute ~ 70% of the marine biomass, are responsible for ~ 50% of the Earth’s primary production and are crucial for global biogeochemical cycles. Marine microbiotas include core taxa that are usually key for ecosystem function. Despite their importance, core marine microbes are relatively unknown, which reflects the lack of consensus on how to identify them. So far, most core microbiotas have been defined based on species occurrence and abundance. Yet, species interactions are also important to identify core microbes, as communities include interacting species. Here, we investigate interconnected bacteria and small protists of the core pelagic microbiota populating a long-term marine-coastal observatory in the Mediterranean Sea over a decade. Results Core microbes were defined as those present in > 30% of the monthly samples over 10 years, with the strongest associations. The core microbiota included 259 Operational Taxonomic Units (OTUs) including 182 bacteria, 77 protists, and 1411 strong and mostly positive (~ 95%) associations. Core bacteria tended to be associated with other bacteria, while core protists tended to be associated with bacteria. The richness and abundance of core OTUs varied annually, decreasing in stratified warmers waters and increasing in colder mixed waters. Most core OTUs had a preference for one season, mostly winter, which featured subnetworks with the highest connectivity. Groups of highly associated taxa tended to include protists and bacteria with predominance in the same season, particularly winter. A group of 13 highly-connected hub-OTUs, with potentially important ecological roles dominated in winter and spring. Similarly, 18 connector OTUs with a low degree but high centrality were mostly associated with summer or autumn and may represent transitions between seasonal communities. Conclusions We found a relatively small and dynamic interconnected core microbiota in a model temperate marine-coastal site, with potential interactions being more deterministic in winter than in other seasons. These core microbes would be essential for the functioning of this ecosystem over the year. Other non-core taxa may also carry out important functions but would be redundant and non-essential. Our work contributes to the understanding of the dynamics and potential interactions of core microbes possibly sustaining ocean ecosystem function.

Ocean microbes are fundamental for the functioning of the Earth system. Yet, our understanding of how they are reacting to global change in terms of evolution is limited. Microbes typically grow in large populations and reproduce quickly, which may allow them to rapidly adapt to environmental stressors compared to larger organisms. However, genetic evidence of contemporary evolution in wild microbes is scarce. We must begin coordinated efforts to establish new microbial time-series and explore novel tools, experiments, and data to fill this knowledge gap. The development of coordinated microbial 'genomic' observatories will provide the unprecedented opportunity to track contemporary microbial evolution in the ocean and explore the role of evolution in enabling wild microbes to respond to global change.

Background Ecological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not. Results We present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges—87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors. Conclusions To reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses.

Rivers connect the carbon cycle in land with that in aquatic ecosystems by transporting and transforming terrestrial organic matter (TeOM). The Amazon River receives huge loads of TeOM from the surrounding rainforest, promoting a substantial microbial heterotrophic activity and consequently, CO2 outgassing. In the Amazon River, microbes degrade up to 55% of the lignin present in the TeOM. Yet, the main microbial genomes involved in TeOM degradation were unknown. Here, we characterize 51 Population Genomes (PGs) representing some of the most abundant microbes in the Amazon River deriving from 106 metagenomes. The 51 reconstructed PGs are among the most abundant microbes in the Amazon River, and 53% of them are not able to degrade TeOM. Among the PGs capable of degrading TeOM, 20% were exclusively cellulolytic, while the others could also oxidize lignin. The transport and consumption of lignin oxidation by‐products seemed to be decoupled from the oxidation process, being apparently performed by different groups of microorganisms. By connecting the genomic features of abundant microbes in the Amazon River with the degradation machinery of TeOM, we suggest that a complex microbial consortium could explain the quick turnover of TeOM previously observed in this ecosystem.