Deep sea hydrothermal vents are abundant on the ocean floor and play important roles in ocean biogeochemistry. In vent ecosystems such as hydrothermal plumes, microorganisms rely on reduced chemicals and gases in hydrothermal fluids to fuel primary production and form diverse and complex microbial communities. However, microbial interactions that drive these complex microbiomes remain poorly understood. Here, we use microbiomes from the Guaymas Basin hydrothermal system in the Pacific Ocean to shed more light on the key species in these communities and their interactions. We built metabolic models from metagenomically assembled genomes (MAGs) and infer possible metabolic exchanges and horizontal gene transfer (HGT) events within the community. We highlight possible archaea-archaea and archaea-bacteria interactions and their contributions to robustness of the community. Cellobiose, D-Mannose 1-phosphate, O2, CO2, and H2S were among the most exchanged metabolites. Ten microbes, including eight bacteria and two archaea, were identified as key contributors. These microorganisms uniquely enhanced the metabolic capabilities of the community by donating metabolites that cannot be produced by any other community member. Archaea from the DPANN group stood out as key microbes, benefiting significantly from accepting metabolites from other members of the microbiome. Amino acids were the key auxotrophy driving metabolic interactions in the community. Finally, over 200 horizontal gene transfer events were predicted in the community, the majority of which were between Gammaproteobacteria and Alphaproteobacteria. Overall, our study provides key insights into the microbial interactions that drive community structure and organisation in complex hydrothermal plumes and deep sea microbiomes.

Deep-sea hydrothermal vents are abundant on the ocean floor and play important roles in ocean biogeochemistry. In vent ecosystems such as hydrothermal plumes, microorganisms rely on reduced chemicals and gases in hydrothermal fluids to fuel primary production and form diverse and complex microbial communities. However, microbial interactions that drive these complex microbiomes remain poorly understood. Here, we use microbiomes from the Guaymas Basin hydrothermal system in the Pacific Ocean to shed more light on the key species in these communities and their interactions. We built metabolic models from metagenomically assembled genomes (MAGs) and infer possible metabolic exchanges and horizontal gene transfer (HGT) events within the community. We highlight possible archaea–archaea and archaea–bacteria interactions and their contributions to the robustness of the community. Cellobiose, D-Mannose 1-phosphate, O2, CO2, and H2S were among the most exchanged metabolites. These interactions enhanced the metabolic capabilities of the community by exchange of metabolites that cannot be produced by any other community member. Archaea from the DPANN group stood out as key microbes, benefiting significantly as acceptors in the community. Overall, our study provides key insights into the microbial interactions that drive community structure and organisation in complex hydrothermal plume microbiomes.

Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.