<div><p>Background Soil microbiomes harbor complex communities from which diverse ecological roles unfold, shaped by syntrophic interactions. Unraveling the mechanisms and consequences of such interactions and the underlying biochemical transformations remains challenging due to niche multidimensionality. The Atacama Desert is an extreme environment that includes unique combinations of stressful abiotic factors affecting microbial life. In particular, the Talabre Lejía transect is a natural laboratory for understanding microbiome composition, functioning, and adaptation.</p></div> <div>Results<p>We propose a computational framework for the simulation of the metabolic potential of microbiomes, as a proxy of how communities are prepared to respond to the environment. Through the coupling of taxonomic and functional profiling, community-wide and genome-resolved metabolic modeling, and regression analyses, we identify key metabolites and species from six contrasting soil samples across the Talabre Lejía transect. We highlight the functional redundancy of whole metagenomes, which act as a gene reservoir, from which site-specific adaptations emerge at the species level. We also link the physicochemistry from the puna and the lagoon samples to metabolic machineries that are likely crucial for sustaining microbial life in these unique environmental conditions. We further provide an abstraction of community composition and structure for each site that allowed us to describe microbiomes as resilient or sensitive to environmental shifts, through putative cooperation events.</p></div> <div>Conclusion<p>Our results show that the study of multi-scale metabolic potential, together with targeted modeling, contributes to elucidating the role of metabolism in the adaptation of microbial communities. Our framework was designed to handle non-model microorganisms, making it suitable for any (meta)genomic dataset that includes high-quality environmental data for enough samples.</p></div>

The oceans buffer against climate change via biogeochemical cycles underpinned by microbial metabolic activities. While planetary-scale surveys provide baseline microbiome data, inferring metabolic and biogeochemical impacts remains challenging. Here, we constructed a model for each TARA Ocean metagenome or metatranscriptome representing heterotrophic prokaryotes and their viruses and assessed these as community-wide metabolic phenotypes. To validate, we showed that even with reaction-mappable genes only (∼1/4 of the total genes), the composition of these models revealed metabolism-inferred ecological zones that matched taxonomy-inferred zones. Model inferences include providing a new metric of community-wide metabolic cooperation and new insights into connections between microbial metabolism and organism diversity, and the ecological role of viruses. The latter suggests they genomically target community-critical metabolic reactions and estimates where viruses remineralize versus sink carbon. While this new constraints-based, agile, and mechanistic modeling framework is highly upgradable, it already begins to convert molecular-scale environmental omics data to ecological and even planetary-scale biogeochemical features that will better bring microbes and their viruses into earth system and climate models.

Soil microbiomes harbor complex communities and exhibit important ecological roles resulting from biochemical transformations and microbial interactions. Difficulties in characterizing the mechanisms and consequences of such interactions together with the multidimensionality of niches hinder our understanding of these ecosystems. The Atacama Desert is an extreme environment that includes unique combinations of stressful abiotic factors affecting microbial life. In particular, the Talabre Lejía transect has been proposed as a unique natural laboratory for understanding adaptation mechanisms. We propose a systems biology-based computational framework for the reconstruction and simulation of community-wide and genome-resolved metabolic models, in order to provide an overview of the metabolic potential as a proxy of how microbial communities are prepared to respond to the environment. Through a multifaceted approach that includes taxonomic and functional profiling of microbiomes, simulation of the metabolic potential, and multivariate analyses, we were able to identify key species and functions from six contrasting soil samples across the Talabre Lejía transect. We highlight the functional redundancy of whole metagenomes, which act as a gene reservoir from which site-specific functions emerge at the species level. We also link the physicochemistry from the puna and the lagoon samples to specific metabolic machineries that could be associated with their adaptation to the unique environmental conditions found there. We further provide an abstraction of community composition and structure for each site that allows to describe them as sensitive or resilient to environmental shifts through putative cooperation events. Our results show that the study of community-wide and genome-resolved metabolic potential, together with targeted modeling, may help to elucidate the role of producible metabolites in the adaptation of microbial communities. Our framework was designed to handle non-model microorganisms, making it suitable for any (meta)genomic dataset that includes nucleotide sequence data and high-quality environmental metadata for different samples.