Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual curation required to obtain good quality models. Here, we present an automated tool, CarveMe, for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We show that CarveMe models perform closely to manually curated models in reproducing experimental phenotypes (substrate utilization and gene essentiality). Additionally, we build a collection of 74 models for human gut bacteria and test their ability to reproduce growth on a set of experimentally defined media. Finally, we create a database of 5587 bacterial models and demonstrate its potential for fast generation of microbial community models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.

The association between metabolic interactions and co-occurrence in microbial communities has been addressed in a previous study (40). That study, based on models of binary communities, found that co-occurring communities could be distinguished from the niche-associated ones by increased competition, but not by cooperation. In contrast, we show, by simulating higher-order communities (to better represent ecological complexity) and without resorting to a growth optimality assumption (for which there is yet little evidence), that metabolic dependency is a hallmark of species co-occurrence. The distinction of co-occurring groups is evident in comparison to random assemblies as well as to habitatfiltered background. This further allowed us to carry out comprehensive simulations identifying metabolites that preferentially connect co-occurring species."The complete reference appears below. www.pnas.org/cgi

SummaryMany microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others.

Bacterial metabolism plays a fundamental role in gut microbiota ecology and host-microbiome interactions. Yet the metabolic capabilities of most gut bacteria have remained unknown. Here we report growth characteristics of 96 phylogenetically diverse gut bacterial strains across 4 rich and 15 defined media. The vast majority of strains (76) grow in at least one defined medium, enabling accurate assessment of their biosynthetic capabilities. These do not necessarily match phylogenetic similarity, thus indicating a complex evolution of nutritional preferences. We identify mucin utilizers and species inhibited by amino acids and short-chain fatty acids. Our analysis also uncovers media for in vitro studies wherein growth capacity correlates well with in vivo abundance. Further value of the underlying resource is demonstrated by correcting pathway gaps in available genome-scale metabolic models of gut microorganisms. Together, the media resource and the extracted knowledge on growth abilities widen experimental and computational access to the gut microbiota.

Resource competition and metabolic cross-feeding are among the main drivers of microbial community assembly. Yet, the degree to which these two conflicting forces are reflected in the composition of natural communities has not been systematically investigated. Here we use genome-scale metabolic modeling to assess resource competition and metabolic cooperation potential in large co-occurring groups (up to 40 members) across thousands of habitats. Our analysis revealed two distinct community types, clustering at opposite ends in a trade-off between competition and cooperation. On one end, lie highly cooperative communities, characterized by smaller genomes and multiple auxotrophies. At the other end, lie highly competitive communities, featuring larger genomes, overlapping nutritional requirements, and harboring more genes related to antimicrobial activity. While the latter are mainly present in soils, the former are found both in free-living and host-associated habitats. Community-scale flux simulations showed that, while the competitive communities can better resist species invasion but not nutrient shift, the cooperative communities are susceptible to species invasion but resilient to nutrient change. In accord, we show, through analyzing an additional dataset, that colonization by probiotic species is positively associated with the presence of cooperative species in the recipient microbiome. Together, our analysis highlights the bifurcation between competitive and cooperative metabolism in the assembly of natural communities and its implications for community modulation.