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      Yeast Creates a Niche for Symbiotic Lactic Acid Bacteria through Nitrogen Overflow

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          Summary

          Many 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.

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          Highlights

          • Yeast overflows amino acids that enable survival of lactic acid bacteria (LAB)

          • Overflow is in proportion to nitrogen excess and regulated via TORC1 pathway

          • Phenotype supporting LAB growth is conserved across diverse yeast isolates

          • Yeast-LAB mutualism readily emerges when lactose is the main C-source

          Abstract

          Yeast and LAB co-occur in a variety of naturally fermented foods and beverages. We show, using metabolomics, transcriptomics, and genetic analysis, how nitrogen overflow by yeast benefits LAB and contributes to the emergence of mutualism.

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          Most cited references65

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          How glycan metabolism shapes the human gut microbiota.

          Symbiotic microorganisms that reside in the human intestine are adept at foraging glycans and polysaccharides, including those in dietary plants (starch, hemicellulose and pectin), animal-derived cartilage and tissue (glycosaminoglycans and N-linked glycans), and host mucus (O-linked glycans). Fluctuations in the abundance of dietary and endogenous glycans, combined with the immense chemical variation among these molecules, create a dynamic and heterogeneous environment in which gut microorganisms proliferate. In this Review, we describe how glycans shape the composition of the gut microbiota over various periods of time, the mechanisms by which individual microorganisms degrade these glycans, and potential opportunities to intentionally influence this ecosystem for better health and nutrition.
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            High-throughput generation, optimization and analysis of genome-scale metabolic models.

            Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking approximately 48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.
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              Metabolic dependencies drive species co-occurrence in diverse microbial communities.

              Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.
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                Author and article information

                Contributors
                Journal
                Cell Syst
                Cell Syst
                Cell Systems
                Cell Press
                2405-4712
                2405-4720
                25 October 2017
                25 October 2017
                : 5
                : 4
                : 345-357.e6
                Affiliations
                [1 ]European Molecular Biology Laboratory, Heidelberg 69117, Germany
                [2 ]Institute of Molecular Systems Biology, ETH-Zürich, Zürich 8093, Switzerland
                [3 ]Department of Biochemistry, University of Cambridge, The Francis Crick Institute, London, NW1 1AT, UK
                Author notes
                []Corresponding author patil@ 123456embl.de
                [4]

                Present address: Cellzome, GlaxoSmithKline R&D, Heidelberg 69117, Germany

                [5]

                Present address: Program in Systems Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA

                [6]

                These authors contributed equally

                [7]

                Lead Contact

                Article
                S2405-4712(17)30390-3
                10.1016/j.cels.2017.09.002
                5660601
                28964698
                9f10b586-e726-49e9-8cc0-cf77310b73cc
                © 2017 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 April 2016
                : 13 July 2017
                : 30 August 2017
                Categories
                Article

                microbial communities,cross-feeding,metabolic interactions,torc1,mutualism,metabolomics

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