Luis Tobalina1, Rafael Bargiela1, Jon Pey1, Florian-Alexander Herbst1, Iván Lores1, David Rojo1, Coral Barbas1, Ana I Peláez1, Jesús Sánchez1, Martin von Bergen2, Jana Seifert1, Manuel Ferrer1, Francisco J Planes1. 1. CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark. 2. CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.
Abstract
MOTIVATION: With the advent of meta-'omics' data, the use of metabolic networks for the functional analysis of microbial communities became possible. However, while network-based methods are widely developed for single organisms, their application to bacterial communities is currently limited. RESULTS: Herein, we provide a novel, context-specific reconstruction procedure based on metaproteomic and taxonomic data. Without previous knowledge of a high-quality, genome-scale metabolic networks for each different member in a bacterial community, we propose a meta-network approach, where the expression levels and taxonomic assignments of proteins are used as the most relevant clues for inferring an active set of reactions. Our approach was applied to draft the context-specific metabolic networks of two different naphthalene-enriched communities derived from an anthropogenically influenced, polyaromatic hydrocarbon contaminated soil, with (CN2) or without (CN1) bio-stimulation. We were able to capture the overall functional differences between the two conditions at the metabolic level and predict an important activity for the fluorobenzoate degradation pathway in CN1 and for geraniol metabolism in CN2. Experimental validation was conducted, and good agreement with our computational predictions was observed. We also hypothesize different pathway organizations at the organismal level, which is relevant to disentangle the role of each member in the communities. The approach presented here can be easily transferred to the analysis of genomic, transcriptomic and metabolomic data.
MOTIVATION: With the advent of meta-'omics' data, the use of metabolic networks for the functional analysis of microbial communities became possible. However, while network-based methods are widely developed for single organisms, their application to bacterial communities is currently limited. RESULTS: Herein, we provide a novel, context-specific reconstruction procedure based on metaproteomic and taxonomic data. Without previous knowledge of a high-quality, genome-scale metabolic networks for each different member in a bacterial community, we propose a meta-network approach, where the expression levels and taxonomic assignments of proteins are used as the most relevant clues for inferring an active set of reactions. Our approach was applied to draft the context-specific metabolic networks of two different naphthalene-enriched communities derived from an anthropogenically influenced, polyaromatic hydrocarbon contaminated soil, with (CN2) or without (CN1) bio-stimulation. We were able to capture the overall functional differences between the two conditions at the metabolic level and predict an important activity for the fluorobenzoate degradation pathway in CN1 and for geraniol metabolism in CN2. Experimental validation was conducted, and good agreement with our computational predictions was observed. We also hypothesize different pathway organizations at the organismal level, which is relevant to disentangle the role of each member in the communities. The approach presented here can be easily transferred to the analysis of genomic, transcriptomic and metabolomic data.
Authors: Jan-Ulrich Kreft; Caroline M Plugge; Clara Prats; Johan H J Leveau; Weiwen Zhang; Ferdi L Hellweger Journal: Front Microbiol Date: 2017-11-27 Impact factor: 5.640