title: Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires.
abstract: BACKGROUND
  The human gastrointestinal tract harbors a diverse microbial community, in which metabolic phenotypes play important roles for the human host. Recent developments in meta-omics attempt to unravel metabolic roles of microbes by linking genotypic and phenotypic characteristics. This connection, however, still remains poorly understood with respect to its evolutionary and ecological context.
  
  
  RESULTS
  We generated automatically refined draft genome-scale metabolic models of 301 representative intestinal microbes in silico. We applied a combination of unsupervised machine-learning and systems biology techniques to study individual and global differences in genomic content and inferred metabolic capabilities. Based on the global metabolic differences, we found that energy metabolism and membrane synthesis play important roles in delineating different taxonomic groups. Furthermore, we found an exponential relationship between phylogeny and the reaction composition, meaning that closely related microbes of the same genus can exhibit pronounced differences with respect to their metabolic capabilities while at the family level only marginal metabolic differences can be observed. This finding was further substantiated by the metabolic divergence within different genera. In particular, we could distinguish three sub-type clusters based on membrane and energy metabolism within the Lactobacilli as well as two clusters within the Bifidobacteria and Bacteroides.
  
  
  CONCLUSIONS
  We demonstrate that phenotypic differentiation within closely related species could be explained by their metabolic repertoire rather than their phylogenetic relationships. These results have important implications in our understanding of the ecological and evolutionary complexity of the human gastrointestinal microbiome.
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. eugen.bauer@uni.lu.
authors.forename: Eugen
authors.initials: E
authors.lastname: Bauer
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. cedric.laczny@uni.lu.
authors.forename: Cedric Christian
authors.initials: CC
authors.lastname: Laczny
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. stefania.magnusdottir@uni.lu.
authors.forename: Stefania
authors.initials: S
authors.lastname: Magnusdottir
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. paul.wilmes@uni.lu.
authors.forename: Paul
authors.initials: P
authors.lastname: Wilmes
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. ines.thiele@uni.lu.
authors.forename: Ines
authors.initials: I
authors.lastname: Thiele
mesh_terms: D015415:Biomarkers; D002462:Cell Membrane / Q000378:metabolism; D016000:Cluster Analysis; D004734:Energy Metabolism; D000069196:Gastrointestinal Microbiome / Q000502:physiology*; D005838:Genotype; D006801:Humans; D054892:Metagenome; D008954:Models, Biological; D010641:Phenotype; D010802:Phylogeny
chemical_list: D015415:Biomarkers