ArticleMicrobiome2015
Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires.
Article in Microbiome, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Mathematical models of the colonic microbiota: an evaluation of accuracy usingFrontiers in nutrition · 2025Article
- Panera: An innovative framework for surmounting uncertainty in microbial community modeling using pan-genera metabolic models.iScience · 2024Article
- Functional comparison of metabolic networks across species.Nature communications · 2023Article
- A Defined Medium for Cultivation and Exometabolite Profiling of Soil Bacteria.Frontiers in microbiology · 2022Article
- TrpNet: Understanding Tryptophan Metabolism across Gut Microbiome.Metabolites · 2021Article
- Genome-Inferred Correspondence between Phylogeny and Metabolic Traits in the Wild Drosophila Gut Microbiome.Genome biology and evolution · 2021Article
- Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance.Nature communications · 2020Article
- The functional repertoire contained within the native microbiota of the model nematode Caenorhabditis elegans.The ISME journal · 2020Article
- Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models.Scientific reports · 2019Article
- A demonstration of unsupervised machine learning in species delimitation.Molecular phylogenetics and evolution · 2019Article
- β-Glucuronidases of opportunistic bacteria are the major contributors to xenobiotic-induced toxicity in the gut.Scientific reports · 2018Article
- Gut microbiota functions: metabolism of nutrients and other food components.European journal of nutrition · 2018Review
- Intestinal Metagenomes and Metabolomes in Healthy Young Males: Inactivity and Hypoxia Generated Negative Physiological Symptoms Precede Microbial Dysbiosis.Frontiers in physiology · 2018Article
- From metagenomic data to personalized in silico microbiotas: predicting dietary supplements for Crohn's disease.NPJ systems biology and applications · 2018Article
- A clinician's guide to microbiome analysis.Nature reviews. Gastroenterology & hepatology · 2017Review
- More than just a gut feeling: constraint-based genome-scale metabolic models for predicting functions of human intestinal microbes.Microbiome · 2017Review
- BacArena: Individual-based metabolic modeling of heterogeneous microbes in complex communities.PLoS computational biology · 2017Article
- Community metabolic modeling approaches to understanding the gut microbiome: Bridging biochemistry and ecology.Free radical biology & medicine · 2017Review
- Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells.Frontiers in molecular biosciences · 2017Review
- Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
resultsWe 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.
conclusionsWe 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.