Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota
By Stefanía Magnúsdóttir, Almut Heinken, Laura Kutt, D. Ravcheev, Eugen Bauer, Alberto Noronha, Kacy Greenhalgh, Christian Jäger, J. Baginska, P. Wilmes and 2 more. Nature Biotechnology, 2016
730 citations recorded by the source corpus.
Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of gut organisms through reconstruction and analysis), a resource of genome-scale metabolic reconstructions semi-automatically generated for 773 human gut bacteria. Using this resource, we identified a defined growth medium for Bacteroides caccae ATCC 34185. We also showed that interactions among modeled species depend on both the metabolic potential of each species and the nutrients available. AGORA reconstructions can integrate either metagenomic or 16S rRNA sequencing data sets to infer the metabolic diversity of microbial communities. AGORA reconstructions could provide a starting point for the generation of high-quality, manually curated metabolic reconstructions. AGORA is fully compatible with Recon 2, a comprehensive metabolic reconstruction of human metabolism, which will facilitate studies of host–microbiome interactions.
Subfields: Molecular Biology, Physiology
View Paper: https://www.semanticscholar.org/paper/3ad0c2b523a0f831c907af09ebc886f8e9592f8d
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In Molecular Biology
- Rasmus Agren
- Ines Thiele
- Jens Nielsen
- Ronan M. T. Fleming
- Almut Heinken
- Alberto Noronha
- Reinhard Schneider
- Eduard J. Kerkhoven
Citations in the corpus
- RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor (2018, background): “Page 3 of 19 strategies [3]; studying microbial communities [4]; finding biomarkers for human diseases and personalized and precision medicines [5,6]; and improving antibiotic production [7].”
- The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease (2018, background): “Each type of entity will be displayed in its corresponding grid (5).”