A geographically-diverse collection of 418 human gut microbiome pathway genome databases

• Main Authors: Hahn, Aria S. (Author), Altman, Tomer (Author), Hanson, Niels W. (Author), Kim, Dongjae (Author), Relman, David A. (Author), Dill, David L. (Author), Konwar, Kishori Mohan (Contributor), Hallam, Steven (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Civil and Environmental Engineering (Contributor)
• Format: Article
• Language: English
• Published: Nature Publishing Group, 2017-06-21T15:17:27Z.
• Subjects: Article
• Online Access: Get fulltext

 Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn's disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.