The gutSMASH web server: automated identification of primary metabolic gene clusters from the gut microbiota

Author:

Pascal Andreu Victòria1,Roel-Touris Jorge2,Dodd Dylan34,Fischbach Michael A456,Medema Marnix H1ORCID

Affiliation:

1. Bioinformatics Group, Wageningen University, 6708PB, Wageningen, The Netherlands

2. Bijvoet Centre for Biomolecular Research, Faculty of Science – Chemistry, Utrecht University, 3584CH, Utrecht, The Netherlands

3. Department of Pathology, Stanford University, Stanford, CA 94305, USA

4. Department of Microbiology & Immunology, Stanford University, Stanford, CA 94305, USA

5. Department of Bioengineering, Stanford University, Stanford, CA 94305, USA

6. Chan Zuckerberg Biohub, San Francisco, CA 94158, USA

Abstract

Abstract Anaerobic bacteria from the human microbiome produce a wide array of molecules at high concentrations that can directly or indirectly affect the host. The production of these molecules, mostly derived from their primary metabolism, is frequently encoded in metabolic gene clusters (MGCs). However, despite the importance of microbiome-derived primary metabolites, no tool existed to predict the gene clusters responsible for their production. For this reason, we recently introduced gutSMASH. gutSMASH can predict 41 different known pathways, including MGCs involved in bioenergetics, but also putative ones that are candidates for novel pathway discovery. To make the tool more user-friendly and accessible, we here present the gutSMASH web server, hosted at https://gutsmash.bioinformatics.nl/. The user can either input the GenBank assembly accession or upload a genome file in FASTA or GenBank format. Optionally, the user can enable additional analyses to obtain further insights into the predicted MGCs. An interactive HTML output (viewable online or downloadable for offline use) provides a user-friendly way to browse functional gene annotations and sequence comparisons with reference gene clusters as well as gene clusters predicted in other genomes. Thus, this web server provides the community with a streamlined and user-friendly interface to analyze the metabolic potential of gut microbiomes.

Funder

Chan-Zuckerberg Biohub

DARPA

NIH

Leducq Foundation

European Research Council

Wageningen University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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