mSystems
(Oct 2021)
Gut Metabolites Are More Predictive of Disease and Cohoused States than Gut Bacterial Features in a Polycystic Ovary Syndrome-Like Mouse Model
Bryan Ho,
Daniel Ryback,
Basilin Benson,
Cayla N. Mason,
Pedro J. Torres,
Robert A. Quinn,
Varykina G. Thackray,
Scott T. Kelley
Affiliations
Bryan Ho
Bioinformatics and Medical Informatics Program, San Diego State University, San Diego, California, USA
Daniel Ryback
Department of Biology, San Diego State University, San Diego, California, USA
Basilin Benson
Bioinformatics and Medical Informatics Program, San Diego State University, San Diego, California, USA
Cayla N. Mason
Bioinformatics and Medical Informatics Program, San Diego State University, San Diego, California, USA
Pedro J. Torres
Department of Biology, San Diego State University, San Diego, California, USA
Robert A. Quinn
Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, California, USA
Varykina G. Thackray
Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Diego, La Jolla, California, USA
Scott T. Kelley
ORCiD Bioinformatics and Medical Informatics Program, San Diego State University, San Diego, California, USA
DOI
https://doi.org/10.1128/mSystems.01149-20
Journal volume & issue
Vol. 6,
no. 5
Abstract
Read online
Using a combination of untargeted metabolomics and metagenomics, we performed a comparative longitudinal analysis of the feces collected in a cohousing study with a PCOS-like mouse model. Our results showed that gut metabolite composition experienced earlier and more pronounced differentiation in both the disease model and cohoused mice compared with the microbial composition.
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