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Abstract

Dysbiosis and impaired gut barrier integrity contribute to chronic immune activation associated with both obesity and HIV infection. Given the increased incidence of obesity in people living with HIV, we explored the impact of obesity on the gut microbiome and microbial translocation (MT) biomarkers during HIV infection and antiretroviral therapy (ART). Lean and obese rhesus macaques were infected with simian immunodeficiency virus (SIV) and subsequently treated with ART. Obese animals exhibited higher initial MT and inflammation biomarkers that remained constant throughout the study, while lean animals exhibited significant increases in these biomarkers that approached levels observed in obese animals. Lean and obese animals exhibited similar observed amplicon sequence variants (ASVs) at baseline, with obese animals exhibiting reduced ASVs during acute SIV infection that rebounded after 39 weeks of ART treatment. Beta diversity differed between groups and was longitudinally altered in obese animals. Obese animals exhibited significant changes in differential abundance in four times as many bacterial genera compared to lean animals. Our finding that MT and inflammation biomarkers significantly changed in lean animals, while obese animals exhibited significant alterations in microbial diversity, suggests that microbiome changes and systemic inflammation may not directly correlate during SIV infection and ART.

Document Type

Article

Publication Date

2025

Notes/Citation Information

Copyright © 2025 McGuire et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

Digital Object Identifier (DOI)

https://doi.org/10.1128/spectrum.00733-25

Funding Information

This work was supported by NIH grants DK123115 to P.K. and DK122843 to J.B.S., P.K., and C.T.R., as well as OD11092 for operation of the Oregon National Primate Research Center. The OncoGenomics Shared Resource Facility of the University of Kentucky Markey Cancer Center (P30CA177558) supported this research. The research reported in this publication used computational infrastructure supported by the Office of Research Infrastructure Programs, Office of the Director, of the National Institutes of Health under Award Number S10OD034224. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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