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Wang, C. ; Lin, J.* ; Duan, M.* ; He, J.* ; Halizere, S.* ; Chen, N.* ; Chen, X.* ; Ye, J.* ; He, W.* ; Dyar, K.A. ; Yang, F.* ; Zhu, S.*

Multi‐omics reveals different signatures of obesity‐prone and obesity‐resistant mice.

iMetaOmics 2:e59 (2025)
Verlagsversion Forschungsdaten DOI
Open Access Gold
Creative Commons Lizenzvertrag
Obesity‐prone (OP) and obesity‐resistant (OR) individuals demonstrate sig-nificant metabolic differences, potentially influenced by variations in the gutmicrobiome. However, the influence of host–microbiota interactions onobesity susceptibility remains unknown. We performed an integrative multi‐omics approach to explore microbial, metabolic, and genetic differences inhigh‐fat diet (HFD)‐fed OP and OR mice, with additional analyses of gutmicrobiota variations in humans. In OP mice, the dynamic gut microbiotawas characterized by a stable presence of Longibaculum, while Kineothrixpredominated in OR mice. We termed both as keystone bacteria. Beyondthese, eight dominant bacterial genera were significantly associated with bileacid metabolites and amino acids. Three of these genera were also identifiedin OR humans and showed positive correlations with genes that may supportintestinal barrier function. We identified 22 specific amino acid profiles aspotential biomarkers for obesity susceptibility, along with significantlyincreased levels of ten non‐12‐OH bile acids in fecal of OR mice. In vivo,mouse experiments demonstrated that ursodeoxycholic and hyodeoxy-cholic acids could reduce HFD‐induced obesity. Additionally, the colon ofOP mice displayed a higher presence of inflammatory cells. These findingssuggest that host–microbiota interactions may contribute to phenotypicdifferences between OP and OR. Our study offers insights into crucialintestinal markers associated with obesity, providing a valuable resourcefor advancing the understanding of obesity‐prone and obesity‐resistantphenotypes.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Omics
ISSN (print) / ISBN 2996-9506
e-ISSN 2996-9514
Zeitschrift iMetaOmics
Quellenangaben Band: 2, Heft: 1, Seiten: , Artikelnummer: e59 Supplement: ,
Verlag Wiley
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes and Cancer (IDC)