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ORIGINAL RESEARCH article

Front. Microbiol.

Sec. Microorganisms in Vertebrate Digestive Systems

Volume 16 - 2025 | doi: 10.3389/fmicb.2025.1613949

Cross-Matrix Multi-Omics Profiling Identifies Host-Microbe Interactions and Diagnostic Signatures in Bovine Subclinical Mastitis

Provisionally accepted
YuQiong LiYuQiong Li1Xiulan XieXiulan Xie1Youli YuYouli Yu1Song HuaSong Hua2Zhengwei ZhaoZhengwei Zhao1Zhuming ZhangZhuming Zhang3Haihui GaoHaihui Gao1Chenglian ZhangChenglian Zhang4Mei-zhou HuangMei-zhou Huang5*
  • 1Institute of Animal Science, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, Henan Province, China
  • 2College of Veterinary Medicine, Northwest A&F University, Xianyang, Shaanxi, China
  • 3Ningxia University, Yinchuan, Ningxia Hui Region, China
  • 4Ningxia Hui Autonomous Region Animal Disease Prevention and Control Center, Yinchuan, Henan Province, China
  • 5The Affiliated Hospital of Southwest Medical University, Luzhou, China

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Subclinical mastitis (SCM) is a widespread but frequently undetected condition in dairy cows, leading to reduced milk quality and compromised animal health. This study utilizes an integrated multi-omics strategy encompassing metabolomics and microbiome analyses to investigate the systemic effects of SCM across four biological matrices: blood, milk, feces, and rumen fluid. Our findings reveal significant alterations in hematological and biochemical parameters, with key biomarkers such as digalacturonic acid and N-ε-methyl-L-lysine indicating systemic metabolic and immune dysregulation. Metabolomic profiling uncovered distinct disease-related metabolic patterns, while 16S rRNA sequencing revealed substantial microbial shifts, particularly involving Succinivibrio and Methanobrevibacter, which are implicated in carbohydrate fermentation and methanogenesis. Noteworthy correlations between specific metabolites (e.g., ropinirole, arachidonic acid) and microbial genera (e.g., Succinivibrionaceae UCG-001, Alistipes) highlight the complex host-microbiomemetabolite interplay associated with SCM. These findings provide new insights into the pathophysiology of SCM and identify candidate biomarkers for early detection. The integrative multi-omics approach adopted in this study offers a valuable framework for developing innovative diagnostic and therapeutic strategies to enhance dairy cow health and productivity.

Keywords: Subclinical mastitis, multi-omics approach, biomarkers, Metabolomics, microbiome

Received: 02 May 2025; Accepted: 24 Jul 2025.

Copyright: © 2025 Li, Xie, Yu, Hua, Zhao, Zhang, Gao, Zhang and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mei-zhou Huang, The Affiliated Hospital of Southwest Medical University, Luzhou, China

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Supplementary Material