Untargeted Sweat Metabolomics and Targeted Plasma Amino Acid Profiling Reveal Dynamic Metabolic Remodeling During Conditioning in Yili Horses

Training induces sweat morphology changes in horses from muddy sweat (MS) to foamy sweat (FS) and clear sweat (CS), reflecting physiological adaptation. However, the metabolic mechanisms linking sweat phenotypes to systemic amino acid dynamics remain unclear. This study integrated sweat untargeted metabolomics and plasma amino acid targeted metabolomics to reveal coordinated metabolic remodeling. Six 2-year-old Yili horse stallions underwent 10-week training. Plasma and sweat were sampled pre- and post-race at each stage. LC-MS/MS and UHPLC-MS/MS were used for sweat metabolome and plasma amino acid analysis, followed by multivariate statistics, KEGG enrichment, and correlation network (CNet) analysis. Differential sweat metabolites decreased across stages (45, 127, and 38 for MS vs. FS, MS vs. CS, and FS vs. CS). Pre-race BCAA concentrations were higher in MS than in FS and CS, while glycine was lower. Post-race valine, histidine, and aspartate were elevated only in MS. Pre-race plasma amino acids positively correlated with sweat lipids and organic acids, shifting to negative post-race. ABC transporters, mTOR signaling, and BCAA metabolic pathways were key co-regulators. The MS-to-CS transition reflects metabolic remodeling from acute stress to homeostatic adaptation. Plasma BCAAs and sweat cortisol are potential biomarkers, with ABC transporters and mTOR pathways mediating sweat-plasma metabolic coordination.

Authors

Institutions

Publication Details

Journal
Biology
Published
2026-06-28
DOI
https://doi.org/10.3390/biology15131033
Primary Topic
Veterinary Equine Medical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Untargeted Sweat Metabolomics and Targeted Plasma Amino Acid Profiling Reveal Dynamic Metabolic Remodeling During Conditioning in Yili Horses

Chen Meng, Wanlu Ren, Y. Xue, Tongliang Wang et al.
Biology
Veterinary Equine Medical Research
article

Untargeted Sweat Metabolomics and Targeted Plasma Amino Acid Profiling Reveal Dynamic Metabolic Remodeling During Conditioning in Yili Horses

Chen Meng, Wanlu Ren, Y. Xue, Tongliang Wang, Jun Meng, Zhenhui Shen, Yaqi Zeng, Penghui Luo, Xinkui Yao
article en

Abstract

Training induces sweat morphology changes in horses from muddy sweat (MS) to foamy sweat (FS) and clear sweat (CS), reflecting physiological adaptation. However, the metabolic mechanisms linking sweat phenotypes to systemic amino acid dynamics remain unclear. This study integrated sweat untargeted metabolomics and plasma amino acid targeted metabolomics to reveal coordinated metabolic remodeling. Six 2-year-old Yili horse stallions underwent 10-week training. Plasma and sweat were sampled pre- and post-race at each stage. LC-MS/MS and UHPLC-MS/MS were used for sweat metabolome and plasma amino acid analysis, followed by multivariate statistics, KEGG enrichment, and correlation network (CNet) analysis. Differential sweat metabolites decreased across stages (45, 127, and 38 for MS vs. FS, MS vs. CS, and FS vs. CS). Pre-race BCAA concentrations were higher in MS than in FS and CS, while glycine was lower. Post-race valine, histidine, and aspartate were elevated only in MS. Pre-race plasma amino acids positively correlated with sweat lipids and organic acids, shifting to negative post-race. ABC transporters, mTOR signaling, and BCAA metabolic pathways were key co-regulators. The MS-to-CS transition reflects metabolic remodeling from acute stress to homeostatic adaptation. Plasma BCAAs and sweat cortisol are potential biomarkers, with ABC transporters and mTOR pathways mediating sweat-plasma metabolic coordination.

BiologyVol. 15(13)
Xinjiang Agricultural University (CN)
Openalex Percentile: Top 7%
Veterinary Equine Medical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.