Toward disease-associated fecal microbiome signatures for domestic mammals
7 affiliations
- 1Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY USA
- 2Department of Animal Science and One Health Microbiome Center, Pennsylvania State University, University Park, PA USA
- 3College of Information Sciences and Technology, Pennsylvania State University, University Park, PA USA
- 4Department of Statistics, Pennsylvania State University, University Park, PA USA
- 5Department of Medicine, Pennsylvania State University, Hershey, PA USA
- 6Department of Epidemiology and Health Statistics, Zhejiang University School of Public Health, Hangzhou, China
- 7Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY USA
Abstract
Conserved fecal microbiome signatures of intestinal diseases across domestic mammals offer a non-invasive avenue to monitor animal health and advance One Health, yet systematic meta-analysis with cross-study, cross-disease, and cross-host validation remains lacking. We present a leave-one-dataset-out meta-analysis defining generalizable intestinal disease signatures in mammalian hosts. Analyzing 512 samples from four bovine diarrhea and three canine IBD studies, we identified 12 bovine and 8 canine stable signature genera marked by depleted short-chain fatty acid (SCFA) producers and enriched pathobionts through a compositional random-effects framework with per-study covariate-adjusted effect sizes. A minimal signature set matched full-feature models across five machine learning models, and study-aware transfer learning improved cross-study generalization. Across 367 samples, signatures outperformed for intestinal versus non-intestinal phenotypes in cross-disease prediction. Cross-host validation across equine, feline, caprine, swine, and human datasets (533 animal and 1,182 human samples) revealed canine IBD-associated signatures outperformed in feline intestinal disease prediction, while bovine diarrhea-associated signatures generalized better to herbivorous hosts and human intestinal diseases. These findings may support the existence of conserved microbial signatures across veterinary and human medicine, warranting further investigation toward diagnostic applications.
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BibTeX
@article{lin2026toward,
title = {{Toward disease-associated fecal microbiome signatures for domestic mammals}},
author = {Dan Lin and Erika Ganda and Justin Silverman and Jiating Huang and Katherine Rose Gottwald and Haowen Hu and Puchun Niu and Jessica Anne Allerton McArt},
journal = {Communications Biology},
year = {2026},
month = jul,
doi = {10.1038/s42003-026-10647-5},
url = {https://doi.org/10.1038/s42003-026-10647-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Toward disease-associated fecal microbiome signatures for domestic mammals
AU - Dan Lin
AU - Erika Ganda
AU - Justin Silverman
AU - Jiating Huang
AU - Katherine Rose Gottwald
AU - Haowen Hu
AU - Puchun Niu
AU - Jessica Anne Allerton McArt
PY - 2026
DA - 2026/07/14
JO - Communications Biology
DO - 10.1038/s42003-026-10647-5
UR - https://doi.org/10.1038/s42003-026-10647-5
AB - Conserved fecal microbiome signatures of intestinal diseases across domestic mammals offer a non-invasive avenue to monitor animal health and advance One Health, yet systematic meta-analysis with cross-study, cross-disease, and cross-host validation remains lacking. We present a leave-one-dataset-out meta-analysis defining generalizable intestinal disease signatures in mammalian hosts. Analyzing 512 samples from four bovine diarrhea and three canine IBD studies, we identified 12 bovine and 8 canine stable signature genera marked by depleted short-chain fatty acid (SCFA) producers and enriched pathobionts through a compositional random-effects framework with per-study covariate-adjusted effect sizes. A minimal signature set matched full-feature models across five machine learning models, and study-aware transfer learning improved cross-study generalization. Across 367 samples, signatures outperformed for intestinal versus non-intestinal phenotypes in cross-disease prediction. Cross-host validation across equine, feline, caprine, swine, and human datasets (533 animal and 1,182 human samples) revealed canine IBD-associated signatures outperformed in feline intestinal disease prediction, while bovine diarrhea-associated signatures generalized better to herbivorous hosts and human intestinal diseases. These findings may support the existence of conserved microbial signatures across veterinary and human medicine, warranting further investigation toward diagnostic applications.
SN - 2399-3642
ER -