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Home / Equine Research Bank / Anim Microbiome / A novel dataset of 2,362 equine fecal microbiomes from veter...
Animal microbiome2025; 7(1); 124; doi: 10.1186/s42523-025-00493-x

A novel dataset of 2,362 equine fecal microbiomes from veterinary teaching hospitals across three countries reveals effects of geography and disease.

Abstract: Horses and other equids are reliant on the gut microbiome for health, and studies have reported associations between certain clinical conditions and features of the fecal microbiome. However, research to date on the equine fecal microbiome has often relied on small sample sizes collected from single and relatively localized geographic regions. Previous work also largely employs single timepoint analyses, or horses selected based on limited health criteria. Results: To address these limitations and expand our understanding of the core microbiome in health, and the changes associated with adverse outcomes, the Equine Gut Group (EGG) has collected and performed 16S rRNA sequencing on 2,362 fecal samples from 1,190 healthy and affected horses. This resource of 16S rRNA sequencing data with accompanying demographic and clinical metadata represent a diverse equine population in health and disease. We identified features making up the core microbiome of healthy equids and metadata factors influencing the relative abundance of those features. We then identified microbial markers of acute gastrointestinal disease at the community and taxonomic levels. Conclusions: Here we present the EGG database and demonstrate its utility in characterizing the equine microbiome in health and acute gastrointestinal disease. The EGG 16S rRNA database is a valuable resource to study the equine microbiome and its role in equine health.
© 2025. The Author(s).
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Publication Date: 2025-12-03 PubMed ID: 41339959PubMed Central: PMC12676801DOI: 10.1186/s42523-025-00493-xGoogle Scholar: Lookup
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  • Journal Article

Summary

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Overview

  • This study presents a large dataset of equine fecal microbiomes from over two thousand samples collected across three countries.
  • The research investigates how geographic location and disease affect the gut microbial community in horses, providing insights into core microbiome components in health as well as markers associated with disease.

Background and Motivation

  • Horses and other equids depend heavily on their gut microbiome for maintaining health.
  • Prior studies found links between certain clinical conditions and fecal microbiome features but were limited by small sample sizes, localized sampling, and focus on single time points or narrow health criteria.
  • This limited scope reduced the ability to generalize findings across diverse equine populations and diseases.

Objectives of the Study

  • To overcome prior limitations by compiling a large, geographically diverse dataset of equine fecal microbiomes.
  • To characterize the core microbiome components in healthy horses across different regions.
  • To identify microbial markers associated with acute gastrointestinal disease across a broad equine population.

Methods

  • The Equine Gut Group (EGG) collected 2,362 fecal samples from 1,190 horses, representing both healthy and diseased individuals.
  • The samples were sourced from veterinary teaching hospitals across three different countries, enabling geographic diversity.
  • Researchers performed 16S rRNA gene sequencing on the fecal samples to profile bacterial communities.
  • Comprehensive demographic and clinical metadata were also gathered to correlate microbiome profiles with health status and geography.

Key Findings

  • The study successfully identified a “core microbiome” — a set of microbial taxa consistently present in healthy horses regardless of location.
  • Various metadata factors, such as geography, influenced the relative abundance of these core microbes but did not fundamentally change the core composition.
  • Distinct microbial signatures indicative of acute gastrointestinal disease were characterized at both community and taxonomic levels.
  • These microbial markers can aid in understanding disease mechanisms and potentially serve as diagnostic indicators in clinical contexts.

Significance and Applications

  • The EGG database is the largest and most geographically diverse collection of equine fecal microbiome data to date.
  • This resource enables more robust studies of microbiome variation due to geography, health, and disease status in horses.
  • Veterinarians and researchers can utilize these findings to improve equine health management through microbiome-informed diagnostics and treatments.
  • The study sets a foundation for future longitudinal investigations and targeted therapeutic development.

Cite This Article

APA
McAdams ZL, Campbell EJ, Dorfmeyer RA, Turner G, Shaffer S, Ford T, Lawson J, Terry J, Raju M, Coghill L, Cresci L, Lascola K, Pridgen T, Blikslager A, Barrell E, Banse H, Paul L, Gillen A, Nott S, VandeCandelaere M, van Galen G, Townsend KS, Martin LM, Johnson PJ, Ericsson AC. (2025). A novel dataset of 2,362 equine fecal microbiomes from veterinary teaching hospitals across three countries reveals effects of geography and disease. Anim Microbiome, 7(1), 124. https://doi.org/10.1186/s42523-025-00493-x

Publication

Animal microbiome
ISSN: 2524-4671
NlmUniqueID: 101759457
Country: England
Language: English
Volume: 7
Issue: 1
Pages: 124
PII: 124

Researcher Affiliations

McAdams, Zachary L
  • Molecular Pathogenesis and Therapeutics Program, University of Missouri, Columbia, Mo, 65201, USA.
  • Department of Pathobiology and Integrative Biomedical Sciences, University of Missouri Metagenomics Center, Columbia, MO, 65201, USA.
Campbell, Emma J
  • University of Missouri, Columbia, MO, 65201, USA.
Dorfmeyer, Rebecca A
  • Department of Pathobiology and Integrative Biomedical Sciences, University of Missouri Metagenomics Center, Columbia, MO, 65201, USA.
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Turner, Giedre
  • Department of Pathobiology and Integrative Biomedical Sciences, University of Missouri Metagenomics Center, Columbia, MO, 65201, USA.
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Shaffer, Samantha
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Ford, Tamara
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Lawson, Jenna
  • University of Missouri, Columbia, MO, 65201, USA.
Terry, Jackson
  • Hickman High School, Columbia, MO, 65203, USA.
Raju, Murugesan
  • Bond Life Sciences Center, University of Missouri Bioinformatics and Analytics Core, Columbia, MO, 65211, USA.
Coghill, Lyndon
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
  • Bond Life Sciences Center, University of Missouri Bioinformatics and Analytics Core, Columbia, MO, 65211, USA.
Cresci, Lucia
  • College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA.
Lascola, Kara
  • College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA.
Pridgen, Tiffany
  • College of Veterinary Medicine, North Carolina State University, Raleigh, NC, 27606, USA.
Blikslager, Anthony
  • College of Veterinary Medicine, North Carolina State University, Raleigh, NC, 27606, USA.
Barrell, Emily
  • Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, MN, 55108, USA.
Banse, Heidi
  • School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
Paul, Linda
  • School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
Gillen, Alexandra
  • Department of Equine Clinical Science, Philip Leverhulme Equine Hospital, University of Liverpool, Chester High Road, Neston, Wirral, CH64 7TE, UK.
Nott, Sascha
  • UQ VETS Equine Specialist Hospital, University of Queensland, Outer Ring Road, UQ Gatton Campus, Lawes, QLD, 4343, Australia.
VandeCandelaere, Marie
  • Sydney School of Veterinary Science, The University of Sydney, Camperdown, NSW, 2006, Australia.
  • Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
van Galen, Gaby
  • Sydney School of Veterinary Science, The University of Sydney, Camperdown, NSW, 2006, Australia.
  • Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Townsend, Kile S
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Martin, Lynn M
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Johnson, Philip J
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA.
Ericsson, Aaron C
  • Molecular Pathogenesis and Therapeutics Program, University of Missouri, Columbia, Mo, 65201, USA. ericssona@missouri.edu.
  • Department of Pathobiology and Integrative Biomedical Sciences, University of Missouri Metagenomics Center, Columbia, MO, 65201, USA. ericssona@missouri.edu.
  • College of Veterinary Medicine, University of Missouri, Columbia, MO, 65201, USA. ericssona@missouri.edu.

Conflict of Interest Statement

Declarations. Ethical approval: Not applicable. Conflict of interest: The authors declare no competing interests.

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