Effect of Management System on Fecal Microbiota in Arabian Horses: Preliminary Results

The gut microbiota plays a basic role in maintaining the psychophysical health and well-being of horses. Understanding the complex interactions among microbial communities in relation to age, management, and health is a topic of growing interest. The equine microbiota, given its complexity, is subject to variations caused by internal or external stressors that can lead to metabolic problems and pathologies, i.e., obesity and laminitis. The aim of this study was to characterize the fecal microbiota of 12 purebred Arabian horses and to compare the microbial communities in two distinct management systems (Group 1 = box 22 h/day + paddock 2 h/day and Group 2 = paddock 24 h). Fecal samples were analyzed using high-throughput sequencing of 16S rRNA V3-V4 amplicons. The microbiota was predominantly composed of Firmicutes (32-53%) and Bacteroidetes (32-47.8%), with Ruminococcaceae emerging as the most prevalent bacterial family (10.9-24%). Comparisons of alpha and beta diversity revealed no statistically significant differences between the groups based on different management systems. This preliminary characterization contributes valuable data for understanding the equine fecal microbiota and lays the groundwork for future studies on the relationship among intestinal microbiota and equine health, performance, and management strategies.

Authors

Institutions

Publication Details

Journal
Veterinary Sciences
Published
2025-03-28
DOI
https://doi.org/10.3390/vetsci12040309
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of Management System on Fecal Microbiota in Arabian Horses: Preliminary Results

Valentina Gazzano, Claudia Vannini, Angelo Gazzano, Fabio Macchioni et al.
Veterinary Sciences
Gut microbiota and health
article

Effect of Management System on Fecal Microbiota in Arabian Horses: Preliminary Results

Valentina Gazzano, Claudia Vannini, Angelo Gazzano, Fabio Macchioni, Maria Claudia Curadi, Flavio Vallone, Martina Tenuzzo
article en

Abstract

The gut microbiota plays a basic role in maintaining the psychophysical health and well-being of horses. Understanding the complex interactions among microbial communities in relation to age, management, and health is a topic of growing interest. The equine microbiota, given its complexity, is subject to variations caused by internal or external stressors that can lead to metabolic problems and pathologies, i.e., obesity and laminitis. The aim of this study was to characterize the fecal microbiota of 12 purebred Arabian horses and to compare the microbial communities in two distinct management systems (Group 1 = box 22 h/day + paddock 2 h/day and Group 2 = paddock 24 h). Fecal samples were analyzed using high-throughput sequencing of 16S rRNA V3-V4 amplicons. The microbiota was predominantly composed of Firmicutes (32-53%) and Bacteroidetes (32-47.8%), with Ruminococcaceae emerging as the most prevalent bacterial family (10.9-24%). Comparisons of alpha and beta diversity revealed no statistically significant differences between the groups based on different management systems. This preliminary characterization contributes valuable data for understanding the equine fecal microbiota and lays the groundwork for future studies on the relationship among intestinal microbiota and equine health, performance, and management strategies.

Veterinary SciencesVol. 12(4)
University of Pisa (IT)
Università di Pisa
Openalex Percentile: Top 95%
Gut microbiota and health
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.