Exploration of the Fecal Microbiota and Biomarker Discovery in Equine Grass Sickness.

This research investigates the fecal microbiota and biofluid metabolic profiles of horses with Equine Grass Sickness (EGS), a disease leading to the death of 1-2% of the UK horse population annually. The goal of the study was to better understand EGS and to identify potential metabolic biomarkers that could assist in its diagnosis.

Introduction and Goals of the Research

• The authors of this study aimed to investigate Equine Grass Sickness (EGS), a disease whose cause remains unconfirmed but is suspected to be associated with the presence of Clostridium botulinum neurotoxin in the horse’s digestive tract.
• Due to the current inability to adequately prevent or noninvasively diagnose EGS, the researchers sought to gain a deeper understanding of the disease’s underlying mechanisms.
• This was done by characterizing the fecal microbiota and biofluid metabolic profiles of horses that suffer from EGS. This characterization could then aid in the identification of metabolic biomarkers for the disease.

Research Methods and Findings

• The study involved collection and analysis of urine, plasma, and feces from a selection of EGS-stricken horses, healthy controls, and hospital controls.
• The researchers sequenced the 16S rRNA gene of the fecal bacterial population of the study horses. This gene sequencing revealed that horses with EGS had a significant imbalance or dysbiosis of gut bacteria, characterized by increased levels of Bacteroidetes and decreased levels of Firmicutes bacteria.
• A metabolic profiling was carried out using hydrogen nuclear magnetic resonance spectroscopy. This revealed that EGS was associated with lower urinary excretion of hippurate and 4-cresyl sulfate, and higher excretion of O-acetyl carnitine and trimethylamine-N-oxide.

Evaluation of Findings and Potential Impact

• The researchers evaluated the predictive ability of the complete urinary metabolic signature and the four discriminatory urinary metabolites by classifying a second set of horses based on their disease status.
• Both the urinary metabolome of the horses and the combination of the four identified biomarkers showed potential in assisting the identification of horses with EGS.
• The discovery and characterization of metabolic shifts associated with EGS potentially paves the way for the development of a noninvasive test to assist with diagnosing EGS before death occurs, consequently improving disease management.