Clinical and microbiota alterations in performance horses undergoing long-distance transport.

Long-distance transport causes subclinical pulmonary inflammation and respiratory microbiota disruption even under optimized trailering conditions.

This prospective cohort study investigated the effects of long-distance road transport on respiratory microbiota and clinical health parameters in 17 performance horses transported from New England to Florida under optimized trailering conditions, compared with 12 non-traveling controls. Clinical assessments including physical examination, hematology, nasopharyngeal wash, endoscopy, tracheal aspirates, and thoracic ultrasonography were performed 48 hours before transport and 24 and 72 hours after arrival. Despite optimized transport conditions, significant post-transport changes were observed: cortisol concentrations decreased (P = .02), while thoracic ultrasound scores (P = .01) and serum amyloid A concentrations (P = .03) increased, indicating systemic and pulmonary inflammation. High-throughput 16S rRNA sequencing revealed that transport timepoint accounted for a small but statistically significant proportion of respiratory microbiota variability (P < .001). Upper and lower airway microbiota were compositionally distinct, with the lower airway exhibiting greater beta diversity and lower temporal stability. Timepoint and ultrasound scores together explained 19% and 10% of nasal and tracheal microbiota variability, respectively. Bacterial taxa enriched post-transport were predominantly plant-associated organisms, particularly within the order Hyphomicrobiales. These findings demonstrate that even under best-practice transport protocols, measurable respiratory microbiota disruption and subclinical pulmonary inflammation occur in healthy athletic horses. The authors suggest that future research incorporating fungal mycobiome analysis may further elucidate mechanisms underlying transport-associated respiratory disease.

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.