Effects of Different Stages of Training on the Intestinal Microbes of Yili Horses Analyzed Using Metagenomics

利用宏基因组学分析不同训练阶段对伊犁马肠道微生物的影响

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Abstract

Objectives: The aim of this study was to investigate the effects of different stages of training on the intestinal microbial abundance of Yili horses. Methods: Ten Yili horses, all aged 2 years old and weighing 305 ± 20 kg, were selected and divided into a training group and an untrained group. The training group performed riding training 6 days a week, and the untrained group moved freely in the activity circle every day. Fecal samples were collected on days 30 and 60, and the intestinal microorganisms were detected and analyzed using metagenomics. Results: Compared with the 30-day untrained group, the relative abundances of Bacteroidetes were significantly increased in the 30-day training group (p < 0.01). Conversely, the abundances of Clostridiaceae, Clostridium, and Ruminococcus were significantly decreased (p < 0.01), whereas those of Prevotella, Bacteroideaceae, and Bacteroidetes were significantly increased (p < 0.05). Additionally, the relative abundances of Firmicutes and Actinomycetes were significantly decreased (p < 0.05). Compared with the 60-day untrained group, no significant differences in the phyla Bacteriaceae and Bacteriae of the 60-day training group (p > 0.05) were observed. In the linear discriminant analysis effect size analysis, seven significantly different bacteria were detected in the fecal flora of horses in the 30-day training group versus the untrained 30-day group, but only one significantly different bacterium was detected after 60 days. The Kyoto Encyclopedia of Genes and Genomes analysis showed that the differentially expressed genes were related to metabolism and the environmental information processing pathway, carbohydrate metabolism, and membrane transport pathways. Conclusions: Therefore, training seems to affect the diversity and composition of the gut microbiota of Yili horses, especially during the first 30 days of training.

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