Key Laboratory of Feed Biotechnology of the Ministry of Agriculture and Rural Affairs, Feed Research Institute, Chinese Academy of Agricultural Sciences, 100081, Beijing, China.
Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
ISME J. 2020 Sep;14(9):2223-2235. doi: 10.1038/s41396-020-0678-3. Epub 2020 May 22.
Perturbations in early life gut microbiota can have long-term impacts on host health. In this study, we investigated antimicrobial-induced temporal changes in diversity, stability, and compositions of gut microbiota in neonatal veal calves, with the objective of identifying microbial markers that predict diarrhea. A total of 220 samples from 63 calves in first 8 weeks of life were used in this study. The results suggest that increase in diversity and stability of gut microbiota over time was a feature of "healthy" (non-diarrheic) calves during early life. Therapeutic antimicrobials delayed the temporal development of diversity and taxa-function robustness (a measure of microbial stability). In addition, predicted genes associated with beta lactam and cationic antimicrobial peptide resistance were more abundant in gut microbiota of calves treated with therapeutic antimicrobials. Random forest machine learning algorithm revealed that Trueperella, Streptococcus, Dorea, uncultured Lachnospiraceae, Ruminococcus 2, and Erysipelatoclostridium may be key microbial markers that can differentiate "healthy" and "unhealthy" (diarrheic) gut microbiota, as they predicted early life diarrhea with an accuracy of 84.3%. Our findings suggest that diarrhea in veal calves may be predicted by the shift in early life gut microbiota, which may provide an opportunity for early intervention (e.g., prebiotics or probiotics) to improve calf health with reduced usage of antimicrobials.
早期生活肠道微生物群的紊乱会对宿主健康产生长期影响。在这项研究中,我们研究了抗微生物药物对新生犊牛肠道微生物群多样性、稳定性和组成的时间变化,目的是确定预测腹泻的微生物标志物。本研究共使用了 63 头犊牛生命前 8 周的 220 个样本。结果表明,随着时间的推移,肠道微生物群多样性和稳定性的增加是“健康”(非腹泻)犊牛早期的特征。治疗性抗生素延迟了多样性和分类功能稳定性(衡量微生物稳定性的指标)的时间发展。此外,与β-内酰胺和阳离子抗菌肽抗性相关的预测基因在接受治疗性抗生素治疗的犊牛肠道微生物群中更为丰富。随机森林机器学习算法显示,真杆菌属、链球菌属、多拉菌属、未培养的毛螺菌科、瘤胃球菌 2 属和产肠毒素梭菌可能是区分“健康”和“不健康”(腹泻)肠道微生物群的关键微生物标志物,因为它们对早期生命腹泻的预测准确率为 84.3%。我们的研究结果表明,犊牛腹泻可以通过早期生活肠道微生物群的变化来预测,这可能为早期干预(例如,使用益生元或益生菌)提供机会,以减少抗生素的使用,改善犊牛的健康状况。