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机器学习模型显示,酿酒酵母与仔猪早期发育阶段生长不良有关。

Machine learning models reveal Saccharomyces yeasts are associated with poor piglet growth in early development.

作者信息

Chhetri Nisan, Summers Katie Lynn, Campos Philip M, Postnikova Olga A, Rivera Israel, Harlow Kalynn, Oliver William T, Wells James E, Davies Cary Pirone

机构信息

Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA.

U.S. Department of Agriculture, ARS, Animal Biosciences and Biotechnology Laboratory, Beltsville Agricultural Research Center, Beltsville, MD 20705, USA.

出版信息

J Anim Sci. 2025 Jan 4;103. doi: 10.1093/jas/skaf133.

DOI:10.1093/jas/skaf133
PMID:40296223
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12242386/
Abstract

Modern swine production relies on consistent growth rates across individuals to maximize efficiency and earnings, but a subset of piglets are born small and grow slowly. Nutrition and management practices can augment the growth of slow growers but there remains a substantial portion of piglets that never reach their full growth potential. Traditionally, in-feed antibiotics were administered to enhance growth but with limitations on use, alternatives are needed. Emerging evidence suggests a role for bacterial members of the gut microbiome in growth, but fungal members have been largely overlooked. Yeasts have been used in the swine industry to improve health and growth, but a limited number of species have been utilized, and study results are mixed. Here, we use ITS2 sequencing to profile the mycobiome of piglets at 2 timepoints in early development, postnatal days 14 (D14) and 21 (D21), just before weaning. Pigs were classified as either good or poor growers, with pigs below the 40th percentile of average daily gain labeled as poor growers, while those above the 60th percentile were labeled as good growers. A total of 27 samples from good growers were analyzed from D14 (n = 27), 27 from poor growers at D14 (n = 27), 29 from good growers at D21 (n = 29), and 28 from poor growers at D21 (n = 28). Machine learning algorithms and differential abundance analyses were applied to identify fungi associated with both growth categories. At D14, Saccharomycetes yeasts are moderately predictive of poor growth, with the yeast genera Pichia, Lodderomyces, Clavispora, more abundant in poor growers than in good growers. Wallemia is significantly more abundant in good growers than in poor growers at D21. Additional fungi were associated with good and poor growth but data were sparse and further large-scale studies are needed to verify these observations. Together, these results contribute to our understanding of the role of the mycobiome in piglet growth and suggest that the reduction of yeasts in early development may improve performance across the weaning transition and beyond.

摘要

现代养猪生产依赖于个体间一致的生长速度,以实现效率和收益最大化,但有一部分仔猪出生时体型小且生长缓慢。营养和管理措施可以促进生长缓慢仔猪的生长,但仍有相当一部分仔猪无法充分发挥其生长潜力。传统上,在饲料中添加抗生素以促进生长,但随着抗生素使用受到限制,需要寻找替代方法。新出现的证据表明肠道微生物群中的细菌成员在生长中发挥作用,但真菌成员在很大程度上被忽视了。酵母已被用于养猪业以改善健康和促进生长,但使用的酵母种类有限,研究结果也参差不齐。在这里,我们使用ITS₂测序对仔猪在早期发育的两个时间点(出生后第14天(D14)和第21天(D21),即断奶前)的真菌群落进行分析。仔猪被分为生长良好或生长不良两类,平均日增重低于第40百分位数的仔猪被标记为生长不良,而高于第60百分位数的仔猪被标记为生长良好。共分析了27个来自D14生长良好仔猪的样本(n = 27)、27个来自D14生长不良仔猪的样本(n = 27)、29个来自D21生长良好仔猪的样本(n = 29)和28个来自D21生长不良仔猪的样本(n = 28)。应用机器学习算法和差异丰度分析来识别与两种生长类别相关的真菌。在D14时,酵母菌对生长不良有中等程度的预测性,毕赤酵母属、罗地酵母属、克勒克酵母属在生长不良仔猪中比在生长良好仔猪中更为丰富。在D21时,威克海姆酵母属在生长良好仔猪中比在生长不良仔猪中显著更为丰富。其他真菌与生长良好和生长不良有关,但数据稀少,需要进一步开展大规模研究来验证这些观察结果。总之,这些结果有助于我们了解真菌群落在仔猪生长中的作用,并表明在早期发育阶段减少酵母菌数量可能会改善断奶过渡期及之后的生长性能。

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