腹泻柴达木马亚成体粪便微生物多样性分析及其生物标记物的筛选
收稿日期: 2021-11-15
录用日期: 2022-05-06
网络出版日期: 2022-07-22
基金资助
中国科学院战略性先导科技专项(XDA2004010305)
Fecal microbiota diversity analysis of the diarrheal sub-adult Qaidam horses and biomarkers screening
Received date: 2021-11-15
Accepted date: 2022-05-06
Online published: 2022-07-22
为比较青藏高原柴达木马亚成体腹泻与健康个体粪便微生物群落多样性和结构组成的差异, 我们利用16S rRNA测序技术对采集的腹泻 (n = 3) 和健康 (n = 13) 个体粪便样本细菌的组成与分布进行分析比较，并利用实时荧光定量PCR测定相关菌属的含量。结果显示，无论健康还是腹泻，厚壁菌门、拟杆菌门、疣微菌门、变形杆菌门和螺旋体门是柴达木马亚成体粪便中的优势菌门。相比健康组，腹泻组粪便微生物的Alpha多样性显著下降 (P < 0.05)，厚壁菌门相对丰度下降而变形杆菌门的相对丰度显著增加 (P < 0.05)，推断这两个门中的梭菌属、普雷沃菌属、纤杆菌属等丰度的失衡可能是导致柴达木马腹泻的原因之一。此外，通过机器学习的随机森林算法筛选出12个对健康和腹泻柴达木马亚成体粪便微生物差异具有较大影响的特征菌属，包括甲烷短杆菌属、纤杆菌属、Paludibacter、肉食杆菌属和迷踪菌属等。研究揭示了健康和腹泻柴达木马亚成体粪便微生物组的变化，为进一步研究青藏高原地区家畜腹泻提供一定的数据支持。
关键词： 16S rRNA测序; 实时荧光定量PCR; 粪便菌群; 生物标记物; 腹泻
王小琪 , 郝文静 , 张志超 , 韩晶 , 王儒敬 , 段子渊 . 腹泻柴达木马亚成体粪便微生物多样性分析及其生物标记物的筛选[J]. 兽类学报, 2022 , 42(4) : 432 -441 . DOI: 10.16829/j.slxb.150637
The study aims to compare the difference in diversity and composition of fecal microbiota between healthy and diarrheal sub-adult Qaidam horses. We analyzed feces of healthy (n = 13) and diarrheal (n = 3) sub-adult Qaidam horses based on 16S rRNA high-throughput sequencing, and determined the absolute abundance of related differential bacteria genera by real-time qPCR. The results indicated that Firmicutes, Bacteroidetes, Verrucomicrobia, Proteobacteria and Spirochaetes were the dominant phyla in feces from both healthy and diarrheal Qaidam horses. Compared to healthy Qaidam horses, the fecal microbial Alpha diversity was significantly lower (P < 0.05), the relative abundance of Firmicutes was relatively lower (P < 0.05), and the ralative abundance of Proteobacteria was significantly higher (P < 0.05) in diarrheal Qaidam horses. It was then deduced that the dysbiosis of these two phyla (Clostridium, Prevotella, Fibrobacter, etc.) in microecology might play an important role in Qaidam horses’ diarrhea. Additionally, 12 biomarkers (feature genera), such as Methanobrevibacter, Fibrobacter, Paludibacter, Carnobacterium and Elusimicrobium, which had significant influence on the difference of fecal bacteria composition between the two groups, were screened by a machine learning algorithm (random forest). The study compared the characteristics of fecal microbial changes in healthy and diarrheal Qaidam horses and provided a data basis for the diarrhea of livestock in the Qinghai-Tibet Plateau.
Key words： 16S rRNA sequencing; Real-time qPCR; Fecal microbiota; Biomarker; Diarrhea
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