[特邀报告]肺炎呼吸道微生物组

肺炎呼吸道微生物组
编号:103 访问权限:仅限参会人 更新:2022-07-04 13:47:42 浏览:338次 特邀报告

报告开始:2022年07月23日 16:40 (Asia/Shanghai)

报告时间:20min

所在会议:[S4] 分会场4 » [S4-1] 群体遗传学与微生物组学

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摘要
Background:
Community acquired pneumonia (CAP) is a heterogeneous disease with a variety of causative pathogens and is a leading cause of morbidity and mortality. The characteristics of the CAP lower respiratory microbiota, as well as its dynamics and association with disease progression, are largely unknown.
Methods:
In this study, 1068 time-series sputum samples from 350 CAP inpatients were sequenced for the V3-V4 region of 16S rRNA.
Results:
The respiratory tract microbiota of CAP patients was composed of a variety of commensal bacteria or dominated by a single opportunistic pathogen (Pseudomonas, Acinetobacter, Mycoplasma, and Enterobacteriaceae), with the former scenario being more frequently observed in non-severe cases. Besides, the microbiota in severe cases had a lower alpha diversity and being enriched with Enterobacteriaceae compared to the non-severe cases and healthy population. Two pathways involved in menaquinol and butyrate synthesis were predicted to be more abundant in non-severe cases. Moreover, there were greater changes in the microbiota of severe patients than those of mild cases after admission, and intubation was frequently followed by Acinetobacter expansion. Additionally, we found that the infection by different pathogens seems to lead to different alterations in the microbiota.  
Conclusion
Despite that the respiratory microbiota of most CAP patients did not include a high abundance of known pathogens, the composition and dynamics of the microbiota were distinct between the severe and non-severe patients. Clarifying the relationship between respiratory microbiota and the development of CAP will facilitate our understanding of the etiology of pneumonia and the establishment of effective diagnostic tools and more efficient treatment.
 
关键字
微生物组;肺炎
报告人
李明锟
研究员 中国科学院北京基因组研究所

李明锟,研究员、博士生导师,德国马普学会进化人类学研究所生物信息学博士。课题组主要研究方向为组学数据深度挖掘与算法开发,目前主要在病原微生物的精准检测、人体微生物组成与功能、智能化基因组变异演化分析三个方向开展研究。2018年后在Am J Respir Crit Care Med、Cell Host Microbes、Clin Infect Dis、Nucleic Acids Res 等期刊发表论文二十余篇,引用超过1000次。
 

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