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不同软件平台分析肠易激综合征患者肠道菌群结构的比较
引用本文:朱诗玮,刘作静,李默,朱怀球,段丽萍.不同软件平台分析肠易激综合征患者肠道菌群结构的比较[J].北京大学学报(医学版),2018,50(2):231-238.
作者姓名:朱诗玮  刘作静  李默  朱怀球  段丽萍
作者单位:(1.北京大学第三医院消化科,北京100191; 2.北京大学工学院生物医学工程系,北京100871)
基金项目:国家自然科学基金(81670491),北京大学临床医学+X项目(PKU2017LCX14)资助 Supported by the National Natural Science Foundation of China(81670491),Peking University Clinical Medicine+X Project(PKU2017LCX14)
摘    要:目的:探讨不同软件平台对肠易激综合征(irritable bowel syndrome, IBS)患者肠道菌群结构的分析结果是否存在差异,以及分析结果对疾病鉴别和疗效评价能力的影响。方法:应用Uparse及Mothur软件平台分别对27例粪便菌群16S rRNA高通量测序结果进行分析,比较两种软件平台所得的肠道菌群结构。27例样本中包含健康对照(healthy control, HC组)9例,腹泻型IBS患者治疗前(IBS组)及治疗后(IBS-treatment, IBSt组)各9例。比较两种软件平台所得的肠道菌群结构在HC组 vs.IBS组和IBS组vs.IBSt组间的差异。结果:(1)Uparse及Mothur平台分析所得的27例粪便样本菌群结构在门水平差异不显著,而科水平和属水平差异显著;(2) 不论是Mothur平台还是Uparse平台,HC组vs.IBS组、IBS组vs.IBSt组,菌群结构差异无统计学意义(Uparse平台: HC组 vs.IBS组, F=0.98,P=0.445;IBS组vs.IBSt组,F=0.47,P=0.926; Mothur平台:HC组 vs.IBS组,F=0.82,P=0.646;IBS组vs.IBSt组,F=0.37,P=0.961);IBSt 组肠道菌群Shannon指数显著低于IBS组;(3)通过差异物种分析,两个平台数据都能得出HC组与IBS组的差异菌属,而仅Uparse平台的数据能够得到IBS组和IBSt组的差异菌属。结论:不同平台对于相同菌群高通量测序分析的结果存在分类学及丰度上的差异,为了提高研究的可重复性和可靠性,尤其是在比较不同研究所得的肠道菌群结构的共性时,特别需要注意数据分析方法的应用与选择。

关 键 词:肠易激综合征  生物信息分析  高通量测序  

Comparison of gut microbiotal compositional analysis of patients with irritable bowel syndrome through different bioinformatics pipelines
ZHU Shi-wei,LIU Zuo-jing,LI Mo,ZHU Huai-qiu,DUAN Li-ping.Comparison of gut microbiotal compositional analysis of patients with irritable bowel syndrome through different bioinformatics pipelines[J].Journal of Peking University:Health Sciences,2018,50(2):231-238.
Authors:ZHU Shi-wei  LIU Zuo-jing  LI Mo  ZHU Huai-qiu  DUAN Li-ping
Institution:(1.Department of Gastroenterology, Peking University Third Hospital, Beijing 100191, China; 2.Department of Biomedi-cal Engineering, College of Engineering, Peking University, Beijing 100187, China)
Abstract:Objective:To assess whether the same biological conclusion,diagnostic or curative effects regarding microbial composition of irritable bowel syndrome (IBS) patients could be reached through different bioinformatics pipelines,we used two common bioinformatics pipelines (Uparse V2.0 and Mothur V1.39.5) to analyze the same fecal microbial 16S rRNA high-throughput sequencing data.Methods:The two pipelines were used to analyze the diversity and richness of fecal microbial 16S rRNA highthroughput sequencing data of 27 samples,including 9 healthy controls (HC group),9 diarrhea IBS patients before (IBS group) and after Rifaximin treatment (IBS-treatment,IBSt group).Analyses such as microbial diversity,principal co-ordinates analysis (PCoA),nonmetric multidimensional scaling (NMDS) and linear discriminant analysis effect size (LEfSe) were used to find out the microbial differences among HC group vs.IBS group and IBS group vs.IBSt group.Results:(1) Microbial composition comparison of the 27 samples in the two pipelines showed significant variations at both family and genera levels while no significant variations at phylum level;(2) There was no significant difference in the comparison of HC vs.IBS or IBS vs.IBSt (Uparse:HC vs.IBS,F =0.98,P =0.445;IBS vs.IBSt,F=0.47,P=0.926;Mothur:HC vs.IBS,F=0.82,P=0.646;IBS vs.IBSt,F=0.37,P=0.961).The Shannon index was significantly decreased in IBSt;(3) Both workshops distinguished the significantly enriched genera between HC and IBS groups.For example,Nitrosomonas and Paraprevotella increased while Pseudoalteromonadaceae and Anaerotruncus decreased in HC group through Uparse pipeline,nevertheless Roseburia 62 increased while Butyricicoccus and Moraxellaceae decreased in HC group through Mothur pipeline.Only Uparse pipeline could pick out significant genera between IBS and IBSt,such as Pseudobutyricibrio,Clostridiaceae 1 and Clostridiumsensustricto 1.Conclusion:There were taxonomic and phylogenetic diversity differences between the two pipelines,Mothur can get more taxonomic details because the count number of each taxonomic level is higher.Both pipelines could distinguish the significantly enriched genera between HC and IBS groups,but Uparse was more capable to identity the difference between IBS and IBSt groups.To increase the reproducibility and reliability and to retain the consistency among similar studies,it is very important to consider the impact on different pipelines.
Keywords:Irritable bowel syndrome  Bioinformatics  High-throughput sequencing  
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