Alternation of the gut microbiota in irritable bowel syndrome: an integrated analysis based on multicenter amplicon sequencing data

Han Chen; Rong Ou; Nana Tang; Wei Su; Ruoyun Yang; Xin Yu; Guoxin Zhang; Jianhua Jiao; Xiaoying Zhou

doi:10.1186/s12967-023-03953-7

Alternation of the gut microbiota in irritable bowel syndrome: an integrated analysis based on multicenter amplicon sequencing data

J Transl Med. 2023 Feb 11;21(1):117. doi: 10.1186/s12967-023-03953-7.

Authors

Han Chen^#^{1

2}, Rong Ou^#³, Nana Tang^#^{1

2}, Wei Su^{1

2}, Ruoyun Yang^{1

2}, Xin Yu^{1

2}, Guoxin Zhang^{1

2}, Jianhua Jiao^{4

5}, Xiaoying Zhou^{6

7}

Affiliations

¹ Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China.
² The First Clinical Medical College, Nanjing Medical University, Nanjing, China.
³ Department of Gastroenterology and Hepatology, Jinhu County People's Hospital, Huaian, China.
⁴ Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China. jiaojh1968@aliyun.com.
⁵ The First Clinical Medical College, Nanjing Medical University, Nanjing, China. jiaojh1968@aliyun.com.
⁶ Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, 300# Guangzhou Road, Nanjing, 210029, People's Republic of China. zhouxiaoying0926@njmu.edu.cn.
⁷ The First Clinical Medical College, Nanjing Medical University, Nanjing, China. zhouxiaoying0926@njmu.edu.cn.

^# Contributed equally.

Abstract

Background: Gut dysbacteriosis has been reported as one of the etiologies for irritable bowel syndrome (IBS). However, the association between gut microbiota and IBS is still inconclusive.

Method: A paired-sample study was designed by retrieving original multicenter 16 s-rRNA data of IBS patients and healthy controls from the GMrepo database. The propensity score matching (PSM) algorithm was applied to reduce confounding bias. The differential analysis of microbiota composition was performed at different taxonomic levels. The co-occurrence network was established. Subgroup analysis was performed to identify specific microbial compositions in different IBS subtypes.

Results: A total of 1522 amplicon samples were initially enrolled. After PSM, 708 individuals (354 IBS and 354 healthy controls) were eligible for further analysis. A total of 1,160 genera were identified. We identified significantly changed taxa in IBS groups (IBS-enriched: the families Enterobacteriaceae, Moraxellaceae and Sphingobacteriaceae; the genera Streptococcus, Bacillus, Enterocloster, Sphingobacterium, Holdemania and Acinetobacter. IBS-depleted: the phyla Firmicutes, Euryarchaeota, Cyanobacteria, Acidobacteria and Lentisphaerae; the families Bifidobacteriaceae, Ruminococcaceae, Methanobacteriaceae and the other 25 families; the genera Faecalibacterium, Bifidobacterium and other 68 genera). The co-occurrence network identified three hub genera and six hub species (including Faecalibacterium prausnitzii) that may be involved in IBS pathophysiology. Strong positive interactions were identified among the Bifidobacterium longum, Bifidobacterium breve and Bifidobacterium adolescentis in the Bifidobacterium community.

Conclusion: This study provides quantitative analysis and visualization of the interaction between the gut microbiota and IBS. The identification of key species should be further validated to evaluate their causal relationships with the pathogenesis of IBS.

Keywords: Amplicon sequencing analysis; GMrepo database; Gut microbiota; Irritable bowel syndrome; Propensity score matching.

Publication types

Multicenter Study
Research Support, Non-U.S. Gov't

MeSH terms

Bacteria / genetics
Feces / microbiology
Gastrointestinal Microbiome* / genetics
Humans
Irritable Bowel Syndrome* / genetics
Irritable Bowel Syndrome* / microbiology
RNA, Ribosomal, 16S / genetics

Substances

RNA, Ribosomal, 16S