Multi-kingdom microbiota analyses identify bacterial–fungal interactions and biomarkers of colorectal cancer across cohorts

基因组 生物 失调 微生物群 肠道菌群 结直肠癌 计算生物学 癌症 生物信息学 遗传学 基因 免疫学
作者
Ning‐Ning Liu,Na Jiao,Jing-Cong Tan,Ziliang Wang,Dingfeng Wu,An-Jun Wang,Jie Chen,Liwen Tao,Chenfen Zhou,Wenjie Fang,Io Hong Cheong,Weihua Pan,Wanqing Liao,Zisis Kozlakidis,Christopher Heeschen,Geromy G. Moore,Lixin Zhu,Xingdong Chen,Guoqing Zhang,Ruixin Zhu
出处
期刊:Nature microbiology [Nature Portfolio]
卷期号:7 (2): 238-250 被引量:177
标识
DOI:10.1038/s41564-021-01030-7
摘要

Abstract Despite recent progress in our understanding of the association between the gut microbiome and colorectal cancer (CRC), multi-kingdom gut microbiome dysbiosis in CRC across cohorts is unexplored. We investigated four-kingdom microbiota alterations using CRC metagenomic datasets of 1,368 samples from 8 distinct geographical cohorts. Integrated analysis identified 20 archaeal, 27 bacterial, 20 fungal and 21 viral species for each single-kingdom diagnostic model. However, our data revealed superior diagnostic accuracy for models constructed with multi-kingdom markers, in particular the addition of fungal species. Specifically, 16 multi-kingdom markers including 11 bacterial, 4 fungal and 1 archaeal feature, achieved good performance in diagnosing patients with CRC (area under the receiver operating characteristic curve (AUROC) = 0.83) and maintained accuracy across 3 independent cohorts. Coabundance analysis of the ecological network revealed associations between bacterial and fungal species, such as Talaromyces islandicus and Clostridium saccharobutylicum . Using metagenome shotgun sequencing data, the predictive power of the microbial functional potential was explored and elevated D-amino acid metabolism and butanoate metabolism were observed in CRC. Interestingly, the diagnostic model based on functional EggNOG genes achieved high accuracy (AUROC = 0.86). Collectively, our findings uncovered CRC-associated microbiota common across cohorts and demonstrate the applicability of multi-kingdom and functional markers as CRC diagnostic tools and, potentially, as therapeutic targets for the treatment of CRC.

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