Liu Ning-Ning, Jiao Na, Tan Jing-Cong, Wang Ziliang, Wu Dingfeng, Wang An-Jun, Chen Jie, Tao Liwen, Zhou Chenfen, Fang Wenjie, Cheong Io Hong, Pan Weihua, Liao Wanqing, Kozlakidis Zisis, Heeschen Christopher, Moore Geromy G, Zhu Lixin, Chen Xingdong, Zhang Guoqing, Zhu Ruixin, Wang Hui
State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
National Clinical Research Center for Child Health, the Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Nat Microbiol. 2022 Feb;7(2):238-250. doi: 10.1038/s41564-021-01030-7. Epub 2022 Jan 27.
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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