Species-level identification of enterotype-specific microbial markers for colorectal cancer and adenoma†

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-05-09 DOI:10.1039/D4MO00016A
Ünzile Güven Gülhan, Emrah Nikerel, Tunahan Çakır, Fatih Erdoğan Sevilgen and Saliha Durmuş
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Abstract

Enterotypes have been shown to be an important factor for population stratification based on gut microbiota composition, leading to a better understanding of human health and disease states. Classifications based on compositional patterns will have implications for personalized microbiota-based solutions. There have been limited enterotype based studies on colorectal adenoma and cancer. Here, an enterotype-based meta-analysis of fecal shotgun metagenomic studies was performed, including 1579 samples of healthy controls (CTR), colorectal adenoma (ADN) and colorectal cancer (CRC) in total. Gut microbiota of healthy people were clustered into three enterotypes (Ruminococcus-, Bacteroides- and Prevotella-dominated enterotypes). Reference-based enterotype assignments were performed for CRC and ADN samples, using the supervised machine learning algorithm, K-nearest neighbors. Differential abundance analyses and random forest classification were conducted on each enterotype between healthy controls and CRC–ADN groups, revealing novel enterotype-specific microbial markers for non-invasive CRC screening strategies. Furthermore, we identified microbial species unique to each enterotype that play a role in the production of secondary bile acids and short-chain fatty acids, unveiling the correlation between cancer-associated gut microbes and dietary patterns. The enterotype-based approach in this study is promising in elucidating the mechanisms of differential gut microbiome profiles, thereby improving the efficacy of personalized microbiota-based solutions.

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从物种水平鉴定大肠癌和腺瘤的肠型特异性微生物标记物
肠型已被证明是根据肠道微生物群组成进行人群分层的一个重要因素,有助于更好地了解人类健康和疾病状态。基于组成模式的分类将对基于微生物群的个性化解决方案产生影响。基于肠型的结直肠腺瘤和癌症研究还很有限。在此,我们对粪便猎枪元基因组研究进行了基于肠型的荟萃分析,共包括 1579 份健康对照(CTR)、结直肠腺瘤(ADN)和结直肠癌(CRC)样本。健康人群的肠道微生物群被分为三种肠型(以反刍球菌、乳酸杆菌和普雷沃特氏菌为主的肠型)。使用监督机器学习算法 K-Nearest Neighbors 对 CRC 和 ADN 样品进行了基于参考的肠型分配。我们对健康对照组和 CRC-ADN 组之间的每种肠型进行了丰度差异分析和随机森林分类,为非侵入性 CRC 筛查策略揭示了新型肠型特异性微生物标记物。此外,我们还发现了每种肠型特有的微生物物种,它们在次级胆汁酸和短链脂肪酸的产生中发挥作用,揭示了癌症相关肠道微生物与饮食模式之间的相关性。本研究中基于肠型的方法有望阐明肠道微生物组特征差异的机制,从而提高基于微生物群的个性化解决方案的功效。
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CiteScore
7.20
自引率
4.30%
发文量
567
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