下呼吸道微生物群被广泛研究，以查明与许多慢性呼吸道疾病相关的微生物多样性或丰度失调。然而，阐明微生物组如何通过释放微生物代谢物影响肺部健康和肿瘤发生至关重要。为了发现微生物代谢物与疾病之间的强大相关性，我们在电子支气管镜检查下收集了配对支气管肺泡灌洗样本来自 28 名肺癌参与者的肿瘤负荷肺段和同侧非肿瘤部位的液体 (BALF)，进一步进行宏基因组测序、短链脂肪酸 (SCFA) 代谢组学和多组学分析，以揭示微生物组和 SCFA 的潜在相关性与同一参与者正常肺段的 BALF 相比，来自肺癌负荷肺段的 BALF 下呼吸道微生物多样性略有下降。对于 18 种不同流行的微生物物种，包括众所周知的致癌物空肠弯曲杆菌和多糖奈瑟菌，两组之间下呼吸道微生物组的相对物种丰度没有显着差异。此外，一组被称为短链脂肪酸的普遍认可的益生菌代谢物在任何一组中都没有显示出独立的显着性，但在使用机器学习的集成模型时显示出很强的预测价值。多组学还发现了与 SCFA 相关的特定物种，尽管在下呼吸道中的检测有限，但在属水平上与 Brachyspira Hydrosenteriae 呈正相关，而与假单胞菌呈负相关。值得注意的是，这些独特的微生物群和代谢物与仍需要确认的临床特征相对应。对宏基因组功能能力的进一步分析表明，编码环境信息处理和代谢途径的基因在肺癌患者的下呼吸道宏基因组中富集，进一步支持了肿瘤发生不同微生物物种通过不同代谢物发挥功能。这些发现指出了综合微生物群-代谢物网络的特定组成部分与肺癌之间的潜在关系，对临床筛查和诊断具有重要意义。版权所有 © 2023 张、陈、王、李、鞠、张、Xi、Wang,邱、刘、常、张、张、王、李、张。

The lower respiratory tract microbiome is widely studied to pinpoint microbial dysbiosis of diversity or abundance that is linked to a number of chronic respiratory illnesses. However, it is vital to clarify how the microbiome, through the release of microbial metabolites, impacts lung health and oncogenesis.In order to discover the powerful correlations between microbial metabolites and disease, we collected, under electronic bronchoscopy examinations, samples of paired bronchoalveolar lavage fluids (BALFs) from tumor-burden lung segments and ipsilateral non-tumor sites from 28 lung cancer participants, further performing metagenomic sequencing, short-chain fatty acid (SCFA) metabolomics, and multiomics analysis to uncover the potential correlations of the microbiome and SCFAs in lung cancer.In comparison to BALFs from normal lung segments of the same participant, those from lung cancer burden lung segments had slightly decreased microbial diversity in the lower respiratory tract. With 18 differentially prevalent microbial species, including the well-known carcinogens Campylobacter jejuni and Nesseria polysaccharea, the relative species abundance in the lower respiratory tract microbiome did not significantly differ between the two groups. Additionally, a collection of commonly recognized probiotic metabolites called short-chain fatty acids showed little significance in either group independently but revealed a strong predictive value when using an integrated model by machine learning. Multiomics also discovered particular species related to SCFAs, showing a positive correlation with Brachyspira hydrosenteriae and a negative one with Pseudomonas at the genus level, despite limited detection in lower airways. Of note, these distinct microbiota and metabolites corresponded with clinical traits that still required confirmation.Further analysis of metagenome functional capacity revealed that genes encoding environmental information processing and metabolism pathways were enriched in the lower respiratory tract metagenomes of lung cancer patients, further supporting the oncogenesis function of various microbial species by different metabolites. These findings point to a potent relationship between particular components of the integrated microbiota-metabolites network and lung cancer, with implications for screening and diagnosis in clinical settings.Copyright © 2023 Zhang, Chen, Wang, Li, Ju, Zhang, Xi, Wang, Qiu, Liu, Chang, Zhang, Zhang, Wang, Li and Zhang.