AUTHOR=Zhang Yong , Chen Xiangxiang , Wang Yuan , Li Ling , Ju Qing , Zhang Yan , Xi Hangtian , Wang Fahan , Qiu Dan , Liu Xingchen , Chang Ning , Zhang Weiqi , Zhang Cong , Wang Ke , Li Ling , Zhang Jian 

TITLE=Alterations of lower respiratory tract microbiome and short-chain fatty acids in different segments in lung cancer: a multiomics analysis

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2023.1261284

DOI=10.3389/fcimb.2023.1261284

ISSN=2235-2988

ABSTRACT=ABSTRACT
The lower respiratory tract microbiome is ostensibly studied to pinpoint microbial dysbiosis of diversity or abundance that is linked to a number of chronic respir-atory illnesses. However, it is vital to clarify the precise impacts of the microbiome on lung health and oncogenesis through release of microbial metabolites. In order to discover their powerful correlations, we collected paired bronchoalveolar lavage fluids (BALFs) samples from tumor-burden lung segment and ipsilateral non-tumor site within 28 lung cancer participants under electronic bronchoscopy examinations, further performing metagenomic sequencing and short chain fatty acid (SCFA) metabolomics, together with multi-omics analysis to uncover their potent correlations 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 lower respiratory tract. With 18 dif-ferentially 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 me-tabolites called short chain fatty acids showed little significance in either group independently but revealed a strong predictive value when using integrated model by machine learning. Multi-omics also discovered particular species re-lated with SCFAs, showing positive correlation of Brachyspira hydrosenteriae and negative one of Pseudomonas at genus level, despite of limited detection in lower airways. Of noting, 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 func-tion of various microbial species by different metabolites. These findings point to a potent relationship between particular components of the integrated microbi-ota-metabolites network and lung cancer, with implications for screening and diagnosis in clinic.