Metabolomics and metagenomics reveal the impact of γδ T inhibition on gut microbiota and metabolism in periodontitis-promoting OSCC

肠道菌群 基因组 生物 代谢组 失调 牙周炎 代谢组学 免疫疗法 癌症 微生物群 微生物学 免疫学 免疫系统 生物信息学 基因 医学 遗传学 内科学
作者
Wei Wei,Jing Li,Boyu Tang,Ye Deng,Yan Li,Qianming Chen
出处
期刊:MSystems [American Society for Microbiology]
标识
DOI:10.1128/msystems.00777-23
摘要

ABSTRACT During the process of periodontitis-promoting oral squamous cell carcinoma (OSCC), the periodontitis microbiota can facilitate OSCC development by activating γδ T cells. Inhibiting γδ T cells through immunotherapy has been shown to significantly alleviate various types of cancer. However, the underlying mechanism by which inhibiting γδ T cells influenced cancer treatment has not been fully elucidated. In this study, a mouse model of OSCC with periodontitis was established, and γδ T cells were inhibited by antibodies. Gut samples from the mice were collected and analyzed by metabolomics, metagenomics, and 16S rRNA. Integrative analysis of the gut metabolome and microbiome revealed that targeting γδ T resulted in changes in the levels of metabolites associated with cancer in the gut. Although there was no difference in the α diversity of microbiota, β diversity was significantly different, with a more heterogeneous community structure in the mice receiving targeted γδ T immunotherapy. Statistical analysis of the gut microbiota at the species level revealed a significant enrichment of Lactobacillus murinus , which was significantly correlated with γδ T abundance. The functional analysis revealed that inhibiting γδ T could impact the functional gene. A comprehensive analysis revealed that L. murinus is especially associated with changes in adenine, which also had connection with the concentration of IL-17 and the abundance of γδ T. IMPORTANCE This study revealed the effect of γδ T cells on gut microbial dysbiosis and identify potential links between gut microbiota and metabolism, providing new insights into the role of γδ T during the process of periodontitis-induced OSCC, and identifying relevant biomarkers for future research and clinical monitoring protocol development.
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