Altered interaction network in the gut microbiota of current cigarette smokers

Abstract

The association between cigarette smoking and the gut microbiota remains unclear, and there is no agreement on how smoking affects the composition of gut microorganisms. In this study, the relationship between smoking status and gut microbial composition was investigated by performing 16S rRNA gene amplicon sequencing analysis of stool samples from 80 healthy Chinese adults. The results showed that smoking did not cause significant changes to the composition and microbial functional pathways of the gut microbiota. However, smoking altered the relative abundance of several specific taxa, where Phascolarctobacterium and Fusobacterium increased and Dialister decreased. Notably, our analysis revealed that smoking introduced more microbial interactions to the interaction network and decreased its modularity. Overall, this study provides new insights into the association between smoking status and the gut microbiota.

Keywords

Cigarette smoking / Gut microbiota / China / Co-occurrence network

Conclusion

In summary, our study revealed that smoking did not cause significant differences in the alpha and beta diversity of the gut microbiota in our cohort. However, smoking affected the relative abundance of specific taxa, where Phascolarctobacterium and Fusobacterium increased and Dialister decreased. Moreover, smoking affected the structure of the co-occurrence network, leading to more interactions between taxa and a decrease in the network modularity. The results of this study provide new insights into the association between smoking and the gut microbiota.

Data Availability Statement

The raw sequence data have been deposited at the Beijing Institute of Genomics Data Center (BIGD) under the genome sequence archive (GSA) number CRA011053 (http://bigd.big.ac.cn/gsa/s/xWfbv74D).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Zhouhai Zhu: Writing - original draft, Methodology. Meng Wang: Writing - original draft, Methodology. Ying Guan: Software, Project administration. Meng Li: Validation, Supervision. Qiyuan Peng: Investigation, Formal analysis. Ning Zheng: Project administration, Formal analysis. Wenbin Ma: Writing - review & editing, Funding acquisition, Conceptualization.

Acknowledgments

This work was supported by Joint Institute of Tobacco and Health Open Project Fund (2021539200340050), Science and Technology Project of China Tobacco Yunnan Industrial Co., Ltd (2021JC07), and the State Key Laboratory of the Microbial Technology Open Projects Fund (M2022-04).

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