Single-cell sequencing reveals lung cell fate evolution initiated by smoking to explore gene predictions of correlative diseases

AbstractContinuous smoking leads to adaptive regulation and physiological changes in lung tissue and cells, and is an inductive factor for many diseases, making smokers face the risk of malignant and non-malignant diseases. The impact research is getting more and more in-depth, but the stimulant effect, mechanism of action and response mechanism of the main cells in the lungs caused by smoke components have not yet been fully elucidated, and the early diagnosis and identification of various diseases induced by smoke toxins have not yet formed a systematic relationship method. In this study, single-cell transcriptome data were generated from three lung samples of smokers and non-smokers through scRNA-seq technology, revealing the influence of smoking on lung tissue and cells and the changes in immune response. The results show that: through UMAP cell clustering, 16 intermediate cell states of 23 cell clusters of the 4 main cell types in the lung are revealed, the differences of the main cell groups between smokers and non-smokers are explained, and the human lung cells are clarified. Components and their marker genes, screen for new marker genes that can be used in the evolution of intermediate state cells, and at the same time, the analysis of lung cell subgroups reveals the changes in the intermediate state of cells under smoke stimulation, forming a subtype intermediate state cell map. Pseudo-time ordering analysis, to determine the pattern of dynamic processes experienced by cells, differential expression analysis of different branch cells, to clarify the expression rules of cells at different positions, to clarify the evolution process of the intermediate state of cells, and to clarify the response of lung tissue and cells to smoke components mechanism. The development of this study provides new diagnosis and treatment ideas for early disease detection, identification, disease prevention and treatment of patients with smoking-related diseases, and lays a theoretical foundation based on cell and molecular regulation.Key words: smokingUMAPsingle-cell transcriptomepathological mechanismpseudo-chronological sequencegene expression regulationintermediate state of cellsearly prediction of diseaseDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. AcknowledgementsThe authors thank the single-cell transcriptome data contributors: Watanabe N, Nakayama J, Yamamoto Y for their help with this manuscript.Data availabilityThe single-cell RNA-sequencing data used in this study were downloaded from the NCBI GEO database with accession number: GSE173896.Declaration of InterestsThe authors declare no competing interests including financial and non-financial.Author contributionsXL and TL performed the experiments. XL and TL analyzed the data. XL wrote the paper, TL and XL critically revised the manuscript. All authors read and approved the final manuscript.FundingThe author(s) reported there is no funding associated with the work featured in this article.