Basic & Clinical Medicine ›› 2024, Vol. 44 ›› Issue (6): 779-785.doi: 10.16352/j.issn.1001-6325.2024.06.0779

• Original Articles • Previous Articles     Next Articles

Dynamic transcriptomic analysis of macrophages infected with Salmonella typhimurium

SONG Boyuan, WU Xueli, LI Xueyuan, WANG Lisha, CHEN Yang*   

  1. Department of Biochemistry and Molecular Biology,Institute of Basic Medical Sciences CAMS,School of Basic Medicine PUMC, Beijing 100005,China
  • Received:2024-01-08 Revised:2024-03-23 Online:2024-06-05 Published:2024-05-24
  • Contact: *yc@ibms.pumc.edu.cn

Abstract: Objective To comprehensively understand the dynamic transcriptional landscape during infection through investigating the temporal molecular changes in macrophages RAW 264.7 upon infection with Salmonella typhimurium SL1344. Methods Macrophages RAW 264.7 were infected with Salmonella typhimurium SL1344, and cell samples were collected at 0 h, 8 h, and 16 h for RNA-sequencing(RNA-seq). Upstream and downstream analyses of the transcriptome data including differential gene expression, clustering, functional annotation, and molecular network studies were conducted to elucidate the signaling pathways changes in macrophages. Results Infected macrophages exhibited significant morphological and transcriptional changes. Differential gene analysis identified significant upregulation and downregulation patterns. Clustering revealed six gene clusters involving various signaling pathways, such as immune response, membrane transport, and lipid catabolic process. Conclusions Macrophages dynamically respond to Salmonella typhimurium infection, displaying distinct temporal gene expression patterns. The coordinated activation of immune response, membrane transport, and lipid catabolic process pathways implies a multifaceted cellular adaptation to external infections, providing essential insights into the molecular mechanisms of macrophage response to Salmonella typhimurium infection.

Key words: macrophages, infection model, immune response, transcriptome, temporal analysis

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