An integrated multi-omics analysis of identifies distinct molecular characteristics in pulmonary infections of Pseudomonas aeruginosa. - Yang Yang; Teng Ma; Jun Zhang; Yu Tang; Miao Tang; Chaoyu Zou; Yige Zhang; Mingbo Wu; Xueli Hu; Huan Liu; Qianhua Zhang; Yilin Liu; et al. (PLoS Pathogens, 2023)
Pseudomonas aeruginosa (P. aeruginosa) can cause severe acute infections, including pneumonia and sepsis, and cause chronic infections, commonly in patients with structural respiratory diseases. However, the molecular and pathophysiological mechanisms of P. aeruginosa respiratory infection are largely unknown. Here, we performed assays for transposase-accessible chromatin using sequencing (ATAC-seq), transcriptomics, and quantitative mass spectrometry-based proteomics and ubiquitin-proteomics in P. aeruginosa-infected lung tissues for multi-omics analysis, while ATAC-seq and transcriptomics were also examined in P. aeruginosa-infected mouse macrophages. To identify the pivotal factors that are involved in host immune defense, we integrated chromatin accessibility and gene expression to investigate molecular changes in P. aeruginosa-infected lung tissues combined with proteomics and ubiquitin-proteomics. Our multi-omics investigation discovered a significant concordance for innate immunological and inflammatory responses following P. aeruginosa infection between hosts and alveolar macrophages. Furthermore, we discovered that multi-omics changes in pioneer factors Stat1 and Stat3 play a crucial role in the immunological regulation of P. aeruginosa infection and that their downstream molecules (e.g., Fas) may be implicated in both immunosuppressive and inflammation-promoting processes. Taken together, these findings indicate that transcription factors and their downstream signaling molecules play a critical role in the mobilization and rebalancing of the host immune response against P. aeruginosa infection and may serve as potential targets for bacterial infections and inflammatory diseases, providing insights and resources for omics analyses.