Data‐Independent Acquisition‐Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response. Issue 2 (10th January 2020)

• Record Type: Journal Article
• Authors: Li, Lei; Chen, Li; Lu, Xinya; Huang, Chenyang; Luo, Haihua; Jin, Jingmiao; Mei, Zhuzhong; Liu, Jinghua; Liu, Cuiting; Shi, Junmin; Chen, Peng; Jiang, Yong
• Is Part Of: Proteomics. Volume 20:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-10
• Subjects: data‐independent acquisition -- inflammation -- lipopolysaccharide -- proteomics -- transcriptome; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201900203
• Languages: English
• ISSNs: 1615-9853

Abstract

Abstract: Understanding of the molecular regulatory mechanisms underlying the inflammatory response is incomplete. The present study focuses on characterizing the proteome in a model of inflammation in macrophages treated with lipopolysaccharide (LPS). A total of 3597 proteins are identified in macrophages with the data‐independent acquisition (DIA) method. Bioinformatic analyses reveal discrete modules and the underlying molecular mechanisms, as well as the signaling network that modulates the development of inflammation. It is found that a total of 87 differentially expressed proteins are shared by all stages of LPS‐induced inflammation in macrophages and that 18 of these proteins participate in metabolic processes by forming a tight interaction network. Data support the hypothesis that ribosome proteins play a key role in regulating the macrophage response to LPS. Interestingly, conjoint analyses of the transcriptome and proteome in macrophages treated with LPS reveal that the genes upregulated at both the mRNA and protein levels are mainly involved in inflammation and the immune response, whereas the genes downregulated are significantly enriched in metabolism‐related processes. These results not only provide a more comprehensive understanding of the molecular mechanisms of inflammation mediated by bacterial infection but also provide a dynamic proteomic resource for further studies.