Data-Independent Acquisition-Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles During the Macrophage Inflammatory Response.

In the present study, we focused on characterizing the proteome in a model of inflammation in macrophages treated with lipopolysaccharide (LPS), which is important for illuminating the fundamental mechanisms of the inflammatory response to bacterial infection. A total of 3597 proteins were identified in macrophages with the data-independent acquisition (DIA) method, which provided a comprehensive view of inflammation in macrophages stimulated with LPS for different times. Bioinformatic analyses, including gene expression pattern analysis, GO enrichment analysis, KEGG pathway analysis and STRING analysis, revealed discrete modules and the underlying molecular mechanisms, as well as the signaling network that modulates the development of inflammation. We found that a total of 87 differentially expressed proteins (DEPs) were 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. Our data support the hypothesis that ribosome proteins play a key role in regulating the macrophage response to LPS, which provides a novel insight into the regulation of inflammation. Interestingly, conjoint analyses of the transcriptome and proteome in macrophages treated with LPS for 6 h revealed that the genes upregulated at both the mRNA and protein levels were mainly involved in inflammation and the immune response, whereas the genes downregulated at both the mRNA and protein levels were significantly enriched in metabolism-related processes. This article is protected by copyright. All rights reserved.