iProXProteomicsProf. Yong JiangMus Musculushttp://www.iprox.org/page/project.html?id=IPX0001908000jiang48231@163.comGuangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, ChinaiProXUnderstanding 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.Data-Independent Acquisition-Based Quantitative Proteomics Analysis Reveals Dynamic Network Profiles during the Macrophage Inflammatory Response.Li Lei L, Chen Li L, Lu Xinya X, Huang Chenyang C, Luo Haihua H, Jin Jingmiao J, Mei Zhuzhong Z, Liu Jinghua J, Liu Cuiting C, Shi Junmin J, Chen Peng P, Jiang Yong YfalseData-independent acquisition-based quantitative proteomics analysis reveals dynamic network profiles during the macrophage inflammatory response.Understanding of the molecular regulatory mechanisms underlying the inflammatory response isincomplete, especially with respect to the global proteomic response to microbial infection. Data-independent acquisition (DIA)-based quantitative proteomic analysis has been widely applied inproteomics research due to its advantages, such as improved protein coverage and reliable dataacquisition. In the present study, we focused on characterizing the proteome in a model ofinflammation in macrophages treated with lipopolysaccharide (LPS), which is important forilluminating the fundamental mechanisms of the inflammatory response to bacterial infection. Atotal of 3597 proteins were identified in macrophages with the DIA method, which provided acomprehensive 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 underlyingmolecular mechanisms, as well as the signaling network that modulates the development ofinflammation. We found that a total of 87 differentially expressed proteins (DEPs) were shared byall stages of LPS-induced inflammation in macrophages and that 18 of these proteins participatein metabolic processes by forming a tight interaction network. Our data support the hypothesisthat ribosome proteins play a key role in regulating the macrophage response to LPS, whichprovides a novel insight into the regulation of inflammation. Interestingly, conjoint analyses of thetranscriptome and proteome in macrophages treated with LPS for 6 h revealed that the genesupregulated at both the mRNA and protein levels were mainly involved in inflammation and theimmune response, whereas the genes downregulated at both the mRNA and protein levels weresignificantly enriched in metabolism-related processes. Taken together, these results not onlyprovide a more comprehensive understanding of the molecular mechanisms of inflammationmediated by bacterial infection but also provide a dynamic proteomic resource for further studieson potential biomarkers for clinical diagnosis and protein targets for drug screening in the contextof various inflammatory diseases.Mon Dec 09 00:00:00 GMT 2019PXD0166681009031876377