Feng Libo, Liu Yu, Chen Muhu, Hu Yingchun
Department of Gastrointestinal Surgery, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.
Department of Electrocardiogram, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2022 Jul;34(7):676-681. doi: 10.3760/cma.j.cn121430-20210706-01011.
To analyze protein profiles in septic patients, and to find potential new targets for the diagnosis and treatment of sepsis.
A cross sectional observational study was conducted. From January to December 2019, 12 septic patients and 9 healthy volunteers were recruited in the emergency intensive care unit (EICU) of the emergency department of the Affiliated Hospital of Southwest Medical University. The peripheral blood of the two groups was collected for protein mass spectrometry analysis, and the data-independent acquisition technology was used to obtain the expression data of each protein. The obtained data was imported into the online network tool Integrated Differential Expression and Pathway analysis (IDEP2), the data underwent ID converted and were homogenized to verify their comparability, and then principal component analysis was used to eliminate outlier data. Then data with P < 0.05, logfold change (FC) > 1 or logFC < -1 were considered to have a statistically significant difference, and the differential proteins were screened out. On the DAVID website, the screened differential proteins would be analyzed by gene ontology (GO), and the biological process, cellular components, and molecular function of the proteins would be analyzed. Protein enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) analysis was performed through the Search Tool for the Retrieval of Interacting Genes Database (STRING) website to find closely related proteins.
The data in this study were shown to be comparable after normalization. A total of 125 differential proteins were screened, of which 99 were up-regulated and 26 were down-regulated. GO enrichment analysis discovered that these proteins were mainly extracellular, with cellular regulatory functions and catalytic functions involved in biological regulation, metabolic process and immune process. KEGG pathway analysis suggested that these proteins were involved in amino acid, carbohydrate metabolism and immune-related pathways. PPI analysis showed that key proteins included matrix metalloproteinase 14 (MMP14), fibulin 1 (FBLN1), plasma kallikrein 1 (KLKB1), etc., and finally screened out MMP14 and KLKB1, which were closely related to inflammation and immunity. Both might be potential new targets for early diagnosis and treatment of sepsis.
MMP14 and KLKB1 may be potential biomarkers for the diagnosis, treatment and prognosis of sepsis.
分析脓毒症患者的蛋白质谱,寻找脓毒症诊断和治疗的潜在新靶点。
进行一项横断面观察性研究。2019年1月至12月,在西南医科大学附属医院急诊科的急诊重症监护病房(EICU)招募了12例脓毒症患者和9名健康志愿者。采集两组的外周血进行蛋白质质谱分析,采用数据非依赖采集技术获取各蛋白质的表达数据。将获得的数据导入在线网络工具综合差异表达和通路分析(IDEP2),对数据进行ID转换并标准化以验证其可比性,然后采用主成分分析去除异常数据。然后将P<0.05、log倍变化(FC)>1或logFC<-1的数据视为具有统计学显著差异,筛选出差异蛋白质。在DAVID网站上,对筛选出的差异蛋白质进行基因本体(GO)分析,分析蛋白质的生物学过程、细胞成分和分子功能。进行蛋白质富集分析和京都基因与基因组百科全书(KEGG)通路分析。通过检索相互作用基因数据库(STRING)网站进行蛋白质-蛋白质相互作用(PPI)分析,以找到密切相关的蛋白质。
本研究数据经标准化后具有可比性。共筛选出125种差异蛋白质,其中99种上调,26种下调。GO富集分析发现这些蛋白质主要位于细胞外,具有细胞调节功能以及参与生物调节、代谢过程和免疫过程的催化功能。KEGG通路分析表明这些蛋白质参与氨基酸、碳水化合物代谢及免疫相关通路。PPI分析显示关键蛋白质包括基质金属蛋白酶14(MMP14)、纤连蛋白1(FBLN1)、血浆激肽释放酶原1(KLKB1)等,最终筛选出与炎症和免疫密切相关的MMP14和KLKB1。两者可能都是脓毒症早期诊断和治疗的潜在新靶点。
MMP14和KLKB1可能是脓毒症诊断、治疗及预后评估的潜在生物标志物。