基于非依赖数据采集的呼出气冷凝液蛋白质组加权基因共表达网络分析

Weighted Gene Co-Expression Network Analysis on Proteomics of Exhaled Breath Condensate Based on Data-Independent Acquisition

呼出气冷凝液(Exhaled Breath Condensate,EBC)是一种呼吸道衬液,其收集过程无创、便捷,常常被作为肺部疾病研究的载体。建立了基于DIA(Data-Independent Acquisition)的EBC蛋白组学方法,共鉴定到2052个蛋白。通过加权基因共表达网络分析(Weighted Gene Co-expression Network Analysis,WGCNA)筛选出61个关键蛋白,分析发现这些关键蛋白活跃参与多个与人类疾病相关的代谢通路。结果表明,基于DIA的EBC蛋白组学方法,结合WGCNA分析,可以有效地挖掘出EBC中与疾病相关的生物标志物,未来可应用于大规模的临床研究。

Exhaled breath condensate(EBC)is a kind of respiratory lining fluid,which is easy to collect and non-invasive.EBC is considered to be the ideal sample for the study of pulmonary diseases.Proteomics is one of the novel methods to develop disease biomarkers,and the proteomics of EBC is widely studied due to its tremendous biological potential.It can reflect different disease status by analyzing the components of EBC protein,explore potential biomarkers,and improve the diagnostic ability of lung cancer and other diseases.In this study,an EBC proteomics method based on data independent acquisition(DIA)was established to overcome the disadvantage of low protein concentration of EBC,and 2052 proteins were identified.On this basis,the weighted gene co-expression network analysis(WGCNA)was carried out.WGCNA is a novel bioinformatic analysis technology,which allows multiple analysis of different omics information.A total of 61 hub proteins were screened by cluster analysis,and the hub proteins were analyzed by gene ontology(GO),Kyoto encyclopedia of genes and genomes(KEGG)and protein-protein interactions(PPIs)analysis.The results showed that the hub proteins mainly existed in the nucleus and cytoplasm,and participated in the metabolic pathways related to human diseases,which indicated that the hub proteins could reflect the disease status and hold the potential to be biomarkers.In conclusion,the DIA-based EBC proteomics combined with WGCNA analysis,could effectively explore the potential biological functions of EBC,which could be applied to large-scale clinical research and contribute to the exploration of biomarkers in the future.