Construction And Application Of Virus Infection Proteomics Analysis Platform

In recent years,proteomics technology based on mass spectrometry has been widely used in the study of viruses and viral infection mechanisms due to their advantages in elucidating the host proteome after virus infection and the process of post-translational modification of host proteins.With the updating of computer technology and mathematical algorithms,many analysis tools for viruses and virus infection data have been developed and applied to virus infection research,but these tools are mainly for virus genome and transcriptome data.General-purpose proteomic data analysis tools can only analyze virus proteins or host proteins alone.At present,there is an urgent need for a data analysis platform for virus infection proteomics,which can analyze virus and host proteomics data at the same time,and provide technical support for the research of virus infection mechanism and disease diagnosis.In this study,a virus infection proteomics data analysis platform was built based on the database and underlying framework of the Z-System platform to achieve more efficient and scientific data analysis.The work content of this platform construction includes:(1)Constructed a Max Quant-based protein qualitative and quantitative analysis workflow,and packaged it into the Z-System to realize the analysis of label-free quantification and TMT-labeled quantitative mass spectrometry search results,and synthesized five virus-host protein sequence databases for use choose from search library.(2)Two data analysis workflows were constructed for the single-factor two-level and single/multi-factor multi-level experimental design types.And by designing workflow parameter forms,marking and grouping samples to be analyzed,workflow computing task management,and visual display of analysis results,the functions of the viral proteome analysis platform are realized.Finally,the constructed data analysis platform was used to re-analyze the mass spectrometry data of urine samples from COVID-19 patients,healthy controls and rehabilitation donors in the public database.We used the fold change ≥2 and p-value﹤0.05 as filters to obtain 467 and 353 differentially expressed proteins between severe and mild diseases compared to the healthy control.There were 460 and 341 significantly down-regulated proteins,and 7 and 12 significantly up-regulated proteins in severe and mild COVID-19 samples.By comparing GO analysis of these differential proteins,it is found that the differential protein is related to platelet degranulation,complement activation,immune response and other functions;through fuzzy cluster analysis,all proteins were divided into 16 clusters.The proteins in cluster 3 showed a tendency of up-regulation from mild to severe.The functional enrichment results showed that these proteins are related to inflammation,apoptosis induced by oxidative stress,and platelet degranulation.Combining the results of difference analysis and fuzzy cluster analysis,we obtained 29 protein markers for distinguishing mild and severe cases,demonstrating the practicality of the virus infection proteomic data analysis platform constructed in this study.