Author:
Wang Yi-Long,Guo Xiao-Tong,Zhu Meng-Ying,Mao Yu-Chen,Xu Xue-Bin,Hua Yi,Xu Lu,Jiang Li-Hua,Zhao Cong-Ying,Zhang Xin,Sheng Guo-Xia,Jiang Pei-Fang,Yuan Zhe-Feng,Gao Feng
Abstract
IntroductionEarly and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis (VE) and/or viral meningitis (VM).MethodsIn our research, Metagenomic next-generation sequencing (mNGS) which can identify viral pathogens unbiasedly was performed on RNA and DNA to identify potential pathogens in cerebrospinal fluid (CSF) samples from 50 pediatric patients with suspected VEs and/or VMs. Then we performed proteomics analysis on the 14 HEV-positive CSF samples and another 12 CSF samples from health controls (HCs). A supervised partial least squaresdiscriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) model was performed using proteomics data.ResultsTen viruses in 48% patients were identified and the most common pathogen was human enterovirus (HEV) Echo18. 11 proteins overlapping between the top 20 DEPs in terms of P value and FC and the top 20 proteins in PLS-DA VIP lists were acquired.DiscussionOur result showed mNGS has certain advantages on pathogens identification in VE and VM and our research established a foundation to identify diagnosis biomarker candidates of HEV-positive meningitis based on MS-based proteomics analysis, which could also contribute toward investigating the HEV-specific host response patterns.
Subject
Infectious Diseases,Microbiology (medical),Immunology,Microbiology
Cited by
2 articles.
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