Metagenomic next-generation sequencing and proteomics analysis in pediatric viral encephalitis and meningitis - 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; et al. (Frontiers in Cellular and Infection Microbiology, 2023)
Early and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis (VE) and/or viral meningitis (VM). In our research, we used mNGS to identify pathogens in the cerebrospinal fluid (CSF) samples obtained from children with suspected VE and/or VM. Mass spectrometry (MS)-based proteomics and data-independent acquisition (DIA) analyses were used to generate proteome maps. A supervised partial least squares-discriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) model was also performed using proteomics data. Nine viruses in 48% patients were identified by using metagenomic next-generation sequencing (mNGS) and we found the most common pathogen was human enterovirus (HEV) Echo18. Subsequently, we identified 816 proteins, including 66 upregulated and 108 downregulated proteins, in the CSF samples of patients in the HEV-positive group, compared with controls by applying proteomics analysis. Then 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. Based on functional analysis, dysregulated proteins were primarily associated with pertussis, complement and coagulation cascades, lysosome and cAMP signaling pathway. Our finding may contribute toward aiding the diagnosis of VE and/or VM and revealing the molecular mechanism of viral infection, facilitating therapy plans.