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Japanese encephalitis virus is a leading cause of neurological infection in the Asia-Pacific region with no means of detection in more remote areas. We aimed to test the hypothesis of a Japanese encephalitis (JE) protein signature in human cerebrospinal fluid (CSF) that could be harnessed in a rapid diagnostic test (RDT), contribute to understanding the host response and predict outcome during infection. Liquid chromatography and tandem mass spectrometry (LC-MS/MS), using extensive offline fractionation and tandem mass tag labeling (TMT), enabled comparison of the deep CSF proteome in JE vs other confirmed neurological infections (non-JE). Verification was performed using data-independent acquisition (DIA) LC-MS/MS. 5,070 proteins were identified, including 4,805 human proteins and 265 pathogen proteins. Feature selection and predictive modeling using TMT analysis of 147 patient samples enabled the development of a nine-protein JE diagnostic signature. This was tested using DIA analysis of an independent group of 16 patient samples, demonstrating 82% accuracy. Ultimately, validation in a larger group of patients and different locations could help refine the list to 2-3 proteins for an RDT. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD034789 and 10.6019/PXD034789.

Original publication

DOI

10.1021/acs.jproteome.2c00563

Type

Journal article

Journal

J Proteome Res

Publication Date

02/06/2023

Volume

22

Pages

1614 - 1629

Keywords

Japanese encephalitis virus, Lao PDR, central nervous system infection, clinical proteomics, data-independent acquisition, diagnosis, encephalitis, flavivirus, machine learning analysis, mass spectrometry, network analysis, neurological infection, predictive modeling., tandem mass tagging, Humans, Encephalitis, Japanese, Encephalitis Virus, Japanese, Chromatography, Liquid, Proteomics, Tandem Mass Spectrometry, Proteome