%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Bharucha, T.
%A Gangadharan, B.
%A Kumar, A.
%A Myall, A. C.
%A Ayhan, N.
%A Pastorino, B.
%A Chanthongthip, A.
%A Vongsouvath, M.
%A Mayxay, M.
%A Sengvilaipaseuth, O.
%A Phonemixay, O.
%A Rattanavong, S.
%A O'Brien, D. P.
%A Vendrell, I.
%A Fischer, R.
%A Kessler, B.
%A Turtle, L.
%A de Lamballerie, X.
%A Dubot Pérès, Audrey
%A Newton, P. N.
%A Zitzmann, N.
%T Deep proteomics network and machine learning analysis of human cerebrospinal fluid in japanese encephalitis virus infection
%D 2023
%L fdi:010088170
%G ENG
%J Journal of Proteome Research
%@ 1535-3893
%K central nervous system infection ; neurological infection ; encephalitis ; flavivirus ; Japanese encephalitis virus ; diagnosis ; clinical proteomics ; mass spectrometry ; tandem mass tagging ; data-independent acquisition ; network analysis ; machine learning analysis ; predictive modeling ; Lao ; PDR
%K LAOS
%M ISI:001012219300001
%N 6
%P 1614-1629
%R 10.1021/acs.jproteome.2c00563
%U https://www.documentation.ird.fr/hor/fdi:010088170
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2023-08/010088170.pdf
%V 22
%W Horizon (IRD)
%X Japanese encephalitis virus is a leading cause of neurologicalinfection in the Asia-Pacific region with no means of detection inmore remote areas. We aimed to test the hypothesis of a Japanese encephalitis(JE) protein signature in human cerebrospinal fluid (CSF) that couldbe harnessed in a rapid diagnostic test (RDT), contribute to understandingthe host response and predict outcome during infection. Liquid chromatographyand tandem mass spectrometry (LC-MS/MS), using extensive offlinefractionation and tandem mass tag labeling (TMT), enabled comparisonof 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 4,805human proteins and 265 pathogen proteins. Feature selection and predictivemodeling using TMT analysis of 147 patient samples enabled the developmentof a nine-protein JE diagnostic signature. This was tested using DIAanalysis of an independent group of 16 patient samples, demonstrating82% accuracy. Ultimately, validation in a larger group of patientsand different locations could help refine the list to 2-3 proteinsfor an RDT. The mass spectrometry proteomics data have been depositedto the ProteomeXchange Consortium via the PRIDE partner repositorywith the dataset identifier PXD034789 and 10.6019/PXD034789.
%$ 050 ; 020 ; 052