@article{fdi:010088170,
  title = {{D}eep proteomics network and machine learning analysis of human cerebrospinal fluid in japanese encephalitis virus infection},
  author = {{B}harucha, {T}. and {G}angadharan, {B}. and {K}umar, {A}. and {M}yall, {A}. {C}. and {A}yhan, {N}. and {P}astorino, {B}. and {C}hanthongthip, {A}. and {V}ongsouvath, {M}. and {M}ayxay, {M}. and {S}engvilaipaseuth, {O}. and {P}honemixay, {O}. and {R}attanavong, {S}. and {O}'{B}rien, {D}. {P}. and {V}endrell, {I}. and {F}ischer, {R}. and {K}essler, {B}. and {T}urtle, {L}. and de {L}amballerie, {X}. and {D}ubot {P}{\'e}r{\`e}s, {A}udrey and {N}ewton, {P}. {N}. and {Z}itzmann, {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{J}apanese encephalitis virus is a leading cause of neurologicalinfection in the {A}sia-{P}acific region with no means of detection inmore remote areas. {W}e aimed to test the hypothesis of a {J}apanese 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. {L}iquid 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}). {V}erification was performed using data-independent acquisition({DIA}) {LC}-{MS}/{MS}. 5,070 proteins were identified, including 4,805human proteins and 265 pathogen proteins. {F}eature selection and predictivemodeling using {TMT} analysis of 147 patient samples enabled the developmentof a nine-protein {JE} diagnostic signature. {T}his was tested using {DIA}analysis of an independent group of 16 patient samples, demonstrating82% accuracy. {U}ltimately, validation in a larger group of patientsand different locations could help refine the list to 2-3 proteinsfor an {RDT}. {T}he mass spectrometry proteomics data have been depositedto the {P}roteome{X}change {C}onsortium via the {PRIDE} partner repositorywith the dataset identifier {PXD}034789 and 10.6019/{PXD}034789.},
  keywords = {central nervous system infection ; neurological infection ; encephalitis ; flavivirus ; {J}apanese encephalitis virus ; diagnosis ; clinical proteomics ; mass spectrometry ; tandem mass tagging ; data-independent acquisition ; network analysis ; machine learning analysis ; predictive modeling ; {L}ao ; {PDR} ; {LAOS}},
  booktitle = {},
  journal = {{J}ournal of {P}roteome {R}esearch},
  volume = {22},
  numero = {6},
  pages = {1614--1629},
  ISSN = {1535-3893},
  year = {2023},
  DOI = {10.1021/acs.jproteome.2c00563},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088170},
}