Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis

Abstract

Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae and treatment options. Here we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell- and plasma proteins in the CSF, where in particular a large increase of neutrophil derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multi-protein LASSO regression model resulted in an 18-protein panel of cell and tissue associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen specific host response patterns in CSF from different disease etiologies to support future classification of pathogen-type based on host response patterns in meningitis.

Deep proteomics network and machine learning analysis of human cerebrospinal fluid in Japanese encephalitis virus infection

“…Additional functional enrichments reflecting different WGCNA modules have previously been described anti-apoptosis (74), heat shock response (75, 76), unfolded protein response (77), translation (78), IgM (79), cell adhesion and pathogen attachment (80), endothelial activation (81) and macrophage activation (82, 83). In comparison to other neurological infections, there was a downregulation in acute phase response proteins and neutrophil enriched proteins, as has been seen by other studies (84–87). In these, however, the sample size for the analysis of proteins predictive of outcome was less substantial and not supported by an a priori power calculation.…”

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

“…Proteins such as β-2-microglobulin (B2M) and α-1-antitrypsin (SERPINA1) increased in urine after sepsis-induced AKI ( 143 ), while levels of α-fibrinogen (FGA) chains are decreased. Another promising potential biomarkers are acidic nucleic protein deglycase DJ-1 (PARK7) and cadherin 16 (CDH16) ( 70 ). PARK7 functions as an inhibitor of cellular oxidative stress and a regulator of mitochondrial function, autophagy, and apoptosis ( 143 ), and CDH16 is exclusively expressed in the kidney ( 142 ).…”

“…New DIA approaches, such as sequential window acquisition of all theoretical mass spectra (SWATH-MS) combine the benefits of both targeted and shotgun approaches to provide high-throughput, accurate quantification and reproducible measurements within a single experimental setup ( 59 , 63 – 65 ). SWATH-MS has become a useful methodology in the context of drug or vaccines development ( 66 ), identification of biomarkers of HIV-1 ( 67 ), evaluation of changes in tissue-specific protein profiles in sepsis ( 68 ), evaluation of changes in the proteome under antibiotic pressure ( 69 ) and providing novel insights from central nervous system (CNS) functioning and the host response with meningitis ( 70 ).…”

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

“…Finally, the peptide-spectrum matches (PSM), the assignment of the peptide sequences to individual MS spectra, are produced using comprehensive compendia of reference protein sequences database [3]. Some of MS's remarkable applications are in the infection medicine proteomics field, where it is employed to characterize the molecular mechanism behind invasive bacterial diseases [4][5][6], modeling host-pathogen interactions [7][8][9][10][11][12][13] and investigate systemic proteome changes [14][15][16][17][18]. The use of the trypsin protease is justified by its efficiency, stability, and specificity to cleave only at the C-terminal of the basic residues, arginine, and lysine [19].…”