Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis.
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ABSTRACT:
SUBMITTER: Bakochi A
PROVIDER: S-EPMC8043743 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Meningitis is a life-threatening condition characterized by the inflammation of the leptomeningeal membranes surrounding the brain and spinal cord. The term meningitis is an umbrella term and includes several different etiologies. The majorities of meningitis cases are caused by viruses (viral meningitis; VM) and are often associated with low mortality rates and low risk of developing neurological. In contrast, meningitis caused by some viral infections, such as tick-borne encephalitis (TBE), can be life-threatening when left untreated with increased risk of developing neurological sequelae. Acute bacterial meningitis (ABM), however, is one of the leading causes of death due to infectious diseases worldwide and is associated with rapid disease progression, high mortality rates and increased risk of long-term neurological sequelae in survivors. As meningitis is caused by numerous different pathogens, the host-response is typically highly variable and it is currently unknown if different pathogens can introduce specific proteome changes in the cerebrospinal fluid (CSF). In this study we applied DIA-MS to provide novel insights for in-depth understanding of central nervous system functioning and host response during meningitis in a cohort of patients with differential diagnosis of meningitis, to account for variability contributed by different disease-causing pathogens. The results reveal drastic changes in the CSF proteome during meningitis, where in particular a massive increase of neutrophil derived proteins in the CSF correlated with ABM, suggesting that activated neutrophils play a particular role in ABM. Additionally both ABM and VM result in marked reduction of brain-specific proteins in the CSF, which could be indicative of pathophysiological mechanisms leading to brain damage. Furthermore, generation of lasso regression model enables separation of ABM with high sensitivity and specificity, demonstrating that several proteins are required to confidently discriminate between ABM, VM and BM.
2021-04-12 | PXD023174 | Pride
Project description:Meningitis is a life-threatening condition characterized by the inflammation of the leptomeningeal membranes surrounding the brain and spinal cord. The term meningitis is an umbrella term and includes several different etiologies. Acute bacterial meningitis (ABM) is one of the leading causes of death due to infectious diseases worldwide and is associated with rapid disease progression, high mortality rates and increased risk of long-term neurological sequelae in survivors. As meningitis is caused by numerous different pathogens, the host-response is typically highly variable and it is currently unknown if different pathogens can introduce specific proteome changes in the cerebrospinal fluid (CSF). By using LC-MS/MS we have generated assay libraries of 8 unique bacterial strains that commonly cause meningitis. These libraries can be used to mine CSF of meningitis samples to detect bacterial peptides.
2021-04-12 | PXD024904 | Pride
Project description:Background and purposeThe diagnosis of tuberculous meningitis (TBM) is difficult due to the lack of sensitive methods. Identification of TBM-specific biomarkers in the cerebrospinal fluid (CSF) may help diagnose and improve our understanding of TBM pathogenesis.Patients and methodsOf the 112 suspected patients with TBM prospectively enrolled in the study, 32 patients with inconclusive diagnosis, non-infectious meningitis, and long-term treatment with hormones and immunosuppressants were excluded. The expression of 8 proteins in the CSF was analyzed using ELISA in 22 patients with definite TBM, 18 patients with probable TBM, and 40 patients with non-TBM.ResultsSignificant differences in the expression of 7 proteins were detected between the TBM and non-TBM groups (P < 0.01). Unsupervised hierarchical clustering (UHC) analysis revealed a disease-specific profile consisting of 7 differentially expressed proteins for TBM diagnosis, with an accuracy of 82.5% (66/80). Logistic regression with forward stepwise analysis indicated that a combination of 3 biomarkers (APOE_APOAI_S100A8) showed a better ability to discriminate TBM from patients with non-TBM [area under the curve (AUC) = 0.916 (95%CI: 0.857-0.976)], with a sensitivity of 95.0% (95%CI: 83.1-99.4%) and a specificity of 77.5% (95%CI: 61.5-89.2%).ConclusionOur results confirmed the potential ability of CSF proteins to distinguish TBM from patients with non-TBM and provided a useful panel for the diagnosis of TBM.
| S-EPMC9393334 | biostudies-literature
Project description:IntroductionStroke is a common complication in children with tuberculous meningitis (TBM). Host proteins may give us insight into the mechanisms of stroke in TBM and serve as biomarkers for detection of stroke, however, they have not been widely explored. In this study, we compared the concentrations of cerebrospinal fluid (CSF) and serum proteins between children who had TBM-related stroke and children with TBM without stroke.MethodsWe collected CSF and serum from 47 children consecutively admitted to the Tygerberg Academic Hospital in Cape Town, South Africa between November 2016, and November 2017, on suspicion of having TBM. A multiplex platform was used to measure the concentrations of 69 host proteins in CSF and serum from all study participants.ResultsAfter classification of study participants, 23 (48.9%) out of the 47 study participants were diagnosed with TBM, of which 14 (60.9%) demonstrated radiological arterial ischemic infarction. The levels of lipocalin-2, sRAGE, IP-10/ CXCL10, sVCAM-1, MMP-1, and PDGF-AA in CSF samples and the levels of D-dimer, ADAMTS13, SAA, ferritin, MCP-1/ CCL2, GDF-15 and IL-13 in serum samples were statistically different between children who had TBM-related stroke and children with TBM without stroke. After correcting for multiple testing, only the levels of sVCAM-1, MMP-1, sRAGE, and IP-10/ CXCL10 in CSF were statistically different between the two groups. CSF and serum protein biosignatures indicated stroke in children diagnosed with TBM with up to 100% sensitivity and 88.9% specificity.ConclusionSerum and CSF proteins may serve as biomarkers for identifying individuals with stroke amongst children diagnosed with TBM at admission and may guide us to understand the biology of stroke in TBM. This was a pilot study, and thus further investigations in larger studies are needed.
| S-EPMC8087017 | biostudies-literature
Project description:In order to improve the diagnosis of pathogenic bacteria in cerebrospinal fluid (CSF) with purulent meningitis, we developed a DNA microarray technique for simultaneous detection and identification of seven target bacterium. DNA were extracted from 24 CSF samples with purulent meningitis (or suspected purulent meningitis). The specific genes of each pathogen were chosen as the amplification target, performed the polymerase chain reaction (PCR), labeled with a fluorescence dye, and hybridized to the oligonucleotide probes on the microarray. There is no significant cross-hybridization fluorescent signal occurred in untargeted bacteria. There were 87.5% (21/24) positive results in DNA microarray compared with the 58.3% (14/24) of the CSF culture test. Of which 58.3% (14/24) of the patients with culture-confirmed purulent meningitis, 37.5% (9/24) patients who were not confirmed by culture test but were demonstrated by the clinical diagnosis and DNA microarray. Multiple bacterial infections were detected in 5 cases by the microarray. In addition, the number of gene copies was carried out to determine the sensitivity of this technique, which was shown to be 3.5?×?101 copies/?L. The results revealed that the microarray technique which target pathogens of the CSF specimen is better specificity, accuracy, and sensitivity than traditional culture method. The microarray method is an effective tool for rapidly detecting more target pathogens and identifying the subtypes of strains which can eliminate the impact of the different individuals with purulent meningitis for prompt diagnosis and treatment.
| S-EPMC6206030 | biostudies-literature
Project description:Antimicrobial therapy necessitates fast and accurate detection of pathogens in purulent meningitis (PM) diagnosis. Although considered a gold standard, the traditional bacterial detection and identification methods based on routine bacterial culture are time-consuming and show low sensitivity and specificity. In order to reduce PM-related deaths and improve the treatment efficiency, we employed trace DNA extraction technology and combined it with Next-Generation Sequencing technology for bacteria identification. We extracted DNA from 31 cerebrospinal fluid (CSF) samples from people with PM. The samples were collected by lumbar puncture at Xi'an Children Hospital under a stringent protocol. Ion PGMTM System Next-Generation Sequencing was used to screen for pathogens in the CSF samples based on their 16S ribosomal RNA (rRNA) genes. Of the 31 CSF samples, 29 were culture negative. Streptococcus was detected in 2 samples by culture-based methods. The species identified by Next-Generation Sequencing showed a diverse bacterial population that included Streptococcus (22.6%), Escherichia (15.9%), Peptostreptococcus (10.7%), Pseudomonas (10.5%), Rothia (8.8%), Acinetobacter (4.9%), Prevotella (4.1%), Bacillus (3.3%), Neisseria (2.5%), Catonella (2.4%), Acitinomyces (2.0%), and Citrobacter (2.0%). Clustering analysis revealed three major bacterial groups, namely Streptococcus, Escherichia and Acinetobacter, each group with a different proportion of bacterial species. The results indicated that PM may result from infections by multiple bacterial species as opposed to a single species, with infectivity determined by abundance of the dominant species. Furthermore, Next-Generation Sequencing allowed a sensitive and specific etiological basis for identification of pathogens not only in the cerebrospinal fluid specimens, but also in other clinical samples.
| S-EPMC7539889 | biostudies-literature
Project description:Streptococcus pneumoniae is responsible for diseases causing major global public health problems, including meningitis, pneumonia and septicaemia. Despite recent advances in antimicrobial therapy, pneumococcal meningitis remains a life-threatening disease. Furthermore, long-term sequelae are a major concern for survivors. Hence, a better understanding of the processes occurring in the central nervous system is crucial to the development of more effective management strategies. We used mass spectrometry based quantitative proteomics to identify protein changes in cerebrospinal fluid from children with Streptococcus pneumoniae infection, compared with children admitted to hospital with bacterial meningitis symptoms but negative diagnosis. Samples were analysed, by label free proteomics, in two independent cohorts (cohort 1: cases (n?=?8) and hospital controls (n?=?4); cohort 2: cases (n?=?8), hospital controls (n?=?8)). Over 200 human proteins were differentially expressed in each cohort, of which 65% were common to both. Proteins involved in the immune response and exosome signalling were significantly enriched in the infected samples. For a subset of proteins derived from the proteome analysis, we corroborated the proteomics data in a third cohort (hospital controls (n?=?15), healthy controls (n?=?5), cases (n?=?20)) by automated quantitative western blotting, with excellent agreement with our proteomics findings. Proteomics data are available via ProteomeXchange with identifier PXD004219.
| S-EPMC5539295 | biostudies-literature
Project description:Listeria monocytogenes meningitis is the third most common cause of bacterial meningitis and is associated with high rates of mortality and unfavorable outcome.We analyzed 101 cytokines, chemokines and complement factors in CSF of adult patients with Listeria meningitis included in a prospective cohort study and compared these biomarkers between Listeria meningitis patients and negative controls, and between Listeria meningitis patients with a favorable and an unfavorable outcome.CSF was available from 26 of 62 (42%) Listeria meningitis patients and 19 negative controls. Fifteen (58%) Listeria meningitis patients had an unfavorable outcome. In Listeria meningitis CSF levels of 51 biomarkers were significantly elevated compared to negative controls after Bonferroni correction. The 11 most significantly elevated (P < .01) biomarkers of unfavorable outcome in Listeria meningitis were markers of T-cell activation (sIL-2Rα, sCD40L and IL-1), interferon-related (IFN-α2, IL-18, CX3CL1, CCL20), markers of complement activation (C3a), and endothelial growth factor related (VEGF, CXCL7).Our data suggest that T-cell activation, complement activation, interferon- and endothelial growth factor production are important in the immune response to Listeria meningitis, and thereby influence outcome.Our study provides target pathways for further studies in the pathophysiology of Listeria meningitis.
| S-EPMC4418767 | biostudies-other
Project description:Differential diagnosis of bacterial meningitis (BM) and viral meningitis (VM) is a critical clinical challenge, as the early and accurate identification of the causative agent determines the appropriate treatment regimen and markedly improves patient outcomes. Clinical and experimental studies have demonstrated that the pathogen and the host immune response contribute to mortality and neurological sequelae. As BM is associated with the activation of an inflammatory cascade, the patterns of pro- and anti-inflammatory cytokines/chemokines (CTs/CKs) present in the cerebrospinal fluid (CSF) in response to the immune assault may be useful as sensitive markers for differentiating BM from VM. In the present study, the ability of CTs/CKs in the CSF to differentiate between BM and VM was investigated. For this, biochemical markers and CT/CK profiles were analysed in 145 CSF samples, divided into three groups: BM (n=61), VM (n=58) and the control group (C; n=26) comprising patients with meningism. The CSF concentrations of monocyte chemoattractant protein-1, interleukin (IL)-8, IL-1β, IL-6, macrophage inflammatory protein-1α (MIP-1α), epithelial-neutrophil activating peptide, IL-10, tumour necrosis factor-α (TNF-α), proteins and white blood cells were significantly higher and the CSF glucose level was significantly lower in the BM group compared with the VM and C groups (P<0.01). Correlation analysis identified 28 significant correlations between various CTs/CKs in the BM group (P<0.01), with the strongest positive correlations being for TNF-α/IL-6 (r=0.75), TNF-α/MIP-1α (r=0.69), TNF-α/IL-1β (r=0.64) and IL-1β/MIP-1α (r=0.64). To identify the optimum CT/CK patterns for predicting and classifying BM and VM, a dataset of 119 BM and VM samples was divided into training (n=90) and testing (n=29) subsets for use as input for a Random Forest (RF) machine learning algorithm. For the 29 test samples (15 BM and 14 VM), the RF algorithm correctly classified 28 samples, with 92% sensitivity and 93% specificity. The results show that the patterns of CT/CK levels in the CSF can be used to aid discrimination of BM and VM.
| S-EPMC10119981 | biostudies-literature
Project description:Acute bacterial meningitis is a medical emergency, and delays in initiating effective antimicrobial therapy result in increased morbidity and mortality. Culture-based methods, thus far considered the "gold standard" for identifying bacterial microorganisms, require 24 to 48 h to provide a diagnosis. In addition, antimicrobial therapy is often started prior to clinical sample collection, thereby decreasing the probability of confirming the bacterial pathogen by culture-based methods. To enable a fast and accurate detection of the most important bacterial pathogens causing meningitis, namely, Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, Streptococcus agalactiae, and Listeria monocytogenes, we evaluated a commercially available multiplex LightMix real-time PCR (RT-PCR) in 220 cerebrospinal fluid (CSF) specimens. The majority of CSF samples were collected by lumbar puncture, but we also included some CSF samples from patients with symptoms of meningitis from the neurology department that were recovered from shunts. CSF samples were analyzed by multiplex RT-PCR enabling a first diagnosis within a few hours after sample arrival at our institute. In contrast, bacterial identification took between 24 and 48 h by culture. Overall, a high agreement of bacterial identification between culture and multiplex RT-PCR was observed (99%). Moreover, multiplex RT-PCR enabled the detection of pathogens, S. pneumoniae (n = 2), S. agalactiae (n = 1), and N. meningitidis (n = 1), in four culture-negative samples. As a complement to classical bacteriological CSF culture, the LightMix RT-PCR assay proved to be valuable by improving the rapidity and accuracy of the diagnosis of bacterial meningitis.
| S-EPMC5786711 | biostudies-literature