Dataset Information

Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis.

ABSTRACT: 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.

SUBMITTER: Gomez-Baena G

PROVIDER: S-EPMC5539295 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis.

Gómez-Baena Guadalupe G Bennett Richard J RJ Martínez-Rodríguez Carmen C Wnęk Małgorzata M Laing Gavin G Hickey Graeme G McLean Lynn L Beynon Robert J RJ Carrol Enitan D ED

Scientific reports 20170801 1

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 spect ...[more]

PMID: 28765563

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Project description:The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

Project description:BACKGROUND: There is little knowledge concerning the content and the mechanisms of filling of arachnoid cysts. The aim of this study was to compare the protein content of arachnoid cysts and cerebrospinal fluid by quantitative proteomics to increase the understanding of arachnoid cysts. METHODS: Arachnoid cyst fluid and cerebrospinal fluid from five patients were analyzed by quantitative proteomics in two separate experiments.In a label-free experiment arachnoid cyst fluid and cerebrospinal fluid samples from individual patients were trypsin digested and analyzed by Orbitrap mass spectrometry in a label-free manner followed by data analysis using the Progenesis software.In the second proteomics experiment, a patient sample pooling strategy was followed by MARS-14 immunodepletion of high abundant proteins, trypsin digestion, iTRAQ labelling, and peptide separation by mix-phase chromatography followed by Orbitrap mass spectrometry analysis. The results from these analyzes were compared to previously published mRNA microarray data obtained from arachnoid membranes. RESULTS: We quantified 348 proteins by the label-free individual patient approach and 1425 proteins in the iTRAQ experiment using a pool from five patients of arachnoid cyst fluid and cerebrospinal fluid. This is by far the largest number of arachnoid cyst fluid proteins ever identified, and the first large-scale quantitative comparison between the protein content of arachnoid cyst fluid and cerebrospinal fluid from the same patients at the same time. Consistently in both experiment, we found 22 proteins with significantly increased abundance in arachnoid cysts compared to cerebrospinal fluid and 24 proteins with significantly decreased abundance. We did not observe any molecular weight gradient over the arachnoid cyst membrane. Of the 46 proteins we identified as differentially abundant in our study, 45 were also detected from the mRNA expression level study. None of them were previously reported as differentially expressed. We did not quantify any of the proteins corresponding to gene products from the ten genes previously reported as differentially abundant between arachnoid cysts and control arachnoid membranes. CONCLUSIONS: From our experiments, the protein content of arachnoid cyst fluid and cerebrospinal fluid appears to be similar. There were, however, proteins that were significantly differentially abundant between arachnoid cyst fluid and cerebrospinal fluid. This could reflect the possibility that these proteins are affected by the filling mechanism of arachnoid cysts or are shed from the membranes into arachnoid cyst fluid. Our results do not support the proposed filling mechanisms of oncotic pressure or valves.

Dataset Information

Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis.

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Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis.

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