Bulk transcriptome sequencing (bulkRNA-seq) of human cerebrospinal fluid (CSF) cells in the bacterial meningitis (BM) of children
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ABSTRACT:
PROVIDER: PRJNA685176 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13253202_1.fastq.gz | Fastqsanger.gz | |||
| SRR13253202_2.fastq.gz | Fastqsanger.gz | |||
| SRR13253203_1.fastq.gz | Fastqsanger.gz | |||
| SRR13253203_2.fastq.gz | Fastqsanger.gz | |||
| SRR13253204_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: Profiling the bulk transcriptomes of CSF cells in sepsis-developed BM progression. Methods: The total RNA of CSF cells from BM patients were extracted, and constructed into cDNA library. Raw data of mRNA profiles were sequenced by paired-end strategy. Gene-counts were generated through handling sequencing data with the combined workflow of UMI-tools, STAR, Subread package and Samtools. Results: Successfully acquirng multiple bulk-transcriptomic profiles of CSF cells from BM patients in different sepsis conditions.
2020-12-15 | GSE163195 | GEO
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:Cerebrospinal fluid transcriptional profiles in children with tuberculous meningitis (TBM) or other infections were compared using RNA-Seq and a biomarker signature driven by NMDA-receptor activation was identified
2019-08-06 | GSE122377 | GEO
Project description:Objectives: Central nervous system (CNS) infections are common causes of morbidity and mortality worldwide. We aimed to discover protein biomarkers that could rapidly and accurately identify the likely cause of the infections, essential for clinical management and improving outcome. Methods: We applied liquid chromatography tandem mass-spectrometry on 45 cerebrospinal fluid (CSF) samples from a cohort of adults with/without CNS infections to discover potential diagnostic biomarkers. We then validated the diagnostic performance of a selected biomarker candidate in an independent cohort of 364 consecutively treated adults with CNS infections admitted to a referral hospital in Vietnam. Results: In the discovery cohort, we identified lipocalin 2 (LCN2) as a potential biomarker of bacterial meningitis (BM) other than tuberculous meningitis. The analysis of the validation cohort showed that LCN2 could discriminate BM from other CNS infections (including tuberculous meningitis, cryptococcal meningitis and viral/antibody-mediated encephalitis), with the sensitivity: 0.88 (95% confident interval (CI): 0.77-0.94), the specificity: 0.91 (95%CI: 0.88-0.94) and the diagnostic odd ratio: 73.8 (95%CI: 31.8-171.4)). LCN2 outperformed other CSF markers (leukocytes, glucose, protein and lactate) commonly used in routine care worldwide. The combination of LCN2, CSF leukocytes, glucose, protein and lactate resulted in the highest diagnostic performance for BM (area under receiver-operating-characteristic-curve 0.96; 95%CI: 0.93-0.99). Conclusions: Our results suggest that LCN2 is a sensitive and specific biomarker for discriminating BM from a broad spectrum of other CNS infections. A prospective study is needed to assess the diagnostic utility of LCN2 in the diagnosis and management of CNS infections..
2020-08-20 | PXD020510 | 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:Tuberculous Meningitis in Pediatric Patients [CSF]
| PRJNA504827 | ENA
Project description:Background: Meningitis can be caused by several viruses and bacteria. Identifying the causative pathogen as quickly as possible is crucial to initiate the most optimal therapy, as acute bacterial meningitis is associated with a significant morbidity and mortality. Bacterial meningitis requires antibiotics, as opposed to enteroviral meningitis, which only requires supportive therapy. Clinical presentation is usually not sufficient to differentiate between viral and bacterial meningitis, thereby necessitating cerebrospinal fluid (CSF) analysis by PCR and/or time-consuming bacterial cultures. However, collecting CSF in children is not always feasible and a rather invasive procedure. Methods: In 12 Belgian hospitals, we obtained acute blood samples from children with signs of meningitis (49 viral and 7 bacterial cases). (aged between 3 months and 16 years). After pathogen confirmation on CSF, the patient was asked to give a convalescent sample after recovery. 3’mRNA sequencing was performed to determine differentially expressed genes (DEGs) to create a host transcriptomic profile. Results: Enteroviral meningitis cases displayed the largest upregulated fold change enrichment in type I interferon production, response and signaling pathways. Patients with bacterial meningitis showed a significant upregulation of genes related to macrophage and neutrophil activation. We found several significantly DEGs between enteroviral and bacterial meningitis. Random forest classification showed that we were able to differentiate enteroviral from bacterial meningitis with an AUC of 0.982 on held-out samples. Conclusions: Enteroviral meningitis has an innate immunity signature with type 1 interferons as key players. Our classifier, based on blood host transcriptomic profiles of different meningitis cases, is a possible strong alternative for diagnosing enteroviral meningitis.
2019-06-27 | GSE133378 | GEO
Project description:Bulk transcriptome sequencing (bulkRNA-seq) of peripheral blood leukocytes (PBLs) in the bacterial meningitis (BM) of children
| PRJNA685177 | ENA
Project description:Purpose: Characterizing the cell heterogeneity of CSF during the BM development in children. Method: CSF samples were obtained via lumbar puncture from numbers of BM patients in different stages of disease progression. CSF cells were separated by direct centrifugation. A mimic assay based on QUARTZ-SEQ2 was adopted here for library preparations for scRNA-seq. Single CSF cells were sorted into two pre-prepared 384-well plates with cell lysis buffer by flow cytometry, in which each well contained a unique cell barcoding primer. An independent scRNA-seq library was constructed for 768 cells of each CSF sample, and was sequenced using a HiSeq X Ten sequencing system (Illumina). The generation of a cell-count matrix were processed in the combined workflow of UMI-tools and STAR. Secondary analysis were handled by Seurat package. Results: The heterogeneities of CSF cells in BM progression were deciphered. Multiple immune cell clusters in CSF were identified, including two neutrophils, two monocytes, one macrophage, four myeloid dendritic cells, five T cells, one natural killer cell, one B cell, one plasmacytoid dendritic cell, and one plasma cell subtype. Their population profiles and dynamics in the initial onset, remission, and recovery stages during BM progression were also characterized. Conclusions: This study conducted an in-depth exploration of the heterogeneities of CSF cells in BM progression, which provided novel insights into immune cell engagement in acute CNS infection.
2020-12-15 | GSE163194 | GEO
Project description:In this study, we performed label-free based CSF quantitative proteomics to identify and analyze the differentially expressed proteins among bacterial meningitis, viral meningitis and hospital controls (children with benign intracranial hypertension). Compared with viral meningitis and hospital controls, we screened 135 differentially expressed proteins to distinguish bacterial meningitis from viral meningitis and controls. Among of them, 69 proteins as potential biomarkers for the diagnosis of bacterial meningitis, including both novel and previously reported candidate protein markers.
2022-05-20 | PXD026663 | Pride