Human metagenome
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR172340_1.fastq.gz | Fastqsanger.gz | |||
| DRR172341_1.fastq.gz | Fastqsanger.gz | |||
| DRR172342_1.fastq.gz | Fastqsanger.gz | |||
| DRR172343_1.fastq.gz | Fastqsanger.gz | |||
| DRR172344_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:Meningitis is a complex disease which can be caused by infection with either viral or bacterial pathogens. Viral meningitis is usually a sterile self-limiting disease with a good clinical prognosis, while bacterial meningitis is a potentially more serious disease with a higher mortality rate. Early diagnosis of bacterial meningitis is of paramount importance, as intervention with antimicrobial therapy increases the likelihood of a favourable clinical outcome. Routine diagnosis in many laboratories is still dependent to some degree on traditional methods e.g. culture, though molecular methods have been developed which can give a shorter time to diagnosis. However, there is not as yet a single test format that can detect all bacterial pathogens capable of causing meningitis. In addition, many tests e.g. real-time PCR have a finite limit for multiplexing and do not provide additional information such as strain or serogroup which is useful during outbreaks and for retrospective epidemiological surveillance. To this end we have developed a microarray probe set for detection of meningitis-associated bacterial pathogens including those in the N. meningitidis serogroups. Here we demonstrate utility of this array in specific detection of represented bacterial species and strains and in detection of pathogen signals in cerebrospinal fluid samples from patients with suspected bacterial meningitis. This method shows promise for development as a diagnostic tool; however, we discuss the technical issues encountered and suggest mechanisms to improve resolution of pathogen-specific signals in complex clinical samples.
2011-07-20 | GSE30794 | GEO
Project description:Meningitis is a complex disease which can be caused by infection with either viral or bacterial pathogens. Viral meningitis is usually a sterile self-limiting disease with a good clinical prognosis, while bacterial meningitis is a potentially more serious disease with a higher mortality rate. Early diagnosis of bacterial meningitis is of paramount importance, as intervention with antimicrobial therapy increases the likelihood of a favourable clinical outcome. Routine diagnosis in many laboratories is still dependent to some degree on traditional methods e.g. culture, though molecular methods have been developed which can give a shorter time to diagnosis. However, there is not as yet a single test format that can detect all bacterial pathogens capable of causing meningitis. In addition, many tests e.g. real-time PCR have a finite limit for multiplexing and do not provide additional information such as strain or serogroup which is useful during outbreaks and for retrospective epidemiological surveillance. To this end we have developed a microarray probe set for detection of meningitis-associated bacterial pathogens including those in the N. meningitidis serogroups. Here we demonstrate utility of this array in specific detection of represented bacterial species and strains and in detection of pathogen signals in cerebrospinal fluid samples from patients with suspected bacterial meningitis. This method shows promise for development as a diagnostic tool; however, we discuss the technical issues encountered and suggest mechanisms to improve resolution of pathogen-specific signals in complex clinical samples. We designed as part of a larger pan-pathogen microarray a sub-set of probes to meningitis-associated bacterial pathogens. We present here data confirming the pathogen-specificity of many of these probes and their potential use in clinical diagnosis through testing on a small number of patient clinical samples using human DNA and no added nucleic acid controls. These data are from single channel Cy3-labelled nucleic acids. Four technical replicates for each feature are included on the array.
2011-07-19 | E-GEOD-30794 | biostudies-arrayexpress
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: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:Diagnosis of infectious diseases by sequencing
| PRJDB7111 | ENA
Project description:Metagenomic Next-Generation Sequencing for Infectious Disease Diagnosis
| PRJNA298217 | ENA
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
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:This study includes 1146 samples of host genotyping data (genotyped) from Illumina Omni arrays. Samples were collected from adults (>16 yrs) patients with CSF confirmed bacterial meningitis in the Netherlands between 2006 and 2015. Metadata includes patient outcome, species of bacteria, and for 467 samples a link to an ENA run with the associated bacterial genome (S. pneumoniae only).
| EGAD00010002328 | EGA
Project description:Metagenomic diagnosis of viral infections - RAPID project
| PRJNA33495 | ENA