Design of a Diagnostic Pan-Pathogen Oligonucleotide Microarray including a sub-Array for Detection of Meningitis-Causing Bacterial Pathogens
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PROVIDER: PRJNA144293 | ENA |
REPOSITORIES: ENA
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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: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:GAS meningitis
| PRJEB57816 | 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:Tuberculous meningitis is one of the fatal forms of extra pulmonary disease associated with high mortality and severe neurological defects in affected individuals. We have carried out transcriptome level analysis using whole human genome microarrays to identify differential expression of genes between tuberculous meningitis and normals. In our gene expression analysis, we found 2,434 genes that were differentially erexpressed with 2 or more than 2 fold changes between tuberculous meningitis compared to normal cases. Most of the genes encoded many of the proteins, which involves metabolism, energy pathways, cell growth and/or maintenance, transport and cell communication and signal transduction. We have performed immunohistochemistry for the validation of some of the novel candidates identified in our microarray studies.!Series_overall_design = Present study carried out mRNA expression profiling of five samples from patients diagnosed with tuberculous meningitis and four head injury cases were used as controls. We have used 4X44K arrays from agilent plaform. To validate our microarray results, we have done Immunohistochemistry on 15 TBM cases with control groups.
2011-07-01 | GSE23074 | GEO
Project description:Tuberculous meningitis is one of the fatal forms of extra pulmonary disease associated with high mortality and severe neurological defects in affected individuals. We have carried out transcriptome level analysis using whole human genome microarrays to identify differential expression of genes between tuberculous meningitis and normals. In our gene expression analysis, we found 2,434 genes that were differentially erexpressed with 2 or more than 2 fold changes between tuberculous meningitis compared to normal cases. Most of the genes encoded many of the proteins, which involves metabolism, energy pathways, cell growth and/or maintenance, transport and cell communication and signal transduction. We have performed immunohistochemistry for the validation of some of the novel candidates identified in our microarray studies.!Series_overall_design = Present study carried out mRNA expression profiling of five samples from patients diagnosed with tuberculous meningitis and four head injury cases were used as controls. We have used 4X44K arrays from agilent plaform. To validate our microarray results, we have done Immunohistochemistry on 15 TBM cases with control groups. Present study carried out mRNA expression profiling of five samples from patients diagnosed with tuberculous meningitis and four head injury cases were used as controls. We have used 4X44K arrays from agilent plaform. To validate our microarray results, we have done Immunohistochemistry on 15 TBM cases with control groups.!Series_type = Expression profiling by array
2011-06-30 | E-GEOD-23074 | biostudies-arrayexpress
Project description:Whole blood transcriptional profiles in children with or without tuberculous meningitis (TBM) were compared using RNA-Seq and a biomarker signature driven by inflammasome activation and signaling was identified
2019-08-06 | GSE111459 | GEO
Project description:BACKGROUND: Microarray comparative genomic hybridization (CGH) is currently one of the most powerful techniques to measure DNA copy number in large genomes. In humans, microarray CGH is widely used to assess copy number variants in healthy individuals and copy number aberrations associated with various diseases, syndromes and disease susceptibility. In model organisms such as Caenorhabditis elegans (C. elegans) the technique has been applied to detect mutations, primarily deletions, in strains of interest. Although various constraints on oligonucleotide properties have been suggested to minimize non-specific hybridization and improve the data quality, there have been few experimental validations for CGH experiments. For genomic regions where strict design filters would limit the coverage it would also be useful to quantify the expected loss in data quality associated with relaxed design criteria. RESULTS: We have quantified the effects of filtering various oligonucleotide properties by measuring the resolving power for detecting deletions in the human and C. elegans genomes using NimbleGen microarrays. Approximately twice as many oligonucleotides are typically required to be affected by a deletion in human DNA samples in order to achieve the same statistical confidence as one would observe for a deletion in C. elegans. Surprisingly, the ability to detect deletions strongly depends on the oligonucleotide 15-mer count, which is defined as the sum of the genomic frequency of all the constituent 15-mers within the oligonucleotide. A similarity level above 80% to non-target sequences over the length of the probe produces significant cross-hybridization. We recommend the use of a fairly large melting temperature window of up to 10 C, the elimination of repeat sequences, the elimination of homopolymers longer than 5 nucleotides, and a threshold of -1 kcal/mol on the oligonucleotide self-folding energy. We observed very little difference in data quality when varying the oligonucleotide length between 50 and 70, and even when using an isothermal design strategy. CONCLUSIONS: We have determined experimentally the effects of varying several key oligonucleotide microarray design criteria for detection of deletions in C. elegans and humans with NimbleGen's CGH technology. Our oligonucleotide design recommendations should be applicable for CGH analysis in most species.
2008-07-26 | GSE12208 | GEO