Ontology highlight
ABSTRACT:
PROVIDER: PRJNA596073 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10714425_1.fastq.gz | Fastqsanger.gz | |||
| SRR10714425_2.fastq.gz | Fastqsanger.gz | |||
| SRR10714426_1.fastq.gz | Fastqsanger.gz | |||
| SRR10714426_2.fastq.gz | Fastqsanger.gz |
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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. 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:Diagnosis of acute respiratory viral infection is currentlybased on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals.
2009-08-06 | GSE17156 | GEO
Project description:This series includes 278 microarrays used to detect respiratory viruses in a set of nasopharyngeal lavage specimens from children with respiratory tract infections Objective: To assess the utility of a pan-viral DNA microarray platform (Virochip) in the detection of viruses associated with pediatric respiratory tract infections. Study Design: The Virochip was compared to conventional clinical direct fluorescent antibody (DFA) and PCR-based testing for the detection of respiratory viruses in 278 consecutive nasopharyngeal aspirate samples from 222 children. Results: The Virochip was superior in performance to DFA, showing a 19% increase in the detection of 7 respiratory viruses included in standard DFA panels, and was similar to virus-specific PCR (sensitivity 85-90%, specificity 99%, PPV 94-96%, NPV 97-98%) in the detection of respiratory syncytial virus, influenza A, and rhino-/enteroviruses. The Virochip also detected viruses not routinely tested for or missed by DFA and PCR, as well as double infections and infections in critically ill patients that DFA failed to detect. Conclusions: Given its favorable sensitivity and specificity profile and greatly expanded spectrum of detection, microarray-based viral testing holds promise for clinical diagnosis of pediatric respiratory tract infections. Keywords: viral detection The series includes 278 clinical specimens
2010-05-26 | E-GEOD-10294 | biostudies-arrayexpress
Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.
2009-08-06 | E-GEOD-17156 | biostudies-arrayexpress
Project description:BACKGROUND. Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging since non-infectious respiratory illnesses appear clinically similar and existing microbiologic tests are often falsely negative or detect incidentally-carried microbes common in children. These challenges result in antimicrobial overuse and adverse patient outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and precision treatment remains unclear. METHODS. We used tracheal aspirate RNA-sequencing to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a random forest gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n=117) or of non-infectious respiratory failure (n=50). We then developed a classifier that integrates the: i) host LRTI probability, ii) abundance of respiratory viruses, and iii) dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm. RESULTS. The host classifier achieved a median AUC of 0.967 by 5-fold cross-validation, driven by activation markers of T cells, alveolar macrophages and the interferon response. The integrated classifier achieved a median AUC of 0.986 and significantly increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n=94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those. CONCLUSIONS. Lower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.
2022-12-06 | GSE212532 | 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.
2011-07-20 | GSE30794 | GEO
Project description:This series includes 278 microarrays used to detect respiratory viruses in a set of nasopharyngeal lavage specimens from children with respiratory tract infections Objective: To assess the utility of a pan-viral DNA microarray platform (Virochip) in the detection of viruses associated with pediatric respiratory tract infections. Study Design: The Virochip was compared to conventional clinical direct fluorescent antibody (DFA) and PCR-based testing for the detection of respiratory viruses in 278 consecutive nasopharyngeal aspirate samples from 222 children. Results: The Virochip was superior in performance to DFA, showing a 19% increase in the detection of 7 respiratory viruses included in standard DFA panels, and was similar to virus-specific PCR (sensitivity 85-90%, specificity 99%, PPV 94-96%, NPV 97-98%) in the detection of respiratory syncytial virus, influenza A, and rhino-/enteroviruses. The Virochip also detected viruses not routinely tested for or missed by DFA and PCR, as well as double infections and infections in critically ill patients that DFA failed to detect. Conclusions: Given its favorable sensitivity and specificity profile and greatly expanded spectrum of detection, microarray-based viral testing holds promise for clinical diagnosis of pediatric respiratory tract infections. Keywords: viral detection
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