Project description:We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 234 patients with COVID-19 (n=93), other viral (n=100) or non-viral (n=41) acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils, macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 27-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.981, 0.954 and 0.885, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.
2020-08-12 | GSE156063 | GEO
Project description:Comparing nucleic acid extraction systems
Project description:Background: The analysis of oligonucleotide microarray data in pathogen surveillance and discovery assays is a challenging task. Target template concentration, nucleic acid integrity, and host nucleic acid composition can each have a profound effect on signal distribution. Exploratory analysis of fluorescent signal distribution in clinical samples has revealed deviations from normality, suggesting that distribution-free approaches should be applied. Results: An examination of both positive predictive value and false positive rates was employed to assess the utility of three well-established nonparametric methods for the analysis of viral array hybridization data: (1) Mann-Whitney U, (2) the Spearman correlation coefficient and (3) the chi-square test. Of the three tests, it was the chi-square that proved most useful. Conclusions: The acceptance of microarray use for routine clinical diagnostics will require that the technology be accompanied by simple yet reliable analytic methods. We report that our implementation of the chi-square test yielded a combination of low false positive rates and a high degree of predictive accuracy. A set of comprehensive probes covering vertebrate viruses was designed and printed using Agilent in-situ fabrication. Cells in tissue culture were infected with various viruses, then RNA was harvested. RNA was converted to cDNA, then amplified, labeled and hybridized to the array.
Project description:Microbiome nucleic acid extraction kit model is a Named Entity Recognition (NER) model that identifies and annotates the name of the kits used in extracting microbiome nucleic acids in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with kits metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
Project description:Sewage samples were collected and concentrated for Human and animal viruses. Viruses were cultured on Buffalo Green Monkey Cells (BGMK) and their genomic DNA/RNA were extracted and labeled with Cy3 and Cy5 respectively. Labeled DNA/RNA were hybridized unto the array and signals generated were analyzed to indicate the presence of target viruses. Keywords: Detection of pathogens within environmental sample (Viruses) Environmental viruses were concentrated using organic flocculation with Beef Extract supplemented with glycine. Viruses were concentrated using 2 successive rounds of centrifugation and resuspended in Sodium Phosphate buffer. Viral nucleic acid was extracted, labeled and hybridized unto the microarray to determine the presence of target viruses within the sample.
Project description:There is an urgent need for robust and high-throughput methods for SARS-CoV-2 detection in suspected pa-tient samples to facilitate disease management, surveillance, and control. Although nucleic acid detection methods such as RT-PCR are the gold standard, during the current pandemic the deployment of RT-PCR tests has been extremely slow, and key reagents such as PCR primers, and RNA extraction kits are at critical shortages. Rapid point-of-care viral antigen detec-tion methods have been previously employed for the diagnosis of respiratory viruses such as influenza and respiratory syn-cytial viruses. Therefore, the direct detection of SARS-CoV-2 viral antigens in patient samples could also be used for diagno-sis of active infection and alternative methodologies for specific and sensitive viral protein detection should be explored. Targeted mass spectrometry techniques have enabled the identification and quantitation of a defined subset of pro-teins/peptides at single amino acid resolution with attomole level sensitivity and high reproducibility. Herein we report a tar-geted mass spectrometry assay for the detection of SARS- CoV-2 spike protein and nucleoprotein in a relevant biologi-cal matrix. Recombinant full-length spike protein and nucleoprotein were digested and prototypic peptides were selected for parallel reaction monitoring (PRM) quantitation using a high resolution Orbitrap instrument. A spectral library, which con-tained 7 proteotypic peptides (4 from spike protein and 3 from nucleoprotein) and the top 3 to 4 transitionsMS2 spectra, was generated and evaluated. From the original spectral library, we selected 2 best performing peptides for the final PRM assay. The assay was evaluated using mock test samples containing inactivated SARS-CoV-2 virions, added to in-vitro de-rived mucus. The PRM assay provided a limit of detection (LOD) of ~200 attomoles and a limit of quantitation (LOQ) of ~ 390 attomoles. Extrapolating from the test samples, the projected titer of virus particles necessary for detection of SARS-CoV-2 spike and nucleoprotein detection was approximately 2E5 viral particles/mL, making it an attractive alternative to RT-PCR assays. Potentially mass spectrometry-based methods for viral antigen detection may deliver higher throughput and could serve as a complementary diagnostic tool to RT-PCR. Furthermore, this assay could be used to evaluate the pres-ence of SARS-CoV-2 in archived or recently collected biological fluids, in-vitro derived research materials, and wastewater samples
Project description:The capability of the U.S. Food and Drug Administration Enteric Viruses tiling microarray (FDA-EVIR) was assessed for rapid molecular identification of human norovirus (NoV) and hepatitis A virus (HAV) extracted from artificially inoculated fresh produce. Two published viral extraction strategies, total RNA extraction or virus particle isolation, were employed to prepare the viral targets. We also assessed the amount of viral RNA extracted from celery by three commercially-available kits and how well that RNA performed on the FDA-EVIR. Our results confirm that FDA-EVIR can correctly identify common enteric viruses isolated from fresh produce and is capable of identifying single and mixed species of viruses, as well as distinguishing among genotypes. Extending microarray methods to other food matrices should provide important support to surveillance and outbreak investigations.
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
Project description:This study aimed to use pan-viral detection microarrays to identify viruses in serum from cases of acute pediatric febrile illness in a tropical setting. Patient clinical data and serum samples were collected between 2005 and 2009 as part of an ongoing pediatric dengue virus study at the Hospital Infantil Manuel de Jesús Rivera in Managua, Nicaragua. This study focused on patients who presented with dengue-like illness but who tested negative for dengue-virus infection. We hypothesized that non-dengue viruses or previously uncharacterized viruses might be causing these illnesses. The Virochip microarray is capable of detecting known viruses and discovering novel viruses. This series includes 153 arrays corresponding to 148 cases and 5 HeLa controls. Keywords: viral detection, tropical febrile illness, dengue virus, Nicaragua, Virochip From each serum sample, total nucleic acid was extracted and used to prepare a randomly-primed dsDNA library. These libraries were fluorescently labeled and hybrized to Virochip arrays.