Ontology highlight
ABSTRACT:
PROVIDER: PRJNA614546 | ENA |
REPOSITORIES: ENA
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Project description:The SARS-CoV-2 virus is continuously evolving, with appearance of new variants characterized by multiple genomic mutations, some of which can affect functional properties, including infectivity, interactions with host immunity, and disease severity. The rapid spread of new SARS-CoV-2 variants has highlighted the urgency to trace the virus evolution, to help limit its diffusion, and to assess effectiveness of containment strategies. We propose here a PCR-based rapid, sensitive and low-cost allelic discrimination assay panel for the identification of SARS-CoV-2 genotypes, useful for detection in different sample types, such as nasopharyngeal swabs and wastewater. The tests carried out demonstrate that this in-house assay, whose results were confirmed by SARS-CoV-2 whole-genome sequencing, can detect variations in up to 10 viral genome positions at once and is specific and highly sensitive for identification of all tested SARS-CoV-2 clades, even in the case of samples very diluted and of poor quality, particularly difficult to analyze.
2022-06-03 | E-MTAB-11261 | biostudies-arrayexpress
Project description:Detection of viral RNA by PCR is currently the main diagnostic tool for COVID-191. The PCR-based test, however, shows limited sensitivity, especially at early and late stages of the disease development, and is relatively time consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemia conditions. Mass-spectrometry is one of such possibilities. We have developed a mass-spectrometry based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs, based on the detection of the viral nucleocapsid N protein. The N protein of the SARS-COV-2 virus, the most abundant protein in the virion, is the best candidate for mass-spectrometric detection of the infection, and MS-based detection of several peptides from the SARS-COoV-2 nucleoprotein has been reported earlier by the Sinz group. Our approach shows confident identification of the N protein in patient samples even with the lowest viral loads and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and adding of isopropanol, and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids. Note: samples containing minor contamination of synthetic S peptides
2020-08-14 | PXD019648 | Pride
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
2022-01-12 | PXD021080 | Pride
Project description:Detection of SARS-CoV-2 using RT–PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT–PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples.
2020-09-11 | PXD021388 | Pride
Project description:The COVID-19 pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has overwhelmed health systems worldwide and highlighted limitations of diagnostic testing. Several types of diagnostic tests including RT-PCR-based assays and antigen detection by lateral flow assays, each with their own strengths and weaknesses, have been developed and deployed in a short time. Here, we describe an immunoaffinity purification approach followed a by high resolution mass spectrometry-based targeted qualitative assay capable of detecting SARS-CoV-2 viral antigen from nasopharyngeal swab samples. Based on our discovery experiments using purified virus, recombinant viral protein and nasopharyngeal swab samples from COVID-19 positive patients, nucleocapsid protein was selected as a target antigen. We then developed an automated antibody capture-based workflow coupled to targeted high-field asymmetric waveform ion mobility spectrometry (FAIMS) - parallel reaction monitoring (PRM) assay on an Orbitrap Exploris 480 mass spectrometer. An ensemble machine learning-based model for determining COVID-19 positive samples was developed using fragment ion intensities from the PRM data. The optimized targeted assay, which was used to analyze 88 positive and 88 negative nasopharyngeal swab samples for validation, resulted in 98% (95% CI = 0.922-0.997) (86/88) sensitivity and 100% (95% CI = 0.958-1.000) (88/88) specificity using RT-PCR-based molecular testing as the reference method. Our results demonstrate that direct detection of infectious agents from clinical samples by tandem mass spectrometry-based assays have potential to be deployed as diagnostic assays in clinical laboratories, which has hitherto been limited to analysis of pure microbial culture
2020-08-13 | PXD020644 | Pride
Project description:COVID-19 vaccines are continuing to become more widely available, but accurate and rapid testing remains a crucial tool for slowing the spread of the SARS-CoV-2 virus. Although quantitative reverse transcription-polymerase chain reaction (qRT-PCR) remains the most prevalent testing methodology, numerous tests have been developed that are predicated on detection of the SARS-CoV-2 nucleocapsid protein, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and immunoassay based approaches. The continuing emergence of SARS-CoV-2 variants has complicated these approaches, as both qRT-PCR and antigen detection methods can be prone to missing viral variants. In this study, we describe a number of cases with COVID-19 where we were unable to detect the expected peptide targets from clinical nasopharyngeal swab samples that are typically identifiable in a targeted mass spectrometric assay. Whole genome sequencing revealed that single nucleotide polymorphisms in the gene encoding the viral nucleocapsid protein led to sequence variants that were not monitored in the targeted assay. Small modifications to the LC-MS/MS method ensured detection of the variants of the target peptide. Additional nucleocapsid variants were detected by performing bottom-up proteomic analysis of whole viral genome sequenced samples. This study demonstrates the importance of considering variants of SARS-CoV-2 in the assay design and highlights the flexibility of mass spectrometry-based approaches to detect variants as they evolve.
2022-02-17 | PXD026795 | Pride
Project description:Serological testing is important methodfor diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Nucleocapsid (N) protein is the most abundant virus derived protein and strong immunogen. We aimed to find its efficient, low-cost production. SARS-CoV-2 recombinant fragment of nucleocapsid protein (rfNP; 58-419 aa) was expressed in E. coli in soluble form, purified and characterized biochemically and immunologically. Purified rfNP has secondary structure of full-length recombinant N protein, with high percentage of disordered structure (34.2 %) and of β-sheet (40.7 %). rfNP was tested in immunoblot using sera of COVID-19 convalescent patients. ELISA was optimized with sera of RT-PCR confirmed positive symptomatic patients and healthy individuals. IgG detection sensitivity was 96% (47/50) and specificity 97% (67/68), while IgM detection was slightly lower (94% and 96.5%, respectively). Cost-effective approach for soluble recombinant N protein fragment production was developed, with reliable IgG and IgM antibodies detection of SARS-CoV-2 infection.
2021-02-17 | PXD023341 | Pride
Project description:Detection of SARS-CoV-2 using RT-PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT-PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples.
| MSV000086175 | MassIVE
Project description:SARS-CoV-2 has created a global disease burden infecting >100 million humans in just over a year. In this study, we adopted a SISCAPA-based enrichment approach using anti-peptide antibodies generated against peptides from the nucleocapsid protein of SARS-CoV-2. We developed a targeted workflow in which nasopharyngeal samples were digested followed by enrichment of viral peptides using the anti-peptide antibodies and targeted parallel reaction monitoring (PRM) analysis using a high-resolution mass spectrometer. This workflow was applied to 41 RT-PCR-confirmed clinical nasopharyngeal swab samples and 30 negative samples. The SISCAPA-based platform described in the current study can serve as one of the alternative methods for SARS-CoV-2 viral detection.
2022-02-16 | PXD028505 | Pride
Project description:SARS-CoV-2 has created a global disease burden infecting >100 million humans in just over a year. In this study, we adopted a SISCAPA-based enrichment approach using anti-peptide antibodies generated against peptides from the nucleocapsid protein of SARS-CoV-2. We developed a targeted workflow in which nasopharyngeal samples were digested followed by enrichment of viral peptides using the anti-peptide antibodies and targeted parallel reaction monitoring (PRM) analysis using a high-resolution mass spectrometer. This workflow was applied to 41 RT-PCR-confirmed clinical nasopharyngeal swab samples and 30 negative samples. The SISCAPA-based platform described in the current study can serve as one of the alternative methods for SARS-CoV-2 viral detection.
2022-06-03 | PXD026273 | Pride