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
Project description:The ongoing COVID-19 pandemic caused by SARS-CoV-2 has affected millions of people worldwide and has significant implications for public health. Host transcriptomics profiling provides comprehensive understanding of how the virus interacts with host cells and how the host responds to the virus. COVID-19 disease alters the host transcriptome, affecting cellular pathways and key molecular functions. To contribute to the global effort to understand the virus’s effect on host cell transcriptome, we have generated a dataset from nasopharyngeal swabs of 35 individuals infected with SARS-CoV-2 from the Campania region in Italy during the three outbreaks, with different clinical conditions. This dataset will help to elucidate the complex interactions among genes and can be useful in the development of effective therapeutic pathways
Project description:We have collected nasal cell swab samples from SARS-CoV-2 infected confirmed COVID-19 patients. Both virus and host RNA were extracted and sequenced by RNA-seq. We mapped and assembled virus sequences and in this study transcriptional profile of host due to virus infection.
Project description:To evaluate the gene expression profiling of peripheral leukocytes in different outcomes of SARS-CoV-2 infections, whole blood samples were collected from individuals with positive SARS-CoV-2 nasopharyngeal swab by RT-PCR (54 patients) and healthy uninfected individuals (12 volunteers). Infected patients were classified into mild, moderate, severe and critical groups according to a modified statement in the Novel Coronavirus Pneumonia Diagnosis and Treatment Guideline. Blood were collected into EDTA tubes and the buffy coat samples were stored in TRIzol reagent at -80 °C until use for RNA extraction. Affymetrix Clariom S array was used to perform the high-throughput gene expression profiling. Microarray analyses were performed using APT Affymetrix software, R packages and Bioconductor libraries. This systemic view of SARS-CoV-2 infections through blood transcriptomics will foster the understanding about molecular mechanisms and immunopathological processes involved in COVID-19 disease and its different outcomes.
Project description:The objective of the study was to characterize the immunoreactivity profiles of IgG-reactive epitopes in COVID-19 patients with distinct disease trajectories as well as SARS-CoV-2-naïve sera, using a high-density SARS-CoV-2 whole proteome peptide microarray. The microarray comprised of a total of 5347 individual peptides, each consisting of 15 amino acids with an overlap of 13 amino acids printed in duplicate. The microarray also had a panel of the most relevant mutations from SARS-CoV-2 variants of concern like omicron, alpha, beta, gamma, delta, and others. This study consisted of 29 participants, including 10 naïve controls (5 pre-pandemic and 5 SARS-CoV-2 seronegative) and 19 RT-PCR-confirmed COVID-19 patients. The COVID-19 patients were stratified into two distinct cohorts based on their disease trajectories: the severe cohort (S), in which the patients presented moderate COVID-19 symptoms initially but eventually progressed toward severity; and the recovered cohort (R), in which severe COVID-19 patients progressed toward recovery. Our findings contribute to a deeper understanding of the immunopathogenesis of COVID-19 in patients with different disease trajectories, the effect of mutations on immunoreactivity, and potential cross-reactivity due to exposure to common cold viruses.
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.
Project description:SARS-CoV-2 can generate viral microRNAs (v-miRNAs) that target host gene expression. This study used small RNAseq to identify the v-miRNAs present in COVID-19 patients' nasopharyngeal swabs. The study identified a specific conserved v-miRNA sequence (CoV2-miR-O8) unique to SARS-CoV-2 that is highly present in COVID-19 patients' samples, interacts with Argonaute, and has features consistent with Dicer and Drosha generation. CoV2-miR-O8 is predicted to target specific human genes and can be detected by RTPCR assays in patients.
Project description:To elucidate key pathways in the host transcriptome of patients infected with SARS-CoV-2, we used RNA sequencing (RNA Seq) to analyze nasopharyngeal (NP) swab and whole blood (WB) samples from 333 COVID-19 patients and controls, including patients with other viral and bacterial infections. Analyses of differentially expressed genes (DEGs) and pathways was performed relative to other infections (e.g. influenza, other seasonal coronaviruses, bacterial sepsis) in both NP swabs and WB. Comparative COVID-19 host responses between NP swabs and WB were examined. Both hospitalized patients and outpatients exhibited upregulation of interferon-associated pathways, although heightened and more robust inflammatory and immune responses were observed in hospitalized patients with more clinically severe disease. A two-layer machine learning-based classifier, run on an independent test set of NP swab samples, was able to discriminate between COVID-19 and non-COVID-19 infectious or non-infectious acute respiratory illness using complete (>1,000 genes), medium (<100) and small (<20) gene biomarker panels with 85.1%-86.5% accuracy, respectively. These findings demonstrate that SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for differential diagnosis of COVID-19 disease.
Project description:<p><strong>INTRODUCTION:</strong> COVID-19 has become a global impediment by bringing everything to a halt starting from January 2020. India underwent the lockdown starting from 22nd March 2020 with the sudden spike in the number of COVID-19 patients in major cities and states. This study focused on how metabolites play a crucial role in SARSCoV-2 prognosis.</p><p><strong>MATERIALS AND METHODS:</strong> Metabolome profiling of 106 plasma samples and 24 swab samples from symptomatic patients in the Indian population of the Mumbai region was done. COVID-19 positive samples were further segregated under the non-severe COVID-19 and severe COVID-19 patient cohort for both plasma and swab.</p><p><strong>RESULTS:</strong> After analyzing the raw files, total 7,949 and 12,871 metabolites in plasma and swab were found. 11 and 35 significantly altered metabolites were found in COVID-19 positive compared to COVID-19 negative plasma and swab samples, respectively. Also, 9 and 23 significantly altered metabolites were found in severe COVID-19 positive to non-severe COVID-19 positive plasma and swab samples, respectively. The majorly affected pathways in COVID-19 patients were found to be the amino acid metabolism pathway, sphingosine metabolism pathway, and bile salt metabolism pathway.</p><p><strong>CONCLUSION:</strong> This study facilitates identification of potential metabolite-based biomarker candidates for rapid diagnosis and prognosis for clinical applications.</p><p><br></p><p><strong>Blood plasma assay</strong> is reported in the current study <strong>MTBLS2291</strong>.</p><p><strong>Nasopharyngeal swab assay</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS2349' rel='noopener noreferrer' target='_blank'><strong>MTBLS2349</strong></a>.</p>
Project description:<p><strong>INTRODUCTION:</strong> COVID-19 has become a global impediment by bringing everything to a halt starting from January 2020. India underwent the lockdown starting from 22nd March 2020 with the sudden spike in the number of COVID-19 patients in major cities and states. This study focused on how metabolites play a crucial role in SARSCoV-2 prognosis.</p><p><strong>MATERIALS AND METHODS:</strong> Metabolome profiling of 106 plasma samples and 24 swab samples from symptomatic patients in the Indian population of the Mumbai region was done. COVID-19 positive samples were further segregated under the non-severe COVID-19 and severe COVID-19 patient cohort for both plasma and swab.</p><p><strong>RESULTS:</strong> After analyzing the raw files, total 7,949 and 12,871 metabolites in plasma and swab were found. 11 and 35 significantly altered metabolites were found in COVID-19 positive compared to COVID-19 negative plasma and swab samples, respectively. Also, 9 and 23 significantly altered metabolites were found in severe COVID-19 positive to non-severe COVID-19 positive plasma and swab samples, respectively. The majorly affected pathways in COVID-19 patients were found to be the amino acid metabolism pathway, sphingosine metabolism pathway, and bile salt metabolism pathway.</p><p><strong>CONCLUSION:</strong> This study facilitates identification of potential metabolite-based biomarker candidates for rapid diagnosis and prognosis for clinical applications.</p><p><br></p><p><strong>Nasopharyngeal swab assay</strong> is reported in the current study <strong>MTBLS2349</strong>.</p><p><strong>Blood plasma assay</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS2291' rel='noopener noreferrer' target='_blank'><strong>MTBLS2291</strong></a>.</p>