A SISCAPA-based approach for detection of SARS-CoV-2 viral antigens from clinical samples

被引:0
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作者
Kiran K. Mangalaparthi
Sandip Chavan
Anil K. Madugundu
Santosh Renuse
Patrick M. Vanderboom
Anthony D. Maus
Jennifer Kemp
Benjamin R. Kipp
Stefan K. Grebe
Ravinder J. Singh
Akhilesh Pandey
机构
[1] Mayo Clinic,Department of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology
[2] Manipal Academy of Higher Education,Center for Molecular Medicine
[3] Institute of Bioinformatics,Center for Individualized Medicine
[4] International Technology Park,Department of Laboratory Medicine and Pathology, Division of Laboratory Genetics and Genomics
[5] National Institute of Mental Health and Neurosciences,Department of Medicine, Division of Endocrinology
[6] Mayo Clinic,undefined
[7] Mayo Clinic,undefined
[8] Mayo Clinic,undefined
来源
Clinical Proteomics | 2021年 / 18卷
关键词
SARS-CoV-2; COVID-19; SISCAPA; Mass spectrometry; Parallel reaction monitoring (PRM);
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学科分类号
摘要
SARS-CoV-2, a novel human coronavirus, has created a global disease burden infecting > 100 million humans in just over a year. RT-PCR is currently the predominant method of diagnosing this viral infection although a variety of tests to detect viral antigens have also been developed. 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 swab 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 SARS-CoV-2 positive nasopharyngeal swab samples and 30 negative samples. The workflow employed was highly specific as none of the target peptides were detected in negative samples. Further, the detected peptides showed a positive correlation with the viral loads as measured by RT-PCR Ct values. The SISCAPA-based platform described in the current study can serve as an alternative method for SARS-CoV-2 viral detection and can also be applied for detecting other microbial pathogens directly from clinical samples.
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