A Galaxy-based evaluation of optimal peptide targets for MS-based detection of SARS-CoV-2 in clinical samples
Year: 2021
Type: other
Abstract: Targeted mass spectrometry detection of SARS-CoV-2 peptides in patient samples represents a powerful complementary diagnostic tool to current qRT-PCR methodologies due to the relative robustness of peptide samples as well as the rapid analyses this method affords. We present here automated workflows in the Galaxy platform used to identify those SARS-CoV-2 peptides which would be most suitable as targets for mass spectrometry assays. In the first workflow, a collection of in vitro and clinical datasets were searched against the SARS-CoV-2 proteome to identify viral peptides. When combined with a bioinformatic study by Orsburn et al., we constructed a 639 peptide panel of SARS-CoV-2 peptides covering most of the viral proteome. The second workflow leveraged the PepQuery search engine (doi: 10.1101/gr.235028.118) to determine which of the prospective targets could be most confidently attributed to SARS-CoV-2 over the human proteome or other coronaviruses in a collection of clinical datasets. Using this workflow, the 639 peptide panel was narrowed down to 87 peptides which showed robust matches to SARS-CoV-2. We ultimately selected four peptides belonging to the SARS-CoV-2 nucleocapsid that showed high confidence matches to SARS-CoV-2, had high quality spectra, and were found in most of the clinical datasets. The results of our investigations were recently published in Clinical Proteomics ( https://doi.org/10.1186/s12014-021-09321-1 ). The Galaxy workflows are available to researchers for analysis of their datasets, including detection of SARS-CoV-2 peptides and co-infecting pathogen peptides ( https://doi.org/10.1021/acs.jproteome.0c00822 ), especially in countries which are experiencing re-emergence of the pandemic.
Institution: University of Minnesota
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4416523205
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