eLife (Nov 2021)

Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis

  • Andreas Hober,
  • Khue Hua Tran-Minh,
  • Dominic Foley,
  • Thomas McDonald,
  • Johannes PC Vissers,
  • Rebecca Pattison,
  • Samantha Ferries,
  • Sigurd Hermansson,
  • Ingvar Betner,
  • Mathias Uhlén,
  • Morteza Razavi,
  • Richard Yip,
  • Matthew E Pope,
  • Terry W Pearson,
  • Leigh N Andersson,
  • Amy Bartlett,
  • Lisa Calton,
  • Jessica J Alm,
  • Lars Engstrand,
  • Fredrik Edfors

DOI
https://doi.org/10.7554/eLife.70843
Journal volume & issue
Vol. 10

Abstract

Read online

Reliable, robust, large-scale molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for monitoring the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a scalable analytical approach to detect viral proteins based on peptide immuno-affinity enrichment combined with liquid chromatography-mass spectrometry (LC-MS). This is a multiplexed strategy, based on targeted proteomics analysis and read-out by LC-MS, capable of precisely quantifying and confirming the presence of SARS-CoV-2 in phosphate-buffered saline (PBS) swab media from combined throat/nasopharynx/saliva samples. The results reveal that the levels of SARS-CoV-2 measured by LC-MS correlate well with their correspondingreal-time polymerase chain reaction (RT-PCR) read-out (r = 0.79). The analytical workflow shows similar turnaround times as regular RT-PCR instrumentation with a quantitative read-out of viral proteins corresponding to cycle thresholds (Ct) equivalents ranging from 21 to 34. Using RT-PCR as a reference, we demonstrate that the LC-MS-based method has 100% negative percent agreement (estimated specificity) and 95% positive percent agreement (estimated sensitivity) when analyzing clinical samples collected from asymptomatic individuals with a Ct within the limit of detection of the mass spectrometer (Ct ≤ 30). These results suggest that a scalable analytical method based on LC-MS has a place in future pandemic preparedness centers to complement current virus detection technologies.

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