Quartz Crystal Microbalance Platform for SARS-CoV-2 Immuno-Diagnostics

Int J Mol Sci. 2023 Nov 24;24(23):16705. doi: 10.3390/ijms242316705.

Abstract

Rapid and accurate serological analysis of SARS-CoV-2 antibodies is important for assessing immune protection from vaccination or infection of individuals and for projecting virus spread within a population. The quartz crystal microbalance (QCM) is a label-free flow-based sensor platform that offers an opportunity to detect the binding of a fluid-phase ligand to an immobilized target molecule in real time. A QCM-based assay was developed for the detection of SARS-CoV-2 antibody binding and evaluated for assay reproducibility. The assay was cross-compared to the Roche electrochemiluminescence assay (ECLIA) Elecsys® Anti-SARS-CoV-2 serology test kit and YHLO's chemiluminescence immunoassay (CLIA). The day-to-day reproducibility of the assay had a correlation of r2 = 0.99, p < 0.001. The assay linearity was r2 = 0.96, p < 0.001, for dilution in both serum and buffer. In the cross-comparison analysis of 119 human serum samples, 59 were positive in the Roche, 52 in the YHLO, and 48 in the QCM immunoassay. Despite differences in the detection method and antigen used for antibody capture, there was good coherence between the assays, 80-100% for positive and 96-100% for negative test results. In summation, the QCM-based SARS-CoV-2 IgG immunoassay showed high reproducibility and linearity, along with good coherence with the ELISA-based assays. Still, factors including antibody titer and antigen-binding affinity may differentially affect the various assays' responses.

Keywords: COVID-19; SARS-CoV-2; chemiluminescence; electrochemiluminescence; quartz crystal microbalance.

MeSH terms

  • Antibodies, Viral
  • COVID-19* / diagnosis
  • Humans
  • Immunoassay / methods
  • Quartz Crystal Microbalance Techniques
  • Reproducibility of Results
  • SARS-CoV-2*
  • Sensitivity and Specificity

Substances

  • Antibodies, Viral

Grants and funding

This research was funded by the Swedish Knowledge Foundation, grant numbers 20190114 and 20230019 (Synergi22).