Development of a Clinical MALDI-ToF Mass Spectrometry Assay for SARS-CoV-2: Rational Design and Multi-Disciplinary Team Work

The COVID-19 pandemic caused by the SARS-CoV-2 coronavirus has stretched national testing capacities to breaking points in almost all countries of the world. The need to rapidly screen vast numbers of a country’s population in order to control the spread of the infection is paramount. However, the logistical requirement for reagent supply (and associated cost) of RT-PCR based testing (the current front-line test) have been hugely problematic. Mass spectrometry-based methods using swab and gargle samples have been reported with promise, but have not approached the task from a systematic analysis of the entire diagnostic process. Here, the pipeline from sample processing, the biological characteristics of the pathogen in human biofluid, the downstream bio- and physical-chemistry and the all-important data processing with clinical interpretation and reporting, are carefully compiled into a single high-throughput and reproducible rapid process. Utilizing MALDI-ToF mass spectrometric detection to viral envelope glycoproteins in a systems biology-multidisciplinary team approach, we have achieved a multifaceted clinical MALDI ToF MS screening test, primarily (but not limited to) SARS-CoV-2, with direct application to other future epidemics/pandemics that may arise. The clinical information generated not only includes SARS-CoV-2 coronavirus detection–(Spike protein fragments S1, S2b, S2a peaks), but other respiratory viral infections detected as well as an assessment of generalised oral upper respiratory immune response (elevated total Ig light chain peak) and a measure of the viral immune response (elevated intensity of IgA heavy chain peak). The advantages of the method include; (1) ease of sampling, (2) speed of analysis, and much reduced cost of testing. These features reveal the diagnostic utility of MALDI-ToF mass spectrometry as a powerful and economically attractive global solution View Full-Text