A Parallelization Strategy for the Time Efficient Analysis of Thousands of LC/MS Runs in High-Performance Computing Environment.

Combining robust proteomics instrumentation with high-throughput enabling liquid chromatography (LC) systems (e.g., timsTOF Pro and the Evosep One system, respectively) enabled mapping the proteomes of 1000s of samples. Fragpipe is one of the few computational protein identification and quantification frameworks that allows for the time-efficient analysis of such large data sets. However, it requires large amounts of computational power and data storage space that leave even state-of-the-art workstations underpowered when it comes to the analysis of proteomics data sets with 1000s of LC mass spectrometry runs. To address this issue, we developed and optimized a Fragpipe-based analysis strategy for a high-performance computing environment and analyzed 3348 plasma samples (6.4 TB) that were longitudinally collected from hospitalized COVID-19 patients under the auspice of the Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study. Our parallelization strategy reduced the total runtime by ∼90% from 116 (theoretical) days to just 9 days in the high-performance computing environment. All code is open-source and can be deployed in any Simple Linux Utility for Resource Management (SLURM) high-performance computing environment, enabling the analysis of large-scale high-throughput proteomics studies.

Mass-Spectrometric Detection of SARS-CoV-2 Virus in Scrapings of the Epithelium of the Nasopharynx of Infected Patients via Nucleocapsid N Protein.

The detection of viral RNA by polymerase chain reaction (PCR) is currently the main diagnostic tool for COVID-19 ( Eurosurveillance 2019, 25 (3), 1). The PCR-based test, however, shows limited sensitivity, especially in the early and late stages of disease development ( Nature 2020, 581, 465-469; J. Formosan Med. Assoc. 2020, 119 (6) 1123), and is relatively time-consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemic conditions. Mass spectrometry is one of such possibilities. We have developed a mass-spectrometry-based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs based on the detection of the viral nucleocapsid N protein. Our approach shows confident identification of the N protein in patient samples, even those with the lowest viral loads, and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and the addition of isopropanol and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids.