High-Sensitivity Detection toward SARS-CoV-2 S1 Glycoprotein by Parallel Reaction Monitoring Mass Spectrometry.

The outbreak of coronavirus disease 2019 (COVID-19) has overwhelmed the global economy and human well-being. On account of the sharp increase in test demand, there is a need for an accurate and alternative diagnosis method for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, with the aim to specifically identify the trace SARS-CoV-2 S1 glycoprotein, we developed a high-sensitivity and high-selectivity diagnostic method based on the targeted parallel reaction monitoring (PRM) assay of eight selected peptides. This study emphasizes the outstanding detection sensitivity of 0.01 pg of the SARS-CoV-2 S1 glycoprotein even in the interference of other structural proteins, which to our knowledge is the current minimum limit of detection for the SARS-CoV-2 S1 glycoprotein. This technology could further identify 0.01 pg of the SARS-CoV-2 S1 glycoprotein in a spike pseudovirus, revealing its practical effectiveness. All our preliminary results throw light on the capability of the mass spectrometry-based targeted PRM assay to identify SARS-CoV-2 as a practicable orthogonal diagnostic tool. Furthermore, this technology could be extended to other pathogens (e.g., MERS-CoV S1 protein or SARS-CoV S1 protein) by quickly adjusting the targeted peptides of MS data acquisition. In summary, this strategy is universal and flexible and could be quickly adjusted to detect and discriminate different mutants and pathogens.

[Recent advances in clustered regularly interspaced short palindromic repeats-based detection of severe acute respiratory syndrome coronavirus 2].

The rapid global spread of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has introduced various challenges in global public health systems. The poor applicability and sensitivity of the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and antigen-based tests, as well as the persistent emergence of SARS-CoV-2 variants with different mutations hinder satisfactory epidemic prevention and control. Therefore, there is an urgent need for diagnostic technologies capable of distinguishing SARS-CoV-2 variants with high sensitivity and low (or no) equipment dependence. Diagnosis based on clustered regularly interspaced short palindromic repeats (CRISPR) has low equipment requirements and is programmable, sensitive, and easy to use. Various nucleic acid detection tools with great clinical potential have been developed for the diagnosis of infectious diseases. Therefore, this review focuses on the reported state-of-the-art CRISPR diagnostic technologies developed for the detection and differentiation of SARS-CoV-2 variants, summarizes their characteristics and provides an outlook for their development.

Discrimination of influenza A virus subtypes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Influenza is a contagious respiratory illness caused by influenza viruses which possess the enormous threat to older people and young children. Rapid and precise discrimination of virus subtypes are quite crucial for the early therapy, prophylaxis and the prevention of epidemic outbreaks. Herein, a universal strategy, with influenza A virus (IAV) as a model, is proposed for the discrimination of virus subtypes based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Reference library based on nine IAVs subtypes (i.e., H1N1, H3N2, H4N8, H5N8, H6N6, H7N7, H9N2, H10N8, and H11N8) was set up for matching various IAVs subtypes. The simulative test spectra from IAVs showed that the corresponding IAVs subtypes could be distinguished in 90 min, accurately. Furthermore, the principal component analysis results also show that nine virus subtypes can be reliably distinguished. More importantly, this strategy provides an alternative method for identifying and distinguishing other viruses with high variability characteristics, such as SARS-CoV-2, which could be helpful for implementing public health strategies to counter pandemics. A MALDI-TOF MS based universal strategy for the discrimination of virus subtypes was developed, which possess the advantages of speed and high-accuracy. [Display omitted] • A home-made identification database of influenza A virus subtypes was set up. • The discrimination of influenza A virus subtypes could be finished within 90 min. • The influenza A virus subtypes could be distinguished with high accuracy. [ FROM AUTHOR]

Discrimination of influenza A virus subtypes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Influenza is a contagious respiratory illness caused by influenza viruses which possess the enormous threat to older people and young children. Rapid and precise discrimination of virus subtypes are quite crucial for the early therapy, prophylaxis and the prevention of epidemic outbreaks. Herein, a universal strategy, with influenza A virus (IAV) as a model, is proposed for the discrimination of virus subtypes based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Reference library based on nine IAVs subtypes (i.e., H1N1, H3N2, H4N8, H5N8, H6N6, H7N7, H9N2, H10N8, and H11N8) was set up for matching various IAVs subtypes. The simulative test spectra from IAVs showed that the corresponding IAVs subtypes could be distinguished in 90 min, accurately. Furthermore, the principal component analysis results also show that nine virus subtypes can be reliably distinguished. More importantly, this strategy provides an alternative method for identifying and distinguishing other viruses with high variability characteristics, such as SARS-CoV-2, which could be helpful for implementing public health strategies to counter pandemics.