ABSTRACT
Background SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/BA.5 have significant differences in transmission and immune escape ability. Currently, no effective detection methods are available for these subtypes. Routine detection methods are prone to missed detection.Methods In this study, a rapid detection method based on ARMS-PCR and molecular beacon probes was developed for the identification of SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5. Specific primers and probes were designed and validated using gel electrophoresis, real-time fluorescence quantitative PCR, and molecular hybridization.Results ARMS-PCR and molecular beacon probe-based assays can be applied in RT-PCR and fluorescence assays to differentiate SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5.Conclusions In the present study, we developed a simple, rapid and accurate detection method based on ARMS-PCR and molecular beacon probes for rapid genotyping of SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5. It can be used in real-time fluorescence quantitative PCR and molecular hybridization to identify subtypes of COVID-19, effectively improving the detection rate to provide guidance for disease prevention and treatment.
Subject(s)
COVID-19ABSTRACT
PM2.5 concentrations in Wuhan, China decreased by 36.0% between the period prior to the COVID-19 pandemic (1‒23 January, 2020) and the COVID-lockdown period (24 January to 29 February, 2020). However, decreases in PM2.5 concentration due to regional PM2.5 transport driven by meteorological changes, and the relationship between the PM2.5 source and receptor, are poorly understood. Therefore, this study assessed how changes in meteorology, local emissions, and regional transport from external source emissions contributed to the decrease in Wuhan’s PM2.5 concentration, using FLEXPART-WRF and WRF-Chem modelling experiments. The results showed that meteorological changes in central China explain up to 22.2% of the total decrease in PM2.5 concentrations in Wuhan, while the remaining 77.8% was due to air pollutant emissions reduction. Reduction in air pollutant emissions depended on both local and external sources, which contributed alomst equally to the reduction in PM2.5 concentrations (38.7% and 39.1% of the total reduction, respectively). The key emissions source areas affecting PM2.5 in Wuhan during the COVID-lockdown were identified by the FLEXPART-WRF modeling, revealing that regional-joint control measures in key areas accounted for 89.3% of the decrease in PM2.5 concentrations in Wuhan. The results show that regional-joint control can be enhanced by identifying key areas of emissions reduction from the source‒receptor relationship of regional PM2.5 transport driven by meteorology under the background of East Asian monsoon climate change.