Abstract
AbstractThe recent emergence of the SARS-CoV-2 Omicron variant is associated with a dramatic surge of cases around the globe in late 2021 and early 2022. The numerous mutations in this variant, particularly in the Spike protein, enhance its transmission, increase immune evasion, and limit treatment with monoclonal antibodies. Identifying a community’s introduction to a novel SARS-CoV-2 variant with new clinical features related to treatment options and infection control needs is imperative to inform decisions by clinicians and public health officials, and traditional sequencing techniques often take weeks to result. Here, we describe a quantitative reverse transcription PCR assay (RT-qPCR) to accurately and precisely detect the presence of the Omicron sublineages BA.1/BA1.1 and BA.2 viral RNA from patient samples in less than four hours. The assay uses primers targeting the BA.1/BA1.1 unique mutations N211del, L212I, and L214 insertion EPE in the Spike protein gene, and the BA.2 specific mutations T19I and L24/P25/P26 deletion in the Spike protein gene. Using this assay, we detected 169 cases of Omicron, 164 BA.1/BA1.1 and 5 BA.2, from 270 residual SARS-CoV-2 positive samples collected for diagnostic purposes from Santa Barbara County (SBC) between December 2021 to February 2022. The RT-qPCR results show concordance with whole viral genome sequencing. Our observations indicate that Omicron was the dominant variant in SB County and is likely responsible for the surge of cases in the area during the sampling period. Using this inexpensive and accurate test, the rapid detection of Omicron in patient samples allowed clinicians to modify treatment strategies and public health officers to enhance contact tracing strategies. This RT-qPCR assay offers an alternative to current variant-specific detection approaches, provides a template for the fast design of similar assays, and allows the rapid, accurate, and inexpensive detection of Omicron variants in patient samples. It can also be readily adapted to new variants as they emerge in the future.
Publisher
Cold Spring Harbor Laboratory