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Misidentification of the SARS-CoV-2 Mu variant using commercial mutation screening assays
Izaskun Alejo-Cancho1,2, Ana Gual-de-Torrella3,4, Mikel Gallego5,4
1Microbiology Department, Hospital Universitario Galdakao-Usansolo, Osakidetza Basque Health Service, Galdakao, Spain. i.alejo.cancho@gmail.com.
Abstract:
Detection of mutations by multiplex real-time RT-PCR is a widely used method for the screening of SARS-CoV-2 variants, but this method has several limitations. We describe three cases in which a Mu strain containing the mutation K417N was initially misclassified as the Beta variant. We recommend the detection of P681H to distinguish between these two variants. Our experience highlights the importance of keeping track of new variants and mutations in order to adapt the current workflows.
Insights
Multiplex real-time RT-PCR can misclassify SARS-CoV-2 variants. Detecting the P681H mutation helps differentiate Mu and Beta strains, improving variant screening accuracy.
Area of Science:
- Virology
- Molecular Biology
- Genetics
Background:
- Multiplex real-time RT-PCR is a common method for SARS-CoV-2 variant screening.
- This technique has limitations that can lead to misclassification of viral strains.
Purpose of the Study:
- To report cases of SARS-CoV-2 Mu variant misclassification as Beta variant.
- To propose an improved method for distinguishing between Mu and Beta strains.
Main Methods:
- Analysis of three cases involving misclassification of SARS-CoV-2 Mu variant.
- Real-time RT-PCR for mutation detection.
Main Results:
- Three instances where the Mu variant (K417N mutation) was incorrectly identified as the Beta variant.
- The P681H mutation was identified as a key differentiator between Mu and Beta variants.
Conclusions:
- The K417N mutation in the Mu strain can lead to its misclassification as the Beta variant using current RT-PCR methods.
- Detecting the P681H mutation is recommended to accurately distinguish between Mu and Beta SARS-CoV-2 variants.
- Continuous monitoring of new variants and mutations is crucial for adapting diagnostic workflows.
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