VarLOCK: sequencing-independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance
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In: Scientific Reports, Vol. 13, No. 1, 20832, 27.11.2023.
Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - VarLOCK: sequencing-independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance
AU - Nan, Xinsheng
AU - Hardinge, Patrick
AU - Hoehn, Sven
AU - Dighe, Shrinivas Nivrutti
AU - Ukeri, John
AU - Pease, Darius F
AU - Griffin, Joshua
AU - Warrington, Jessica I
AU - Saud, Zack
AU - Hottinger, Emma
AU - Webster, Gordon
AU - Jones, Davey
AU - Kille, Peter
AU - Weightman, Andrew
AU - Stanton, Richard
AU - Castell, Oliver K
AU - Murray, James A H
AU - Jurkowski, Tomasz P
N1 - © 2023. The Author(s).
PY - 2023/11/27
Y1 - 2023/11/27
N2 - The COVID-19 pandemic demonstrated the need for rapid molecular diagnostics. Vaccination programs can provide protection and facilitate the opening of society, but newly emergent and existing viral variants capable of evading the immune system endanger their efficacy. Effective surveillance for Variants of Concern (VOC) is therefore important. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. Here we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to provide rapid and sensitive discrimination of SARS-CoV-2 VOCs that can be used at point of care, implemented in the pipelines of small or large testing facilities, and even determine the proportion of VOCs in pooled population-level wastewater samples. This technology complements sequencing efforts to allow facile and rapid identification of individuals infected with VOCs to help break infection chains. We show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants and the rapid adaptability of the technique for new and emerging VOCs.
AB - The COVID-19 pandemic demonstrated the need for rapid molecular diagnostics. Vaccination programs can provide protection and facilitate the opening of society, but newly emergent and existing viral variants capable of evading the immune system endanger their efficacy. Effective surveillance for Variants of Concern (VOC) is therefore important. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. Here we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to provide rapid and sensitive discrimination of SARS-CoV-2 VOCs that can be used at point of care, implemented in the pipelines of small or large testing facilities, and even determine the proportion of VOCs in pooled population-level wastewater samples. This technology complements sequencing efforts to allow facile and rapid identification of individuals infected with VOCs to help break infection chains. We show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants and the rapid adaptability of the technique for new and emerging VOCs.
KW - Humans
KW - SARS-CoV-2/genetics
KW - COVID-19/diagnosis
KW - Wastewater
KW - Pandemics
KW - Wastewater-Based Epidemiological Monitoring
KW - Point-of-Care Testing
U2 - 10.1038/s41598-023-47289-0
DO - 10.1038/s41598-023-47289-0
M3 - Article
C2 - 38012215
VL - 13
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
IS - 1
M1 - 20832
ER -