Multiplex Fragment Analysis for Flexible Detection of All SARS-CoV-2 Variants of Concern.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and effective tracking requires rapid return of results. Surveillance of variants is typically performed by whole genome sequencing (WGS), which can be financially prohibitive and requires specialized equipment and bioinformatic expertise. Genotyping approaches are rapid methods for monitoring SARS-CoV-2 variants but require continuous adaptation. Fragment analysis may represent an approach for improved SARS-CoV-2 variant detection. METHODS: A multiplex fragment analysis approach (CoVarScan) was validated using PCR targeting variants by size and fluorescent color. Eight SARS-CoV-2 mutational hot spots in variants of concern (VOCs) were targeted. Three primer pairs (recurrently deleted region [RDR] 1, RDR2, and RDR3-4) flank RDRs in the S-gene. Three allele-specific primers target recurrent spike receptor binding domain mutants. Lastly, 2 primer pairs target recurrent deletions or insertions in ORF1A and ORF8. Fragments were resolved and analyzed by capillary electrophoresis (ABI 3730XL), and mutational signatures were compared to WGS results. RESULTS: We validated CoVarScan using 3544 clinical respiratory specimens. The assay exhibited 96% sensitivity and 99% specificity compared to WGS. The limit of detection for the core targets (RDR1, RDR2, and ORF1A) was 5 copies/reaction. Variants were identified in 95% of samples with cycle threshold (CT) <30 and 75% of samples with a CT 34 to 35. Assay design was frozen April 2021, but all subsequent VOCs have been detected including Delta (n = 2820), Mu, (n = 6), Lambda (n = 6), and Omicron (n = 309). Genotyping results are available in as little as 4 h. CONCLUSIONS: Multiplex fragment analysis is adaptable and rapid and has similar accuracy to WGS to classify SARS-CoV-2 variants.

A short plus long-amplicon based sequencing approach improves genomic coverage and variant detection in the SARS-CoV-2 genome.

High viral transmission in the COVID-19 pandemic has enabled SARS-CoV-2 to acquire new mutations that may impact genome sequencing methods. The ARTIC.v3 primer pool that amplifies short amplicons in a multiplex-PCR reaction is one of the most widely used methods for sequencing the SARS-CoV-2 genome. We observed that some genomic intervals are poorly captured with ARTIC primers. To improve the genomic coverage and variant detection across these intervals, we designed long amplicon primers and evaluated the performance of a short (ARTIC) plus long amplicon (MRL) sequencing approach. Sequencing assays were optimized on VR-1986D-ATCC RNA followed by sequencing of nasopharyngeal swab specimens from fifteen COVID-19 positive patients. ARTIC data covered 94.47% of the virus genome fraction in the positive control and patient samples. Variant analysis in the ARTIC data detected 217 mutations, including 209 single nucleotide variants (SNVs) and eight insertions & deletions. On the other hand, long-amplicon data detected 156 mutations, of which 80% were concordant with ARTIC data. Combined analysis of ARTIC + MRL data improved the genomic coverage to 97.03% and identified 214 high confidence mutations. The combined final set of 214 mutations included 203 SNVs, 8 deletions and 3 insertions. Analysis showed 26 SARS-CoV-2 lineage defining mutations including 4 known variants of concern K417N, E484K, N501Y, P618H in spike gene. Hybrid analysis identified 7 nonsynonymous and 5 synonymous mutations across the genome that were either ambiguous or not called in ARTIC data. For example, G172V mutation in the ORF3a protein and A2A mutation in Membrane protein were missed by the ARTIC assay. Thus, we show that while the short amplicon (ARTIC) assay provides good genomic coverage with high throughput, complementation of poorly captured intervals with long amplicon data can significantly improve SARS-CoV-2 genomic coverage and variant detection.