Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Bioinformatics Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Clin Chem. 2022 Jul 27;68(8):1042-1052. doi: 10.1093/clinchem/hvac081.
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.
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.
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.
Multiplex fragment analysis is adaptable and rapid and has similar accuracy to WGS to classify SARS-CoV-2 variants.
严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）变体不断出现，有效追踪需要快速返回结果。变体监测通常通过全基因组测序（WGS）进行，但这可能成本高昂，需要专门的设备和生物信息学专业知识。基因分型方法是监测 SARS-CoV-2 变体的快速方法，但需要不断适应。片段分析可能是一种改进 SARS-CoV-2 变体检测的方法。
使用针对大小和荧光颜色的变体的 PCR 验证了多重片段分析方法（CoVarScan）。针对关注变体（VOC）中的 8 个 SARS-CoV-2 突变热点进行了靶向。三个引物对（重复缺失区[RDR]1、RDR2 和 RDR3-4）侧翼 S 基因中的 RDR。三个等位基因特异性引物靶向重复的刺突受体结合域突变体。最后，2 对引物靶向 ORF1A 和 ORF8 中的重复缺失或插入。片段通过毛细管电泳（ABI 3730XL）进行解析和分析，并将突变特征与 WGS 结果进行比较。
我们使用 3544 份临床呼吸道标本验证了 CoVarScan。与 WGS 相比，该测定法的灵敏度为 96%，特异性为 99%。核心靶标（RDR1、RDR2 和 ORF1A）的检测限为 5 个拷贝/反应。在 CT<30 的 95%的样本中和 CT 为 34 到 35 的 75%的样本中都可以识别到变体。该检测方法的设计于 2021 年 4 月冻结，但已检测到所有后续的 VOC，包括 Delta（n=2820）、Mu（n=6）、Lambda（n=6）和奥密克戎（n=309）。基因分型结果可在短短 4 小时内获得。
多重片段分析具有适应性和快速性，与 WGS 相比具有类似的准确性，可用于对 SARS-CoV-2 变体进行分类。
