Bayega Anthony, Reiling Sarah J, Liu Ju Ling, Dubuc Isabelle, Gravel Annie, Flamand Louis, Ragoussis Jiannis
McGill Genome Centre, Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC, Canada.
Department of Human Genetics, McGill University, Montreal, QC, Canada.
Front Genet. 2025 Aug 15;16:1516791. doi: 10.3389/fgene.2025.1516791. eCollection 2025.
The raging COVID-19 pandemic caused by SARS-CoV-2 has so far claimed the lives of 7 million people and continues to infect many more. Further, virus evolution has caused mutations that have compromised public health interventions like vaccination regimes and monoclonal antibody and convalescent sera treatments. In response, unprecedented large-scale whole genome viral surveillance approaches have been devised to keep track of the evolution and transmission patterns of the virus within and across populations. Here, we aimed to compare efficiencies of SARS-CoV-2 whole genome sequencing approaches using synthetic SARS-CoV-2 genome and six cell culture SARS-CoV-2 variants titrated to represent samples at high, medium, and low viral load. We found that the ARTIC protocols performed best in terms of PCR amplicon yield returning 67% more amplicons than Entebbe protocol which was the second highest PCR amplicon yielding protocol. ARTIC v4.1 protocol yields were only slightly better than ARTIC v3. Despite yielding the lowest PCR amplicons, the SNAP protocol showed the highest genome completeness using a synthetic genome at high viral titre followed by ARTIC protocols. However, the ARTIC protocols showed highest genome completeness with cell culture SARS-CoV-2 variants across high, medium and low viral titres. ARTIC protocol also performed best in calling the correct lineage among cell culture SARS-CoV-2 variants across different viral titres. We also designed a new method termed ARTIC-Amp which leverages ARTIC protocol and performs a rolling circle amplification to increase yield of amplicons. In a proof-of-principle experiment, this method showed 100% coverage in all four targeted genes across three replicates unlike the ARTIC protocol missed one gene in two of the three replicates. Our results demonstrate the robustness of the ARTIC protocol and propose an improved method that could be useful for samples that routinely have limited SARS-CoV-2 RNA such as wastewater samples.
由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引发的肆虐的新冠疫情，迄今已导致700万人死亡，且仍在持续感染更多人。此外，病毒进化产生的突变削弱了疫苗接种计划、单克隆抗体及康复血清治疗等公共卫生干预措施的效果。作为应对措施，人们设计了前所未有的大规模全基因组病毒监测方法，以追踪病毒在人群内部及人群之间的进化和传播模式。在此，我们旨在使用合成的SARS-CoV-2基因组以及六种经滴定以代表高、中、低病毒载量样本的细胞培养SARS-CoV-2变体，比较SARS-CoV-2全基因组测序方法的效率。我们发现，ARTIC方案在PCR扩增子产量方面表现最佳，其产生的扩增子比第二高的恩德比方案多67%。ARTIC v4.1方案的产量仅略高于ARTIC v3。尽管SNAP方案产生的PCR扩增子最少，但在高病毒滴度下使用合成基因组时，其基因组完整性最高，其次是ARTIC方案。然而，在高、中、低病毒滴度的细胞培养SARS-CoV-2变体中，ARTIC方案显示出最高的基因组完整性。在不同病毒滴度的细胞培养SARS-CoV-2变体中，ARTIC方案在确定正确谱系方面也表现最佳。我们还设计了一种名为ARTIC-Amp的新方法，该方法利用ARTIC方案并进行滚环扩增以提高扩增子产量。在一项原理验证实验中，与ARTIC方案在三个重复样本中有两个遗漏了一个基因不同，该方法在三个重复样本中所有四个目标基因的覆盖率均达到100%。我们的结果证明了ARTIC方案的稳健性，并提出了一种改进方法，该方法可能对诸如废水样本等通常SARS-CoV-2 RNA有限的样本有用。
