Xu Xiaoqing, Deng Yu, Ding Jiahui, Zheng Xiawan, Wang Chunxiao, Wang Dou, Liu Lei, Gu Haogao, Peiris Malik, Poon Leo L M, Zhang Tong
Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China.
Water Res. 2023 Oct 1;244:120444. doi: 10.1016/j.watres.2023.120444. Epub 2023 Aug 3.
Wastewater-based epidemiology (WBE) has been widely used as a complementary approach to SARS-CoV-2 clinical surveillance. Wastewater genomic sequencing could provide valuable information on the genomic diversity of SARS-CoV-2 in the surveyed population. However, reliable detection and quantification of variants or mutations remain challenging. In this study, we used mock wastewater samples created by spiking SARS-CoV-2 variant standard RNA into wastewater RNA to evaluate the impacts of sequencing throughput on various aspects such as genome coverage, mutation detection, and SARS-CoV-2 variant deconvolution. We found that wastewater datasets with sequencing throughput greater than 0.5 Gb yielded reliable results in genomic analysis. In addition, using in silico mock datasets, we evaluated the performance of the adopted pipeline for variant deconvolution. By sequencing 86 wastewater samples covering more than 6 million people over 7 months, we presented two use cases of wastewater genomic sequencing for surveying COVID-19 in Hong Kong in WBE applications, including the replacement of Delta variants by Omicron variants, and the prevalence and development trends of three Omicron sublineages. Importantly, the wastewater genomic sequencing data were able to reveal the variant trends 16 days before the clinical data did. By investigating mutations of the spike (S) gene of the SARS-CoV-2 virus, we also showed the potential of wastewater genomic sequencing in identifying novel mutations and unique alleles. Overall, our study demonstrated the crucial role of wastewater genomic surveillance in providing valuable insights into the emergence and monitoring of new SARS-CoV-2 variants and laid a solid foundation for the development of genomic analysis methodologies for WBE of other novel emerging viruses in the future.
基于废水的流行病学(WBE)已被广泛用作严重急性呼吸综合征冠状病毒2(SARS-CoV-2)临床监测的补充方法。废水基因组测序可以提供有关被调查人群中SARS-CoV-2基因组多样性的有价值信息。然而,对变异体或突变进行可靠的检测和定量仍然具有挑战性。在本研究中,我们通过将SARS-CoV-2变异体标准RNA掺入废水RNA中创建模拟废水样本,以评估测序通量对基因组覆盖、突变检测和SARS-CoV-2变异体反卷积等各个方面的影响。我们发现,测序通量大于0.5 Gb的废水数据集在基因组分析中产生了可靠的结果。此外,我们使用计算机模拟数据集评估了所采用的变异体反卷积流程的性能。通过对7个月内覆盖600多万人的86个废水样本进行测序,我们展示了废水基因组测序在基于废水的流行病学(WBE)应用中用于香港地区2019冠状病毒病(COVID-19)监测的两个案例,包括奥密克戎变异体取代德尔塔变异体,以及三种奥密克戎亚谱系的流行情况和发展趋势。重要的是,废水基因组测序数据能够在临床数据出现前16天揭示变异体趋势。通过研究SARS-CoV-2病毒刺突(S)基因的突变,我们还展示了废水基因组测序在识别新突变和独特等位基因方面的潜力。总体而言,我们的研究证明了废水基因组监测在深入了解新的SARS-CoV-2变异体的出现和监测方面的关键作用,并为未来开发针对其他新型新兴病毒的基于废水的流行病学基因组分析方法奠定了坚实基础。