Ramachandran Padmini, Kayikcioglu Tunc, Walsky Tamara, Judy Kathryn, Amirzadegan Jasmine, Bias Candace Hope, Tesfaldet Bereket, Balkey Maria, EppSchmidt Dietrich, Rand Hugh, Pettengill James, Tallent Sandra, Brown Eric, Pfefer Tina, Timme Ruth, Windsor Amanda, Grim Christopher, Hoffmann Maria
Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA.
Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA; Joint Institute for Food Safety and Applied Nutrition, University of Maryland, 5825, University Research Ct, Suite 1400, College Park, MD, USA.
Environ Res. 2025 Aug 1;278:121633. doi: 10.1016/j.envres.2025.121633. Epub 2025 Apr 18.
Wastewater-based analysis has emerged as a pivotal method for monitoring SARS-CoV-2 (SC2). Leveraging high-throughput sequencing on wastewater samples facilitates a comprehensive, population-level assessment of circulating and emerging SC2 variants within a community. This study meticulously evaluates the detection performance, variant calling accuracy, and the time taken from sample collection to public data release for wastewater SC2 monitoring. Two different SC2 target enrichment panels were employed, Illumina MiSeq and Oxford Nanopore Technologies (ONT) GridION sequencing platforms for a robust analysis. Daily collection of routine raw grab and composite samples took place at a wastewater treatment plant (WWTP) site in Maryland, USA (MD) from mid-January 2022 to the end of June 2022. Total Nucleic Acid (TNA) was extracted from samples and target enrichment was executed using QIAseq DIRECT and NEBNext VarSkip Short amplicon kits, with subsequent sequencing on MiSeq or ONT GridION platforms, respectively. Obtained sequences was analyzed using custom CFSAN Wastewater Analysis Pipeline (C-WAP). Raw sequence data and detailed metadata were submitted to NCBI (BioProject PRJNA757291) as it became available. Wastewater data successfully detected the onset of new variants BA.2, BA.2.12, BA.4.6, and BA.5 to the observed population. Notably, Omicron sub-variants were identified approximately a week ahead of publicly available clinical data at the MD ZIP-code level. Variation in quality metrics paralleled the rise and fall of BA waves, underscoring the impact of viral load on sequencing quality. Regular updates of estimated variant proportions were made available on the FDA-CFSAN "Wastewater Surveillance for SARS-CoV-2 Variants" website. In contrast to the median 28-day turnaround, the lead time from sample collection to public release of raw sequence data via NCBI was remarkably swift, accomplished within a mere 57 h in this specific exercise. Processing, sequencing, and analysis methods empowered the swift and accurate detection of SC2 trends and circulating variants within a community, offering insights for public health decision-making.
基于废水的分析已成为监测严重急性呼吸综合征冠状病毒2（SARS-CoV-2，简称SC2）的关键方法。对废水样本进行高通量测序有助于对社区内循环和新出现的SC2变体进行全面的人群水平评估。本研究精心评估了废水SC2监测的检测性能、变异体识别准确性以及从样本采集到公共数据发布所需的时间。采用了两种不同的SC2目标富集面板，Illumina MiSeq和牛津纳米孔技术公司（ONT）的GridION测序平台进行稳健分析。2022年1月中旬至2022年6月底，在美国马里兰州（MD）的一个污水处理厂（WWTP）现场每天采集常规原始抓取样本和混合样本。从样本中提取总核酸（TNA），并分别使用QIAseq DIRECT和NEBNext VarSkip短扩增子试剂盒进行目标富集，随后分别在MiSeq或ONT GridION平台上进行测序。使用定制的美国食品药品监督管理局食品安全与应用营养中心废水分析管道（C-WAP）对获得的序列进行分析。原始序列数据和详细的元数据在可用时提交给了美国国立医学图书馆（NCBI，生物项目PRJNA757291）。废水数据成功检测到新变体BA.2、BA.2.12、BA.4.6和BA.5在观察人群中的出现。值得注意的是，在MD邮政编码级别，奥密克戎亚变体的识别比公开可用的临床数据提前了大约一周。质量指标的变化与BA波的起伏平行，突出了病毒载量对测序质量的影响。美国食品药品监督管理局食品安全与应用营养中心（FDA-CFSAN）的“SARS-CoV-2变体废水监测”网站定期更新估计的变体比例。与28天的中位数周转时间相比，从样本采集到通过NCBI公开发布原始序列数据的前置时间非常迅速，在本次特定操作中仅用了57小时就完成了。处理、测序和分析方法能够快速准确地检测社区内SC2的趋势和循环变体，为公共卫生决策提供见解。
