National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India.
National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
Sci Total Environ. 2022 Feb 10;807(Pt 3):151038. doi: 10.1016/j.scitotenv.2021.151038. Epub 2021 Oct 22.
Given a large number of SARS-CoV-2 infected individuals, clinical detection has proved challenging. The wastewater-based epidemiological paradigm would cover the clinically escaped asymptomatic individuals owing to the faecal shedding of the virus. We hypothesised using wastewater as a valuable resource for analysing SARS-CoV-2 mutations circulating in the wastewater of Pune region (Maharashtra; India), one of the most affected during the covid-19 pandemic. We conducted study in open wastewater drains from December 2020-March 2021 to assess the presence of SARS-CoV-2 nucleic acid and further detect mutations using ARTIC protocol of MinION sequencing. The analysis revealed 108 mutations across six samples categorised into 39 types of mutations. We report the occurrence of mutations associated with Delta variant lineage in March-2021 samples, simultaneously also reported as a Variant of Concern (VoC) responsible for the rapid increase in infections. The study also revealed four mutations; S:N801, S:C480R, NSP14:C279F and NSP3:L550del not currently reported from wastewater or clinical data in India but reported worldwide. Further, a novel mutation NSP13:G206F mapping to NSP13 region was observed from wastewater. Notably, S:P1140del mutation was detected in December 2020 samples while it was reported in February 2021 from clinical data, indicating the instrumentality of wastewater data in early detection. This is the first study in India to demonstrate utility of sequencing in wastewater-based epidemiology to identify mutations associated with SARS-CoV-2 virus fragments from wastewater as an early warning indicator system.
鉴于大量的 SARS-CoV-2 感染个体，临床检测已被证明具有挑战性。基于污水的流行病学模式将涵盖由于病毒粪便排出而临床逃脱的无症状个体。我们假设利用污水作为分析在浦那地区（印度马哈拉施特拉邦）污水中循环的 SARS-CoV-2 突变的有价值资源，该地区是新冠疫情期间受影响最严重的地区之一。我们在 2020 年 12 月至 2021 年 3 月期间对开放污水渠进行了研究，以评估污水中 SARS-CoV-2 核酸的存在，并进一步使用 MinION 测序的 ARTIC 方案检测突变。分析显示，在六个样本中发现了 108 个突变，分为 39 种类型的突变。我们报告了与 Delta 变异株系相关的突变的发生，这些突变发生在 2021 年 3 月的样本中，同时也被报告为导致感染迅速增加的关注变异株（VoC）。该研究还发现了四个突变，即 S：N801、S：C480R、NSP14：C279F 和 NSP3：L550del，这些突变目前在印度的污水或临床数据中没有报告，但在全球范围内有报告。此外，还从污水中观察到了一个位于 NSP13 区域的新型突变 NSP13：G206F。值得注意的是，S：P1140del 突变于 2020 年 12 月的样本中被检测到，而在 2021 年 2 月的临床数据中被报告，这表明污水数据在早期检测中的工具性。这是印度首例研究利用测序技术在污水中进行流行病学研究，以识别与 SARS-CoV-2 病毒片段相关的突变，作为早期预警指标系统。
