Assess the Variability and Robustness of an Aluminum-Based Adsorption-Precipitation Method for Virus Detection in Wastewater Samples

评估基于铝的吸附-沉淀法检测废水样品中病毒的变异性和稳健性

阅读:1

Abstract

Wastewater-based molecular epidemiology enables the surveillance of both symptomatic and asymptomatic individuals in a non-invasive, cost-effective, rapid, and early-detection manner. The use of wastewater analysis to monitor the prevalence of viral pathogens in a given population has increased significantly since the COVID-19 pandemic. These studies typically involve three main steps: viral concentration, nucleic acid extraction, and DNA/RNA quantification. However, the absence of a standardized methodology remains a major limitation, hindering result comparability across studies. Among the available viral concentration techniques, aluminum-based adsorption-precipitation is one of the most commonly used due to its simplicity, efficiency, and low cost. This study evaluates the robustness and variability of the viral concentration and nucleic acid extraction steps by implementing different process controls in wastewater samples across 122 independent experiments. Additionally, correlations between viral recovery efficiencies and relevant physicochemical parameters were also analyzed (n = 600). The results indicate that, despite the overall robustness of the method, the concentration step exhibits the highest variability (CV = 53.82%), which accounted for 53.73% of the overall variability. In addition, our results show that, on average, 0.65 logarithmic units were lost during the viral concentration step. Furthermore, viral recovery rates were influenced by seasonality and sample characteristics, while no significant correlation was observed with pH or conductivity. These findings highlight the importance of process controls, confirming the robustness of the methodology, and identifying key parameters that should be considered in future studies for improved data interpretation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。