最近的SARS-CoV-2废水流行病学(WBE)监测表明,污水场中COVID-19患者的数量与废水中病毒遗传物质的水平呈正相关。已尝试使用多变量回归方法使用废水SARS-CoV-2病毒载量来预测每个污水箱内的受感染人群。然而,据报道,在接受工业废水的处理设施中,SARS-CoV-2病毒载量的明显和持续的变化使临床预测具有挑战性。区域工业和制造设施释放的几类分子,特别是食品加工业,可以通过破坏膜的脂质双层来显着抑制废水中的SARS-CoV-2信号。因此,开发了与代谢组学分析结合的系统排名过程,以鉴定表现出SARS-CoV-2抑制的废水处理设施,并鉴定和量化抑制SARS-COV-2信号的化学物质。通过对每个诊断病例在下水道中的病毒载量进行排名,我们成功地确定了密苏里州的污水处理设施,美国显示SARS-CoV-2抑制(显着低于5×1011基因拷贝/报道病例)并确定其抑制率。通过无针对性的全球化学剖析和有针对性的废水样品分析,40种化合物被鉴定为SARS-CoV-2信号抑制剂的候选物。在这些化合物中,与未抑制的对照设施相比,14在表现出SARS-CoV-2信号抑制的废水处理设施中具有更高的浓度。逐步回归分析表明,4-壬基酚,棕榈酸,油酸钠,聚乙二醇二油酸酯与SARS-CoV-2信号抑制率呈正相关。孵化研究进一步证实了抑制活动,并测定每种生物活性化合物的抑制动力学。根据这些实验的结果,废水中的生物活性分子可显著降低SARS-CoV-2遗传标记信号的稳定性。根据这些化学抑制剂的浓度,可以开发一个校正系数,以便对接收来自类似行业的废水的废水处理设施获得更可靠和无偏见的监测结果。
Recent SARS-CoV-2 wastewater-based epidemiology (WBE) surveillance have documented a positive correlation between the number of COVID-19 patients in a sewershed and the level of viral genetic material in the wastewater. Efforts have been made to use the wastewater SARS-CoV-2 viral load to predict the infected population within each sewershed using a multivariable regression approach. However, reported clear and sustained variability in SARS-CoV-2 viral load among treatment facilities receiving industrial wastewater have made clinical prediction challenging. Several classes of molecules released by regional industries and manufacturing facilities, particularly the food processing industry, can significantly suppress the SARS-CoV-2 signals in wastewater by breaking down the lipid-bilayer of the membranes. Therefore, a systematic ranking process in conjugation with metabolomic analysis was developed to identify the wastewater treatment facilities exhibiting SARS-CoV-2 suppression and identify and quantify the chemicals suppressing the SARS-COV-2 signals. By ranking the viral load per diagnosed case among the sewersheds, we successfully identified the wastewater treatment facilities in Missouri, USA that exhibit SARS-CoV-2 suppression (significantly lower than 5 × 1011 gene copies/reported case) and determined their suppression rates. Through both untargeted global chemical profiling and targeted analysis of wastewater samples, 40 compounds were identified as candidates of SARS-CoV-2 signal suppressors. Among these compounds, 14 had higher concentrations in wastewater treatment facilities that exhibited SARS-CoV-2 signal suppression compared to the unsuppressed control facilities. Stepwise regression analyses indicated that 4-nonylphenol, palmitelaidic acid, sodium oleate, and polyethylene glycol dioleate are positively correlated with SARS-CoV-2 signal suppression rates. Suppression activities were further confirmed by incubation studies, and the suppression kinetics for each bioactive compound were determined. According to the results of these experiments, bioactive molecules in wastewater can significantly reduce the stability of SARS-CoV-2 genetic marker signals. Based on the concentrations of these chemical suppressors, a correction factor could be developed to achieve more reliable and unbiased surveillance results for wastewater treatment facilities that receive wastewater from similar industries.