ABSTRACT
The effective application of wastewater surveillance is dependent on testing capacity and sensitivity to obtain high spatial resolution testing results for a timely targeted public health response. To achieve this purpose, the development of rapid, high-throughput, and sensitive virus concentration methods is urgently needed. Various protocols have been developed and implemented in wastewater surveillance networks so far, however, most of them lack the ability to scale up testing capacity or cannot achieve sufficient sensitivity for detecting SARS-CoV-2 RNA at low prevalence. In the present study, using positive raw wastewater in Hong Kong, a PEG precipitation-based three-step centrifugation method was developed, including low-speed centrifugation for large particles removal and the recovery of viral nucleic acid, and medium-speed centrifugation for the concentration of viral nucleic acid. This method could process over 100 samples by two persons per day to reach the process limit of detection (PLoD) of 3286 copies/L wastewater. Additionally, it was found that the testing capacity could be further increased by decreasing incubation and centrifugation time without significantly influencing the method sensitivity. The entire procedure uses ubiquitous reagents and instruments found in most laboratories to obtain robust testing results. This high-throughput, cost-effective, and sensitive tool will promote the establishment of nearly real-time wastewater surveillance networks for valuable public health information.
Subject(s)
COVID-19 , Nucleic Acids , Humans , RNA, Viral , SARS-CoV-2 , Wastewater , Wastewater-Based Epidemiological MonitoringABSTRACT
Sewage surveillance is increasingly employed as a supplementary tool for COVID-19 control. Experiences learnt from large-scale trials could guide better interpretation of the sewage data for public health interventions. Here, we compared the performance of seven commonly used primer-probe sets in RT-qPCR and evaluated the usefulness in the sewage surveillance program in Hong Kong. All selected primer-probe sets reliably detected SARS-CoV-2 in pure water at 7 copies per µL. Sewage matrix did not influence RT-qPCR determination of SARS-CoV-2 concentrated from a small-volume sewage (30 mL) but introduced inhibitory impacts on a large-volume sewage (920 mL) with a ΔCt of 0.2-10.8. Diagnostic performance evaluation in finding COVID-19 cases showed that N1 was the best single primer-probe set, while the ORF1ab set is not recommended. Sewage surveillance using the N1 set for over 3200 samples effectively caught the outbreak trend and, importantly, had a 56% sensitivity and a 96% specificity in uncovering the signal sources from new cases and/or convalescent patients in the community. Our study paves the way for selecting detection primer-probe sets in wider applications in responding to the COVID-19 pandemic.
Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Pandemics , Public Health , RNA, Viral/analysis , SARS-CoV-2/genetics , Sensitivity and Specificity , SewageABSTRACT
OBJECTIVE: To develop a method for noninvasive prenatal paternity testing based on targeted sequencing of single nucleotide polymorphisms (SNPs). METHOD: SNPs were selected based on population genetics data. Target-SNPs in cell-free DNA extracted from maternal blood (maternal cfDNA) were analyzed by targeted sequencing wherein target enrichment was based on multiplex amplification using QIAseq Targeted DNA Panels with Unique Molecular Identifiers. Fetal SNP genotypes were called using a novel bioinformatics algorithm, and the combined paternity indices (CPIs) and resultant paternity probabilities were calculated. RESULTS: Fetal SNP genotypes obtained from targeted sequencing of maternal cfDNA were 100% concordant with those from amniotic fluid-derived fetal genomic DNA. From an initial panel of 356 target-SNPs, an average of 148 were included in paternity calculations in 15 family trio cases, generating paternity probabilities of greater than 99.9999%. All paternity results were confirmed by short-tandem-repeat analysis. The high specificity of the methodology was validated by successful paternity discrimination between biological fathers and their siblings and by large separations between the CPIs calculated for the biological fathers and those for 60 unrelated men. CONCLUSION: The novel method is highly effective, with substantial improvements over similar approaches in terms of reduced number of target-SNPs, increased accuracy, and reduced costs.
