Comparison of Two Concentration Methods for the Molecular Detection of Enteroviruses in Raw and Treated Sewage

Abstract

Human enteric viruses are a major causative agent of emerging waterborne diseases and constitute a serious public health concern. Environmental contamination occurs through discharge of waste materials from infected persons. Methods for viral detection should be developed to detect low infective dose of enteric viruses in environment. In this study, we aimed at comparing two concentration methods for the detection of naturally occurring enteroviruses in raw and treated sewage. In the first method, polyethylene glycol is used to concentrate viral particles from the collected samples. The second method is based on ultracentrifugation of viral particles at high speed (110,0009g). Genomes of enteroviruses were quantified by the quantitative real-time PCR method in raw and treated sewage samples. PEG-based method yielded higher genomic copies of enteric viruses (with an average of 5.9 log 10 genomic copies/100 mL) when applied to raw sewage samples. While the ultracentrifugation assay in the second method decreases genomic copies number (with an average of 5.4 log 10 genomic copies/100 mL). The recovery differences between the two methods were not significant when applied to clean samples (treated sewage). This could be explained by the presence of inhibitors, which interfere with qRT-PCR, in less quantity comparatively to raw sewage. PEG-based method would be more accurate for samples with highorganic matter load. This report emphasizes the importance of matrices nature on the recovery of enteroviruses from sewage samples. This should be taken into consideration for establishing standardized virological assays to ensure the virological quality control of discharged water in environment.

Molecular detection and genotyping of group A rotavirus in two wastewater treatment plants, Iran

“…Although in our study it is indicated that the rotavirus removal is not complete in the effluent of WWTPs, the virus pollution has been significant and revealed a critical public health danger. This result is an agreement with the result of previous studies that display the presence of rotaviruses not only in sewage raw but also in treated wastewater [4,11,19,26]. Studies conducted to evaluate the efficacy of wastewater treatment plants in developing countries are limited to bacterial indicators such as coliforms, while viruses are ignored.…”

“…The stools of infected people contain many enteric viruses, usually 10 5 -10 11 virus particles/g stool, meaning the contamination of different types of environmental water samples like river, groundwater, seawater, and drinking water. Several viruses, such as norovirus, rotavirus, adenovirus, astrovirus, and sapovirus, are responsible for gastroenteritis [4].…”

“…Rotaviruses are the most important pathogenic viruses can be detected in wastewater, even when sewage treatment is fully and effectively carried out. 4. Analysis of rotavirus strains/genotypes is the key to evaluating the suitability of mass vaccination of children around the world.…”

Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications

“…However, no method is completely perfect by taking into account the principle and procedure of each method. For instance, the detection of pathogenic viruses is obtained in a disinfection procedure, but this method is not suitable for the detection of coliform bacteria due to low concentration of bacteria indicator [167]. The generation of DNA-based amplification method has evolved due to demands in producing combined method of detection with higher specificity and rapidity.…”

“…Initially, the model-based event detection method involves a signal-to-noise principles using laboratory and sensor test-loop evaluation. Indication of contamination events is derived from the chemical changes in background water quality signals [88,89], [137][138][139][140][141][142][143], [163], [167], [217], [244,245], [429,430] Sensor Placements Approach [372][373][374][375][376][377], [380][381][382][383][384][385][386][387][388], [391], [400][401][402][403][404][405][406][407], [434][435][436][437][438] Event Detection Model-based -High true positive alarm rate -Low false alarm detections -Fast response time -Complicated calibration process -Highly dependable on predictions and estimations -Computationally intensive…”