RT-LAMP: A Cheaper, Simpler and Faster Alternative for the Detection of SARS-CoV-2 in Wastewater.

Reverse transcription loop-mediated isothermal amplification (RT-LAMP) has the potential to become a cheaper and faster option for monitoring COVID-19 infections through wastewater-based epidemiology. However, its application in COVID-19 surveillance has been limited to clinical testing only. We present in this paper two optimized RT-LAMP protocols based on colour change and fluorescence detection and application of these protocols for wastewater monitoring from four wastewater treatment plants over 4 weeks. The optimized RT-LAMP protocols have a limit of detection of 10 copies/25 µl reaction with positive amplification within 35 minutes. Over the 4 weeks of monitoring, the colorimetric protocol detected a prevalence of 12.5%, when 1 µl of extracted RNA with 92.7(± 28.2) ng/µl concentration was analysed. When the RNA template was increased by fivefold, the prevalence increased to 44%. The fluorescent RT-LAMP had a prevalence of 31% and 47% for starting templates of 92.7(± 28.2) ng/µl and 480(± 134.5) ng/µl of the extracted RNA, respectively. All samples were positive for SARS-CoV-2 when analysed with droplet digital PCR, with viral loads ranging from 18.1 to 195.6 gc/ml of wastewater. The RT-ddPCR, therefore, confirms the presence of the viral RNA in the wastewater samples, albeit at low concentrations. Additionally, the RT-LAMP protocols positively detected SARS-CoV-2 in wastewater samples with copies as low as 20.7 gc/ml. The results obtained in our study show the potential application of RT-LAMP for the detection of SARS-CoV-2 in wastewater, which could provide a cheaper and faster alternative to RT-qPCR or RT-ddPCR for wastewater-based epidemiological monitoring of COVID-19 and other viral infections.

Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective.

Monitoring of COVID-19 infections within communities via wastewater-based epidemiology could provide a cost-effective alternative to clinical testing. This approach, however, still requires improvement for its efficient application. In this paper, we present the use of wastewater-based epidemiology in monitoring COVID-19 infection dynamics in the KwaZulu-Natal province of South Africa, focusing on four wastewater treatment plants for 14 weeks. The SARS-CoV-2 viral load in influent wastewater was determined using droplet digital PCR, and the number of people infected was estimated using published models as well as using a modified model to improve efficiency. On average, viral loads ranged between 0 and 2.73 × 105 copies/100 ml, 0-1.52 × 105 copies/100 ml, 3 × 104-7.32 × 105 copies/100 ml and 1.55 × 104-4.12 × 105 copies/100 ml in the four wastewater treatment plants studied. The peak in viral load corresponded to the reported COVID-19 infections within the districts where these catchments are located. In addition, we also observed that easing of lockdown restrictions by authorities corresponded with an increase in viral load in the untreated wastewater. Estimation of infection numbers based on the viral load showed that a higher number of people could potentially be infected, compared to the number of cases reported based on clinical testing. The findings reported in this paper contribute to the field of wastewater-based epidemiology for COVID-19 surveillance, whilst highlighting some of the challenges associated with this approach, especially in developing countries.

Impact of sludge bulking on receiving environment using quantitative microbial risk assessment (QMRA)-based management for full-scale wastewater treatment plants.

During sludge bulking in wastewater treatment plants (WWTPs), high amounts of potentially pathogenic bacteria would release into the environment, causing various human-health risks. This is the first study attempting to assess the microbial infections associated with the reuse of WWTP effluents under various bulking conditions. Three common waterborne pathogens, viz., E. coli O157:H7, Salmonella, and Mycobacterium, were quantified from full-scale WWTPs using DNA extraction and qPCR at different sludge volume indices (SVIs). The detected pathogens were incorporated into a quantitative microbial risk assessment (QMRA) model to determine the applicability of WWTP discharge for recreational (bathing) activities and agricultural practices. The QMRA exposures were children, women, and men during swimming, and farmers and vegetable consumers during irrigation. Bacterial abundance in the treated wastewater increased in response to SVIs, and the QMRA values at all bulking events exceeded the tolerable risk of one case of infection per 10,000 people per year. Hence, various disinfection scenarios (chlorination, ultraviolet, and ozonation) were hypothetically tested to control the risks associated with pathogenic bacteria, allowing for safe disposal and reuse of the treated effluent. The ultraviolet application provided the highest ability to inactivate the pathogenic bacteria, except for the case of children exposed to Salmonella infection during swimming. The reduction of Mycobacterium infection risks with either chlorination or ozonation showed inefficient results. This study would be helpful for the management of human health risks associated with effluent wastewater containing pathogens, i.e., particularly concerning the case of sludge bulking.

A logistic model for the remediation of filamentous bulking in a biological nutrient removal wastewater treatment plant.

Biological nutrient removal (BNR) systems across the globe frequently experience bulking and foaming episodes, which present operational challenges such as poor sludge settling due to excessive filamentous bacteria. A full-scale BNR plant treating primarily domestic wastewater was monitored over a period of 1 year to investigate filamentous bacterial growth response under various plant operating parameters. Identification of filamentous bacteria by conventional microscopy and fluorescent in situ hybridisation indicated the dominance of Eikelboom Type021N, Thiothrix spp., Eikelboom Type 1851 and Eikelboom Type 0092. A cumulative logit model (CLM) was applied to elucidate significant relationships between the filamentous bacteria and plant operational parameters. The model could predict the potential abundance of dominant filamentous bacteria in relation to wastewater treatment plant operational parameters. Data obtained from the model corroborated with previous findings on the dominance of most filaments identified, except for Type 0092, which exhibited some unique traits. With further validation, the model could be successfully applied for identifying specific parameters which could contribute towards filamentous bulking, thus, providing a useful tool for regulating specific filamentous growth in full-scale wastewater treatment plants.