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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.

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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.