Assessing the potential for nevirapine removal and its ecotoxicological effects on Coelastrella tenuitheca and Tetradesmus obliquus in aqueous environment.

Remediation of the antiretroviral (ARV) drug, nevirapine (NVP) has attracted considerable scientific attention in recent years due to its frequent detection and persistence in aquatic environments and potential hazards to living organisms. Algae-based technologies have been emerging as an environmentally friendly option for the removal of pharmaceutical compounds, but their ARV drug removal potential has not been fully explored yet. This study aimed to explore the ecotoxicity and removal potential of NVP by two microalgal species, Coelastrella tenuitheca and Tetradesmus obliquus. Lower environmental concentrations (up to 200 ng L-1) of NVP enhanced the microalgal growth, and the highest dry cell weight of 941.27 mg L-1 was obtained in T. obliquus at 50 ng L-1 NVP concentration. Both microalgae showed varying removal efficiencies (19.53-74.56%) when exposed to NVP concentration levels of up to 4000 ng L-1. At the late log phase (day 8), T. obliquus removed the highest percentage of NVP (74.56%), while C. tenuitheca removed 48% at an initial NVP concentration of 50 ng L-1. Photosynthetic efficiency (Fv/Fm and rETR) of the two microalgal species, however, was not affected by environmental concentrations of NVP (up to 4000 ng L-1) at the mid log phase of growth. SEM analysis demonstrated that both algal species produced distinct ridges on their cell surfaces after NVP uptake. In the ecotoxicity study, the calculated IC50 values of NVP (0-100 mg L-1) after 96 h of exposure were 23.45 mg L-1 (C. tenuitheca) and 18.20 mg L-1 (T. obliquus). The findings of the present study may contribute to a better understanding of the environmental hazards associated with NVP and the efficacy of microalgae in removing this pharmaceutical from aquatic environments.

Effect of selected wastewater characteristics on estimation of SARS-CoV-2 viral load in wastewater.

Wastewater-based epidemiology has been used as a tool for surveillance of COVID-19 infections. This approach is dependent on the detection and quantification of SARS-CoV-2 RNA in untreated/raw wastewater. However, the quantification of the viral RNA could be influenced by the physico-chemical properties of the wastewater. This study presents the first use of Adaptive Neuro-Fuzzy Inference System (ANFIS) to determine the potential impact of physico-chemical characteristics of wastewater on the detection and concentration of SARS-CoV-2 RNA in wastewater. Raw wastewater samples from four wastewater treatment plants were investigated over four months. The physico-chemical characteristics of the raw wastewater was recorded, and the SARS-CoV-2 RNA concentration determined via amplification with droplet digital polymerase chain reaction. The wastewater characteristics considered were chemical oxygen demand, flow rate, ammonia, pH, permanganate value, and total solids. The mean SARS-CoV-2 RNA concentrations ranged from 648.1(±514.6) copies/mL to 1441.0(±1977.8) copies/mL. Among the parameters assessed using the ANFIS model, ammonia and pH showed significant association with the concentration of SARS-CoV-2 RNA measured. Increasing ammonia concentration was associated with increasing viral RNA concentration and pH between 7.1 and 7.4 were associated with the highest SARS-CoV-2 concentration. Other parameters, such as total solids, were also observed to influence the viral RNA concentration, however, this observation was not consistent across all the wastewater treatment plants. The results from this study indicate the importance of incorporating wastewater characteristic assessment into wastewater-based epidemiology for a robust and accurate COVID-19 surveillance.

Valorization of poultry litter using Acutodesmus obliquus and its integrated application for lipids and fertilizer production.

Microalgae are recognized as potential candidates for resource recovery from wastewater and projected for biorefinery models. This study was undertaken to evaluate the potential of poultry litter and municipal wastewater as nutrient and water sources, for the cultivation of Acutodesmus obliquus for lipids production for biodiesel application. The efficacy of lipid extracted biomass (LEA) as fertilizer for mung bean crops was also assessed in microcosm. A. obliquus cultivation in acid pre-treated poultry litter extract (PPLE) showed maximum biomass production of 1.90 g L-1, which was 74.67% and 12.61% higher than the raw poultry litter extract (RPPE) and BG11 respectively. Higher NO3-N, NH3-N, and PO4-P removal of 79.51%, 81.82%, and 80.52% respectively were observed in PPLE as compared to RPLE treatment. The highest biomass (140.36 mg L-1 d-1), lipids (38.49 mg L-1 d-1), and carbohydrates (49.55 mg L-1 d-1) productivities were observed in the PPLE medium. The application of LEA as a fertilizer for mung bean crops showed improvement in plant growth and soil microbial activity. A maximum increase in organic carbon (59.5%) and dehydrogenase activity (130.8%) was observed in LEA amended soil which was significantly higher than chemical fertilizer (CF) control in 30 days. Whilst plant fresh weight and leaf chlorophyll in the LEA amended soil was comparable to whole algal biomass (WA) and CF control. The strategy developed could be a basis for sustainable biorefinery for the valorization of wastewater for the production of microalgae-derived biofuel and byproducts for agricultural application.

Detection of SARS-CoV-2 RNA on contact surfaces within shared sanitation facilities.

Contamination of contact surfaces with SARS-CoV-2 has been reported as a potential route for the transmission of COVID-19. This could be a major issue in developing countries where access to basic sanitation is poor, leading to the sharing of toilet facilities. In this study, we report SARS-CoV-2 contamination of key contact surfaces in shared toilets and the probabilistic risks of COVID-19 infections based on detection and quantification of the nucleic acid on the surfaces. We observed that 54-69% of the contact surfaces were contaminated, with SARS-CoV-2 loads ranging from 28.1 to 132.7 gene copies per cm2. Toilet seats had the highest contamination, which could be attributed to shedding of the virus in feces and urine. We observed a significant reduction in viral loads on the contaminated surfaces after cleaning, showing the potential of effective cleaning on the reduction of contamination. The pattern of contamination indicates that the most contaminated surfaces are those that are either commonly touched by users of the shared toilets or easily contaminated with feces and urine. These surfaces were the toilet seats, cistern handles and tap handles. The likelihood (probability) of infection with COVID-19 on these surfaces was highest on the toilet seat (1.76 × 10-4(1.58 × 10-6)) for one time use of the toilet. These findings highlight the potential risks for COVID-19 infections in the event that intact infectious viral particles are deposited on these contact surfaces. Therefore, this study shows that shared toilet facilities in densely populated areas could lead to an increase in risks of COVID-19 infections. This calls for the implementation of risk reduction measures, such as regular washing of hands with soap, strict adherence to wearing face masks, and effective and regular cleaning of shared facilities.

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.

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.