Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates.

Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.

Detection of SARS-CoV-2 in clinical and environmental samples using highly sensitive reduced graphene oxide (rGO)-based biosensor.

Quantitative RT-PCR (qRT-PCR) is the most commonly used diagnostic tool for SARS-CoV-2 detection during the COVID-19 pandemic. Despite its sensitivity and accuracy, qRT-PCR is a time-consuming method that requires expensive laboratories with highly trained personnel. In this work, on-site detection of SARS-CoV-2 in municipal wastewater was investigated for the first time. The wastewater was unprocessed and did not require any prefiltration, prior spiking with virus, or viral concentration in order to be suitable for use with the biosensor. The prototype reported here is a reduced graphene oxide (rGO)-based biosensor for rapid, sensitive and selective detection of SARS-CoV-2. The biosensor achieved a limit of detection (LOD) of 0.5 fg/mL in phosphate-buffered saline (PBS) and exhibited specificity when exposed to various analytes. The response time was measured to be around 240 ms. To further explore the capabilities of the biosensor in real clinical and municipal wastewater samples, three different tests were performed to determine the presence or absence of the virus: (i) qRT-PCR, (ii) a rapid antigen-based commercially available test (COVID-19 Test Strips), and (iii) the biosensor constructed and reported here. Taken together, our results demonstrate that a biosensor that can detect SARS-CoV-2 in clinical samples as well as unfiltered and unprocessed municipal wastewater is feasible.

Optimization of an rGO-based biosensor for the sensitive detection of bovine serum albumin: Effect of electric field on detection capability.

Despite significant progress in the field of biosensing, the impact of electric field on biosensor detection capability and the feasibility of the biosensor application in wastewater has yet to be investigated. The objective of this study was to develop a low-cost, highly sensitive, and selective reduced graphene oxide (rGO)-based biosensor. The constructed biosensor consists of an in-house prepared GO and a four-terminal Kelvin sensing. Spin-coating was chosen as the deposition technique and results revealed an optimal GO number of layers and concentration of 7 and 2 mg/mL, respectively. Experiments to determine the effects of electric field on the performance of the biosensor showed significant changes in the biosensor surface, also presenting a direct impact on the biosensor functionality, such that the biosensor showed an increase in limit of detection (LOD) from 1 to 106 fg/mL when the applied voltage was increased from 0.0008 to 0.2 V. Furthermore, this study successfully explores a pilot scale setup, mimicking wastewater flow through sewage pipelines. The demonstrated improvements in the detection capability and sensitivity of this biosensor at optimized testing conditions make it a promising candidate for further development and deployment for the detection of protein analytes present at very low concentrations in aqueous solutions. In addition, the application of this biosensor could be extended to the detection of protein analytes of interest (such as the spike protein of SARS-CoV-2) in much more complex solutions, like wastewater.

Recent advances in the biosensors application for the detection of bacteria and viruses in wastewater.

The presence of disease-causing pathogens in wastewater can provide an excellent diagnostic tool for infectious diseases. Biosensors are far superior to conventional methods used for regular infection screening and surveillance testing. They are rapid, sensitive, inexpensive portable and carry no risk of exposure in their detection schemes. In this context, this review summarizes the most recently developed biosensors for the detection of bacteria and viruses in wastewater. The review also provides information on the new detection methods aimed at screening for SARS-CoV-2, which has now caused more than 4 million deaths. In addition, the review highlights the potential behind on-line and real-time detection of pathogens in wastewater pipelines. Most of the biosensors reported were not targeted to wastewater samples due to the complexity of the matrix. However, this review highlights on the performance factors of recently developed biosensors and discusses the importance of nanotechnology in amplifying the output signals, which in turn increases the accuracy and reliability of biosensors. Current research on the applicability of biosensors in wastewater promises a dramatic change to the conventional approach in the field of medical screening.