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.

Analysis of SARS-CoV-2 viral loads in stool samples and nasopharyngeal swabs from COVID-19 patients in the United Arab Emirates.

Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25% tested negative in both sample types at the time of this study and 53% of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients.

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.

Gut Microbiota Interplay With COVID-19 Reveals Links to Host Lipid Metabolism Among Middle Eastern Populations.

The interplay between the compositional changes in the gastrointestinal microbiome, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility and severity, and host functions is complex and yet to be fully understood. This study performed 16S rRNA gene-based microbial profiling of 143 subjects. We observed structural and compositional alterations in the gut microbiota of the SARS-CoV-2-infected group in comparison to non-infected controls. The gut microbiota composition of the SARS-CoV-2-infected individuals showed an increase in anti-inflammatory bacteria such as Faecalibacterium (p-value = 1.72 × 10-6) and Bacteroides (p-value = 5.67 × 10-8). We also revealed a higher relative abundance of the highly beneficial butyrate producers such as Anaerostipes (p-value = 1.75 × 10-230), Lachnospiraceae (p-value = 7.14 × 10-65), and Blautia (p-value = 9.22 × 10-18) in the SARS-CoV-2-infected group in comparison to the control group. Moreover, phylogenetic investigation of communities by reconstructing unobserved state (PICRUSt) functional prediction analysis of the 16S rRNA gene abundance data showed substantial differences in the enrichment of metabolic pathways such as lipid, amino acid, carbohydrate, and xenobiotic metabolism, in comparison between both groups. We discovered an enrichment of linoleic acid, ether lipid, glycerolipid, and glycerophospholipid metabolism in the SARS-CoV-2-infected group, suggesting a link to SARS-CoV-2 entry and replication in host cells. We estimate the major contributing genera to the four pathways to be Parabacteroides, Streptococcus, Dorea, and Blautia, respectively. The identified differences provide a new insight to enrich our understanding of SARS-CoV-2-related changes in gut microbiota, their metabolic capabilities, and potential screening biomarkers linked to COVID-19 disease severity.

Detection and quantification of SARS-CoV-2 RNA in wastewater and treated effluents: Surveillance of COVID-19 epidemic in the United Arab Emirates.

Testing SARS-CoV-2 viral loads in wastewater has recently emerged as a method of tracking the prevalence of the virus and an early-warning tool for predicting outbreaks in the future. This study reports SARS-CoV-2 viral load in wastewater influents and treated effluents of 11 wastewater treatment plants (WWTPs), as well as untreated wastewater from 38 various locations, in the United Arab Emirates (UAE) in May and June 2020. Composite samples collected over twenty-four hours were thermally deactivated for safety, followed by viral concentration using ultrafiltration, RNA extraction using commercially available kits, and viral quantification using RT-qPCR. Furthermore, estimates of the prevalence of SARS-CoV-2 infection in different regions were simulated using Monte Carlo. Results showed that the viral load in wastewater influents from these WWTPs ranged from 7.50E+02 to over 3.40E+04 viral gene copies/L with some plants having no detectable viral RNA by RT-qPCR. The virus was also detected in 85% of untreated wastewater samples taken from different locations across the country, with viral loads in positive samples ranging between 2.86E+02 and over 2.90E+04 gene copies/L. It was also observed that the precautionary measures implemented by the UAE government correlated with a drop in the measured viral load in wastewater samples, which were in line with the reduction of COVID-19 cases reported in the population. Importantly, none of the 11 WWTPs' effluents tested positive during the entire sampling period, indicating that the treatment technologies used in the UAE are efficient in degrading SARS-CoV-2, and confirming the safety of treated re-used water in the country. SARS-CoV-2 wastewater testing has the potential to aid in monitoring or predicting an outbreak location and can shed light on the extent viral spread at the community level.