ABSTRACT
The development of sensitive and affordable testing devices for infectious diseases is essential to preserve public health, especially in pandemic scenarios. In this work, we have developed an attractive analytical method to monitor products of genetic amplification, particularly the loop-mediated isothermal amplification reaction (RT-LAMP). The method is based on electrochemical impedance measurements and the distribution of relaxation times model, to provide the so-called time-constant-domain spectroscopy (TCDS). The proposed method is tested for the SARS-CoV-2 genome, since it has been of worldwide interest due to the COVID-19 pandemic. Particularly, once the method is calibrated, its performance is demonstrated using real wastewater samples. Moreover, we propose a simple classification algorithm based on TCDS data to discriminate among positive and negative samples. Results show how a TCDS-based method provides an alternative mechanism for label-free and automated assays, exhibiting robustness and specificity for genetic detection.
ABSTRACT
The study aims to determine SARS-CoV-2 RNA in sewage of Cancun wastewater treatment plants, the main touristic destination of Mexico, and to estimate the infected persons during the sampling period. SARS-CoV-2 RNA traces were detected in the inlet of the five plants during almost all the sampling months. However, there is no presence of SARS-CoV-2 RNA traces in the effluent of the five WWTPs during the study period. ANOVA analysis showed differences in the concentrations of RNA traces of SARS-CoV-2 between the sample dates, but no differences were found from one WWTP to another. Estimated infected individuals by Markov chain Monte Carlo simulation are higher (between 77% and 91%) than the cases reported by the health authority. Wastewater monitoring and the estimation of infected individuals are a helpful tool, because estimation provides early warning signs on how broadly SARS-CoV-2 is circulating in the city, and led to the authorities to take measures wisely. PRACTITIONER POINTS: There is no presence of SARS-CoV-2 RNA traces in the effluent of the facilities, suggesting the effectiveness of treatment. Surveillance of viral RNA concentrations at treatment plants revealed presence in the influent of five plants Estimated infected individuals by MCMC simulation are higher than cases reported by health authority Environmental surveillance approach in wastewater influent is helpful to identify the clusters and to take informed decisions.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , Wastewater , RNA, Viral/genetics , Mexico , Caribbean RegionABSTRACT
The current pandemic COVID-19 caused by the coronavirus SARS-CoV-2, has generated different economic, social and public health problems. Moreover, wastewater-based epidemiology could be a predictor of the virus rate of spread to alert on new outbreaks. To assist in epidemiological surveillance, this work introduces a simple, low-cost and affordable electrochemical sensor to specifically detect N and ORF1ab genes of the SARS-CoV-2 genome. The proposed sensor works based on screen-printed electrodes acting as a disposable test strip, where the reverse transcription loop-mediated isothermal amplification (RT-LAMP) reaction takes place. Electrochemical detection relies upon methylene blue as a redox intercalator probe, to provide a diffusion-controlled current encoding the presence and concentration of RT-LAMP products, namely amplicons or double-stranded DNA. We test the performance of the sensor by testing real wastewater samples using end-point and time course measurements. Results show the ability of the electrochemical test strip to specifically detect and quantify RT-LAMP amplicons below to ~ 2.5 × 10-6 ng/µL exhibiting high reproducibility. In this sense, our RT-LAMP electrochemical sensor is an attractive, efficient and powerful tool for rapid and reliable wastewater-based epidemiology studies.
ABSTRACT
The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has proven the need for developing reliable and affordable technologies to detect pathogens. Particularly, the detecting the genome in wastewater could be an indicator of the transmission rate to alert on new outbreaks. However, wastewater-based epidemiology remains a technological challenge to develop affordable technologies for sensing pathogens. In this work, we introduce a label-free and portable field-effect transistor (FET)-based sensor to detect N and ORF1ab genes of the SARS-CoV-2 genome. Our sensor integrates the reverse transcription loop-mediated isothermal amplification (RT-LAMP) reaction as a cost-effective molecular detection exhibiting high specificity. The detection relies upon pH changes, due to the RT-LAMP reaction products, which are detected through a simple, but effective, extended-gate FET sensor (EGFET). We evaluate the proposed device by measuring real wastewater samples to detect the presence of SARS-CoV-2 genome, achieving a limit of detection of 0.31 × 10−3 ng/ μ L for end-point measurement. Moreover, we find the ability of the sensor to perform real-time-like analysis, showing that the RT-LAMP reaction provides a good response after 15 min for concentrations as low as 0.37 ng/ μ L. Hence, we show that our EGFET sensor offers a powerful tool to detect the presence of the SARS-CoV-2 genome with a naked-eye method, in a straightforward way than the conventional molecular methods for wastewater analysis. [Display omitted] • Label-free extended-gate field-effect transistor sensor for detect SARS-CoV-2 genome. • Portable and reliable sensing based on isothermal amplification reaction. • Detection and quantification of nucleic-acids in real wastewater samples. • End-pint and time course detection of RT-LAMP products. • The wastewater-based epidemiology can use this method in limited-resource conditions. [ FROM AUTHOR]
ABSTRACT
The biotransformation of the SARS-CoV-2 antiviral drugs, ribavirin and tenofovir, was studied in methanogenic bioreactors. The role of iron-rich minerals, recovered from a metallurgic effluent, on the biotransformation process was also assessed. Enrichment of anaerobic sludge with recovered minerals promoted superior removal efficiency for both antivirals (97.4 % and 94.7 % for ribavirin and tenofovir, respectively) as compared to the control bioreactor lacking minerals, which achieved 58.5 % and 37.9 % removal for the same drugs, respectively. Further analysis conducted by liquid chromatography coupled to mass spectroscopy revealed several metabolites derived from the biotransformation of both antivirals. Interestingly, tracer analysis with 13CH4 revealed that anaerobic methane oxidation coupled to Fe(III) reduction occurred in the enriched bioreactor, which was reflected in a lower content of methane in the biogas produced from this system, as compared to the control bioreactor. This treatment proposal is suitable within the circular economy concept, in which recovered metals from an industrial wastewater are applied in bioreactors to create a biocatalyst for promoting the biotransformation of emerging pollutants. This strategy may be appropriate for the anaerobic treatment of wastewaters originated from hospitals, as well as from the pharmaceutical and chemical sectors.
ABSTRACT
The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has proven the need for developing reliable and affordable technologies to detect pathogens. Particularly, the detecting the genome in wastewater could be an indicator of the transmission rate to alert on new outbreaks. However, wastewater-based epidemiology remains a technological challenge to develop affordable technologies for sensing pathogens. In this work, we introduce a label-free and portable field-effect transistor (FET)-based sensor to detect N and ORF1ab genes of the SARS-CoV-2 genome. Our sensor integrates the reverse transcription loop-mediated isothermal amplification (RT-LAMP) reaction as a cost-effective molecular detection exhibiting high specificity. The detection relies upon pH changes, due to the RT-LAMP reaction products, which are detected through a simple, but effective, extended-gate FET sensor (EGFET). We evaluate the proposed device by measuring real wastewater samples to detect the presence of SARS-CoV-2 genome, achieving a limit of detection of 0.31 × 10−3 ng/μL for end-point measurement. Moreover, we find the ability of the sensor to perform real-time-like analysis, showing that the RT-LAMP reaction pro-vides a good response after 15 min for concentrations as low as 0.37 ng/μL. Hence, we show that our EGFET sensor offers a powerful tool to detect the presence of the SARS- CoV-2 genome with a naked-eye method, in a straightforward way than the conventional molecular methods for wastewater analysis.
ABSTRACT
The SARS-CoV-2 virus causing COVID-19 is spread in sewage by the stool of infected individuals, and viral material in sewage can be quantified using molecular tools. This study aimed to monitor the presence of SARS-CoV-2 RNA in sewage in Mexico based on RdRP, S, and N gene analysis. The influent, effluent, and activated sludge from two domestic wastewater treatment plants (WWTP) were evaluated from the early stage of the epidemic to July 2020. Additionally, sampling points in sewer systems were examined, comparing two different RNA-concentration methods: centrifugal ultrafiltration and adsorption-based methods. The adsorption method resulted in RNA titration that was two orders of magnitude higher than with ultrafiltration (up to 3.38 log10 copies RdRP gene/mL of sewage). The surveillance of SARS-CoV-2 RNA in the influent of two WWTP correlated with the cumulative COVID-19 cases in Queretaro city. The higher RNA level in secondary sludge compared to influent suggests that viral RNA becomes concentrated in activated sludge. This result supports SARS-CoV-2 RNA removal in WWTP, where all effluent samples were negative for virus quantification. This work proves that wastewater-based epidemiology is a very valuable tool in developing countries where diagnostic tests for COVID-19 are limited.