Sunlight photolysis of SARS-CoV-2 N1 gene target in the water environment: considerations for the environmental surveillance of wastewater-impacted surface waters.
Fiona B DunnAndrea I SilvermanPublished in: Journal of water and health (2023)
Wastewater surveillance of SARS-CoV-2 has been used around the world to supplement clinical testing data for situational awareness of COVID-19 disease trends. Many regions of the world lack centralized wastewater collection and treatment infrastructure, which presents additional considerations for wastewater surveillance of SARS-CoV-2, including environmental decay of the RT-qPCR gene targets used for quantification of SARS-CoV-2 virions. Given the role of sunlight in the environmental decay of RNA, we evaluated sunlight photolysis kinetics of the N1 gene target in heat-inactivated SARS-CoV-2 with a solar simulator under laboratory conditions. Insignificant photolysis of the N1 target was observed in a photosensitizer-free matrix. Conversely, significant decay of the N1 target was observed in wastewater at a shallow depth (<1 cm). Given that sunlight irradiance is affected by several environmental factors, first-order decay rate models were used to evaluate the effect of water column depth, time of the year, and latitude on decay kinetics. Decay rate constants were found to decrease significantly with greater depth of the well-mixed water column, at high latitudes, and in the winter. Therefore, sunlight-mediated decay of the N1 gene target is likely to be minimal, and is unlikely to confound results from wastewater-based epidemiology programs utilizing wastewater-impacted surface waters.
Keyphrases
- sars cov
- wastewater treatment
- respiratory syndrome coronavirus
- anaerobic digestion
- public health
- copy number
- genome wide
- genome wide identification
- optical coherence tomography
- photodynamic therapy
- human health
- transcription factor
- liquid chromatography
- electronic health record
- big data
- mass spectrometry
- machine learning
- risk assessment
- dna methylation
- high resolution
- artificial intelligence