Abstract

Rotavirus-induced viral gastroenteritis outbreaks result in over two million hospitalizations globally yearly. Wastewater-based epidemiology (WBE) has emerged as a crucial tool for detecting and monitoring viral outbreaks. The adoption of WBE has been instrumental in the early detection and surveillance of such viral outbreaks, providing a non-invasive method to assess public health. This study aims to utilize droplet digital polymerase chain reaction (ddPCR) technology to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India, thereby contributing to the understanding and management of viral gastroenteritis outbreaks through environmental surveillance. In this study, we used ddPCR to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India. We monitored its viral presence in municipal sewage treatment plants bi-weekly using an advanced ddPCR assay. Targeting the rotavirus non-structural protein 3 (NSP-3) region with custom primers and TaqMan probes, we detected virus concentration employing polyethylene glycol (PEG). Following RNA isolation, complementary DNA (cDNA) synthesis, and ddPCR analysis, our novel method eliminated standard curve dependence, propelling virus research and treatment forward. Out of the 42 samples collected, a 16.60% positivity rate was observed, indicating a moderate presence of Rotavirus in Bhopal. The wastewater treatment plants (WWTP) attached to a hospital exhibited a 42.85% positivity rate, indicating the need for targeted monitoring. Leveraging ddPCR, precise quantification of rotavirus concentrations (ranging from 0.75 to 28.9 copies/µL) facilitated understanding and supported effective remediation. This study emphasizes the importance of vigilant wastewater surveillance, especially in WWTPs with higher rotavirus prevalence. The significance of ddPCR in comparison to conventional and real-time PCR lies in its superior sensitivity and specificity in detecting and quantifying positive samples. Furthermore, it can identify positive samples even in the smallest quantities without the need for a standard curve to evaluate. This makes ddPCR a valuable tool for accurate and precise detection and quantification of samples.

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