Globally, the emergence of the coronavirus disease (COVID-19) has had a significant impact on life. The need for ongoing SARS-CoV-2 screening employing inexpensive and quick diagnostic approaches is undeniable, given the ongoing pandemic and variations in vaccine administration in resource-constrained regions. This study presents results as proof of concept to use hybridization chain reaction (HCR) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a complex for detecting SARS-CoV-2. HCR hairpin probes were designed using the NUPACK web-based program and further used to amplify the SARS-CoV-2 N gene in archived nasopharyngeal samples. The results were visualized using agarose gels and CRISPR Cas12a-based lateral flow strips. The assay was evaluated using the gold standard, real-time polymerase chain reaction (RT-PCR), as recommended by the World Health Organization (WHO). The results show the comparative efficiency of HCR to RT-PCR. This study shows that HCR and CRISPR are viable alternatives for diagnosing SARS-CoV-2 in samples.

Objective: This study analyzed the metatranscriptome of wastewater samples from different sites with a focus of identifying antibiotic resistance genes and the bacterial community. Methods: Twenty-four wastewater samples were collected from a hospital, university sewer, and the influent and effluent of a wastewater treatment plant (WWTP). The metatranscriptome was sequenced to identify antimicrobial resistance genes (ARGs), mobile genetic elements, and bacterial community composition. Results: Metatranscriptome analysis revealed varying abundances of ARG transcripts across different sites, with 84, 27, 14, and 9 ARG transcripts identified in wastewater collected from the hospital, university, influent, and effluent of a WWTP, respectively. Notably, hospital wastewater contained clinically relevant beta-lactam ARGs, including bla-NDM-1 and several blaOXA transcripts. Four core ARGs, against sulfonamides sul1 and sul2 and aminoglycosides aph(6)-ld and aph(’3’)-lb were also identified. The predominant bacterial community comprised of Gammaproteobacteria, with priority pathogens like Neisseria gonorrhea and Helicobacter pylori present in hospital wastewater and WWTP influent. Conclusion: These findings provide insights into the wastewater resistome and how meta-transcriptomic data can be utilized for the surveillance of antibiotic resistance. Overall, our study highlights the utility of wastewater surveillance in understanding and addressing the dissemination of antibiotic resistance and emphasizes the crucial role of proper wastewater management in protecting public and environmental health.