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Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant's inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis.

Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant’s inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis.

As of November 2021, the SARS-CoV-2 Omicron variant had made its appearance, gradually replacing the predominant Delta variant. Since its emergence, the Omicron variant has been continuously evolving through more than 500 strains, most of which belong to five sub-variants known as BA.1, BA.2, BA.3, BA.4, and BA.5. The aim of this study was to develop a multiplex polymerase chain reaction (PCR) that will be able to distinguish the basic sub-variants of Omicron in a rapid and specific way. Full genome sequences of Omicron strains with high frequency and wide geographical distribution were retrieved by the NCBI Virus and ENA databases. These sequences were compared to each other in order to locate single nucleotide polymorphisms common to all strains of the same sub-variant. These polymorphisms should also be capable of distinguishing Omicron sub-variants not only from each other but from previously circulating variants of SARS-CoV-2 as well. Thus, specific primers targeting characteristic polymorphisms of the four Omicron main branches BA.1, BA.2, BA.4, and BA.5 were designed according to the principles of the amplification refractory mutation system (ARMS) and with the ability to react under multiplex PCR conditions. According to our results, the ARMS-multiplex PCR could successfully distinguish all Omicron sub-variants that carry the corresponding mutations.

Several SARS-CoV-2 variants have emerged and early detection for monitoring their prevalence is crucial. Many identification strategies have been implemented in cases where sequencing data for confirmation is pending or not available. The presence of B.1.1.318 among prevalent variants was indicated by an unusual amplification pattern in various RT-qPCR commercial assays. Positive samples for SARS-CoV-2, as determined using the Allplex SARS-CoV-2 Assay, the Viasure SARS-CoV-2 Real Time Detection Kit and the GeneFinder COVID-19 Plus RealAmp Kit, presented a delay or failure in the amplification of the N gene, which was further investigated. Whole-genome sequencing was used for variant characterization. The differences between the mean Ct values for amplification of the N gene vs. other genes were calculated for each detection system and found to be at least 14 cycles. Sequencing by WGS revealed that all the N gene dropout samples contained the B.1.1.318 variant. All the isolates harbored three non-synonymous mutations in the N gene, which resulted in four amino acid changes (R203K, G204R, A208G, Met234I). Although caution should be taken when the identification of SARS-CoV-2 variants is based on viral gene amplification failure, such patterns could serve as a basis for rapid and cost-effective screening, functioning as indicators of community circulation of specific variants, requiring subsequent verification via sequencing.