Design of SARS-CoV-2 Variant-Specific PCR Assays Considering Regional and Temporal Characteristics

Integration of Whole-Genome Sequencing with ddPCR Kit for Detection of Omicron Subvariants in Wastewater in the Upper Peninsula of Michigan

This study explores the integration of genome sequencing and digital droplet polymerase chain reaction (ddPCR)-based methods for tracking the diversity of COVID-19 variants in wastewater. The research focuses on monitoring various Omicron subvariants during a period of significant viral evolution. Genome sequencing, particularly using Oxford Nanopore Technology (ONT), provides a detailed view of emerging variants, surpassing the limitations of PCR-based detection kits that rely on known sequences. Of the 43 samples analyzed, 39.5% showed matching results between the GT Molecular ddPCR kits and sequencing, though only 4% were exact matches. Some mismatches occurred due to newer subvariants like XBB and BQ.1, which the ddPCR kits could not detect. This emphasized the limitations of ddPCR kits, which rely on known variant sequences, while sequencing provides real-time data on emerging variants, offering a more comprehensive view of circulating strains. This study highlights the effectiveness of combining these methodologies to enhance early detection and inform public health strategies, especially in regions with limited clinical sequencing capabilities.

Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater

An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.

Portable, single nucleotide polymorphism-specific duplex assay for virus surveillance in wastewater

The Argonaute protein from the archaeon Pyrococcus furiosus (PfAgo) is a DNA-guided nuclease that targets DNA with any sequence. We designed a virus detection assay in which the PfAgo enzyme cleaves the reporter probe, thus generating fluorescent signals when amplicons from a reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) assay contain target sequences. We confirmed that the RT-LAMP-PfAgo assay for the SARS-CoV-2 Delta variant produced significantly higher fluorescent signals (p < 0.001) when a single nucleotide polymorphism (SNP), exclusive to the Delta variant, was present, compared to the samples without the SNP. Additionally, the duplex assay for Pepper mild mottle virus (PMMOV) and SARS-CoV-2 detection produced specific fluorescent signals (FAM or ROX) only when the corresponding sequences were present. Furthermore, the RT-LAMP-PfAgo assay does not require dilution to reduce the impact of environmental inhibitors. The limit of detection of the PMMOV assay, determined with 30 wastewater samples, was 28 gc/μL, with a 95 % confidence interval of [11,103]. Finally, using a point-of-use device, the RT-LAMP-PfAgo assay successfully detected PMMOV in wastewater samples. Based on our findings, we conclude that the RT-LAMP-PfAgo assay can be used as a portable, SNP-specific duplex assay, which will significantly improve virus surveillance in wastewater.

CRISPR-Cas system: A promising tool for rapid detection of SARS-CoV-2 variants

COVID-19, caused by SARS-CoV-2, remains a global health crisis. The emergence of multiple variants with enhanced characteristics necessitates their detection and monitoring. Genome sequencing, the gold standard, faces implementation challenges due to complexity, cost, and limited throughput. The CRISPR-Cas system offers promising potential for rapid variant detection, with advantages such as speed, sensitivity, specificity, and programmability. This review provides an in-depth examination of the applications of CRISPR-Cas in mutation detection specifically for SARS-CoV-2. It begins by introducing SARS-CoV-2 and existing variant detection platforms. The principles of the CRISPR-Cas system are then clarified, followed by an exploration of three CRISPR-Cas-based mutation detection platforms, which are evaluated from different perspectives. The review discusses strategies for mutation site selection and the utilization of CRISPR-Cas, offering valuable insights for the development of mutation detection methods. Furthermore, a critical analysis of the clinical applications, advantages, disadvantages, challenges, and prospects of the CRISPR-Cas system is provided.

Improved performance of nucleic acid-based assays for genetically diverse norovirus surveillance

Nucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of their genetic diversity. Here, we calculated the variability of nucleotides within the genomes of 10 human viral species in silico and found that endemic viruses exhibit a high percentage of variable nucleotides (e.g., 51.4% for norovirus genogroup II). This genetic diversity led to the variable probability of detection of PCR assays (the proportion of viral sequences that contain the assay's target sequences divided by the total number of viral sequences). We then experimentally confirmed that the probability of the target sequence detection is indicative of the number of mismatches between PCR assays and norovirus genomes. Next, we developed a degenerate PCR assay that detects 97% of known norovirus genogroup II genome sequences and recognized norovirus in eight clinical samples. By contrast, previously developed assays with 31% and 16% probability of detection had 1.1 and 2.5 mismatches on average, respectively, which negatively impacted RNA quantification. In addition, the two PCR assays with a lower probability of detection also resulted in false negatives for wastewater-based epidemiology. Our findings suggest that the probability of detection serves as a simple metric for evaluating nucleic acid-based assays for genetically diverse virus surveillance.IMPORTANCENucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are employed widely as a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of the rapid evolution and genetic variation of viruses. The study analyzed clinical and wastewater samples using multiple PCR assays and found significant performance variation among the PCR assays for genetically diverse norovirus surveillance. This finding suggests that some PCR assays may miss detecting certain virus strains, leading to a compromise in detection sensitivity. To address this issue, we propose a metric called the probability of detection, which can be simply calculated in silico using a code developed in this study, to evaluate nucleic acid-based assays for genetically diverse virus surveillance. This new approach can help improve the sensitivity and accuracy of virus detection, which is crucial for effective infectious disease surveillance and control.

Outbreak report of SARS-CoV-2 infection by airborne transmission: Epidemiologic and molecular evidence

INTRODUCTION

It has been shown that the transmission of SARS-CoV-2 occurs mainly by air, and the risk of infection is greater in closed spaces.

OBJECTIVE

To describe the epidemiology, virology and molecular characterization of a COVID-19 outbreak at a closed vaccination point during the third wave of SARS-CoV-2 in Colombia.

MATERIALS AND METHODS

Diagnostic tests, interviews, sampling, cell cultures and viral sequencing were carried out, the latter being molecular characterization and lineage identification.

RESULTS

Seven workers were positive for SARS-CoV-2; among these, 3 samples were analyzed, plus an additional sample belonging to the mother of the presumed index case; all samples were identified with lineage B.1.625, with a maximum of 2 nucleotides difference between them.

CONCLUSIONS

Variant B.1.625 was identified as the cause of the COVID-19 outbreak, and a co-worker was also identified as the index case. Unexpectedly, attending a vaccination day became a risk factor for acquiring the infection.

Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America - Lessons from the past and a look to the future

Wastewater-based epidemiology (WBE) is an approach with the potential to complement clinical surveillance systems. Using WBE, it is possible to carry out an early warning of a possible outbreak, monitor spatial and temporal trends of infectious diseases, produce real-time results and generate representative epidemiological information in a territory, especially in areas of social vulnerability. Despite the historical uses of this approach, particularly in the Global Polio Eradication Initiative, and for other pathogens, it was during the COVID-19 pandemic that occurred an exponential increase in environmental surveillance programs for SARS-CoV-2 in wastewater, with many experiences and developments in the field of public health using data for decision making and prioritizing actions to control the pandemic. In Latin America, WBE was applied in heterogeneous contexts and with emphasis on populations that present many socio-environmental inequalities, a condition shared by all Latin American countries. This manuscript addresses the concepts and applications of WBE in public health actions, as well as different experiences in Latin American countries, and discusses a model to implement this surveillance system at the local or national level. We emphasize the need to implement this sentinel surveillance system in countries that want to detect the early entry and spread of new pathogens and monitor outbreaks or epidemics of infectious agents in their territories as a complement of public health surveillance systems.

Tracing COVID-19 Trails in Wastewater: A Systematic Review of SARS-CoV-2 Surveillance with Viral Variants

The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally.

Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations

Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.

Nucleic acid testing of SARS-CoV-2: A review of current methods, challenges, and prospects

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has brought a huge threat to public health and the global economy. Rapid identification and isolation of SARS-CoV-2-infected individuals are regarded as one of the most effective measures to control the pandemic. Because of its high sensitivity and specificity, nucleic acid testing has become the major method of SARS-CoV-2 detection. A deep understanding of different diagnosis methods for COVID-19 could help researchers make an optimal choice in detecting COVID-19 at different symptom stages. In this review, we summarize and evaluate the latest developments in current nucleic acid detection methods for SARS-CoV-2. In particular, we discuss biosensors and CRISPR-based diagnostic systems and their characteristics and challenges. Furthermore, the emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis are systematically introduced and discussed. Considering the disease dynamics, we also recommend optional diagnostic tests for different symptom stages. From sample preparation to results readout, we conclude by pointing out the pain points and future directions of COVID-19 detection.

Efficient Tracing of the SARS-CoV-2 Omicron Variants in Santa Barbara County Using a Rapid Quantitative Reverse Transcription PCR Assay

The emergence of the SARS-CoV-2 Omicron variant in 2021 is associated with a global surge of cases in late 2021 and early 2022. Identifying the introduction of novel SARS-CoV-2 variants to a population is imperative to inform decisions by clinicians and public health officials. Here, we describe a quantitative reverse transcription PCR-based assay (RT-qPCR) targeting unique mutations in the Omicron BA.1/BA1.1 and BA.2 viral genomes. This assay accurately and precisely detect the presence of these Omicron variants in patient samples in less than four hours. Using this assay, we tested 270 clinical samples and detected the introduction of Omicron BA.1/BA1.1 and BA.2 in the Santa Barbara County (SBC) population in December 2021 and February 2022, respectively. Identifying Omicron variants using this RT-qPCR assay showed complete concordance with whole viral genome sequencing; both assays indicated that Omicron was the dominant variant in SB County. Our data substantiate that RT-qPCR-based virus detection assays offer a fast and inexpensive alternative to NGS for virus variant-specific detection approach, which allows streamlining the detection of Omicron variants in patient samples.