Detection of SARS-CoV-2 variants by genomic analysis of wastewater samples in Israel.
Ontology highlight
ABSTRACT:
SUBMITTER: Bar-Or I
PROVIDER: S-EPMC8142738 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.
| S-EPMC9352586 | biostudies-literature
Project description:The recent COVID-19 pandemic overwhelmed the health system worldwide, and there was a need to track outbreaks and try to use this information as an early warning system. Wastewater-based epidemiology (WBE) enabled detection of the SARS-CoV-2 virus in wastewater treatment plant influents. Until now, the most used technique for this detection has been the quantitative polymerase chain reaction (qPCR)-based quantification of SARS-CoV-2 RNA. This study proposes a mass spectrometry (MS)-based method that detected specific SARS-CoV-2 proteins in wastewater, 5 and 6 days ahead of the case data for two municipalities. We identified unique peptides of eight proteins related to the SARS-CoV-2 virus and COVID-19 infection. We detected the nonstructural protein (NSP) pp1ab (transcribed after host cell infection) most frequently in all of the samples. As a result, we suspect that in the active cases of COVID-19, the pp1ab protein is present in high abundance in the urine and feces and that this protein could be used as an alternative biomarker. These data were collected before mass vaccination occurred in the population.
| S-EPMC8982736 | biostudies-literature
Project description:Clinical and surveillance testing for the SARS-CoV-2 virus relies overwhelmingly on RT-qPCR-based diagnostics, yet several popular assays require 2-3 separate reactions or rely on detection of a single viral target, which adds significant time, cost, and risk of false-negative results. Furthermore, multiplexed RT-qPCR tests that detect at least two SARS-CoV-2 genes in a single reaction are typically not affordable for large scale clinical surveillance or adaptable to multiple PCR machines and plate layouts. We developed a RT-qPCR assay using the Luna Probe Universal One-Step RT-qPCR master mix with publicly available primers and probes to detect SARS-CoV-2 N gene, E gene, and human RNase P (LuNER) to address these shortcomings and meet the testing demands of a university campus and the local community. This cost-effective test is compatible with BioRad or Applied Biosystems qPCR machines, in 96 and 384-well formats, with or without sample pooling, and has a detection sensitivity suitable for both clinical reporting and wastewater surveillance efforts.
| S-EPMC8580221 | biostudies-literature
Project description:In this report, we describe a national-scale monitoring of the SARS-CoV-2 (SC-2) variant dynamics in Israel, using multiple-time sampling of 13 wastewater treatment plants. We used a combination of inclusive and selective quantitative PCR assays that specifically identify variants A19/A20 or B.1.1.7 and tested each sample for the presence and relative viral RNA load of each variant. We show that between December 2020 and March 2021, a complete shift in the SC-2 variant circulation was observed, where the B.1.1.7 replaced the A19 in all examined test points. We further show that the normalized viral load (NVL) values and the average new cases per week reached a peak in January 2021 and then decreased gradually in almost all test points, in parallel with the progression of the national vaccination campaign, during February-March 2021. This study demonstrates the importance of monitoring SC-2 variant by using a combination of inclusive and selective PCR tests on a national scale through wastewater sampling, which is far more amendable for high-throughput monitoring compared with sequencing. This approach may be useful for real-time dynamics surveillance of current and future variants, such as the Omicron (BA.1, BA.2) and other variants.
| S-EPMC9227326 | biostudies-literature
Project description:On March 12, 2020, the World Health Organization (WHO) declared COVID-19 as a global pandemic. COVID-19 is produced by a novel β-coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) [1]. Several studies have detected SARS-CoV-2 RNA in urine, feces, and other biofluids from both symptomatic and asymptomatic people with COVID-19 [2], suggesting that SARS-CoV-2 RNA could be detected in human wastewater [3]. Thus, wastewater-based epidemiology (WBE) is now used as an approach to monitor COVID-19 prevalence in many different places around the world [4-10] . Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is the most common SARS-CoV-2 detection method in WBE, but there are other methods for viral biomolecule detection that could work as well. The aim of this study was to evaluate the presence of SARS-CoV-2 proteins in untreated wastewater (WW) influents collected from six wastewater treatment plants (WWTPs), from Durham Region, Ontario, Canada, using a LC-MS/MS-based proteomics approach. We identified many SARS-CoV-2 proteins in these wastewater samples, with peptides from pp1ab being the most consistently detected and with consistent abundance.
2022-03-31 | PXD026412 | Pride
Project description:In the Fall of 2020, university campuses in the United States resumed on-campus instruction and implemented wastewater monitoring for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While quantitative polymerase chain reaction (qPCR) tests were deployed successfully to detect viral RNA in wastewater across campuses, the feasibility of detecting viral variants from a residential building like a dormitory was unclear. Here, we demonstrate that wastewater surveillance from a dormitory with at least three infected students could lead to the identification of viral genomes with more than 95% coverage. Our results indicate that viral variant detection from wastewater is achievable at a dormitory and that coronavirus disease 2019 (COVID-19) wastewater surveillance programs will benefit from the implementation of viral whole genome sequencing at universities.
| S-EPMC8421076 | biostudies-literature
Project description:The monitoring of SARS-CoV-2 RNA in sewage has been proposed as a simple and unbiased means of assessing epidemic evolution and the efficiency of the COVID-19 control measures. The past year has been marked by the emergence of variants that have led to a succession of epidemic waves. It thus appears that monitoring the presence of SARS-CoV-2 in wastewater alone is insufficient, and it may be important in the future to also monitor the evolution of these variants. We used a real-time RT-PCR screening test for variants in the wastewater of our city to assess the effectiveness of direct SARS-CoV-2 sequencing from the same wastewater. We compared the genome sequencing results obtained over the large RS network and the smaller B7 network with the different distributions of the variants observed by RT-PCR screening. The prevalence of the "UK variant" in the RS and B7 networks was estimated to be 70% and 8% using RT-PCR screening compared to 95% and 64% using genome sequencing, respectively. The latter values were close to the epidemiology observed in patients of the corresponding area, which were 91% and 58%, respectively. Genome sequencing in sewage identified SARS-CoV-2 of lineage B.1.525 in B7 at 27% (37% in patients), whereas it was completely missed by RT-PCR. We thus determined that direct sequencing makes it possible to observe, in wastewater, a distribution of the variants comparable to that revealed by genomic monitoring in patients and that this method is more accurate than RT-PCR. It also shows that, rather than a single large sample, it would be preferable to analyse several targeted samples if we want to more appropriately assess the geographical distribution of the different variants. In conclusion, this work supports the wider surveillance of SARS-CoV-2 variants in wastewater by genome sequencing and targeting small areas on the condition of having a sequencing capacity and, when this is not the case, to developing more precise screening tests based on the multiplexed detection of the mutations of interest.
| S-EPMC8401729 | biostudies-literature
Project description:ImportanceGenomic footprints of pathogens shed by infected individuals can be traced in environmental samples. Analysis of these samples can be employed for noninvasive surveillance of infectious diseases.ObjectiveTo evaluate the efficacy of environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for predicting COVID-19 cases in a college dormitory.DesignUsing a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory from March to May 2021. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases.SettingThis study was conducted in a residential dormitory at the University of Miami, Coral Gables campus, FL, USA. The dormitory housed about 500 students.ParticipantsStudents from the dormitory were randomly screened, for COVID-19 for 2-3 days / week while entering or exiting the dormitory.Main outcomeClinically diagnosed COVID-19 cases were of our main interest. We hypothesized that SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases in the dormitory, and SARS-CoV-2 can be detected in the environmental samples several days prior to the clinical diagnosis of COVID-19 cases.ResultsSARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively.ConclusionProactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks.Key pointsQuestion: How effective is environmental surveillance of SARS-CoV-2 in public places for early detection of COVID-19 cases in a community?Findings: All clinically confirmed COVID-19 cases were predicted with the aid of 2 day lagged SARS-CoV-2 in environmental samples in a college dormitory. However, the prediction efficiency varied by sample type: best prediction by air samples, followed by wastewater and surface swab samples. SARS-CoV-2 was also detected in these samples even on days without any reported cases of COVID-19, suggesting underreporting of COVID-19 cases.Meaning: SARS-CoV-2 can be detected in environmental samples several days prior to clinical reporting of COVID-19 cases. Thus, proactive environmental surveillance of microbiome in public places can serve as a mean for early detection of location-time specific outbreaks of infectious diseases. It can also be used for underreporting of infectious diseases.
| S-EPMC8936103 | biostudies-literature
Project description:Wastewater-based epidemiology (WBE) is a promising approach for monitoring the spread of SARS-CoV-2 within communities. Although qPCR-based WBE is powerful in that it allows quick and highly sensitive detection of this virus, it can provide limited information about which variants are responsible for the overall increase or decrease of this virus in sewage, and this hinders accurate risk assessments. To resolve this problem, we developed a next generation sequencing (NGS)-based method to determine the identity and composition of individual SARS-CoV-2 variants in wastewater samples. Combination and optimization of targeted amplicon-sequencing and nested PCR allowed detection of each variant with sensitivity comparable to that of qPCR. In addition, by targeting the receptor binding domain (RBD) of the S protein, which has mutations informative for variant classification, we could discriminate most variants of concern (VOC) and even sublineages of Omicron (BA.1, BA.2, BA.4/5, BA.2.75, BQ.1.1 and XBB.1). Focusing on a limited domain has a benefit of decreasing the sequencing reads. We applied this method to wastewater samples collected from a wastewater treatment plant in Kyoto city throughout 13 months (from January 2021 to February 2022) and successfully identified lineages of wild-type, alpha, delta, omicron BA.1 and BA.2 as well as their compositions in the samples. The transition of these variants was in good agreement with the epidemic situation reported in Kyoto city during that period based on clinical testing. These data indicate that our NGS-based method is useful for detecting and tracking emerging variants of SARS-CoV-2 in sewage samples. Coupled with the advantages of WBE, this method has the potential to serve as an efficient and low cost means for the community risk assessment of SARS-CoV-2 infection.
| S-EPMC10258123 | biostudies-literature
Project description:Municipal wastewater provides an integrated sample of a diversity of human-associated microbes across a sewershed, including viruses. Wastewater-based epidemiology (WBE) is a promising strategy to detect pathogens and may serve as an early warning system for disease outbreaks. Notably, WBE has garnered substantial interest during the coronavirus disease 2019 (COVID-19) pandemic to track disease burden through analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. Throughout the COVID-19 outbreak, tracking SARS-CoV-2 in wastewater has been an important tool for understanding the spread of the virus. Unlike traditional sequencing of SARS-CoV-2 isolated from clinical samples, which adds testing burden to the health care system, in this study, metatranscriptomics was used to sequence virus directly from wastewater. Here, we present a study in which we explored RNA viral diversity through sequencing 94 wastewater influent samples across seven wastewater treatment plants (WTPs), collected from August 2020 to January 2021, representing approximately 16 million people in Southern California. Enriched viral libraries identified a wide diversity of RNA viruses that differed between WTPs and over time, with detected viruses including coronaviruses, influenza A, and noroviruses. Furthermore, single-nucleotide variants (SNVs) of SARS-CoV-2 were identified in wastewater, and we measured proportions of overall virus and SNVs across several months. We detected several SNVs that are markers for clinically important SARS-CoV-2 variants along with SNVs of unknown function, prevalence, or epidemiological consequence. Our study shows the potential of WBE to detect viruses in wastewater and to track the diversity and spread of viral variants in urban and suburban locations, which may aid public health efforts to monitor disease outbreaks. IMPORTANCE Wastewater-based epidemiology (WBE) can detect pathogens across sewersheds, which represents the collective waste of human populations. As there is a wide diversity of RNA viruses in wastewater, monitoring the presence of these viruses is useful for public health, industry, and ecological studies. Specific to public health, WBE has proven valuable during the coronavirus disease 2019 (COVID-19) pandemic to track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) without adding burden to health care systems. In this study, we used metatranscriptomics and reverse transcription-droplet digital PCR (RT-ddPCR) to assay RNA viruses across Southern California wastewater from August 2020 to January 2021, representing approximately 16 million people from Los Angeles, Orange, and San Diego counties. We found that SARS-CoV-2 quantification in wastewater correlates well with county-wide COVID-19 case data, and that we can detect SARS-CoV-2 single-nucleotide variants through sequencing. Likewise, wastewater treatment plants (WTPs) harbored different viromes, and we detected other human pathogens, such as noroviruses and adenoviruses, furthering our understanding of wastewater viral ecology.
| S-EPMC8579973 | biostudies-literature