Real-Time Genomic Surveillance for SARS-CoV-2 Variants of Concern, Uruguay.
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ABSTRACT:
SUBMITTER: Rego N
PROVIDER: S-EPMC8544970 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide. Many variants of SARS-CoV-2 have been reported, some of which have increased transmissibility and/or reduced susceptibility to vaccines. There is an urgent need for variant phenotyping for epidemiological surveillance of circulating lineages. Whole-genome sequencing is the gold standard for identifying SARS-CoV-2 variants, which constitutes a major bottleneck in developing countries. Methodological simplification could increase epidemiological surveillance feasibility and efficiency. We designed a novel multiplex real-time reverse transcriptase PCR (RT-PCR) to detect SARS-CoV-2 variants with S gene mutations. This multiplex PCR typing method was established to detect 9 mutations with specific primers and probes (ΔHV 69/70, K417T, K417N, L452R, E484K, E484Q, N501Y, P681H, and P681R) against the receptor-binding domain of the spike protein of SARS-CoV-2 variants. In silico analyses showed high specificity of the assays. Variants of concern (VOC) typing results were found to be highly specific for our intended targets, with no cross-reactivity observed with other upper respiratory viruses. The PCR-based typing methods were further validated using whole-genome sequencing and a commercial kit that was applied to clinical samples of 250 COVID-19 patients from Taiwan. The screening of these samples allowed the identification of epidemic trends by time intervals, including B.1.617.2 in the third Taiwan wave outbreak. This PCR typing strategy allowed the detection of five major variants of concern and also provided an open-source PCR assay which could rapidly be deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, P.1, and B.1.617.2 variants and of four Omicron mutations on the spike protein (ΔHV 69/70, K417N, N501Y, P681H). IMPORTANCE COVID-19 has spread globally. SARS-CoV-2 variants of concern (VOCs) are leading the next waves of the COVID-19 pandemic. Previous studies have pointed out that these VOCs may have increased infectivity, have reduced vaccine susceptibility, change treatment regimens, and increase the difficulty of epidemic prevention policy. Understanding SARS-CoV-2 variants remains an issue of concern for all local government authorities and is critical for establishing and implementing effective public health measures. A novel SARS-CoV-2 variant identification method based on a multiplex real-time RT-PCR was developed in this study. Five SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, and Omicron) were identified simultaneously using this method. PCR typing can provide rapid testing results with lower cost and higher feasibility, which is well within the capacity for any diagnostic laboratory. Characterizing these variants and their mutations is important for tracking SAR-CoV-2 evolution and is conducive to public infection control and policy formulation strategies.
| S-EPMC8865422 | biostudies-literature
Project description:Age-matched K18-hACE2 transgenic mice were infected intranasally with different SARS-CoV-2 viruses, including (1) USA-WA1/2020 (WA) of lineage A, (2) New York-PV09158/2020 (NY) of lineage B.1.3, (3) USA/CA_CDC_5574/2020 (CA) of lineage B.1.1.7 and (4) hCoV-19/South Africa/KRISP-EC-K005321/2020 (SA) of lineage B.1.351. Mouse lungs were harvested on 3 days post infection (dpi). Total RNA was extracted using QIAgen RNeasy Plus Mini Kit and was reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific). Resultant cDNA was used as the template along with RT2 SYBR Green ROX qPCR Mastermix (Qiagen) to perform RT² Profiler™ PCR Array Mouse Hypoxia Signaling Pathway (Qiagen) real-time PCR in Stratagene MX3000p qPCR system.
2021-10-10 | GSE183621 | GEO
Project description:To effectively control the ongoing outbreaks of fast-spreading SARS-CoV-2 variants, there is an urgent need to add rapid variant detection and discrimination methods to the existing sewage surveillance systems established worldwide. We designed eight assays based on allele-specific RT-qPCR for real-time allelic discrimination of eight SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, Lambda, Mu, and Kappa) in sewage. In silico analysis of the designed assays for identifying SARS-CoV-2 variants using more than four million SARS-CoV-2 variant sequences yielded ∼100% specificity and >90% sensitivity. All assays could sensitively discriminate and quantify target variants at levels as low as 10 viral RNA copy/µL with minimal cross-reactivity to the corresponding nontarget genotypes, even for sewage samples containing mixtures of SARS-CoV-2 variants with differential abundances. Integration of this method into the routine sewage surveillance in Hong Kong successfully identified the Beta variant in a community sewage. Complete concordance was observed between the results of viral whole-genome sequencing and those of our novel assays in sewage samples that contained exclusively the Delta variant discharged by a clinically diagnosed COVID-19 patient living in a quarantine hotel. Our assays in this method also provided real-time discrimination of the newly emerging Omicron variant in sewage two days prior to clinical test results in another quarantine hotel in Hong Kong. These novel allelic discrimination assays offer a rapid, sensitive, and specific way for detecting multiple SARS-CoV-2 variants in sewage and can be directly integrated into the existing sewage surveillance systems.
| S-EPMC9148393 | biostudies-literature
Project description:Rapid identification and continuous surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are critical for guiding the response to the COVID-19 pandemic. Whole-genome sequencing (WGS) is a preferred tool for this aim, but many laboratories suffer from a lack of resources to support population-level sequencing. Here, we describe two PCR strategies targeting spike protein mutations to identify the Alpha, Delta, and Omicron variants. Signature mutations were selected using a dedicated bioinformatic program. The selected mutations in Alpha and Delta variants were detected using multicolor melting curve analysis (MMCA). Thirty-two mutations of the Omicron variant were targeted using the MeltArray approach in one reaction, which was able to detect the Omicron subvariants BA.1, BA.2, BA.3, and BA.4/5. The limits of detection varied from five to 50 copies of RNA templates/reactions. No cross-reactivity was observed with nine other respiratory viruses, including other coronaviruses. We validated the MMCA and MeltArray assays using 309 SARS-CoV-2 positive samples collected at different time points. These assays exhibited 98.3% to 100% sensitivity and 100% specificity compared with WGS. Multiplexed real-time PCR strategies represent an alternative tool capable of identifying current SARS-CoV-2 VOCs, adaptable for emerging variants and accessible for laboratories using existing equipment and personnel. IMPORTANCE Rapid detection and mutation surveillance of SARS-CoV-2 VOCs is crucial for COVID-19 control, management, and prevention. We developed two rapid molecular assays based on the real-time PCR platform to identify important variants of concern, including the Omicron variant with a large number of mutations. Signature mutations were selected by an R program. Then, MMCA assays were established for Alpha and Delta variants, and a MeltArray assay targeting 32 mutations was developed for Omicron variant. These multiplexed PCR assays could be performed in a 96-well real-time PCR instrument within 2.5 h, offering a high-throughput choice for dynamic monitoring of SARS-CoV-2 VOCs in a standard microbiology laboratory.
| S-EPMC9603638 | biostudies-literature
Project description:The ongoing COVID-19 pandemic represents an unprecedented global health crisis. Here, we report the identification of a synthetic nanobody (sybody) pair, Sb#15 and Sb#68, that can bind simultaneously to the SARS-CoV-2 spike-RBD and efficiently neutralize pseudotyped and live-viruses by interfering with ACE2 interaction. Cryo-EM confirms that Sb#15 and Sb#68 engage two spatially-discrete epitopes, influencing rational design of bispecific and tri-bispecific fusion constructs that exhibit up to 100- and 1000-fold increase in neutralization potency, respectively. Cryo-EM of the sybody-spike complex additionally reveals a novel up-out RBD conformation. While resistant viruses emerge rapidly in the presence of single binders, no escape variants are observed in presence of the bispecific sybody. The multivalent bispecific constructs further increase the neutralization potency against globally-circulating SARS-CoV-2 variants of concern. Our study illustrates the power of multivalency and biparatopic nanobody fusions for the potential development of therapeutic strategies that mitigate the emergence of new SARS-CoV-2 escape mutants.
| S-SCDT-EMBOR-2021-54199V1 | biostudies-other
Project description: Not available
| S-EPMC7946415 | biostudies-literature
Project description:With the emergence of SARS-CoV-2 variants that may increase transmissibility and/or cause escape from immune responses 1-3 , there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant first detected in the UK 4,5 could be serendipitously detected by the ThermoFisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike Δ69-70, would cause a "spike gene target failure" (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern that lack spike Δ69-70, such as B.1.351 (also 501Y.V2) detected in South Africa 6 and P.1 (also 501Y.V3) recently detected in Brazil 7 . We identified a deletion in the ORF1a gene (ORF1a Δ3675-3677) in all three variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675-3677 as the primary target and spike Δ69-70 to differentiate, we designed and validated an open source PCR assay to detect SARS-CoV-2 variants of concern 8 . Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence spread of B.1.1.7, B.1.351, and P.1.
| S-EPMC7987060 | 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:With the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants that may increase transmissibility and/or cause escape from immune responses, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant, first detected in the United Kingdom, could be serendipitously detected by the Thermo Fisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike Δ69-70, would cause a "spike gene target failure" (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern (VOC) that lack spike Δ69-70, such as B.1.351 (also 501Y.V2), detected in South Africa, and P.1 (also 501Y.V3), recently detected in Brazil. We identified a deletion in the ORF1a gene (ORF1a Δ3675-3677) in all 3 variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675-3677 as the primary target and spike Δ69-70 to differentiate, we designed and validated an open-source PCR assay to detect SARS-CoV-2 VOC. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, and P.1.
| S-EPMC8133773 | biostudies-literature
Project description:Novel variants continue to emerge in the SARS-CoV-2 pandemic. University testing programs may provide timely epidemiologic and genomic surveillance data to inform public health responses. We conducted testing from September 2021 to February 2022 in a university population under vaccination and indoor mask mandates. A total of 3,048 of 24,393 individuals tested positive for SARS-CoV-2 by RT-PCR; whole genome sequencing identified 209 Delta and 1,730 Omicron genomes of the 1,939 total sequenced. Compared to Delta, Omicron had a shorter median serial interval between genetically identical, symptomatic infections within households (2 versus 6 days, P = 0.021). Omicron also demonstrated a greater peak reproductive number (2.4 versus 1.8), and a 1.07 (95% confidence interval: 0.58, 1.57; P < 0.0001) higher mean cycle threshold value. Despite near universal vaccination and stringent mitigation measures, Omicron rapidly displaced the Delta variant to become the predominant viral strain and led to a surge in cases in a university population.
| S-EPMC9446629 | biostudies-literature