scholarly journals SARS-CoV-2 testing in the community: Testing positive samples with the TaqMan SARS-CoV-2 Mutation Panel to find variants in real-time

2021 ◽  
Author(s):  
Fiona Ashford ◽  
Angus Best ◽  
Steven Dunn ◽  
Zahra Ahmed ◽  
Henna Siddiqui ◽  
...  
Keyword(s):  
Real Time ◽  
Genome Sequencing ◽  
Drop Out ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Health Value ◽  
Genotyping Assay ◽  
Thermo Fisher Scientific ◽  
Fisher Scientific

Genome sequencing is a powerful tool for identifying SARS-CoV-2 variant lineages, however there can be limitations due to sequence drop-out when used to identify specific key mutations. Recently, Thermo Fisher Scientific have developed genotyping assays to help bridge the gap between testing capacity and sequencing capability to generate real-time genotyping results based on specific variants. Over a 6-week period during the months of April and May 2021, we set out to assess the Thermo Fisher TaqMan Mutation Panel Genotyping Assay, initially for three mutations of concern and then an additional two mutations of concern, against SARS-CoV-2 positive clinical samples and the corresponding COG-UK sequencing data. We demonstrate that genotyping is a powerful in-depth technique for identifying specific mutations, an excellent complement to genome sequencing and has real clinical health value potential allowing laboratories to report and action variants of concern much quicker.

scholarly journals High-precision and cost-efficient sequencing for real-time COVID-19 surveillance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Yong Park ◽  
Gina Faraci ◽  
Pamela M. Ward ◽  
Jane F. Emerson ◽  
Ha Youn Lee
Keyword(s):  
Los Angeles ◽  
Whole Genome Sequencing ◽  
Real Time ◽  
Genome Sequencing ◽  
High Precision ◽  
High Throughput Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Public Health Response ◽  
Cost Efficient

AbstractCOVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients’ Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

scholarly journals Novel Nested-Seq Approach for SARS-CoV-2 Real-Time Epidemiology and In-Depth Mutational Profiling in Wastewater

2021 ◽  
Vol 22 (16) ◽  
pp. 8498
Author(s):  
Margaritis Avgeris ◽  
Panagiotis G. Adamopoulos ◽  
Aikaterini Galani ◽  
Marieta Xagorari ◽  
Dimitrios Gourgiotis ◽  
...  
Keyword(s):  
Real Time ◽  
Nested Pcr ◽  
Mutational Analysis ◽  
National Level ◽  
Rna Stability ◽  
3D Structure ◽  
Cost Effective ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Alpha Variant

Considering the lack of effective treatments against COVID-19, wastewater-based epidemiology (WBE) is emerging as a cost-effective approach for real-time population-wide SARS-CoV-2 monitoring. Here, we report novel molecular assays for sensitive detection and mutational/variant analysis of SARS-CoV-2 in wastewater. Highly stable regions of SARS-CoV-2 RNA were identified by RNA stability analysis and targeted for the development of novel nested PCR assays. Targeted DNA sequencing (DNA-seq) was applied for the analysis and quantification of SARS-CoV-2 mutations/variants, following hexamers-based reverse transcription and nested PCR-based amplification of targeted regions. Three-dimensional (3D) structure models were generated to examine the predicted structural modification caused by genomic variants. WBE of SARS-CoV-2 revealed to be assay dependent, and significantly improved sensitivity achieved by assay combination (94%) vs. single-assay screening (30%–60%). Targeted DNA-seq allowed the quantification of SARS-CoV-2 mutations/variants in wastewater, which agreed with COVID-19 patients’ sequencing data. A mutational analysis indicated the prevalence of D614G (S) and P323L (RdRP) variants, as well as of the Β.1.1.7/alpha variant of concern, in agreement with the frequency of Β.1.1.7/alpha variant in clinical samples of the same period of the third pandemic wave at the national level. Our assays provide an innovative cost-effective platform for real-time monitoring and early-identification of SARS-CoV-2 variants at community/population levels.

A heuristic platform for clinical interpretation of cancer genome sequencing data.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10502-10502
Author(s):  
Eliezer Mendel Van Allen ◽  
Nikhil Wagle ◽  
Gregory Kryukov ◽  
Alexis Ramos ◽  
Gad Getz ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Genome Sequencing ◽  
Heuristic Algorithm ◽  
Genetic Alterations ◽  
Cancer Genome ◽  
Clinical Samples ◽  
Whole Genome ◽  
Cancer Genes ◽  
Sequencing Data ◽  
Clinical Interpretation

10502 Background: The ability to identify and effectively sort the full spectrum of biologically and therapeutically relevant genetic alterations identified by massively parallel sequencing may improve cancer care. A major challenge involves rapid and rational categorization of data-intensive output, including somatic mutations, insertions/deletions, copy number alterations, and rearrangements into ranked categories for clinician review. Methods: A database of clinically actionable alterations was created, consisting of over 100 annotated genes known to undergo somatic genomic alterations in cancer that may impact clinical decision-making. A heuristic algorithm was developed, which selectively identifies somatic alterations based on the clinically actionable alterations database. Remaining variants are sorted based on additional heuristics, including high priority alterations based on presence in the Cancer Gene Census, biologically significant cancer genes based on presence in COSMIC or MSigDB, and low priority alterations in the same gene family as biologically significant cancer genes. The heuristic algorithm was applied to whole exome sequencing data of clinical samples and whole genome sequencing data from a cohort of prostate cancer samples processed using established Broad Institute pipelines. Results: Application of the heuristic algorithm to the prostate cancer whole genome rearrangement data identified 172 (out of 5978) rearrangements involving actionable genes (averaging 2-3 events per tumor). Furthermore, two clinical samples processed prospectively were analyzed, yielding three potentially actionable alterations for clinical review. Conclusions: The heuristic model for clinical interpretation of next generation sequencing data may facilitate rapid analysis of tumor genomic information for clinician review by identifying and prioritizing alterations that can directly impact care. Our platform can also be applied to research data to prospectively explore clinically relevant findings from existing cohorts. Future analytical approaches using heuristic or probabilistic algorithms should underpin a robust prospective assessment of clinical cancer genome data.

scholarly journals Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

2019 ◽  
Author(s):  
Ronan M. Doyle ◽  
Denise M. O’Sullivan ◽  
Sean D. Aller ◽  
Sebastian Bruchmann ◽  
Taane Clark ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Laboratory Study ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractBackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

scholarly journals Rapid Direct Detection of Multiple Rifampin and Isoniazid Resistance Mutations in Mycobacterium tuberculosis in Respiratory Samples by Real-Time PCR

2004 ◽  
Vol 48 (11) ◽  
pp. 4293-4300 ◽  
Author(s):  
Mercedes Marín ◽  
Darío García de Viedma ◽  
María Jesús Ruíz-Serrano ◽  
Emilio Bouza
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Real Time ◽  
Real Time Pcr ◽  
Rapid Detection ◽  
Direct Detection ◽  
Bacterial Load ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Resistance Mutations ◽  
Time Required

ABSTRACT Rapid detection of resistance in Mycobacterium tuberculosis can optimize the efficacy of antituberculous therapy and control the transmission of resistant M. tuberculosis strains. Real-time PCR has minimized the time required to obtain the susceptibility pattern of M. tuberculosis strains, but little effort has been made to adapt this rapid technique to the direct detection of resistance from clinical samples. In this study, we adapted and evaluated a real-time PCR design for direct detection of resistance mutations in clinical respiratory samples. The real-time PCR was evaluated with (i) 11 clinical respiratory samples harboring bacilli resistant to isoniazid (INH) and/or rifampin (RIF), (ii) 10 culture-negative sputa spiked with a set of strains encoding 14 different resistance mutations in 10 independent codons, and (iii) 16 sputa harboring susceptible strains. The results obtained with this real-time PCR design completely agreed with DNA sequencing data. In all sputa harboring resistant M. tuberculosis strains, the mutation encoding resistance was successfully detected. No mutation was detected in any of the susceptible sputa. The test was applied only to smear-positive specimens and succeeded in detecting a bacterial load equivalent to 103 CFU/ml in sputum samples (10 acid-fast bacilli/line). The analytical specificity of this method was proved with a set of 14 different non-M. tuberculosis bacteria. This real-time PCR design is an adequate method for the specific and rapid detection of RIF and INH resistance in smear-positive clinical respiratory samples.

scholarly journals Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management

2021 ◽  
Vol 7 (6) ◽  
Author(s):  
Andrew J. Page ◽  
Alison E. Mather ◽  
Thanh Le-Viet ◽  
Emma J. Meader ◽  
Nabil-Fareed Alikhan ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Large Scale ◽  
Control Measures ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Outbreak Management ◽  
Infection Control Measures ◽  
Care Facilities ◽  
Surrounding Areas ◽  
Public Health Epidemiology

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organizations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1565 positive samples (172 per 100 000 population) from 1376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6 % of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. In total, 1035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a discrete sublineage associated with six care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients, indicating infection control measures were effective; and found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.

scholarly journals Neuroblastoma Risk Assessment and Treatment Stratification with Hybrid Capture-Based Panel Sequencing

2021 ◽  
Vol 11 (8) ◽  
pp. 691
Author(s):  
Annabell Szymansky ◽  
Louisa-Marie Kruetzfeldt ◽  
Lukas C. Heukamp ◽  
Falk Hertwig ◽  
Jessica Theissen ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Neuroblastoma Cell ◽  
Tumor Biology ◽  
Clinical Samples ◽  
Risk Markers ◽  
Sequencing Data ◽  
High Coverage ◽  
Routine Diagnostics ◽  
Hybrid Capture ◽  
Panel Sequencing

For many years, the risk-based therapy stratification of children with neuroblastoma has relied on clinical and molecular covariates. In recent years, genome analysis has revealed further alterations defining risk, tumor biology, and therapeutic targets. The implementation of a robust and scalable method for analyzing traditional and new molecular markers in routine diagnostics is an urgent clinical need. Here, we investigated targeted panel sequencing as a diagnostic approach to analyze all relevant genomic neuroblastoma risk markers in one assay. Our “neuroblastoma hybrid capture sequencing panel” (NB-HCSP) assay employs a technology for the high-coverage sequencing (>1000×) of 55 selected genes and neuroblastoma-relevant genomic regions, which allows for the detection of single nucleotide changes, structural rearrangements, and copy number alterations. We validated our assay by analyzing 15 neuroblastoma cell lines and a cohort of 20 neuroblastomas, for which reference routine diagnostic data and genome sequencing data were available. We observed a high concordance for risk markers identified by the NB-HSCP assay, clinical routine diagnostics, and genome sequencing. Subsequently, we demonstrated clinical applicability of the NB-HCSP assay by analyzing routine clinical samples. We conclude that the NB-HCSP assay may be implemented into routine diagnostics as a single assay that covers all essential covariates for initial neuroblastoma classification, extended risk stratification, and targeted therapy selection.

scholarly journals Internal validation and improvement of mitochondrial genome sequencing using the Precision ID mtDNA Whole Genome Panel

2021 ◽  
Author(s):  
Christian Faccinetto ◽  
Daniele Sabbatini ◽  
Patrizia Serventi ◽  
Martina Rigato ◽  
Cecilia Salvoro ◽  
...  
Keyword(s):  
Mitochondrial Genome ◽  
Genome Sequencing ◽  
Dna Sequences ◽  
Data Interpretation ◽  
Whole Genome ◽  
Internal Validation ◽  
Forensic Practice ◽  
Thermo Fisher Scientific ◽  
Next Generation Sequencing Ngs ◽  
Fisher Scientific

AbstractWith the recent advances in next-generation sequencing (NGS), mitochondrial whole-genome sequencing has begun to be applied to the field of the forensic biology as an alternative to the traditional Sanger-type sequencing (STS). However, experimental workflows, commercial solutions, and output data analysis must be strictly validated before being implemented into the forensic laboratory. In this study, we performed an internal validation for an NGS-based typing of the entire mitochondrial genome using the Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific) on the Ion S5 sequencer (Thermo Fisher Scientific). Concordance, repeatability, reproducibility, sensitivity, and heteroplasmy detection analyses were assessed using the 2800 M and 9947A standard control DNA as well as typical casework specimens, and results were compared with conventional Sanger sequencing and another NGS sequencer in a different laboratory. We discuss the strengths and limitations of this approach, highlighting some issues regarding noise thresholds and heteroplasmy detection, and suggesting solutions to mitigate these effects and improve overall data interpretation. Results confirmed that the Precision ID Whole mtDNA Genome Panel is highly reproducible and sensitive, yielding useful full mitochondrial DNA sequences also from challenging DNA specimens, thus providing further support for its use in forensic practice.

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