Evaluating whole-genome sequencing quality metrics for enteric pathogen outbreaks.
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ABSTRACT:
SUBMITTER: Wagner DD
PROVIDER: S-EPMC8627651 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPathogen whole genome sequencing (WGS) is being incorporated into public health surveillance and disease control systems worldwide and has the potential to make significant contributions to infectious disease surveillance, outbreak investigation and infection prevention and control. However, to date, there are limited data regarding (i) the optimal models for integration of genomic data into epidemiological investigations and (ii) how to quantify and evaluate public health impacts resulting from genomic epidemiological investigations.MethodsWe developed the Pathogen Genomics in Public HeAlth Surveillance Evaluation (PG-PHASE) Framework to guide examination of the use of WGS in public health surveillance and disease control. We illustrate the use of this framework with three pathogens as case studies: Listeria monocytogenes, Mycobacterium tuberculosis and SARS-CoV-2.ResultsThe framework utilises an adaptable whole-of-system approach towards understanding how interconnected elements in the public health application of pathogen genomics contribute to public health processes and outcomes. The three phases of the PG-PHASE Framework are designed to support understanding of WGS laboratory processes, analysis, reporting and data sharing, and how genomic data are utilised in public health practice across all stages, from the decision to send an isolate or sample for sequencing to the use of sequence data in public health surveillance, investigation and decision-making. Importantly, the phases can be used separately or in conjunction, depending on the need of the evaluator. Subsequent to conducting evaluation underpinned by the framework, avenues may be developed for strategic investment or interventions to improve utilisation of whole genome sequencing.ConclusionsComprehensive evaluation is critical to support health departments, public health laboratories and other stakeholders to successfully incorporate microbial genomics into public health practice. The PG-PHASE Framework aims to assist public health laboratories, health departments and authorities who are either considering transitioning to whole genome sequencing or intending to assess the integration of WGS in public health practice, including the capacity to detect and respond to outbreaks and associated costs, challenges and facilitators in the utilisation of microbial genomics and public health impacts.
| S-EPMC8317677 | biostudies-literature
Project description:Identification of enteric bacteria species by whole genome sequence (WGS) analysis requires a rapid and an easily standardized approach. We leveraged the principles of average nucleotide identity using MUMmer (ANIm) software, which calculates the percent bases aligned between two bacterial genomes and their corresponding ANI values, to set threshold values for determining species consistent with the conventional identification methods of known species. The performance of species identification was evaluated using two datasets: the Reference Genome Dataset v2 (RGDv2), consisting of 43 enteric genome assemblies representing 32 species, and the Test Genome Dataset (TGDv1), comprising 454 genome assemblies which is designed to represent all species needed to query for identification, as well as rare and closely related species. The RGDv2 contains six Campylobacter spp., three Escherichia/Shigella spp., one Grimontia hollisae, six Listeria spp., one Photobacterium damselae, two Salmonella spp., and thirteen Vibrio spp., while the TGDv1 contains 454 enteric bacterial genomes representing 42 different species. The analysis showed that, when a standard minimum of 70% genome bases alignment existed, the ANI threshold values determined for these species were ≥95 for Escherichia/Shigella and Vibrio species, ≥93% for Salmonella species, and ≥92% for Campylobacter and Listeria species. Using these metrics, the RGDv2 accurately classified all validation strains in TGDv1 at the species level, which is consistent with the classification based on previous gold standard methods.
| S-EPMC10752928 | biostudies-literature
Project description:BackgroundAvian avulavirus-1 (AAvV-1, previously Newcastle Disease Virus) is responsible for poultry and wild birds' disease outbreaks. Numerous whole genome sequencing methods were reported for this virus. These methods included cloning, specific primers amplification, shotgun PCR approaches, Sequence Independent Single Primer Amplification and next generation sequencing platform kits.MethodsThree methods were used to sequence 173 Israeli Avian avulavirus-1 field isolates and one vaccine strain (VH). The sequencing was performed on Proton and Ion Torrent Personal Genome Machine and to a lesser extent, Illumina MiSeq and NextSeq sequencers. Target specific primers (SP) and Sequence Independent Single Primer Amplification (SISPA) products sequenced via the Ion torrent sequencer had a high error rate and truncated genomes. All the next generation sequencing platform sequencing kits generated high sequence accuracy and near-complete genomic size.ResultsA high level of mutations was observed in the intergenic regions between the avian avulavirus-1 genes. Within genes, multiple regions are more mutated than the Fusion region currently used for typing.ConclusionsOur findings suggest that the whole genome sequencing by the Ion torrent sequencing kit is sufficient. However, when higher fidelity is desired, the Illumina NextSeq and Proton torrent sequencing kits were found to be preferable.
| S-EPMC7285907 | biostudies-literature
Project description:BackgroundTuberculosis incidence in the UK has risen in the past decade. Disease control depends on epidemiological data, which can be difficult to obtain. Whole-genome sequencing can detect microevolution within Mycobacterium tuberculosis strains. We aimed to estimate the genetic diversity of related M tuberculosis strains in the UK Midlands and to investigate how this measurement might be used to investigate community outbreaks.MethodsIn a retrospective observational study, we used Illumina technology to sequence M tuberculosis genomes from an archive of frozen cultures. We characterised isolates into four groups: cross-sectional, longitudinal, household, and community. We measured pairwise nucleotide differences within hosts and between hosts in household outbreaks and estimated the rate of change in DNA sequences. We used the findings to interpret network diagrams constructed from 11 community clusters derived from mycobacterial interspersed repetitive-unit-variable-number tandem-repeat data.FindingsWe sequenced 390 separate isolates from 254 patients, including representatives from all five major lineages of M tuberculosis. The estimated rate of change in DNA sequences was 0.5 single nucleotide polymorphisms (SNPs) per genome per year (95% CI 0.3-0.7) in longitudinal isolates from 30 individuals and 25 families. Divergence is rarely higher than five SNPs in 3 years. 109 (96%) of 114 paired isolates from individuals and households differed by five or fewer SNPs. More than five SNPs separated isolates from none of 69 epidemiologically linked patients, two (15%) of 13 possibly linked patients, and 13 (17%) of 75 epidemiologically unlinked patients (three-way comparison exact p<0.0001). Genetic trees and clinical and epidemiological data suggest that super-spreaders were present in two community clusters.InterpretationWhole-genome sequencing can delineate outbreaks of tuberculosis and allows inference about direction of transmission between cases. The technique could identify super-spreaders and predict the existence of undiagnosed cases, potentially leading to early treatment of infectious patients and their contacts.FundingMedical Research Council, Wellcome Trust, National Institute for Health Research, and the Health Protection Agency.
| S-EPMC3556524 | biostudies-literature
Project description:Bovine respiratory syncytial virus (BRSV) is a major cause of respiratory disease in cattle. Genomic sequencing can resolve phylogenetic relationships between virus populations, which can be used to infer transmission routes and potentially inform the design of biosecurity measures. Sequencing of short (<2000 nt) segments of the 15 000-nt BRSV genome has revealed geographic and temporal clustering of BRSV populations, but insufficient variation to distinguish viruses collected from herds infected close together in space and time. This study investigated the potential for whole-genome sequencing to reveal sufficient genomic variation for inferring transmission routes between herds. Next-generation sequencing (NGS) data were generated from experimental infections and from natural outbreaks in Jämtland and Uppsala counties in Sweden. Sufficient depth of coverage for analysis of consensus and sub-consensus sequence diversity was obtained from 47 to 20 samples respectively. Few (range: 0-6 polymorphisms across the six experiments) consensus-level polymorphisms were observed along experimental transmissions. A much higher level of diversity (146 polymorphic sites) was found among the consensus sequences from the outbreak samples. The majority (144/146) of polymorphisms were between rather than within counties, suggesting that consensus whole-genome sequences show insufficient spatial resolution for inferring direct transmission routes, but might allow identification of outbreak sources at the regional scale. By contrast, within-sample diversity was generally higher in the experimental than the outbreak samples. Analyses to infer known (experimental) and suspected (outbreak) transmission links from within-sample diversity data were uninformative. In conclusion, analysis of the whole-genome sequence of BRSV from experimental samples discriminated between circulating isolates from distant areas, but insufficient diversity was observed between closely related isolates to aid local transmission route inference.
| S-EPMC9746130 | biostudies-literature
Project description:Formalin fixed, paraffin embedded tissues are most commonly used for routine pathology analysis and for long term tissue preservation in the clinical setting. Many institutions have large archives of Formalin fixed, paraffin embedded tissues that provide a unique opportunity for understanding genomic signatures of disease. However, genome-wide expression profiling of Formalin fixed, paraffin embedded samples have been challenging due to RNA degradation. Because of the significant heterogeneity in tissue quality, normalization and analysis of these data presents particular challenges. The distribution of intensity values from archival tissues are inherently noisy and skewed due to differential sample degradation raising two primary concerns; whether a highly skewed array will unduly influence initial normalization of the data and whether outlier arrays can be reliably identified.Two simple extensions of common regression diagnostic measures are introduced that measure the stress an array undergoes during normalization and how much a given array deviates from the remaining arrays post-normalization. These metrics are applied to a study involving 1618 formalin-fixed, paraffin-embedded HER2-positive breast cancer samples from the N9831 adjuvant trial processed with Illumina's cDNA-mediated Annealing Selection extension and Ligation assay.Proper assessment of array quality within a research study is crucial for controlling unwanted variability in the data. The metrics proposed in this paper have direct biological interpretations and can be used to identify arrays that should either be removed from analysis all together or down-weighted to reduce their influence in downstream analyses.
| S-EPMC3626608 | biostudies-literature
Project description:Acinetobacter baumannii frequently causes nosocomial infections and outbreaks. Whole-genome sequencing (WGS) is a promising technique for strain typing and outbreak investigations. We compared the performance of conventional methods with WGS for strain typing clinical Acinetobacter isolates and analyzing a carbapenem-resistant A. baumannii (CRAB) outbreak. We performed two band-based typing techniques (pulsed-field gel electrophoresis and repetitive extragenic palindromic-PCR), multilocus sequence type (MLST) analysis, and WGS on 148 Acinetobacter calcoaceticus-A. baumannii complex bloodstream isolates collected from a single hospital from 2005 to 2012. Phylogenetic trees inferred from core-genome single nucleotide polymorphisms (SNPs) confirmed three Acinetobacter species within this collection. Four major A. baumannii clonal lineages (as defined by MLST) circulated during the study, three of which are globally distributed and one of which is novel. WGS indicated that a threshold of 2,500 core SNPs accurately distinguished A. baumannii isolates from different clonal lineages. The band-based techniques performed poorly in assigning isolates to clonal lineages and exhibited little agreement with sequence-based techniques. After applying WGS to a CRAB outbreak that occurred during the study, we identified a threshold of 2.5 core SNPs that distinguished nonoutbreak from outbreak strains. WGS was more discriminatory than the band-based techniques and was used to construct a more accurate transmission map that resolved many of the plausible transmission routes suggested by epidemiologic links. Our study demonstrates that WGS is superior to conventional techniques for A. baumannii strain typing and outbreak analysis. These findings support the incorporation of WGS into health care infection prevention efforts.
| S-EPMC4767972 | biostudies-literature
Project description:Background: Whole-genome sequencing (WGS) can support the investigation of tuberculosis (TB) outbreaks. The technique has been applied to estimate the timing and directionality of transmission and to exclude cases from an investigation. This review assesses how WGS was applied in international outbreak investigations and discusses the advantages and challenges of the application of WGS. Methods: Databases were searched for reports on international TB outbreak investigations. Information was extracted on: Why was WGS applied?; How was WGS applied?; Organizational issues; WGS methodology; What was learned/what were the implications of the WGS investigation?; and challenges and lessons learned. Results: Three studies reporting on international outbreak investigations were identified. Retrospective WGS sequencing was performed in all studies and prospective typing in two to study TB transmission. In one study, WGS data were produced centrally (i.e., in one laboratory) and analysis was done centrally. In two studies, WGS data production was done in a decentralized manner, and analysis was centralized in one laboratory. Three groups of professionals were involved in the international outbreak investigation: public health authorities, laboratory experts, and clinicians. The reported WGS methodology applied differed between the studies in some aspects, e.g., sequencing platform; quality measures, percentage of the reference genome covered, and the mean genomic coverage; analysis, use of a reference genome or de novo assembly; and software used for alignment and analysis. In all three studies, in-house scripts were used for variance calling, and the single nucleotide polymorphism (SNP) approach was used for analysis. All outbreak investigation reports stated that WGS refuted suspected transmission events and provided supporting evidence for epidemiological data. Several challenges were reported of which most were not related to WGS. The only challenge related to WGS was the timeframe of getting WGS data if WGS is not routinely performed. Conclusions: WGS was considered a useful addition in international TB outbreak investigations. Further standardization of the WGS methodology and good structures for international collaboration and coordination are needed to take full advantage of this new technology. Whether the use of WGS results in earlier detection of cases and thus limits transmission still needs to be determined.
| S-EPMC6478655 | biostudies-literature
Project description:Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies.
| S-EPMC4928038 | biostudies-literature
Project description:The BAM and CRAM formats provide a supplementary linear index that facilitates rapid access to sequence alignments in arbitrary genomic regions. Comparing consecutive entries in a BAM or CRAM index allows one to infer the number of alignment records per genomic region for use as an effective proxy of sequence depth in each genomic region. Based on these properties, we have developed indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at https://github.com/brentp/goleft under the MIT license.
| S-EPMC5737511 | biostudies-literature