Routine use of microbial whole genome sequencing in diagnostic and public health microbiology.
Ontology highlight
ABSTRACT:
SUBMITTER: Koser CU
PROVIDER: S-EPMC3410874 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Genomics and whole genome sequencing (WGS) have the capacity to greatly enhance knowledge and understanding of infectious diseases and clinical microbiology.The growth and availability of bench-top WGS analysers has facilitated the feasibility of genomics in clinical and public health microbiology.Given current resource and infrastructure limitations, WGS is most applicable to use in public health laboratories, reference laboratories, and hospital infection control-affiliated laboratories.As WGS represents the pinnacle for strain characterisation and epidemiological analyses, it is likely to replace traditional typing methods, resistance gene detection and other sequence-based investigations (e.g., 16S rDNA PCR) in the near future.Although genomic technologies are rapidly evolving, widespread implementation in clinical and public health microbiology laboratories is limited by the need for effective semi-automated pipelines, standardised quality control and data interpretation, bioinformatics expertise, and infrastructure.
| S-EPMC4389090 | biostudies-other
Project description:ImportanceThe latest generation of benchtop DNA sequencing platforms can provide an accurate whole-genome sequence (WGS) for a broad range of bacteria in less than a day. These could be used to more effectively contain the spread of multidrug-resistant pathogens.ObjectiveTo compare WGS with standard clinical microbiology practice for the investigation of nosocomial outbreaks caused by multidrug-resistant bacteria, the identification of genetic determinants of antimicrobial resistance, and typing of other clinically important pathogens.Design, setting, and participantsA laboratory-based study of hospital inpatients with a range of bacterial infections at Cambridge University Hospitals NHS Foundation Trust, a secondary and tertiary referral center in England, comparing WGS with standard diagnostic microbiology using stored bacterial isolates and clinical information.Main outcomes and measuresSpecimens were taken and processed as part of routine clinical care, and cultured isolates stored and referred for additional reference laboratory testing as necessary. Isolates underwent DNA extraction and library preparation prior to sequencing on the Illumina MiSeq platform. Bioinformatic analyses were performed by persons blinded to the clinical, epidemiologic, and antimicrobial susceptibility data.ResultsWe investigated 2 putative nosocomial outbreaks, one caused by vancomycin-resistant Enterococcus faecium and the other by carbapenem-resistant Enterobacter cloacae; WGS accurately discriminated between outbreak and nonoutbreak isolates and was superior to conventional typing methods. We compared WGS with standard methods for the identification of the mechanism of carbapenem resistance in a range of gram-negative bacteria (Acinetobacter baumannii, E cloacae, Escherichia coli, and Klebsiella pneumoniae). This demonstrated concordance between phenotypic and genotypic results, and the ability to determine whether resistance was attributable to the presence of carbapenemases or other resistance mechanisms. Whole-genome sequencing was used to recapitulate reference laboratory typing of clinical isolates of Neisseria meningitidis and to provide extended phylogenetic analyses of these.Conclusions and relevanceThe speed, accuracy, and depth of information provided by WGS platforms to confirm or refute outbreaks in hospitals and the community, and to accurately define transmission of multidrug-resistant and other organisms, represents an important advance.
| S-EPMC4001082 | biostudies-literature
Project description:Public health microbiology laboratories (PHLs) are on the cusp of unprecedented improvements in pathogen identification, antibiotic resistance detection, and outbreak investigation by using whole-genome sequencing (WGS). However, considerable challenges remain due to the lack of common standards. Here, we describe the validation of WGS on the Illumina platform for routine use in PHLs according to Clinical Laboratory Improvements Act (CLIA) guidelines for laboratory-developed tests (LDTs). We developed a validation panel comprising 10 Enterobacteriaceae isolates, 5 Gram-positive cocci, 5 Gram-negative nonfermenting species, 9 Mycobacterium tuberculosis isolates, and 5 miscellaneous bacteria. The genome coverage range was 15.71× to 216.4× (average, 79.72×; median, 71.55×); the limit of detection (LOD) for single nucleotide polymorphisms (SNPs) was 60×. The accuracy, reproducibility, and repeatability of base calling were >99.9%. The accuracy of phylogenetic analysis was 100%. The specificity and sensitivity inferred from multilocus sequence typing (MLST) and genome-wide SNP-based phylogenetic assays were 100%. The following objectives were accomplished: (i) the establishment of the performance specifications for WGS applications in PHLs according to CLIA guidelines, (ii) the development of quality assurance and quality control measures, (iii) the development of a reporting format for end users with or without WGS expertise, (iv) the availability of a validation set of microorganisms, and (v) the creation of a modular template for the validation of WGS processes in PHLs. The validation panel, sequencing analytics, and raw sequences could facilitate multilaboratory comparisons of WGS data. Additionally, the WGS performance specifications and modular template are adaptable for the validation of other platforms and reagent kits.
| S-EPMC5527429 | biostudies-literature
Project description:UnlabelledThe implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasive Staphylococcus aureus isolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show that in silico predictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools.ImportanceThe spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine whole-genome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.
| S-EPMC4959656 | biostudies-literature
Project description:There is growing evidence for the value of bacterial whole-genome sequencing in hospital outbreak investigations. Our aim was to develop methods that support efficient and accurate low-throughput clinical sequencing of methicillin-resistant Staphylococcus aureus (MRSA) isolates. Using a test panel of 25 MRSA isolates previously associated with outbreak investigations, we devised modifications to library preparation that reduced the processing time by 1 hour. We determined the maximum number of isolates that could be sequenced per run using an Illumina MiniSeq platform and a 13-hour (overnight) run time, which equated to 21 MRSA isolates and 3 controls (no template, positive, and negative). Repeatability and reproducibility assays based on this sequencing methodology demonstrated 100% accuracy in assigning species and sequence type (ST) and in detecting mecA Established genetic relatedness between isolates was recapitulated. Quality control (QC) metrics were evaluated over nine sequencing runs. Of the test panel MRSA genomes, 168/173 (97%) passed QC metrics based on the correct species assigned, detection of mecA and ST, and depth/coverage metrics. An evaluation of contamination in these 9 runs showed that positive and negative controls and test MRSA sequence files contained <0.14% and <0.48% of fragments that matched another species, respectively. Deliberate contamination experiments confirmed that this was insufficient to impact data interpretation. These methods support reliable and reproducible clinical MRSA sequencing with a turnaround time (from DNA extraction to availability of data files) of 24 hours.
| S-EPMC6535593 | biostudies-literature
Project description:Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.
| S-EPMC8634525 | biostudies-literature
Project description:In April 2015, Public Health England implemented whole genome sequencing (WGS) as a routine typing tool for public health surveillance of Salmonella, adopting a multilocus sequence typing (MLST) approach as a replacement for traditional serotyping. The WGS derived sequence type (ST) was compared to the phenotypic serotype for 6,887 isolates of S. enterica subspecies I, and of these, 6,616 (96%) were concordant. Of the 4% (n = 271) of isolates of subspecies I exhibiting a mismatch, 119 were due to a process error in the laboratory, 26 were likely caused by the serotype designation in the MLST database being incorrect and 126 occurred when two different serovars belonged to the same ST. The population structure of S. enterica subspecies II-IV differs markedly from that of subspecies I and, based on current data, defining the serovar from the clonal complex may be less appropriate for the classification of this group. Novel sequence types that were not present in the MLST database were identified in 8.6% of the total number of samples tested (including S. enterica subspecies I-IV and S. bongori) and these 654 isolates belonged to 326 novel STs. For S. enterica subspecies I, WGS MLST derived serotyping is a high throughput, accurate, robust, reliable typing method, well suited to routine public health surveillance. The combined output of ST and serovar supports the maintenance of traditional serovar nomenclature while providing additional insight on the true phylogenetic relationship between isolates.
| S-EPMC4824889 | biostudies-literature
Project description:Next-generation sequencing (NGS) of bacterial genomes has recently become more accessible and is now available to the routine diagnostic microbiology laboratory. However, questions remain regarding its feasibility, particularly with respect to data analysis in nonspecialist centers. To test the applicability of NGS to outbreak investigations, Ion Torrent sequencing was used to investigate a putative multidrug-resistant Escherichia coli outbreak in the neonatal unit of the Mercy Hospital for Women, Melbourne, Australia. Four suspected outbreak strains and a comparator strain were sequenced. Genome-wide single nucleotide polymorphism (SNP) analysis demonstrated that the four neonatal intensive care unit (NICU) strains were identical and easily differentiated from the comparator strain. Genome sequence data also determined that the NICU strains belonged to multilocus sequence type 131 and carried the bla(CTX-M-15) extended-spectrum beta-lactamase. Comparison of the outbreak strains to all publicly available complete E. coli genome sequences showed that they clustered with neonatal meningitis and uropathogenic isolates. The turnaround time from a positive culture to the completion of sequencing (prior to data analysis) was 5 days, and the cost was approximately $300 per strain (for the reagents only). The main obstacles to a mainstream adoption of NGS technologies in diagnostic microbiology laboratories are currently cost (although this is decreasing), a paucity of user-friendly and clinically focused bioinformatics platforms, and a lack of genomics expertise outside the research environment. Despite these hurdles, NGS technologies provide unparalleled high-resolution genotyping in a short time frame and are likely to be widely implemented in the field of diagnostic microbiology in the next few years, particularly for epidemiological investigations (replacing current typing methods) and the characterization of resistance determinants. Clinical microbiologists need to familiarize themselves with these technologies and their applications.
| S-EPMC3647928 | biostudies-literature
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:Next-generation sequencing has revolutionized the molecular diagnosis of individuals affected by genetic kidney diseases. Indeed, rapid genetic testing in individuals with suspected inherited nephropathy has not only important implications for diagnosis and prognosis but also for genetic counseling. Nephronophthisis (NPHP) and related syndromes, a leading cause of end-stage renal failure, are autosomal recessive disorders characterized by the variable presentation and considerable locus heterogeneity with more than 90 genes described as single-gene causes. In this case report, we demonstrate the utility of whole-genome sequencing (WGS) for the molecular diagnosis of NPHP by identifying two putative disease-causing intronic mutations in the NPHP3 gene, including one deep intronic variant. We further show that both intronic variants, by affecting splicing, result in a truncated nephrocystin-3 protein. This study provides a framework for applying WGS as a first-line diagnostic tool for highly heterogeneous disease such as NPHP and further suggests that deep intronic variations are an important underestimated cause of monogenic disorders.
| S-EPMC7506526 | biostudies-literature