scholarly journals Integration of Whole-Genome Sequencing into Infection Control Practices: the Potential and the Hurdles

2015 ◽  
Vol 53 (4) ◽  
pp. 1054-1055 ◽  
Author(s):  
Elizabeth Robilotti ◽  
Mini Kamboj

Microbial whole-genome sequencing (WGS) is poised to transform many of the currently used approaches in medical microbiology. Recent reports on the application of WGS to understand genetic evolution and reconstruct transmission pathways have provided valuable information that will influence infection control practices. While this technology holds great promise, obstacles to full implementation remain. Two articles in this issue of the Journal of Clinical Microbiology (S. Octavia, Q. Wang, M. M. Tanaka, S. Kaur, V. Sintchenko, and R. Lan, J Clin Microbiol 53:1063–1071, 2015, doi:10.1128/JCM.03235-14, andS. J. Salipante, D. J. SenGupta, L. A. Cummings, T. A. Land, D. R. Hoogestraat, and B. T. Cookson, J Clin Microbiol 53:1072–1079, 2015, doi:10.1128/JCM.03385-14) describe the breadth of application of WGS to the field of clinical epidemiology.

2015 ◽  
Vol 53 (8) ◽  
pp. 2402-2403 ◽  
Author(s):  
Claire Jenkins

The accessibility of whole-genome sequencing (WGS) presents the opportunity for national reference laboratories to provide a state-of-the-art public health surveillance service. The replacement of traditional serology-based typing ofEscherichia coliby WGS is supported by user-friendly, freely available data analysis Web tools. Anarticle in this issueof theJournal of Clinical Microbiology(K. G. Joensen, A. M. M. Tetzschner, A. Iguchi, F. M. Aarestrup, and F. Scheutz, J Clin Microbiol, 53:2410–2426, 2015,http://dx.doi.org/10.1128/JCM.00008-15) describes SerotypeFinder, an essential guide to serotypingE. coliin the 21st century.


2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S255-S255
Author(s):  
Donald S Chen ◽  
Moira Quinn ◽  
Rita M Sussner ◽  
Guiqing Wang ◽  
John T Fallon ◽  
...  

Abstract Background Whole-genome sequencing (WGS) of bacteria is becoming a routine tool within microbiology, yet its utility to help guide infection control (IC) practice longitudinally is underexplored. As with any technology adopted in the hospital, the integration of WGS into IC practice must be carefully managed and considered. We qualitatively report an evidence-based implementation workflow that considers WGS to help proactively guide IC professionals during investigation of infectious outbreaks. Methods We built upon lessons learned in an ongoing surveillance effort at a tertiary care hospital—utilizing retrospective WGS data within the Philips IntelliSpace Epidemiology system—to understand facilitators and barriers to the use of bacterial WGS longitudinally to inform IC workflow. Our team established a 9-month workgroup to study the practical aspects of implementing WGS in routine IC practice. From expert opinion collected via the workgroup, in addition to evidence from the literature, a workflow guidance document and checklist were codified. New ideas included incorporating education to promote the establishment of an IC triage process. Results Facilitators to implementation included ability to display genomic relatedness alongside relevant patient data to enable clinical actionability, ability to pivot time and resources rapidly when infections are a pseudo outbreak (false positive) or missed outbreak (false negative), opportunities for nuanced staff education, and willingness to be a first-of-kind adopter. Barriers were communication of genomic concepts to IC professionals and relevant institutional stakeholders, maintaining sharable notes of active investigations to promote data-sharing practices, and timing and review of relevant interventions into the facility workflow. Strategies to address these issues are considered. Conclusion This study provides a novel framework for adaptation of existing IC workflow strategies to leverage the utility of bacterial WGS, and it presents a schema to effectively engage relevant stakeholders, based on an analysis of the unique challenges inherent within IC practice. It also offers an innovative model for the development and implementation of IC workflows to account for, and adapt to, site-specific conditions. Disclosures All authors: No reported disclosures.


2018 ◽  
Author(s):  
Kim Lee Ng ◽  
Thor Bech Johannesen ◽  
Mark Østerlund ◽  
Kristoffer Kiil ◽  
Paal Skytt Andersen ◽  
...  

AbstractWhole-genome sequencing is becoming the method of choice but provides redundant data for many tasks. ReadFilter (https://github.com/ssi-dk/serum_readfilter) is offered as a way to improve run time of these tasks by rapidly filtering reads against user-specified sequences in order to work with a small fraction of original reads while maintaining accuracy. This can noticeably reduce mapping time and substantially reduce de novo assembly time.


2021 ◽  
Vol 7 (7) ◽  
Author(s):  
Casper Jamin ◽  
Sien De Koster ◽  
Stefanie van Koeveringe ◽  
Dieter De Coninck ◽  
Klaas Mensaert ◽  
...  

Whole-genome sequencing (WGS) is becoming the de facto standard for bacterial typing and outbreak surveillance of resistant bacterial pathogens. However, interoperability for WGS of bacterial outbreaks is poorly understood. We hypothesized that harmonization of WGS for outbreak surveillance is achievable through the use of identical protocols for both data generation and data analysis. A set of 30 bacterial isolates, comprising of various species belonging to the Enterobacteriaceae family and Enterococcus genera, were selected and sequenced using the same protocol on the Illumina MiSeq platform in each individual centre. All generated sequencing data were analysed by one centre using BioNumerics (6.7.3) for (i) genotyping origin of replications and antimicrobial resistance genes, (ii) core-genome multi-locus sequence typing (cgMLST) for Escherichia coli and Klebsiella pneumoniae and whole-genome multi-locus sequencing typing (wgMLST) for all species. Additionally, a split k-mer analysis was performed to determine the number of SNPs between samples. A precision of 99.0% and an accuracy of 99.2% was achieved for genotyping. Based on cgMLST, a discrepant allele was called only in 2/27 and 3/15 comparisons between two genomes, for E. coli and K. pneumoniae, respectively. Based on wgMLST, the number of discrepant alleles ranged from 0 to 7 (average 1.6). For SNPs, this ranged from 0 to 11 SNPs (average 3.4). Furthermore, we demonstrate that using different de novo assemblers to analyse the same dataset introduces up to 150 SNPs, which surpasses most thresholds for bacterial outbreaks. This shows the importance of harmonization of data-processing surveillance of bacterial outbreaks. In summary, multi-centre WGS for bacterial surveillance is achievable, but only if protocols are harmonized.


2021 ◽  
Vol 7 (11) ◽  
Author(s):  
Isabelle Bernaquez ◽  
Christiane Gaudreau ◽  
Pierre A. Pilon ◽  
Sadjia Bekal

Many public health laboratories across the world have implemented whole-genome sequencing (WGS) for the surveillance and outbreak detection of foodborne pathogens. PulseNet-affiliated laboratories have determined that most single-strain foodborne outbreaks are contained within 0–10 multi-locus sequence typing (MLST)-based allele differences and/or core genome single-nucleotide variants (SNVs). In addition to being a food- and travel-associated outbreak pathogen, most Shigella spp. cases occur through continuous person-to-person transmission, predominantly involving men who have sex with men (MSM), leading to long-term and recurrent outbreaks. Continuous transmission patterns coupled to genetic evolution under antibiotic treatment pressure require an assessment of existing WGS-based subtyping methods and interpretation criteria for cluster inclusion/exclusion. An evaluation of 4 WGS-based subtyping methods [SNVPhyl, coreMLST, core genome MLST (cgMLST) and whole-genome MLST (wgMLST)] was performed on 9 foodborne-, travel- and MSM-related retrospective outbreaks from a collection of 91 Shigella flexneri and 232  Shigella sonnei isolates to determine the methods’ epidemiological concordance, discriminatory power, robustness and ability to generate stable interpretation criteria. The discriminatory powers were ranked as follows: coreMLST<SNVPhyl<cgMLST<wgMLST (range: 0.970–1.000). The genetic differences observed for non-MSM-related Shigella spp. outbreaks respect the standard 0–10 allele/SNV guideline; however, mobile genetic element (MGE)-encoded loci caused inflated genetic variation and discrepant phylogenies for prolonged MSM-related S. sonnei outbreaks via wgMLST. The S. sonnei correlation coefficients of wgMLST were also the lowest at 0.680, 0.703 and 0.712 for SNVPhyl, coreMLST and cgMLST, respectively. Plasmid maintenance, mobilization and conjugation-associated genes were found to be the main source of genetic distance inflation in addition to prophage-related genes. Duplicated alleles arising from the repeated nature of IS elements were also responsible for many false cg/wgMLST differences. The coreMLST approach was shown to be the most robust, followed by SNVPhyl and wgMLST for inter-laboratory comparability. Our results highlight the need for validating species-specific subtyping methods based on microbial genome plasticity and outbreak dynamics in addition to the importance of filtering confounding MGEs for cluster detection.


2017 ◽  
Author(s):  
Lennard Epping ◽  
Andries J. van Tonder ◽  
Rebecca A. Gladstone ◽  
Stephen D. Bentley ◽  
Andrew J. Page ◽  
...  

ABSTRACTStreptococcus pneumoniae is responsible for 240,000 - 460,000 deaths in children under 5 years of age each year. Accurate identification of pneumococcal serotypes is important for tracking the distribution and evolution of serotypes following the introduction of effective vaccines. Recent efforts have been made to infer serotypes directly from genomic data but current software approaches are limited and do not scale well. Here, we introduce a novel method, SeroBA, which uses a hybrid assembly and mapping approach. We compared SeroBA against real and simulated data and present results on the concordance and computational performance against a validation dataset, the robustness and scalability when analysing a large dataset, and the impact of varying the depth of coverage in the cps locus region on sequence-based serotyping. SeroBA can predict serotypes, by identifying the cps locus, directly from raw whole genome sequencing read data with 98% concordance using a k-mer based method, can process 10,000 samples in just over 1 day using a standard server and can call serotypes at a coverage as low as 10x. SeroBA is implemented in Python3 and is freely available under an open source GPLv3 license from: https://github.com/sanger-pathogens/seroba.DATA SUMMARYThe reference genome Streptococcus pneumoniae ATCC 700669 is available from National Center for Biotechnology Information (NCBI) with the accession number: FM211187Simulated paired end reads for experiment 2 have been deposited in FigShare: https://doi.org/10.6084/m9.figshare.5086054.v1Accession numbers for all other experiments are listed in Supplementary Table S1 and Supplementary Table S2.I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENTThis article describes SeroBA, a A-mer based method for predicting the serotypes of Streptococcus pneumoniae from Whole Genome Sequencing (WGS) data. SeroBA can identify 92 serotypes and 2 subtypes with constant memory usage and low computational costs. We showed that SeroBA is able to reliably predict serotypes at a depth of coverage as low as 10x and is scalable to large datasets.


2020 ◽  
Vol 6 (7) ◽  
Author(s):  
Bede Constantinides ◽  
Kevin K. Chau ◽  
T. Phuong Quan ◽  
Gillian Rodger ◽  
Monique I. Andersson ◽  
...  

Escherichia coli and Klebsiella spp. are important human pathogens that cause a wide spectrum of clinical disease. In healthcare settings, sinks and other wastewater sites have been shown to be reservoirs of antimicrobial-resistant E. coli and Klebsiella spp., particularly in the context of outbreaks of resistant strains amongst patients. Without focusing exclusively on resistance markers or a clinical outbreak, we demonstrate that many hospital sink drains are abundantly and persistently colonized with diverse populations of E. coli , Klebsiella pneumoniae and Klebsiella oxytoca , including both antimicrobial-resistant and susceptible strains. Using whole-genome sequencing of 439 isolates, we show that environmental bacterial populations are largely structured by ward and sink, with only a handful of lineages, such as E. coli ST635, being widely distributed, suggesting different prevailing ecologies, which may vary as a result of different inputs and selection pressures. Whole-genome sequencing of 46 contemporaneous patient isolates identified one (2 %; 95 % CI 0.05–11 %) E. coli urine infection-associated isolate with high similarity to a prior sink isolate, suggesting that sinks may contribute to up to 10 % of infections caused by these organisms in patients on the ward over the same timeframe. Using metagenomics from 20 sink-timepoints, we show that sinks also harbour many clinically relevant antimicrobial resistance genes including bla CTX-M, bla SHV and mcr, and may act as niches for the exchange and amplification of these genes. Our study reinforces the potential role of sinks in contributing to Enterobacterales infection and antimicrobial resistance in hospital patients, something that could be amenable to intervention. This article contains data hosted by Microreact.


2020 ◽  
Vol 41 (Supplement_1) ◽  
pp. S45-S45
Author(s):  
Irma D Fleming ◽  
Carla Tang ◽  
Lois Remington ◽  
Giavonni Lewis

Abstract Introduction In the wake of Hurricane Maria, many US hospitals experienced massive drug shortages requiring substitution with alternative therapies. Our regional center experienced an increased incidence of Carbapenem-Polymyxin-Quat-Resistant Acinetobacter baumannii(CPQRA) infections, compared to a previous year of no infections. Here we describe a successful interdisciplinary approach to its eradication. Methods We conducted a retrospective review of CPQRA outbreaks for November and December 2018 in the burn ICU. De-identified data was collected and analyzed. In collaboration with the state’s department of health and epidemiology section, whole-genome sequencing was carried out on bacterial isolates. In addition, we instituted adenosine triphosphate (ATP) monitoring on all surfaces, a process of rapidly measuring actively growing microorganisms. Results Resistant Acinetobacter was isolated from five ICU patients, two of whom died with CPQRA bacteremia, producing a case-fatality rate of 40%. The two cases that died both suffered traumatic injuries with multiple fractures in addition to an average TBSA of 58%.Non-fatal cases suffered no other traumatic injuries and had an average TBSA of 51%.During this period, genitourinary irrigant (neomycin-Polymyxin B) and polymyxin ointment were the primary topical agents for wound care. Whole genome sequencing revealed a qacEdelta1 positive strain and identified the primary source as a patient that returned from a long-term care facility carrying the converted A. Baumannii infection. ATP testing also showed increased levels in patient rooms and surgical suite. Conclusions As a result of these findings, we achieved eradication by developing new and reinforcing traditional practices of infection control. This included UV light therapy to all ICU rooms and surgical suite, oversight of environmental services procedures, rigorous enforcement of hospital infection control procedures, auditing hand hygiene, increased efforts in antibiotic stewardshipand discontinuing Polymyxin containing topicals. By January 2019 there were no new cases of CPQRA in the ICU. This study shows that the resistance and rapid spread of CPQRA can be controlled with the cooperation of hospital staff, environmental services, infection control, pharmacy and the state’s department of health. With the coordinated efforts of all parties, we were able to successfully eradicate a virulent and fatal resistant A. baumannii strain. Applicability of Research to Practice Describe an approach to eradicating resistant organisms and provide a roadmap to characterize the source, implement control measures to terminate an outbreak, and institute preventive measures.


2019 ◽  
Vol 85 (23) ◽  
Author(s):  
Shaokang Zhang ◽  
Hendrik C. den Bakker ◽  
Shaoting Li ◽  
Jessica Chen ◽  
Blake A. Dinsmore ◽  
...  

ABSTRACT SeqSero, launched in 2015, is a software tool for Salmonella serotype determination from whole-genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here, we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include (i) additional sequence markers for identification of Salmonella species and subspecies and certain serotypes, (ii) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies, and (iii) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common U.S. serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification. IMPORTANCE Serotyping is the basis of public health surveillance of Salmonella. It remains a first-line subtyping method even as surveillance continues to be transformed by whole-genome sequencing. SeqSero allows the integration of Salmonella serotyping into a whole-genome-sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large-scale surveillance of Salmonella by whole-genome sequencing.


2016 ◽  
Vol 37 (8) ◽  
pp. 987-990 ◽  
Author(s):  
Kalisvar Marimuthu ◽  
Oon Tek Ng ◽  
Wei Xin Khong ◽  
Eryu Xia ◽  
Yik-Ying Teo ◽  
...  

Genetically distinct isolates of New Delhi metallo-β-lactamase (NDM)–producing Enterobacteriaceae were identified from the clinical cultures of 6 patients. Screening of shared-ward contacts identified 2 additional NDM-positive patients. Phylogenetic analysis proved that 1 contact was a direct transmission while the other was unrelated to the index, suggesting hidden routes of transmission.Infect Control Hosp Epidemiol 2016;37:987–990


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