Evaluation of Molecular Methods for Identification of Salmonella Serovars

Classification by serotyping is the essential first step in the characterization ofSalmonellaisolates and is important for surveillance, source tracking, and outbreak detection. To improve detection and reduce the burden of salmonellosis, several rapid and high-throughput molecularSalmonellaserotyping methods have been developed.The aim of this study was to compare three commercial kits, Salm SeroGen (Salm Sero-Genotyping AS-1 kit), Check&Trace (Check-Points), and xMAP (xMAPSalmonellaserotyping assay), to theSalmonellagenoserotyping array (SGSA) developed by our laboratory. They were assessed using a panel of 321 isolates that represent commonly reported serovars from human and nonhuman sources globally. The four methods correctly identified 73.8% to 94.7% of the isolates tested. The methods correctly identified 85% and 98% of the clinically importantSalmonellaserovars Enteritidis and Typhimurium, respectively. The methods correctly identified 75% to 100% of the nontyphoidal, broad host rangeSalmonellaserovars, including Heidelberg, Hadar, Infantis, Kentucky, Montevideo, Newport, and Virchow. The sensitivity and specificity ofSalmonellaserovars Typhimurium and Enteritidis ranged from 85% to 100% and 99% to 100%, respectively.It is anticipated that whole-genome sequencing will replace serotyping in public health laboratories in the future. However, at present, it is approximately three times more expensive than molecular methods. Until consistent standards and methodologies are deployed for whole-genome sequencing, data analysis and interlaboratory comparability remain a challenge. The use of molecular serotyping will provide a valuable high-throughput alternative to traditional serotyping. This comprehensive analysis provides a detailed comparison of commercial kits available for the molecular serotyping ofSalmonella.

Download Full-text

Evaluation of whole-genome sequencing-based subtyping methods for the surveillance of Shigella spp. and the confounding effect of mobile genetic elements in long-term outbreaks

Microbial Genomics ◽

10.1099/mgen.0.000672 ◽

2021 ◽

Vol 7 (11) ◽

Author(s):

Isabelle Bernaquez ◽

Christiane Gaudreau ◽

Pierre A. Pilon ◽

Sadjia Bekal

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Type Species ◽

Core Genome ◽

Outbreak Detection ◽

Whole Genome ◽

Content Type ◽

Link Type ◽

Interpretation Criteria

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.

Download Full-text

Prospective Whole-Genome Sequencing Enhances National Surveillance of Listeria monocytogenes

Journal of Clinical Microbiology ◽

10.1128/jcm.02344-15 ◽

2015 ◽

Vol 54 (2) ◽

pp. 333-342 ◽

Cited By ~ 130

Author(s):

Jason C. Kwong ◽

Karolina Mercoulia ◽

Takehiro Tomita ◽

Marion Easton ◽

Hua Y. Li ◽

...

Keyword(s):

Listeria Monocytogenes ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Variable Number Tandem Repeat ◽

Variable Number ◽

Outbreak Detection ◽

Whole Genome ◽

Genetic Population ◽

Content Type ◽

Epidemiologic Surveillance

Whole-genome sequencing (WGS) has emerged as a powerful tool for comparing bacterial isolates in outbreak detection and investigation. Here we demonstrate that WGS performed prospectively for national epidemiologic surveillance ofListeria monocytogeneshas the capacity to be superior to our current approaches using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), multilocus variable-number tandem-repeat analysis (MLVA), binary typing, and serotyping. Initially 423L. monocytogenesisolates underwent WGS, and comparisons uncovered a diverse genetic population structure derived from three distinct lineages. MLST, binary typing, and serotyping results inferredin silicofrom the WGS data were highly concordant (>99%) with laboratory typing performed in parallel. However, WGS was able to identify distinct nested clusters within groups of isolates that were otherwise indistinguishable using our current typing methods. Routine WGS was then used for prospective epidemiologic surveillance on a further 97L. monocytogenesisolates over a 12-month period, which provided a greater level of discrimination than that of conventional typing for inferring linkage to point source outbreaks. A risk-based alert system based on WGS similarity was used to inform epidemiologists required to act on the data. Our experience shows that WGS can be adopted for prospectiveL. monocytogenessurveillance and investigated for other pathogens relevant to public health.

Download Full-text

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

Journal of Clinical Microbiology ◽

10.1128/jcm.00017-17 ◽

2017 ◽

Vol 55 (5) ◽

pp. 1269-1275 ◽

Cited By ~ 35

Author(s):

Ann-Katrin Llarena ◽

Eduardo Taboada ◽

Mirko Rossi

Keyword(s):

Whole Genome Sequencing ◽

Campylobacter Jejuni ◽

Genome Sequencing ◽

Outbreak Detection ◽

Whole Genome ◽

Ample Evidence ◽

Content Type ◽

Routine Monitoring ◽

Outbreak Investigations ◽

Bacterial Gastroenteritis

ABSTRACT This review describes the current state of knowledge regarding the application of whole-genome sequencing (WGS) in the epidemiology of Campylobacter jejuni , the leading cause of bacterial gastroenteritis worldwide. We describe how WGS has increased our understanding of the evolutionary and epidemiological dynamics of this pathogen and how WGS has the potential to improve surveillance and outbreak detection. We have identified hurdles to the full implementation of WGS in public health settings. Despite these challenges, we think that ample evidence is available to support the benefits of integrating WGS into the routine monitoring of C. jejuni infections and outbreak investigations.

Download Full-text

Utility of Whole-Genome Sequencing of Escherichia coli O157 for Outbreak Detection and Epidemiological Surveillance

Journal of Clinical Microbiology ◽

10.1128/jcm.01066-15 ◽

2015 ◽

Vol 53 (11) ◽

pp. 3565-3573 ◽

Cited By ~ 48

Author(s):

Anne Holmes ◽

Lesley Allison ◽

Melissa Ward ◽

Timothy J. Dallman ◽

Richard Clark ◽

...

Keyword(s):

Escherichia Coli ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Outbreak Detection ◽

Epidemiological Surveillance ◽

Personal Genome ◽

Whole Genome ◽

Content Type ◽

E Coli ◽

Antimicrobial Resistance Genes

Detailed laboratory characterization ofEscherichia coliO157 is essential to inform epidemiological investigations. This study assessed the utility of whole-genome sequencing (WGS) for outbreak detection and epidemiological surveillance ofE. coliO157, and the data were used to identify discernible associations between genotypes and clinical outcomes. One hundred fiveE. coliO157 strains isolated over a 5-year period from human fecal samples in Lothian, Scotland, were sequenced with the Ion Torrent Personal Genome Machine. A total of 8,721 variable sites in the core genome were identified among the 105 isolates; 47% of the single nucleotide polymorphisms (SNPs) were attributable to six “atypical”E. coliO157 strains and included recombinant regions. Phylogenetic analyses showed that WGS correlated well with the epidemiological data. Epidemiological links existed between cases whose isolates differed by three or fewer SNPs. WGS also correlated well with multilocus variable-number tandem repeat analysis (MLVA) typing data, with only three discordant results observed, all among isolates from cases not known to be epidemiologically related. WGS produced a better-supported, higher-resolution phylogeny than MLVA, confirming that the method is more suitable for epidemiological surveillance ofE. coliO157. A combination ofinsilicoanalyses (VirulenceFinder, ResFinder, and local BLAST searches) were used to determinestxsubtypes, multilocus sequence types (15 loci), and the presence of virulence and acquired antimicrobial resistance genes. There was a high level of correlation between the WGS data and our routine typing methods, although some discordant results were observed, mostly related to the limitation of short sequence read assembly. The data were used to identify sublineages and clades ofE. coliO157, and when they were correlated with the clinical outcome data, they showed that one clade, Ic3, was significantly associated with severe disease. Together, the results show that WGS data can provide higher resolution of the relationships betweenE. coliO157 isolates than that provided by MLVA. The method has the potential to streamline the laboratory workflow and provide detailed information for the clinical management of patients and public health interventions.

Download Full-text

Rapid and EasyIn SilicoSerotyping of Escherichia coli Isolates by Use of Whole-Genome Sequencing Data

Journal of Clinical Microbiology ◽

10.1128/jcm.00008-15 ◽

2015 ◽

Vol 53 (8) ◽

pp. 2410-2426 ◽

Cited By ~ 309

Author(s):

Katrine G. Joensen ◽

Anna M. M. Tetzschner ◽

Atsushi Iguchi ◽

Frank M. Aarestrup ◽

Flemming Scheutz

Keyword(s):

Escherichia Coli ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Antigen Processing ◽

Processing System ◽

Outbreak Detection ◽

Whole Genome ◽

Content Type ◽

E Coli ◽

O Antigen

Accurate and rapid typing of pathogens is essential for effective surveillance and outbreak detection. Conventional serotyping ofEscherichia coliis a delicate, laborious, time-consuming, and expensive procedure. With whole-genome sequencing (WGS) becoming cheaper, it has vast potential in routine typing and surveillance. The aim of this study was to establish a valid and publicly available tool for WGS-basedin silicoserotyping ofE. coliapplicable for routine typing and surveillance. A FASTA database of specific O-antigen processing system genes for O typing and flagellin genes for H typing was created as a component of the publicly available Web tools hosted by the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org). AllE. coliisolates available with WGS data and conventional serotype information were subjected to WGS-based serotyping employing this specific SerotypeFinder CGE tool. SerotypeFinder was evaluated on 682E. coligenomes, 108 of which were sequenced for this study, where both the whole genome and the serotype were available. In total, 601 and 509 isolates were included for O and H typing, respectively. The O-antigen geneswzx,wzy,wzm, andwztand the flagellin genesfliC,flkA,fllA,flmA, andflnAwere detected in 569 and 508 genome sequences, respectively. SerotypeFinder for WGS-based O and H typing predicted 560 of 569 O types and 504 of 508 H types, consistent with conventional serotyping. In combination with other available WGS typing tools,E. coliserotyping can be performed solely from WGS data, providing faster and cheaper typing than current routine procedures and making WGS typing a superior alternative to conventional typing strategies.

Download Full-text

Evaluation of Whole Genome Sequencing for outbreak detection of Salmonella enterica serovar Enteritidis

10.26226/morressier.5f4ccc57648d3d8b3f362bad ◽

2020 ◽

Author(s):

Ainhoa Arrieta-Gisasola ◽

Aitor Atxaerandio Landa ◽

Javier Garaizar ◽

Joseba Bikandi ◽

José Karkamo ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Salmonella Enterica ◽

Outbreak Detection ◽

Whole Genome ◽

Salmonella Enterica Serovar Enteritidis

Download Full-text

Expanding U.S. Laboratory Capacity for Neisseria gonorrhoeae Antimicrobial Susceptibility Testing and Whole-Genome Sequencing through the CDC's Antibiotic Resistance Laboratory Network

Journal of Clinical Microbiology ◽

10.1128/jcm.01461-19 ◽

2020 ◽

Vol 58 (4) ◽

Cited By ~ 2

Author(s):

Ellen N. Kersh ◽

Cau D. Pham ◽

John R. Papp ◽

Robert Myers ◽

Richard Steece ◽

...

Keyword(s):

Public Health ◽

Antibiotic Resistance ◽

Neisseria Gonorrhoeae ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Antimicrobial Susceptibility ◽

Susceptibility Testing ◽

Whole Genome ◽

Content Type ◽

Laboratory Capacity

ABSTRACT U.S. gonorrhea rates are rising, and antibiotic-resistant Neisseria gonorrhoeae (AR-Ng) is an urgent public health threat. Since implementation of nucleic acid amplification tests for N. gonorrhoeae identification, the capacity for culturing N. gonorrhoeae in the United States has declined, along with the ability to perform culture-based antimicrobial susceptibility testing (AST). Yet AST is critical for detecting and monitoring AR-Ng. In 2016, the CDC established the Antibiotic Resistance Laboratory Network (AR Lab Network) to shore up the national capacity for detecting several resistance threats including N. gonorrhoeae. AR-Ng testing, a subactivity of the CDC’s AR Lab Network, is performed in a tiered network of approximately 35 local laboratories, four regional laboratories (state public health laboratories in Maryland, Tennessee, Texas, and Washington), and the CDC’s national reference laboratory. Local laboratories receive specimens from approximately 60 clinics associated with the Gonococcal Isolate Surveillance Project (GISP), enhanced GISP (eGISP), and the program Strengthening the U.S. Response to Resistant Gonorrhea (SURRG). They isolate and ship up to 20,000 isolates to regional laboratories for culture-based agar dilution AST with seven antibiotics and for whole-genome sequencing of up to 5,000 isolates. The CDC further examines concerning isolates and monitors genetic AR markers. During 2017 and 2018, the network tested 8,214 and 8,628 N. gonorrhoeae isolates, respectively, and the CDC received 531 and 646 concerning isolates and 605 and 3,159 sequences, respectively. In summary, the AR Lab Network supported the laboratory capacity for N. gonorrhoeae AST and associated genetic marker detection, expanding preexisting notification and analysis systems for resistance detection. Continued, robust AST and genomic capacity can help inform national public health monitoring and intervention.

Download Full-text

A common protocol for the simultaneous processing of multiple clinically relevant bacterial species for whole genome sequencing

Scientific Reports ◽

10.1038/s41598-020-80031-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kathy E. Raven ◽

Sophia T. Girgis ◽

Asha Akram ◽

Beth Blane ◽

Danielle Leek ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Dna Extraction ◽

Genome Sequencing ◽

Clinical Microbiology ◽

Bacterial Species ◽

Outbreak Detection ◽

Whole Genome ◽

Library Preparation ◽

Simultaneous Processing ◽

Antimicrobial Resistance Gene

AbstractWhole-genome sequencing is likely to become increasingly used by local clinical microbiology laboratories, where sequencing volume is low compared with national reference laboratories. Here, we describe a universal protocol for simultaneous DNA extraction and sequencing of numerous different bacterial species, allowing mixed species sequence runs to meet variable laboratory demand. We assembled test panels representing 20 clinically relevant bacterial species. The DNA extraction process used the QIAamp mini DNA kit, to which different combinations of reagents were added. Thereafter, a common protocol was used for library preparation and sequencing. The addition of lysostaphin, lysozyme or buffer ATL (a tissue lysis buffer) alone did not produce sufficient DNA for library preparation across the species tested. By contrast, lysozyme plus lysostaphin produced sufficient DNA across all 20 species. DNA from 15 of 20 species could be extracted from a 24-h culture plate, while the remainder required 48–72 h. The process demonstrated 100% reproducibility. Sequencing of the resulting DNA was used to recapitulate previous findings for species, outbreak detection, antimicrobial resistance gene detection and capsular type. This single protocol for simultaneous processing and sequencing of multiple bacterial species supports low volume and rapid turnaround time by local clinical microbiology laboratories.

Download Full-text

Tracing Melioidosis Back to the Source: Using Whole-Genome Sequencing To Investigate an Outbreak Originating from a Contaminated Domestic Water Supply

Journal of Clinical Microbiology ◽

10.1128/jcm.03453-14 ◽

2015 ◽

Vol 53 (4) ◽

pp. 1144-1148 ◽

Cited By ~ 18

Author(s):

Evan McRobb ◽

Derek S. Sarovich ◽

Erin P. Price ◽

Mirjam Kaestli ◽

Mark Mayo ◽

...

Keyword(s):

Water Supply ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Clinical Isolates ◽

Whole Genome ◽

Northern Australia ◽

Source Attribution ◽

Environmental Strain ◽

Content Type ◽

Groundwater Supply

Melioidosis, a disease of public health importance in Southeast Asia and northern Australia, is caused by the Gram-negative soil bacillusBurkholderia pseudomallei. Melioidosis is typically acquired through environmental exposure, and case clusters are rare, even in regions where the disease is endemic.B. pseudomalleiis classed as a tier 1 select agent by the Centers for Disease Control and Prevention; from a biodefense perspective, source attribution is vital in an outbreak scenario to rule out a deliberate release. Two cases of melioidosis within a 3-month period at a residence in rural northern Australia prompted an investigation to determine the source of exposure.B. pseudomalleiisolates from the property's groundwater supply matched the multilocus sequence type of the clinical isolates. Whole-genome sequencing confirmed the water supply as the probable source of infection in both cases, with the clinical isolates differing from the likely infecting environmental strain by just one single nucleotide polymorphism (SNP) each. For the first time, we report a phylogenetic analysis of genomewide insertion/deletion (indel) data, an approach conventionally viewed as problematic due to high mutation rates and homoplasy. Our whole-genome indel analysis was concordant with the SNP phylogeny, and these two combined data sets provided greater resolution and a better fit with our epidemiological chronology of events. Collectively, this investigation represents a highly accurate account of source attribution in a melioidosis outbreak and gives further insight into a frequently overlooked reservoir ofB. pseudomallei. Our methods and findings have important implications for outbreak source tracing of this bacterium and other highly recombinogenic pathogens.

Download Full-text

Whole-Genome Sequencing for Bacterial Strain Typing Using the iSeq100 Platform

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1098 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s434-s434

Author(s):

Grant Vestal ◽

Steven Bruzek ◽

Amanda Lasher ◽

Amorce Lima ◽

Suzane Silbert

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Outbreak Detection ◽

Epidemiological Surveillance ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Dna Libraries ◽

Patient Health ◽

Hospital Acquired ◽

Reference Genomes

Background: Hospital-acquired infections pose a significant threat to patient health. Laboratories are starting to consider whole-genome sequencing (WGS) as a molecular method for outbreak detection and epidemiological surveillance. The objective of this study was to assess the use of the iSeq100 platform (Illumina, San Diego, CA) for accurate sequencing and WGS-based outbreak detection using the bioMérieux EPISEQ CS, a novel cloud-based software for sequence assembly and data analysis. Methods: In total, 25 isolates, including 19 MRSA isolates and 6 ATCC strains were evaluated in this study: A. baumannii ATCC 19606, B. cepacia ATCC 25416, E. faecalis ATCC 29212, E. coli ATCC 25922, P. aeruginosa ATCC 27853 and S. aureus ATCC 25923. DNA extraction of all isolates was performed on the QIAcube (Qiagen, Hilden, Germany) using the DNEasy Ultra Clean Microbial kit extraction protocol. DNA libraries were prepared for WGS using the Nextera DNA Flex Library Prep Kit (Illumina) and sequenced at 2×150-bp on the iSeq100 according to the manufacturer’s instructions. The 19 MRSA isolates were previously characterized by the DiversiLab system (bioMérieux, France). Upon validation of the iSeq100 platform, a new outbreak analysis was performed using WGS analysis using EPISEQ CS. ATCC sequences were compared to assembled reference genomes from the NCBI GenBank to assess the accuracy of the iSeq100 platform. The FASTQ files were aligned via BowTie2 version 2.2.6 software, using default parameters, and FreeBayes version 1.1.0.46-0 was used to call homozygous single-nucleotide polymorphisms (SNPs) with a minimum coverage of 5 and an allele frequency of 0.87 using default parameters. ATCC sequences were analyzed using ResFinder version 3.2 and were compared in silico to the reference genome. Results: EPISEQ CS classified 8 MRSA isolates as unrelated and grouped 11 isolates into 2 separate clusters: cluster A (5 isolates) and cluster B (6 isolates) with similarity scores of ≥99.63% and ≥99.50%, respectively. This finding contrasted with the previous characterization by DiversiLab, which identified 3 clusters of 2, 8, and 11 isolates, respectively. The EPISEQ CS resistome data detected the mecA gene in 18 of 19 MRSA isolates. Comparative analysis of the ATCCsequences to the reference genomes showed 99.9986% concordance of SNPs and 100.00% concordance between the resistance genes present. Conclusions: The iSeq100 platform accurately sequenced the bacterial isolates and could be an affordable alternative in conjunction with EPISEQ CS for epidemiological surveillance analysis and infection prevention.Funding: NoneDisclosures: None

Download Full-text