Loss and Gain in the Evolution of theSalmonella entericaSerovar Gallinarum Biovar Pullorum Genome

ABSTRACTSalmonella entericasubspeciesentericaserovar Gallinarum biovar Pullorum (S. Pullorum) is the etiological agent of pullorum disease, causing white diarrhea with high mortality in chickens. There are many unsolved issues surrounding the epidemiology ofS. Pullorum, including its origin and transmission history as well as the discordance between its phenotypic heterogeneity and genetic monomorphism. In this paper, we report the results of whole-genome sequencing of a panel of 97S. Pullorum strains isolated between 1962 and 2014 from four countries across three continents. We utilized 6,795 core genome single nucleotide polymorphisms (SNPs) to reconstruct a phylogenetic tree within a spatiotemporal Bayesian framework, estimating that the most recent common ancestor ofS. Pullorum emerged in ∼914 CE (95% confidence interval [95%CI], 565 to 1273 CE). The extantS. Pullorum strains can be divided into four distinct lineages, each of which is significantly associated with geographical distribution. The intercontinental transmissions of lineages III and IV can be traced to the mid-19th century and are probably related to the “Hen Fever” prevalent at that time. Further genomic analysis indicated that the loss or pseudogenization of functional genes involved in metabolism and virulence inS. Pullorum has been ongoing since before and after divergence from the ancestor. In contrast, multiple prophages and plasmids have been acquired byS. Pullorum, and these have endowed it with new characteristics, especially the multidrug resistance conferred by two large plasmids in lineage I. The results of this study provide insight into the evolution ofS. Pullorum and prove the efficiency of whole-genome sequencing in epidemiological surveillance of pullorum disease.IMPORTANCEPullorum disease, an acute poultry septicemia caused bySalmonellaGallinarum biovar Pullorum, is fatal for young chickens and is a heavy burden on poultry industry. The pathogen is rare in most developed countries but still extremely difficult to eliminate in China. Efficient epidemiological surveillance necessitates clarifying the origin of the isolates from different regions and their phylogenic relationships. Genomic epidemiological analysis of 97S. Pullorum strains was carried out to reconstruct the phylogeny and transmission history ofS. Pullorum. Further analysis demonstrated that functional gene loss and acquisition occurred simultaneously throughout the evolution ofS. Pullorum, both of which reflected adaptation to the changing environment. The result of our study will be helpful in surveillance and prevention of pullorum disease.

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Whole genome sequencing reveals the emergence of aPseudomonas aeruginosashared strain sub-lineage among patients treated within a single cystic fibrosis centre

10.1101/261586 ◽

2018 ◽

Cited By ~ 1

Author(s):

Bryan A. Wee ◽

Anna S. Tai ◽

Laura J. Sherrard ◽

Nouri L. Ben Zakour ◽

Kirt R. Hanks ◽

...

Keyword(s):

Cystic Fibrosis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Common Ancestor ◽

Recent Common Ancestor ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Short Branch ◽

Synonymous Mutations ◽

Most Recent Common Ancestor

AbstractBackgroundChronic lung infections byPseudomonas aeruginosaare a significant cause of morbidity and mortality in people with cystic fibrosis (CF). SharedP. aeruginosastrains, that can be transmitted between patients, are of concern and in Australia the AUST-02 shared strain is predominant in individuals attending CF centres in Queensland and Western Australia. M3L7 is a multidrug resistant sub-type of AUST-02 that was recently identified in a Queensland CF centre and was shown to be associated with poorer clinical outcomes. The main aim of this study was to resolve the relationship of the emergent M3L7 sub-type within the AUST-02 group of strains using whole genome sequencing.ResultsA whole-genome core phylogeny of 63 isolates indicated that M3L7 is a monophyletic sub-lineage within the context of the broader AUST-02 group. Relatively short branch lengths connected all of the M3L7 isolates. A phylogeny based on nucleotide polymorphisms present across the genome showed that the chronological estimation of the most recent common ancestor was around 2001 (± 3 years). SNP differences between sequential M3L7 isolates collected 3-4 years apart from five patients suggested both continuous infection of the same strain and cross-infection of some M3L7 variants between patients. The majority of polymorphisms that were characteristic of M3L7 (i.e. acquired after divergence from all other AUST-02 isolates sequenced) were found to produce non-synonymous mutations in virulence and antibiotic resistance genes.ConclusionsM3L7 has recently diverged from a common ancestor indicating descent from a single carrier at a CF treatment centre in Australia. Both adaptation to the lung and transmission of M3L7 between adults attending this centre may have contributed to its rapid dissemination. The study emphasises the importance of clinical management in controlling the emergence of shared strains in CF.

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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

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Population Structure of Mycobacterium bovis in Germany: a Long-Term Study Using Whole-Genome Sequencing Combined with Conventional Molecular Typing Methods

Journal of Clinical Microbiology ◽

10.1128/jcm.01573-20 ◽

2020 ◽

Vol 58 (11) ◽

Author(s):

Thomas A. Kohl ◽

Katharina Kranzer ◽

Sönke Andres ◽

Thierry Wirth ◽

Stefan Niemann ◽

...

Keyword(s):

Population Structure ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Mycobacterium Bovis ◽

Variable Number Tandem Repeat ◽

Epidemiological Surveillance ◽

Whole Genome ◽

Content Type ◽

Long Term Study ◽

Wide Range

ABSTRACT Mycobacterium bovis is the primary cause of bovine tuberculosis (bTB) and infects a wide range of domestic animal and wildlife species and humans. In Germany, bTB still emerges sporadically in cattle herds, free-ranging wildlife, diverse captive animal species, and humans. In order to understand the underlying population structure and estimate the population size fluctuation through time, we analyzed 131 M. bovis strains from animals (n = 38) and humans (n = 93) in Germany from 1999 to 2017 by whole-genome sequencing (WGS), mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) typing, and spoligotyping. Based on WGS data analysis, 122 out of the 131 M. bovis strains were classified into 13 major clades, of which 6 contained strains from both human and animal cases and 7 only strains from human cases. Bayesian analyses suggest that the M. bovis population went through two sharp anticlimaxes, one in the middle of the 18th century and another one in the 1950s. WGS-based cluster analysis grouped 46 strains into 13 clusters ranging in size from 2 to 11 members and involving strains from distinct host types, e.g., only cattle and also mixed hosts. Animal strains of four clusters were obtained over a 9-year span, pointing toward autochthonous persistent bTB infection cycles. As expected, WGS had a higher discriminatory power than spoligotyping and MIRU-VNTR typing. In conclusion, our data confirm that WGS and suitable bioinformatics constitute the method of choice to implement prospective molecular epidemiological surveillance of M. bovis. The population of M. bovis in Germany is diverse, with subtle, but existing, interactions between different host groups.

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Whole-Genome Sequencing Reveals the Contribution of Long-Term Carriers in Staphylococcus aureus Outbreak Investigation

Journal of Clinical Microbiology ◽

10.1128/jcm.00363-17 ◽

2017 ◽

Vol 55 (7) ◽

pp. 2188-2197 ◽

Cited By ~ 17

Author(s):

N. C. Gordon ◽

B. Pichon ◽

T. Golubchik ◽

D. J. Wilson ◽

J. Paul ◽

...

Keyword(s):

Staphylococcus Aureus ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Recent Common Ancestor ◽

Whole Genome ◽

Epidemiological Evidence ◽

Host Diversity ◽

Most Recent Common Ancestor ◽

Highest Posterior Density

ABSTRACTWhole-genome sequencing (WGS) makes it possible to determine the relatedness of bacterial isolates at a high resolution, thereby helping to characterize outbreaks. However, forStaphylococcus aureus, the accumulation of within-host diversity during carriage might limit the interpretation of sequencing data. In this study, we hypothesized the converse, namely, that within-host diversity can in fact be exploited to reveal the involvement of long-term carriers (LTCs) in outbreaks. We analyzed WGS data from 20 historical outbreaks and applied phylogenetic methods to assess genetic relatedness and to estimate the time to most recent common ancestor (TMRCA). The findings were compared with the routine investigation results and epidemiological evidence. Outbreaks with epidemiological evidence for an LTC source had a mean estimated TMRCA (adjusted for outbreak duration) of 243 days (95% highest posterior density interval [HPD], 143 to 343 days) compared with 55 days (95% HPD, 28 to 81 days) for outbreaks lacking epidemiological evidence for an LTC (P= 0.004). A threshold of 156 days predicted LTC involvement with a sensitivity of 0.875 and a specificity of 1. We also found 6/20 outbreaks included isolates with differing antimicrobial susceptibility profiles; however, these had only modestly increased pairwise diversity (mean 17.5 single nucleotide variants [SNVs] [95% confidence interval {CI}, 17.3 to 17.8]) compared with isolates with identical antibiograms (12.7 SNVs [95% CI, 12.5 to 12.8]) (P< 0.0001). Additionally, for 2 outbreaks, WGS identified 1 or more isolates that were genetically distinct despite having the outbreak pulsed-field gel electrophoresis (PFGE) pulsotype. The duration-adjusted TMRCA allowed the involvement of LTCs in outbreaks to be identified and could be used to decide whether screening for long-term carriage (e.g., in health care workers) is warranted. Requiring identical antibiograms to trigger investigation could miss important contributors to outbreaks.

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Neisseria gonorrhoeae clustering to reveal major European whole-genome-sequencing-based genogroups in association with antimicrobial resistance

Microbial Genomics ◽

10.1099/mgen.0.000481 ◽

2020 ◽

Author(s):

Miguel Pinto ◽

Vítor Borges ◽

Joana Isidro ◽

João Carlos Rodrigues ◽

Luís Vieira ◽

...

Keyword(s):

Antimicrobial Resistance ◽

Neisseria Gonorrhoeae ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Type Species ◽

Transmitted Disease ◽

Epidemiological Surveillance ◽

Whole Genome ◽

Content Type ◽

Link Type

Neisseria gonorrhoeae , the bacterium responsible for the sexually transmitted disease gonorrhoea, has shown an extraordinary ability to develop antimicrobial resistance (AMR) to multiple classes of antimicrobials. With no available vaccine, managing N. gonorrhoeae infections demands effective preventive measures, antibiotic treatment and epidemiological surveillance. The latter two are progressively being supported by the generation of whole-genome sequencing (WGS) data on behalf of national and international surveillance programmes. In this context, this study aims to perform N. gonorrhoeae clustering into genogroups based on WGS data, for enhanced prospective laboratory surveillance. Particularly, it aims to identify the major circulating WGS-genogroups in Europe and to establish a relationship between these and AMR. Ultimately, it enriches public databases by contributing with WGS data from Portuguese isolates spanning 15 years of surveillance. A total of 3791 carefully inspected N. gonorrhoeae genomes from isolates collected across Europe were analysed using a gene-by-gene approach (i.e. using cgMLST). Analysis of cluster composition and stability allowed the classification of isolates into a two-step hierarchical genogroup level determined by two allelic distance thresholds revealing cluster stability. Genogroup clustering in general agreed with available N. gonorrhoeae typing methods [i.e. MLST (multilocus sequence typing), NG-MAST ( N. gonorrhoeae multi-antigen sequence typing) and PubMLST core-genome groups], highlighting the predominant genogroups circulating in Europe, and revealed that the vast majority of the genogroups present a dominant AMR profile. Additionally, a non-static gene-by-gene approach combined with a more discriminatory threshold for potential epidemiological linkage enabled us to match data with previous reports on outbreaks or transmission chains. In conclusion, this genogroup assignment allows a comprehensive analysis of N. gonorrhoeae genetic diversity and the identification of the WGS-based genogroups circulating in Europe, while facilitating the assessment (and continuous monitoring) of their frequency, geographical dispersion and potential association with specific AMR signatures. This strategy may benefit public-health actions through the prioritization of genogroups to be controlled, the identification of emerging resistance carriage, and the potential facilitation of data sharing and communication.

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Utility of Whole-Genome Sequencing in Characterizing Acinetobacter Epidemiology and Analyzing Hospital Outbreaks

Journal of Clinical Microbiology ◽

10.1128/jcm.01818-15 ◽

2015 ◽

Vol 54 (3) ◽

pp. 593-612 ◽

Cited By ~ 44

Author(s):

Margaret A. Fitzpatrick ◽

Egon A. Ozer ◽

Alan R. Hauser

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Phylogenetic Trees ◽

Acinetobacter Calcoaceticus ◽

Whole Genome ◽

Strain Typing ◽

Nucleotide Polymorphisms ◽

Content Type ◽

Carbapenem Resistant ◽

Outbreak Investigations

Acinetobacter baumanniifrequently 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 clinicalAcinetobacterisolates and analyzing a carbapenem-resistantA. 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 148Acinetobacter calcoaceticus-A. baumanniicomplex bloodstream isolates collected from a single hospital from 2005 to 2012. Phylogenetic trees inferred from core-genome single nucleotide polymorphisms (SNPs) confirmed threeAcinetobacterspecies within this collection. Four majorA. baumanniiclonal 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 distinguishedA. baumanniiisolates 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 forA. baumanniistrain typing and outbreak analysis. These findings support the incorporation of WGS into health care infection prevention efforts.

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Salmonella entericaPhylogeny Based on Whole-Genome Sequencing Reveals Two New Clades and Novel Patterns of Horizontally Acquired Genetic Elements

mBio ◽

10.1128/mbio.02303-18 ◽

2018 ◽

Vol 9 (6) ◽

Cited By ~ 24

Author(s):

Jay Worley ◽

Jianghong Meng ◽

Marc W. Allard ◽

Eric W. Brown ◽

Ruth E. Timme

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Foodborne Pathogens ◽

Bacterial Species ◽

Whole Genome Sequence ◽

Nucleotide Sequencing ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Content Type ◽

Genetic Elements

ABSTRACTUsing whole-genome sequence (WGS) data from the GenomeTrakr network, a globally distributed network of laboratories sequencing foodborne pathogens, we present a new phylogeny ofSalmonella entericacomprising 445 isolates from 266 distinct serovars and originating from 52 countries. This phylogeny includes two previously unidentifiedS. entericasubsp.entericaclades. Serovar Typhi is shown to be nested within clade A. Our findings are supported by both phylogenetic support, based on a core genome alignment, and Bayesian approaches, based on single-nucleotide polymorphisms. Serovar assignments were refined byin silicoanalysis using SeqSero. More than 10% of serovars were either polyphyletic or paraphyletic. We found variable genetic content in these isolates relating to gene mobilization and virulence factors which have different distributions within clades. Gifsy-1- and Gifsy-2-like phages appear more prevalent in clade A; other viruses are more evenly distributed. Our analyses reveal IncFII is the predominant plasmid replicon inS. enterica. Few core or clade-defining virulence genes are observed, and their distributions appear probabilistic in nature. Together, these patterns demonstrate that genetic exchange withinS. entericais more extensive and frequent than previously realized, which significantly alters how we view the genetic structure of the bacterial species.IMPORTANCERapid improvements in nucleotide sequencing access and affordability have led to a drastic increase in availability of genetic information. This information will improve the accuracy of molecular descriptions, including serovars, withinS. enterica. Although the concept of serovars continues to be useful, it may have more significant limitations than previously understood. Furthermore, the discrete absence or presence of specific genes can be an unstable indicator of phylogenetic identity. Whole-genome sequencing provides more rigorous tools for assessing the distributions of these genes. Our phylogenetic and genetic content analyses reveal how active genetic elements are dynamically distributed within a species, allowing us to better understand genetic reservoirs and underlying bacterial evolution.

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Genomic Analysis Reveals Antibiotic-Susceptible Clones and Emerging Resistance in Neisseria gonorrhoeae in Saskatchewan, Canada

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.02514-19 ◽

2020 ◽

Vol 64 (9) ◽

Author(s):

Nidhi R. Parmar ◽

Reema Singh ◽

Irene Martin ◽

Sumudu R. Perera ◽

Walter Demczuk ◽

...

Keyword(s):

Antibiotic Resistance ◽

Neisseria Gonorrhoeae ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genomic Analysis ◽

Phylogenomic Analysis ◽

Whole Genome ◽

Content Type ◽

Clonal Spread

ABSTRACT Whole-genome sequencing was used to identify mutations in antibiotic resistance-conferring genes to compare susceptibility predictions with MICs and to ascertain strain types in 99 isolates of Neisseria gonorrhoeae. Genotypes associated with susceptibility, as well as MIC creep or emerging resistance, were noted. Phylogenomic analysis revealed three distinctive clades and putative gonococcal transmission linkages involving a tetracycline-resistant N. gonorrhoeae outbreak and the clonal spread of susceptible isolates in men.

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Evolution of Carbapenem-Resistant Acinetobacter baumannii Revealed through Whole-Genome Sequencing and Comparative Genomic Analysis

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.04609-14 ◽

2014 ◽

Vol 59 (2) ◽

pp. 1168-1176 ◽

Cited By ~ 23

Author(s):

Henan Li ◽

Fei Liu ◽

Yawei Zhang ◽

Xiaojuan Wang ◽

Chunjiang Zhao ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Acinetobacter Baumannii ◽

Genome Sequencing ◽

Resistance Genes ◽

Genomic Analysis ◽

Comparative Genomic Analysis ◽

Comparative Genomic ◽

Whole Genome ◽

Content Type ◽

Carbapenem Resistant

ABSTRACTAcinetobacter baumanniiis a globally important nosocomial pathogen characterized by an evolving multidrug resistance. A total of 35 representative clinicalA. baumanniistrains isolated from 13 hospitals in nine cities in China from 1999 to 2011, including 32 carbapenem-resistant and 3 carbapenem-susceptibleA. baumanniistrains, were selected for whole-genome sequencing and comparative genomic analysis. Phylogenetic analysis revealed that the earliest strain, strain 1999BJAB11, and two strains isolated in Zhejiang Province in 2004 were the founder strains of carbapenem-resistantA. baumannii. Ten types of AbaR resistance islands were identified, and a previously unreported AbaR island, which comprised a two-component response regulator, resistance-related proteins, and RND efflux system proteins, was identified in two strains isolated in Zhejiang in 2004. Multiple transposons or insertion sequences (ISs) existed in each strain, and these gradually tended to diversify with evolution. Some of these IS elements or transposons were the first to be reported, and most of them were mainly found in strains from two provinces. Genome feature analysis illustrated diversified resistance genes, surface polysaccharides, and a restriction-modification system, even in strains that were phylogenetically and epidemiologically very closely related. IS-mediated deletions were identified in the type VI secretion system region, thecsuEregion, and core lipooligosaccharide (LOS) loci. Recombination occurred in the heme utilization region, and intrinsic resistance genes (blaADCandblaOXA-51-likevariants) and three novelblaOXA-51-likevariants (blaOXA-424,blaOXA-425, andblaOXA-426) were identified. Our results could improve the understanding of the evolutionary processes that contribute to the emergence of carbapenem-resistantA. baumanniistrains and help elucidate the molecular evolutionary mechanism inA. baumannii.

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Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks ofCampylobacter jejuniandSalmonella enterica

Journal of Clinical Microbiology ◽

10.1128/jcm.00161-18 ◽

2018 ◽

Vol 56 (11) ◽

Cited By ~ 9

Author(s):

Kelly F. Oakeson ◽

Jennifer Marie Wagner ◽

Andreas Rohrwasser ◽

Robyn Atkinson-Dunn

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Raw Milk ◽

Bioinformatic Analysis ◽

Foodborne Illness ◽

Reference Sequence ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Content Type ◽

Evolutionary Relatedness

ABSTRACTWhole-genome sequencing (WGS) via next-generation sequencing (NGS) technologies is a powerful tool for determining the relatedness of bacterial isolates in foodborne illness detection and outbreak investigations. WGS has been applied to national outbreaks (for example,Listeria monocytogenes); however, WGS has rarely been used in smaller local outbreaks. The current study demonstrates the superior resolution of genetic and evolutionary relatedness generated by WGS data analysis, compared to pulsed-field gel electrophoresis (PFGE). The current study retrospectively applies WGS and a reference-free bioinformatic analysis to a Utah-specific outbreak ofCampylobacter jejuniassociated with raw milk and to a national multistate outbreak ofSalmonella entericasubsp.entericaserovar Typhimurium associated with rotisserie chicken, both of which were characterized previously by PFGE. Together, these analyses demonstrate how a reference-free WGS workflow is not reliant on determination of a reference sequence, like WGS workflows that are based on single-nucleotide polymorphisms, or the need for curated allele databases, like multilocus sequence typing workflows.

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