scholarly journals Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines

2016 ◽  
Vol 54 (8) ◽  
pp. 2135-2148 ◽  
Author(s):  
Sophia David ◽  
Massimo Mentasti ◽  
Rediat Tewolde ◽  
Martin Aslett ◽  
Simon R. Harris ◽  
...  
Keyword(s):  
Legionella Pneumophila ◽  
Gold Standard ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Typing Method ◽  
Content Type ◽  
Typing Scheme ◽  
Full Profile

Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current “gold standard” typing method for investigation of legionellosis outbreaks caused byLegionella pneumophila. However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method.L. pneumophilaserogroup 1 isolates (n= 106) from the standard “typing panel,” previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method forL. pneumophila.

scholarly journals Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Listeria monocytogenes

2015 ◽  
Vol 53 (9) ◽  
pp. 2869-2876 ◽  
Author(s):  
Werner Ruppitsch ◽  
Ariane Pietzka ◽  
Karola Prior ◽  
Stefan Bletz ◽  
Haizpea Lasa Fernandez ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Genome Sequence ◽  
Core Genome ◽  
Target Genes ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Typing Scheme ◽  
Reference Strains

Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterizeListeria monocytogenesoutbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a newL. monocytogenestyping scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of theL. monocytogenespopulation based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67L. monocytogenesisolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated fiveL. monocytogenesgroups. Using all available NCBI RefSeq genomes (n= 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.

scholarly journals Epidemiological information is key when interpreting whole genome sequence data – lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013

2017 ◽  
Vol 22 (45) ◽  
Author(s):  
Markus Petzold ◽  
Karola Prior ◽  
Jacob Moran-Gilad ◽  
Dag Harmsen ◽  
Christian Lück
Keyword(s):  
Legionella Pneumophila ◽  
Sequence Data ◽  
Lessons Learned ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Typing Method ◽  
Epidemic Clone ◽  
Genomic Epidemiology ◽  
Outbreak Investigations ◽  
Epidemiological Information

Introduction Whole genome sequencing (WGS) is increasingly used in Legionnaires’ disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L. pneumophila. Methods: We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results: Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion: The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26 kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak.

scholarly journals Capsular Typing Method for Streptococcus agalactiae Using Whole-Genome Sequence Data

2016 ◽  
Vol 54 (5) ◽  
pp. 1388-1390 ◽  
Author(s):  
Anna E. Sheppard ◽  
Alison Vaughan ◽  
Nicola Jones ◽  
Paul Turner ◽  
Claudia Turner ◽  
...  
Keyword(s):  
Sequence Data ◽  
Vaccine Coverage ◽  
Group B Streptococcus ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Typing Method ◽  
Potential Vaccine ◽  
Group B ◽  
Capsular Typing ◽  
Strong Agreement

Group B streptococcus (GBS) capsular serotypes are major determinants of virulence and affect potential vaccine coverage. Here we report a whole-genome-sequencing-based method for GBS serotype assignment. This method shows strong agreement (kappa of 0.92) with conventional methods and increased serotype assignment (100%) to all 10 capsular types.

scholarly journals Clostridium botulinum Group II Isolate Phylogenomic Profiling Using Whole-Genome Sequence Data

2015 ◽  
Vol 81 (17) ◽  
pp. 5938-5948 ◽  
Author(s):  
K. A. Weedmark ◽  
P. Mabon ◽  
K. L. Hayden ◽  
D. Lambert ◽  
G. Van Domselaar ◽  
...  
Keyword(s):  
Genome Sequence ◽  
In Silico ◽  
Clostridium Botulinum ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Snp Analysis ◽  
Whole Genome ◽  
Content Type ◽  
Genome Sequence Data ◽  
Group Ii

ABSTRACTClostridium botulinumgroup II isolates (n= 163) from different geographic regions, outbreaks, and neurotoxin types and subtypes were characterizedin silicousing whole-genome sequence data. Two clusters representing a variety of botulinum neurotoxin (BoNT) types and subtypes were identified by multilocus sequence typing (MLST) and core single nucleotide polymorphism (SNP) analysis. While one cluster included BoNT/B4/F6/E9 and nontoxigenic members, the other comprised a wide variety of different BoNT/E subtype isolates and a nontoxigenic strain.In silicoMLST and core SNP methods were consistent in terms of clade-level isolate classification; however, core SNP analysis showed higher resolution capability. Furthermore, core SNP analysis correctly distinguished isolates by outbreak and location. This study illustrated the utility of next-generation sequence-based typing approaches for isolate characterization and source attribution and identified discrete SNP loci and MLST alleles for isolate comparison.

scholarly journals Prediction of Fluoroquinolone Susceptibility Directly from Whole-Genome Sequence Data by Using Liquid Chromatography-Tandem Mass Spectrometry To Identify Mutant Genotypes

2017 ◽  
Vol 62 (3) ◽  
Author(s):  
Wan Ahmad Kamil Wan Nur Ismah ◽  
Yuiko Takebayashi ◽  
Jacqueline Findlay ◽  
Kate J. Heesom ◽  
Juan-Carlos Jiménez-Castellanos ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Tandem Mass Spectrometry ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Tandem Mass ◽  
Whole Genome ◽  
Content Type ◽  
Chromatography Tandem Mass Spectrometry ◽  
Liquid Chromatography Tandem Mass

ABSTRACTFluoroquinolone resistance in Gram-negative bacteria is multifactorial, involving target site mutations, reductions in fluoroquinolone entry due to reduced porin production, increased fluoroquinolone efflux, enzymes that modify fluoroquinolones, and Qnr, a DNA mimic that protects the drug target from fluoroquinolone binding. Here we report a comprehensive analysis, using transformation andin vitromutant selection, of the relative importance of each of these mechanisms for fluoroquinolone nonsusceptibility usingKlebsiella pneumoniaeas a model system. Our improved biological understanding was then used to generate 47 rules that can predict fluoroquinolone susceptibility inK. pneumoniaeclinical isolates. Key to the success of this predictive process was the use of liquid chromatography-tandem mass spectrometry to measure the abundance of proteins in extracts of cultured bacteria, identifying which sequence variants seen in the whole-genome sequence data were functionally important in the context of fluoroquinolone susceptibility.

scholarly journals Emergence of a Plant Pathogen in Europe Associated with Multiple Intercontinental Introductions

2019 ◽  
Vol 86 (3) ◽  
Author(s):  
Blanca B. Landa ◽  
Andreina I. Castillo ◽  
Annalisa Giampetruzzi ◽  
Alexandra Kahn ◽  
Miguel Román-Écija ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genome Sequence ◽  
Sequence Data ◽  
Xylella Fastidiosa ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Genome Sequence Data ◽  
Multiple Introductions ◽  
Limited Genetic Diversity

ABSTRACT Pathogen introductions have led to numerous disease outbreaks in naive regions of the globe. The plant pathogen Xylella fastidiosa has been associated with various recent epidemics in Europe affecting agricultural crops, such as almond, grapevine, and olive, but also endemic species occurring in natural forest landscapes and ornamental plants. We compared whole-genome sequences of X. fastidiosa subspecies multiplex from America and strains associated with recent outbreaks in southern Europe to infer their likely origins and paths of introduction within and between the two continents. Phylogenetic analyses indicated multiple introductions of X. fastidiosa subspecies multiplex into Italy, Spain, and France, most of which emerged from a clade with limited genetic diversity with a likely origin in California, USA. The limited genetic diversity observed in X. fastidiosa subspecies multiplex strains originating from California is likely due to the clade itself being an introduction from X. fastidiosa subspecies multiplex populations in the southeastern United States, where this subspecies is most likely endemic. Despite the genetic diversity found in some areas in Europe, there was no clear evidence of recombination occurring among introduced X. fastidiosa strains in Europe. Sequence type taxonomy, based on multilocus sequence typing (MLST), was shown, at least in one case, to not lead to monophyletic clades of this pathogen; whole-genome sequence data were more informative in resolving the history of introductions than MLST data. Although additional data are necessary to carefully tease out the paths of these recent dispersal events, our results indicate that whole-genome sequence data should be considered when developing management strategies for X. fastidiosa outbreaks. IMPORTANCE Xylella fastidiosa is an economically important plant-pathogenic bacterium that has emerged as a pathogen of global importance associated with a devastating epidemic in olive trees in Italy associated with X. fastidiosa subspecies pauca and other outbreaks in Europe, such as X. fastidiosa subspecies fastidiosa and X. fastidiosa subspecies multiplex in Spain and X. fastidiosa subspecies multiplex in France. We present evidence of multiple introductions of X. fastidiosa subspecies multiplex, likely from the United States, into Spain, Italy, and France. These introductions illustrate the risks associated with the commercial trade of plant material at global scales and the need to develop effective policy to limit the likelihood of pathogen pollution into naive regions. Our study demonstrates the need to utilize whole-genome sequence data to study X. fastidiosa introductions at outbreak stages, since a limited number of genetic markers does not provide sufficient phylogenetic resolution to determine dispersal paths or relationships among strains that are of biological and quarantine relevance.

scholarly journals rMAP: the Rapid Microbial Analysis Pipeline for ESKAPE bacterial group whole-genome sequence data

2021 ◽  
Vol 7 (6) ◽  
Author(s):  
Ivan Sserwadda ◽  
Gerald Mboowa
Keyword(s):  
Low Income ◽  
Type Species ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Analysis Pipeline ◽  
Content Type ◽  
Link Type ◽  
Microbial Analysis

The recent re-emergence of multidrug-resistant pathogens has exacerbated their threat to worldwide public health. The evolution of the genomics era has led to the generation of huge volumes of sequencing data at an unprecedented rate due to the ever-reducing costs of whole-genome sequencing (WGS). We have developed the Rapid Microbial Analysis Pipeline (rMAP), a user-friendly pipeline capable of profiling the resistomes of ESKAPE pathogens ( Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumoniae , Acinetobacter baumannii , Pseudomonas aeruginosa and Enterobacter species) using WGS data generated from Illumina’s sequencing platforms. rMAP is designed for individuals with little bioinformatics expertise, and automates the steps required for WGS analysis directly from the raw genomic sequence data, including adapter and low-quality sequence read trimming, de novo genome assembly, genome annotation, single-nucleotide polymorphism (SNP) variant calling, phylogenetic inference by maximum likelihood, antimicrobial resistance (AMR) profiling, plasmid profiling, virulence factor determination, multi-locus sequence typing (MLST), pangenome analysis and insertion sequence characterization (IS). Once the analysis is finished, rMAP generates an interactive web-like html report. rMAP installation is very simple, it can be run using very simple commands. It represents a rapid and easy way to perform comprehensive bacterial WGS analysis using a personal laptop in low-income settings where high-performance computing infrastructure is limited.

scholarly journals Lowering the Barriers to Routine Whole-Genome Sequencing of Bacteria in the Clinical Microbiology Laboratory

2018 ◽  
Vol 56 (9) ◽  
Author(s):  
Daniel D. Rhoads
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Clinical Microbiology Laboratory ◽  
Whole Genome ◽  
Content Type ◽  
Antibacterial Susceptibility ◽  
Susceptibility And Resistance

ABSTRACT Whole-genome sequencing of bacterial isolates is increasingly being used to predict antibacterial susceptibility and resistance. Mason and coauthors describe the phenotypic susceptibility interpretations of more than 1,300 Staphylococcus aureus isolates tested against a dozen antistaphylococcal agents, and they compared these findings to susceptibility predictions made by analyzing whole-genome sequence data (J Clin Microbiol 56:e01815-17, 2018, https://doi.org/10.1128/JCM.01815-17). The genotype-phenotype susceptibility interpretations correlated in 96.3% (2,720/2,825) of resistant findings and 98.8% (11,504/11,639) of susceptible findings. This work by Mason and colleagues is helping to lower the barriers to using whole-genome sequencing of S. aureus in clinical microbiology practice.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

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