scholarly journals Whole Genome and Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analyses of Listeria monocytogenes Isolates Associated with an Outbreak Linked to Cheese, United States, 2013

2017 ◽  
Vol 83 (15) ◽  
Author(s):  
Yi Chen ◽  
Yan Luo ◽  
Heather Carleton ◽  
Ruth Timme ◽  
David Melka ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Clustering Analysis ◽  
Multilocus Sequence Typing ◽  
Core Genome ◽  
Variant Calling ◽  
Discriminatory Power ◽  
Sufficient Evidence ◽  
Whole Genome ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide

ABSTRACT Epidemiological findings of a listeriosis outbreak in 2013 implicated Hispanic-style cheese produced by company A, and pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) were performed on clinical isolates and representative isolates collected from company A cheese and environmental samples during the investigation. The results strengthened the evidence for cheese as the vehicle. Surveillance sampling and WGS 3 months later revealed that the equipment purchased by company B from company A yielded an environmental isolate highly similar to all outbreak isolates. The whole genome and core genome multilocus sequence typing and single nucleotide polymorphism (SNP) analyses results were compared to demonstrate the maximum discriminatory power obtained by using multiple analyses, which were needed to differentiate outbreak-associated isolates from a PFGE-indistinguishable isolate collected in a nonimplicated food source in 2012. This unrelated isolate differed from the outbreak isolates by only 7 to 14 SNPs, and as a result, the minimum spanning tree from the whole genome analyses and certain variant calling approach and phylogenetic algorithm for core genome-based analyses could not provide differentiation between unrelated isolates. Our data also suggest that SNP/allele counts should always be combined with WGS clustering analysis generated by phylogenetically meaningful algorithms on a sufficient number of isolates, and the SNP/allele threshold alone does not provide sufficient evidence to delineate an outbreak. The putative prophages were conserved across all the outbreak isolates. All outbreak isolates belonged to clonal complex 5 and serotype 1/2b and had an identical inlA sequence which did not have premature stop codons. IMPORTANCE In this outbreak, multiple analytical approaches were used for maximum discriminatory power. A PFGE-matched, epidemiologically unrelated isolate had high genetic similarity to the outbreak-associated isolates, with as few as 7 SNP differences. Therefore, the SNP/allele threshold should not be used as the only evidence to define the scope of an outbreak. It is critical that the SNP/allele counts be complemented by WGS clustering analysis generated by phylogenetically meaningful algorithms to distinguish outbreak-associated isolates from epidemiologically unrelated isolates. Careful selection of a variant calling approach and phylogenetic algorithm is critical for core-genome-based analyses. The whole-genome-based analyses were able to construct the highly resolved phylogeny needed to support the findings of the outbreak investigation. Ultimately, epidemiologic evidence and multiple WGS analyses should be combined to increase confidence levels during outbreak investigations.

scholarly journals Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analysis in the Epidemiology of Brucella melitensis Infections

2018 ◽  
Vol 56 (9) ◽  
Author(s):  
Anna Janowicz ◽  
Fabrizio De Massis ◽  
Massimo Ancora ◽  
Cesare Cammà ◽  
Claudio Patavino ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Multilocus Sequence Typing ◽  
Core Genome ◽  
Brucella Melitensis ◽  
Reference Sequence ◽  
Snp Analysis ◽  
Phylogenetic Distance ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Content Type

ABSTRACT The use of whole-genome sequencing (WGS) using next-generation sequencing (NGS) technology has become a widely accepted method for microbiology laboratories in the application of molecular typing for outbreak tracing and genomic epidemiology. Several studies demonstrated the usefulness of WGS data analysis through single-nucleotide polymorphism (SNP) calling from a reference sequence analysis for Brucella melitensis, whereas gene-by-gene comparison through core-genome multilocus sequence typing (cgMLST) has not been explored so far. The current study developed an allele-based cgMLST method and compared its performance to that of the genome-wide SNP approach and the traditional multilocus variable-number tandem repeat analysis (MLVA) on a defined sample collection. The data set was comprised of 37 epidemiologically linked animal cases of brucellosis as well as 71 isolates with unknown epidemiological status, composed of human and animal samples collected in Italy. The cgMLST scheme generated in this study contained 2,704 targets of the B. melitensis 16M reference genome. We established the potential criteria necessary for inclusion of an isolate into a brucellosis outbreak cluster to be ≤6 loci in the cgMLST and ≤7 in WGS SNP analysis. Higher phylogenetic distance resolution was achieved with cgMLST and SNP analysis than with MLVA, particularly for strains belonging to the same lineage, thereby allowing diverse and unrelated genotypes to be identified with greater confidence. The application of a cgMLST scheme to the characterization of B. melitensis strains provided insights into the epidemiology of this pathogen, and it is a candidate to be a benchmark tool for outbreak investigations in human and animal brucellosis.

scholarly journals Novel Single Nucleotide Polymorphism-Based Assay for Genotyping Mycobacterium avium subsp. paratuberculosis

2015 ◽  
Vol 54 (3) ◽  
pp. 556-564 ◽  
Author(s):  
Célia Leão ◽  
Robert J. Goldstone ◽  
Josephine Bryant ◽  
Joyce McLuckie ◽  
João Inácio ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Mycobacterium Avium ◽  
Discriminatory Power ◽  
Whole Genome ◽  
Nucleotide Polymorphism ◽  
Phylogenetic Groups ◽  
Single Nucleotide ◽  
Content Type

Typing ofMycobacterium aviumsubspeciesparatuberculosisstrains presents a challenge, since they are genetically monomorphic and traditional molecular techniques have limited discriminatory power. The recent advances and availability of whole-genome sequencing have extended possibilities for the characterization ofMycobacterium aviumsubspeciesparatuberculosis, and whole-genome sequencing can provide a phylogenetic context to facilitate global epidemiology studies. In this study, we developed a single nucleotide polymorphism (SNP) assay based on PCR and restriction enzyme digestion or sequencing of the amplified product. The SNP analysis was performed using genome sequence data from 133Mycobacterium aviumsubspeciesparatuberculosisisolates with different genotypes from 8 different host species and 17 distinct geographic regions around the world. A total of 28,402 SNPs were identified among all of the isolates. The minimum number of SNPs required to distinguish between all of the 133 genomes was 93 and between only the type C isolates was 41. To reduce the number of SNPs and PCRs required, we adopted an approach based on sequential detection of SNPs and a decision tree. By the analysis of 14 SNPsMycobacterium aviumsubspeciesparatuberculosisisolates can be characterized within 14 phylogenetic groups with a higher discriminatory power than mycobacterial interspersed repetitive unit–variable number tandem repeat assay and other typing methods. Continuous updating of genome sequences is needed in order to better characterize new phylogenetic groups and SNP profiles. The novel SNP assay is a discriminative, simple, reproducible method and requires only basic laboratory equipment for the large-scale global typing ofMycobacterium aviumsubspeciesparatuberculosisisolates.

scholarly journals Whole-Genome Single-Nucleotide-Polymorphism Analysis for Discrimination of Clostridium botulinum Group I Strains

2014 ◽  
Vol 80 (7) ◽  
pp. 2125-2132 ◽  
Author(s):  
Narjol Gonzalez-Escalona ◽  
Ruth Timme ◽  
Brian H. Raphael ◽  
Donald Zink ◽  
Shashi K. Sharma
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Clostridium Botulinum ◽  
Toxin Gene ◽  
Polymorphism Analysis ◽  
Snp Analysis ◽  
Whole Genome ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Content Type ◽  
Group I

ABSTRACTClostridium botulinumis a genetically diverse Gram-positive bacterium producing extremely potent neurotoxins (botulinum neurotoxins A through G [BoNT/A-G]). The complete genome sequences of three strains harboring only the BoNT/A1 nucleotide sequence are publicly available. Although these strains contain a toxin cluster (HA+OrfX−) associated with hemagglutinin genes, little is known about the genomes of subtype A1 strains (termed HA−OrfX+) that lack hemagglutinin genes in the toxin gene cluster. We sequenced the genomes of three BoNT/A1-producingC. botulinumstrains: two strains with the HA+OrfX−cluster (69A and 32A) and one strain with the HA−OrfX+cluster (CDC297). Whole-genome phylogenic single-nucleotide-polymorphism (SNP) analysis of these strains along with other publicly availableC. botulinumgroup I strains revealed five distinct lineages. Strains 69A and 32A clustered with theC. botulinumtype A1 Hall group, and strain CDC297 clustered with theC. botulinumtype Ba4 strain 657. This study reports the use of whole-genome SNP sequence analysis for discrimination ofC. botulinumgroup I strains and demonstrates the utility of this analysis in quickly differentiatingC. botulinumstrains harboring identical toxin gene subtypes. This analysis further supports previous work showing that strains CDC297 and 657 likely evolved from a common ancestor and independently acquired separate BoNT/A1 toxin gene clusters at distinct genomic locations.

scholarly journals Whole‐Genome Approach Discovers Novel Genetic and Nongenetic Variance Components Modulated by Lifestyle for Cardiovascular Health

2020 ◽  
Vol 9 (8) ◽  
Author(s):  
Xuan Zhou ◽  
Julius van der Werf ◽  
Kristin Carson‐Chahhoud ◽  
Guiyan Ni ◽  
John McGrath ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Heart Rate ◽  
Single Nucleotide Polymorphism ◽  
Cardiovascular Risk ◽  
Lifestyle Factors ◽  
Whole Genome ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Cardiovascular Traits

Background Both genetic and nongenetic factors can predispose individuals to cardiovascular risk. Finding ways to alter these predispositions is important for cardiovascular disease prevention. Methods and Results We used a novel whole‐genome approach to estimate the genetic and nongenetic effects on—and hence their predispositions to—cardiovascular risk and determined whether they vary with respect to lifestyle factors such as physical activity, smoking, alcohol consumption, and dietary intake. We performed analyses on the ARIC (Atherosclerosis Risk in Communities) Study (N=6896–7180) and validated findings using the UKBB (UK Biobank, N=14 076–34 538). Lifestyle modulation was evident for many cardiovascular traits such as body mass index and resting heart rate. For example, alcohol consumption modulated both genetic and nongenetic effects on body mass index, whereas smoking modulated nongenetic effects on heart rate, pulse pressure, and white blood cell count. We also stratified individuals according to estimated genetic and nongenetic effects that are modulated by lifestyle factors and showed distinct phenotype–lifestyle relationships across the stratified groups. Finally, we showed that neglecting lifestyle modulations of cardiovascular traits would on average reduce single nucleotide polymorphism heritability estimates of these traits by a small yet significant amount, primarily owing to the overestimation of residual variance. Conclusions Lifestyle changes are relevant to cardiovascular disease prevention. Individual differences in the genetic and nongenetic effects that are modulated by lifestyle factors, as shown by the stratified group analyses, implies a need for personalized lifestyle interventions. In addition, single nucleotide polymorphism–based heritability of cardiovascular traits without accounting for lifestyle modulations could be underestimated.

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