Last data update: May 20, 2024. (Total: 46824 publications since 2009)
Records 1-5 (of 5 Records) |
Query Trace: Petkau A[original query] |
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Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr.
Bharat A , Petkau A , Avery BP , Chen J , Folster J , Carson CA , Kearney A , Nadon C , Mabon P , Thiessen J , Alexander DC , Allen V , ElBailey S , Bekal S , German GJ , Haldane D , Hoang L , Chui L , Minion J , Zahariadis G , VanDomselaar G , Reid-Smith RJ , Mulvey MR . Microorganisms 2022 10 (2) Whole genome sequencing (WGS) of Salmonella supports both molecular typing and detection of antimicrobial resistance (AMR). Here, we evaluated the correlation between phenotypic antimicrobial susceptibility testing (AST) and in silico prediction of AMR from WGS in Salmonella enterica (n = 1321) isolated from human infections in Canada. Phenotypic AMR results from broth microdilution testing were used as the gold standard. To facilitate high-throughput prediction of AMR from genome assemblies, we created a tool called Staramr, which incorporates the ResFinder and PointFinder databases and a custom gene-drug key for antibiogram prediction. Overall, there was 99% concordance between phenotypic and genotypic detection of categorical resistance for 14 antimicrobials in 1321 isolates (18,305 of 18,494 results in agreement). We observed an average sensitivity of 91.2% (range 80.5100%), a specificity of 99.7% (98.6100%), a positive predictive value of 95.4% (68.2100%), and a negative predictive value of 99.1% (95.6100%). The positive predictive value of gentamicin was 68%, due to seven isolates that carried aac(3)-IVa, which conferred MICs just below the breakpoint of resistance. Genetic mechanisms of resistance in these 1321 isolates included 64 unique acquired alleles and mutations in three chromosomal genes. In general, in silico prediction of AMR in Salmonella was reliable compared to the gold standard of broth microdilution. WGS can provide higher-resolution data on the epidemiology of resistance mechanisms and the emergence of new resistance alleles. 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology.
Petkau A , Mabon P , Sieffert C , Knox NC , Cabral J , Iskander M , Weedmark K , Zaheer R , Katz LS , Nadon C , Reimer A , Taboada E , Beiko RG , Hsiao W , Brinkman F , Graham M , Van Domselaar G . Microb Genom 2017 3 (6) e000116 The recent widespread application of whole-genome sequencing (WGS) for microbial disease investigations has spurred the development of new bioinformatics tools, including a notable proliferation of phylogenomics pipelines designed for infectious disease surveillance and outbreak investigation. Transitioning the use of WGS data out of the research laboratory and into the front lines of surveillance and outbreak response requires user-friendly, reproducible and scalable pipelines that have been well validated. Single Nucleotide Variant Phylogenomics (SNVPhyl) is a bioinformatics pipeline for identifying highquality single-nucleotide variants (SNVs) and constructing a whole-genome phylogeny from a collection of WGS reads and a reference genome. Individual pipeline components are integrated into the Galaxy bioinformatics framework, enabling data analysis in a user-friendly, reproducible and scalable environment. We show that SNVPhyl can detect SNVs with high sensitivity and specificity, and identify and remove regions of high SNV density (indicative of recombination). SNVPhyl is able to correctly distinguish outbreak from non-outbreak isolates across a range of variant-calling settings, sequencing-coverage thresholds or in the presence of contamination. SNVPhyl is available as a Galaxy workflow, Docker and virtual machine images, and a Unix-based command-line application. SNVPhyl is released under the Apache 2.0 license and available at http://snvphyl.readthedocs.io/ or at https://github.com/phac-nml/snvphyl-galaxy. |
A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens.
Katz LS , Griswold T , Williams-Newkirk AJ , Wagner D , Petkau A , Sieffert C , Van Domselaar G , Deng X , Carleton HA . Front Microbiol 2017 8 375 Modern epidemiology of foodborne bacterial pathogens in industrialized countries relies increasingly on whole genome sequencing (WGS) techniques. As opposed to profiling techniques such as pulsed-field gel electrophoresis, WGS requires a variety of computational methods. Since 2013, United States agencies responsible for food safety including the CDC, FDA, and USDA, have been performing whole-genome sequencing (WGS) on all Listeria monocytogenes found in clinical, food, and environmental samples. Each year, more genomes of other foodborne pathogens such as Escherichia coli, Campylobacter jejuni, and Salmonella enterica are being sequenced. Comparing thousands of genomes across an entire species requires a fast method with coarse resolution; however, capturing the fine details of highly related isolates requires a computationally heavy and sophisticated algorithm. Most L. monocytogenes investigations employing WGS depend on being able to identify an outbreak clade whose inter-genomic distances are less than an empirically determined threshold. When the difference between a few single nucleotide polymorphisms (SNPs) can help distinguish between genomes that are likely outbreak-associated and those that are less likely to be associated, we require a fine-resolution method. To achieve this level of resolution, we have developed Lyve-SET, a high-quality SNP pipeline. We evaluated Lyve-SET by retrospectively investigating 12 outbreak data sets along with four other SNP pipelines that have been used in outbreak investigation or similar scenarios. To compare these pipelines, several distance and phylogeny-based comparison methods were applied, which collectively showed that multiple pipelines were able to identify most outbreak clusters and strains. Currently in the US PulseNet system, whole genome multi-locus sequence typing (wgMLST) is the preferred primary method for foodborne WGS cluster detection and outbreak investigation due to its ability to name standardized genomic profiles, its central database, and its ability to be run in a graphical user interface. However, creating a functional wgMLST scheme requires extended up-front development and subject-matter expertise. When a scheme does not exist or when the highest resolution is needed, SNP analysis is used. Using three Listeria outbreak data sets, we demonstrated the concordance between Lyve-SET SNP typing and wgMLST. Availability: Lyve-SET can be found at https://github.com/lskatz/Lyve-SET. |
Evolutionary dynamics of Vibrio cholerae O1 following a single-source introduction to Haiti
Katz LS , Petkau A , Beaulaurier J , Tyler S , Antonova ES , Turnsek MA , Guo Y , Wang S , Paxinos EE , Orata F , Gladney LM , Stroika S , Folster JP , Rowe L , Freeman MM , Knox N , Frace M , Boncy J , Graham M , Hammer BK , Boucher Y , Bashir A , Hanage WP , Van Domselaar G , Tarr CL . mBio 2013 4 (4) Prior to the epidemic that emerged in Haiti in October of 2010, cholera had not been documented in this country. After its introduction, a strain of Vibrio cholerae O1 spread rapidly throughout Haiti, where it caused over 600,000 cases of disease and >7,500 deaths in the first two years of the epidemic. We applied whole-genome sequencing to a temporal series of V. cholerae isolates from Haiti to gain insight into the mode and tempo of evolution in this isolated population of V. cholerae O1. Phylogenetic and Bayesian analyses supported the hypothesis that all isolates in the sample set diverged from a common ancestor within a time frame that is consistent with epidemiological observations. A pangenome analysis showed nearly homogeneous genomic content, with no evidence of gene acquisition among Haiti isolates. Nine nearly closed genomes assembled from continuous-long-read data showed evidence of genome rearrangements and supported the observation of no gene acquisition among isolates. Thus, intrinsic mutational processes can account for virtually all of the observed genetic polymorphism, with no demonstrable contribution from horizontal gene transfer (HGT). Consistent with this, the 12 Haiti isolates tested by laboratory HGT assays were severely impaired for transformation, although unlike previously characterized noncompetent V. cholerae isolates, each expressed hapR and possessed a functional quorum-sensing system. Continued monitoring of V. cholerae in Haiti will illuminate the processes influencing the origin and fate of genome variants, which will facilitate interpretation of genetic variation in future epidemics. IMPORTANCE Vibrio cholerae is the cause of substantial morbidity and mortality worldwide, with over three million cases of disease each year. An understanding of the mode and rate of evolutionary change is critical for proper interpretation of genome sequence data and attribution of outbreak sources. The Haiti epidemic provides an unprecedented opportunity to study an isolated, single-source outbreak of Vibrio cholerae O1 over an established time frame. By using multiple approaches to assay genetic variation, we found no evidence that the Haiti strain has acquired any genes by horizontal gene transfer, an observation that led us to discover that it is also poorly transformable. We have found no evidence that environmental strains have played a role in the evolution of the outbreak strain. |
Comparative genomics of Vibrio cholerae from Haiti, Asia, and Africa.
Reimer AR , Van Domselaar G , Stroika S , Walker M , Kent H , Tarr C , Talkington D , Rowe L , Olsen-Rasmussen M , Frace M , Sammons S , Dahourou GA , Boncy J , Smith AM , Mabon P , Petkau A , Graham M , Gilmour MW , Gerner-Smidt P . Emerg Infect Dis 2011 17 (11) 2113-2121 Cholera was absent from the island of Hispaniola at least a century before an outbreak that began in Haiti in the fall of 2010. Pulsed-field gel electrophoresis (PFGE) analysis of clinical isolates from the Haiti outbreak and recent global travelers returning to the United States showed indistinguishable PFGE fingerprints. To better explore the genetic ancestry of the Haiti outbreak strain, we acquired 23 whole-genome Vibrio cholerae sequences: 9 isolates obtained in Haiti or the Dominican Republic, 12 PFGE pattern-matched isolates linked to Asia or Africa, and 2 nonmatched outliers from the Western Hemisphere. Phylogenies for whole-genome sequences and core genome single-nucleotide polymorphisms showed that the Haiti outbreak strain is genetically related to strains originating in India and Cameroon. However, because no identical genetic match was found among sequenced contemporary isolates, a definitive genetic origin for the outbreak in Haiti remains speculative. |
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