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31 results on '"Petkau, Aaron"'

1. Author Correction: Surveillance of Enterococcus spp. reveals distinct species and antimicrobial resistance diversity across a One-Health continuum

Author

Zaheer, Rahat, Cook, Shaun R., Barbieri, Ruth, Goji, Noriko, Cameron, Andrew, Petkau, Aaron, Polo, Rodrigo Ortega, Tymensen, Lisa, Stamm, Courtney, Song, Jiming, Hannon, Sherry, Jones, Tineke, Church, Deirdre, Booker, Calvin W., Amoako, Kingsley, Van Domselaar, Gary, Read, Ron R., and McAllister, Tim A.

Published
2020
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3. CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database

Author

Alcock, Brian P, primary, Huynh, William, additional, Chalil, Romeo, additional, Smith, Keaton W, additional, Raphenya, Amogelang R, additional, Wlodarski, Mateusz A, additional, Edalatmand, Arman, additional, Petkau, Aaron, additional, Syed, Sohaib A, additional, Tsang, Kara K, additional, Baker, Sheridan J C, additional, Dave, Mugdha, additional, McCarthy, Madeline C, additional, Mukiri, Karyn M, additional, Nasir, Jalees A, additional, Golbon, Bahar, additional, Imtiaz, Hamna, additional, Jiang, Xingjian, additional, Kaur, Komal, additional, Kwong, Megan, additional, Liang, Zi Cheng, additional, Niu, Keyu C, additional, Shan, Prabakar, additional, Yang, Jasmine Y J, additional, Gray, Kristen L, additional, Hoad, Gemma R, additional, Jia, Baofeng, additional, Bhando, Timsy, additional, Carfrae, Lindsey A, additional, Farha, Maya A, additional, French, Shawn, additional, Gordzevich, Rodion, additional, Rachwalski, Kenneth, additional, Tu, Megan M, additional, Bordeleau, Emily, additional, Dooley, Damion, additional, Griffiths, Emma, additional, Zubyk, Haley L, additional, Brown, Eric D, additional, Maguire, Finlay, additional, Beiko, Robert G, additional, Hsiao, William W L, additional, Brinkman, Fiona S L, additional, Van Domselaar, Gary, additional, and McArthur, Andrew G, additional

Published
2022
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4. A framework for the indexing, querying, clustering, and visualization of microbial genomes for surveillance and outbreak investigation

Author

Tremblay-Savard, Olivier (Computer Science), Van Domselaar, Gary (Medical Microbiology and Infectious Diseases), Taboada, Eduardo (Food and Human Nutritional Sciences), Domaratzki, Mike (Computer Science), Tremblay-Savard, Olivier, Van Domselaar, Gary, Petkau, Aaron, Tremblay-Savard, Olivier (Computer Science), Van Domselaar, Gary (Medical Microbiology and Infectious Diseases), Taboada, Eduardo (Food and Human Nutritional Sciences), Domaratzki, Mike (Computer Science), Tremblay-Savard, Olivier, Van Domselaar, Gary, and Petkau, Aaron

Abstract

Whole-genome sequencing (WGS) has increasingly become a routine part of monitoring infectious diseases. The genomes of bacteria, viruses, or other infectious agents are sequenced and used to identify nucleotide variants or other genetic differences—providing a wealth of detailed information. This has particularly become relevant with the COVID-19 pandemic, where sequencing of millions of viral genomes over the course of the pandemic has been essential in early identification of new viral lineages. The continuous generation of WGS data at this scale has introduced a number of challenges for efficiently generating timely reports and searching for epidemiologically significant patterns. I have designed and implemented a framework to address these problems—the Genomics Data Index (https://github.com/apetkau/genomics-data-index)—which uses ideas from the field of information retrieval to transform WGS data into a collection of genomics features (nucleotide variants, kmers, and genes) and index these features for rapid querying. I provide a command-line interface and Python API for incrementally adding new data and querying the index. The query API integrates with existing methods for working with tabular and phylogenetic data to provide a common interface for clustering, visualization, and statistical analysis of microbial genomes. I evaluated this framework using three datasets containing assembled genomes and sequence reads. Indexing assemblies was more sensitive for nucleotide variant detection when there were fewer variants (sensitivity = 0.948 for 6.77% divergence compared to reads sensitivity = 0.663), but sensitivity when indexing with reads surpassed assemblies as variants increased. The software was able to scale to tens of thousands of SARS-CoV-2 genomes (2.17 hours for loading 20,000 genomes) and construct phylogenies consistent with the existing Pangolin lineage system. Constructing phylogenies using nucleotide variants derived from bacterial WGS reads was fo

Published
2022

5. Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr

Author

Bharat, Amrita, primary, Petkau, Aaron, additional, Avery, Brent P., additional, Chen, Jessica C., additional, Folster, Jason P., additional, Carson, Carolee A., additional, Kearney, Ashley, additional, Nadon, Celine, additional, Mabon, Philip, additional, Thiessen, Jeffrey, additional, Alexander, David C., additional, Allen, Vanessa, additional, El Bailey, Sameh, additional, Bekal, Sadjia, additional, German, Greg J., additional, Haldane, David, additional, Hoang, Linda, additional, Chui, Linda, additional, Minion, Jessica, additional, Zahariadis, George, additional, Domselaar, Gary Van, additional, Reid-Smith, Richard J., additional, and Mulvey, Michael R., additional

Published
2022
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6. CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

Author

Alcock, Brian P, Huynh, William, Chalil, Romeo, Smith, Keaton W, Raphenya, Amogelang R, Wlodarski, Mateusz A, Edalatmand, Arman, Petkau, Aaron, Syed, Sohaib A, Tsang, Kara K, Baker, Sheridan J C, Dave, Mugdha, McCarthy, Madeline C, Mukiri, Karyn M, Nasir, Jalees A, Golbon, Bahar, Imtiaz, Hamna, Jiang, Xingjian, Kaur, Komal, and Kwong, Megan

Published
2023
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7. Comparative genomics of Vibrio cholerae from Haiti, Asia, and Africa

Author

Reimer, Aleisha R., Van Domselaar, Gary, Stroika, Steven, Walker, Matthew, Kent, Heather, Tarr, Cheryl, Talkington, Deborah, Rowe, Lori, Olsen-Rasmussen, Melissa, Frace, Michael, Sammons, Scott, Dahourou, Georges Anicet, Boncy, Jacques, Smith, Anthony M., Mabon, Philip, Petkau, Aaron, Graham, Morag, Gilmour, Matthew W., and Gerner-Smidt, Peter

Subjects
United States. Centers for Disease Control and Prevention -- Analysis, Cholera toxin -- Analysis, Genomics -- Analysis, Genomes -- Analysis, Cholera -- Analysis, Health
Abstract

The current (seventh) cholera pandemic was caused by serogroup O1 El Tor biotypes of Vibrio cholerae. This biotype first emerged on the Indonesian island of Sulawesi in 1961, then subsequently [...]

Published
2011
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10. Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria

Author

Reimer, Aleisha, primary, Weedmark, Kelly, additional, Petkau, Aaron, additional, Peterson, Christy-Lynn, additional, Walker, Matthew, additional, Knox, Natalie, additional, Kent, Heather, additional, Mabon, Philip, additional, Berry, Chrystal, additional, Tyler, Shaun, additional, Tschetter, Lorelee, additional, Jerome, Morganne, additional, Allen, Vanessa, additional, Hoang, Linda, additional, Bekal, Sadjia, additional, Clark, Clifford, additional, Nadon, Celine, additional, Van Domselaar, Gary, additional, Pagotto, Franco, additional, Graham, Morag, additional, Farber, Jeff, additional, and Gilmour, Matthew, additional

Published
2019
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12. The Integrated Rapid Infectious Disease Analysis (IRIDA) Platform

Author

Matthews, Thomas C, primary, Bristow, Franklin R, additional, Griffiths, Emma J, additional, Petkau, Aaron, additional, Adam, Josh, additional, Dooley, Damion, additional, Kruczkiewicz, Peter, additional, Curatcha, John, additional, Cabral, Jennifer, additional, Fornika, Dan, additional, Winsor, Geoffrey L., additional, Courtot, Melanie, additional, Bertelli, Claire, additional, Roudgar, Ataollah, additional, Feijao, Pedro, additional, Mabon, Philip, additional, Enns, Eric, additional, Thiessen, Joel, additional, Keddy, Alexander, additional, Isaac-Renton, Judith, additional, Gardy, Jennifer L., additional, Tang, Patrick, additional, João A Carriço, The IRIDA Consortium, additional, Chindelevitch, Leonid, additional, Chauve, Cedric, additional, Graham, Morag R, additional, McArthur, Andrew G, additional, Taboada, Eduardo N, additional, Beiko, Robert G, additional, Brinkman, Fiona SL, additional, Hsiao, William WL, additional, and Domselaar, Gary Van, additional

Published
2018
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13. Additional file 4: Figure S2. of Genomic insights from whole genome sequencing of four clonal outbreak Campylobacter jejuni assessed within the global C. jejuni population

Author

Clark, Clifford, Berry, Chrystal, Walker, Matthew, Petkau, Aaron, Barker, Dillon, Guan, Cai, Aleisha Reimer, and Taboada, Eduardo

Abstract

Comparison of the ~93-kb invertible region for strains NCTC11168 = ATCC 700819 and 00–2425. Note that the 00–2425 region has been inverted for the diagram to highlight the synteny of this region between the two strains. The genes outside this region were found in the same locations in both NCTC11168 = ATCC 700819 and 00–2425, but appear at different places in the figure due to this inversion. Diagrams for each strain were obtained using GView Server [56] and further annotated using Adobe Illustrator. (PDF 177 kb)

Published
2016
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14. Additional file 1: Figure S1. of Genomic insights from whole genome sequencing of four clonal outbreak Campylobacter jejuni assessed within the global C. jejuni population

Author

Clark, Clifford, Berry, Chrystal, Walker, Matthew, Petkau, Aaron, Barker, Dillon, Guan, Cai, Aleisha Reimer, and Taboada, Eduardo

Abstract

Dendrogram showing Neighbour-Joining analysis of C. jejuni complete whole genomes. The alignment was performed using Progressive Mauve [61] and the dendrogram produced using FigTree v1.4 [53]. (PDF 3 kb)

Published
2016
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16. SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology

Author

Petkau, Aaron, primary, Mabon, Philip, additional, Sieffert, Cameron, additional, Knox, Natalie C., additional, Cabral, Jennifer, additional, Iskander, Mariam, additional, Iskander, Mark, additional, Weedmark, Kelly, additional, Zaheer, Rahat, additional, Katz, Lee S., additional, Nadon, Celine, additional, Reimer, Aleisha, additional, Taboada, Eduardo, additional, Beiko, Robert G., additional, Hsiao, William, additional, Brinkman, Fiona, additional, Graham, Morag, additional, and Van Domselaar, Gary, additional

Published
2017
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19. A multilocus sequence typing scheme for Mycobacterium abscessus complex (MAB-multilocus sequence typing) using whole-genome sequencing data.

Author

Wuzinski, Michelle, Bak, Aneta, Petkau, Aaron, B. Demczuk, Walter, Soualhine, Hafid, and Sharma, Meenu

Abstract

Background:Mycobacterium abscessus is a rapid growing nontuberculous mycobacteria (NTM) and a clinically significant pathogen capable of causing variable infections in humans that are difficult to treat and may require months of therapy/surgical interventions. Like other NTMs, M. abscessus can be associated with outbreaks leading to complex investigations and treatment of affected cases. Typing schemes for bacterial pathogens provide numerous applications; including identifying chain of transmission and tracking genomic evolution, are lacking or limited for many NTMs including M. abscessus. Methods: We extended the existing scheme from PubMLST using whole-genome data for M. abscessus by extracting data for 15 genetic regions within the M. abscessus genome. A total of 168 whole genomes and 11 gene sequences were used to build this scheme (MAB-multilocus sequence typing [MLST]). Results: All seven genes from the PubMLST scheme, namely argH, cya, gnd, murC, pta, purH, and rpoB, were expanded by 10, 14, 13, 10, 13, 10, and 9 alleles, respectively. Another eight novel genes were added including hsp 65, erm(41), arr, rrs, rrl, gyrA, gyrB, and recA with 16, 16, 25, 7, 32, 35, 29, and 15 alleles, respectively, with 85 unique sequence types identified among all isolates. Conclusion: MAB-MLST can provide identification of M. abscessus complex to the subspecies level based on three genes and can provide antimicrobial resistance susceptibility prediction based on results from seven genes. MAB-MLST generated a total of 85 STs, resulting in subtyping of 90 additional isolates that could not be genotyped using PubMLST and yielding results comparable to whole-genome sequencing (WGS). Implementation of a Galaxy-based data analysis tool, MAB-MLST, that simplifies the WGS data and yet maintains a high discriminatory index that can aid in deciphering an outbreak has vast applicability for routine diagnostics. [ABSTRACT FROM AUTHOR]

Published
2019
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22. Evolutionary dynamics of Vibrio cholerae O1 following a single-source introduction to Haiti

Author

Boucher, Yan, Rowe, Lori, Beaulaurier, John, Frace, Mike, Boncy, Jacques, Van Domselaar, Gary, Turnsek, Maryann A., Hanage, William P., Knox, Natalie, Paxinos, Ellen E., Bashir, Ali, Freeman, Molly M., Katz, Lee S., Hammer, Brian K., Petkau, Aaron, Stroika, Steven, Tyler, Shaun, Gladney, Lori M., Guo, Yan, Folster, Jason P., Orata, Fabini, Graham, Morag, Tarr, Cheryl L., Wang, Susana, and Antonova, Elena S.

Published
2013
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23. Evolutionary Dynamics of Vibrio cholerae O1 following a Single-Source Introduction to Haiti

Author

Katz, Lee S., primary, Petkau, Aaron, additional, Beaulaurier, John, additional, Tyler, Shaun, additional, Antonova, Elena S., additional, Turnsek, Maryann A., additional, Guo, Yan, additional, Wang, Susana, additional, Paxinos, Ellen E., additional, Orata, Fabini, additional, Gladney, Lori M., additional, Stroika, Steven, additional, Folster, Jason P., additional, Rowe, Lori, additional, Freeman, Molly M., additional, Knox, Natalie, additional, Frace, Mike, additional, Boncy, Jacques, additional, Graham, Morag, additional, Hammer, Brian K., additional, Boucher, Yan, additional, Bashir, Ali, additional, Hanage, William P., additional, Van Domselaar, Gary, additional, and Tarr, Cheryl L., additional

Published
2013
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24. Sequence database versioning for command line and Galaxy bioinformatics servers.

Author

Dooley, Damion M., Petkau, Aaron J., Van Domselaar, Gary, and Hsiao, William W. L.

Subjects
*DATABASES, *BIOINFORMATICS, *COMPUTATIONAL biology, *MOORE'S law, *GALAXIES, *COMPUTER network resources
Abstract

Motivation: There are various reasons for rerunning bioinformatics tools and pipelines on sequencing data, including reproducing a past result, validation of a new tool or workflow using a known dataset, or tracking the impact of database changes. For identical results to be achieved, regularly updated reference sequence databases must be versioned and archived. Database administrators have tried tofill the requirements by supplying users with one-off versions of databases, but these are time consuming to set up and are inconsistent across resources. Disk storage and data backup performance has also discouraged maintaining multiple versions of databases since databases such as NCBI nr can consume 50Gb or more disk space per version, with growth rates that parallel Moore's law. Results: Our end-to-end solution combines our own Kipper software package--a simple key-value large file versioning system--with BioMAJ (software for downloading sequence databases), and Galaxy (a web-based bioinformatics data processing platform). Available versions of databases can be recalled and used by command-line and Galaxy users. The Kipper data store format makes publishing curated FASTA databases convenient since in most cases it can store a range of versions into a file marginally larger than the size of the latest version. Availability and implementation: Kipper v1.0.0 and the Galaxy Versioned Data tool are written in Python and released as free and open source software available at https://github.com/Public-Health-Bioinformatics/kipper and https://github.com/Public-Health-Bioinformatics/versioned_data, respectively; detailed setup instructions can be found at https://github.com/Public-Health-Bioinformatics/versioned_data/blob/master/doc/setup.md [ABSTRACT FROM AUTHOR]

Published
2016
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31. Evolutionary Dynamics of Vibrio choleraeO1 following a Single-Source Introduction to Haiti

Author

Katz, Lee S., Petkau, Aaron, Beaulaurier, John, Tyler, Shaun, Antonova, Elena S., Turnsek, Maryann A., Guo, Yan, Wang, Susana, Paxinos, Ellen E., Orata, Fabini, Gladney, Lori M., Stroika, Steven, Folster, Jason P., Rowe, Lori, Freeman, Molly M., Knox, Natalie, Frace, Mike, Boncy, Jacques, Graham, Morag, Hammer, Brian K., Boucher, Yan, Bashir, Ali, Hanage, William P., Van Domselaar, Gary, and Tarr, Cheryl L.

Abstract

ABSTRACTPrior 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 choleraeO1 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. choleraeisolates from Haiti to gain insight into the mode and tempo of evolution in this isolated population of V. choleraeO1. 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. choleraeisolates, each expressed hapRand possessed a functional quorum-sensing system. Continued monitoring of V. choleraein Haiti will illuminate the processes influencing the origin and fate of genome variants, which will facilitate interpretation of genetic variation in future epidemics.IMPORTANCEVibrio choleraeis 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 choleraeO1 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.

Published
2013
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