Catherine Yoshida
Public Health Agency of Canada
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Featured researches published by Catherine Yoshida.
PLOS ONE | 2016
Catherine Yoshida; Peter Kruczkiewicz; Chad R. Laing; Erika J. Lingohr; Victor P. J. Gannon; John H. E. Nash; Eduardo N. Taboada
For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.
Journal of Clinical Microbiology | 2011
Kristyn Franklin; Erika J. Lingohr; Catherine Yoshida; Muna F. Anjum; Levente Bodrossy; Clifford G. Clark; Andrew M. Kropinski; Mohamed A. Karmali
ABSTRACT We have developed a Salmonella genoserotyping array (SGSA) which rapidly generates an antigenic formula consistent with the White-Kauffmann-Le Minor scheme, currently the gold standard for Salmonella serotyping. A set of 287 strains representative of 133 Salmonella serovars was assembled to validate the array and to test the array probes for accuracy, specificity, and reproducibility. Initially, 76 known serovars were utilized to validate the specificity and repeatability of the array probes and their expected probe patterns. The SGSA generated the correct serovar designations for 100% of the known subspecies I serovars tested in the validation panel and an antigenic formula consistent with that of the White-Kauffmann-Le Minor scheme for 97% of all known serovars tested. Once validated, the SGSA was assessed against a blind panel of 100 Salmonella enterica subsp. I samples serotyped using traditional methods. In summary, the SGSA correctly identified all of the blind samples as representing Salmonella and successfully identified 92% of the antigens found within the unknown samples. Antigen- and serovar-specific probes, in combination with a pepT PCR for confirmation of S. enterica subsp. Enteritidis determinations, generated an antigenic formula and/or a serovar designation consistent with the White-Kauffmann-Le Minor scheme for 87% of unknown samples tested with the SGSA. Future experiments are planned to test the specificity of the array probes with other Salmonella serovars to demonstrate the versatility and utility of this array as a public health tool in the identification of Salmonella.
Frontiers in Microbiology | 2017
Jean Guillaume Emond-Rheault; Julie Jeukens; Luca Freschi; Irena Kukavica-Ibrulj; Brian Boyle; Marie Josée Dupont; Anna Colavecchio; Virginie Barrère; Brigitte Cadieux; Gitanjali Arya; Sadjia Bekal; Chrystal Berry; Elton Burnett; Camille Cavestri; Travis Chapin; Alanna Crouse; Michelle D. Danyluk; Pascal Delaquis; Ken Dewar; Florence Doualla-Bell; Ismail Fliss; Karen Fong; Eric Fournier; Eelco Franz; Rafael Garduno; Alexander Gill; Samantha Gruenheid; Linda J. Harris; Carol Huang; Hongsheng Huang
The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.
Frontiers in Microbiology | 2017
Chris Yachison; Catherine Yoshida; James Robertson; John H. E. Nash; Peter Kruczkiewicz; Eduardo N. Taboada; Matthew Walker; Aleisha Reimer; Sara Christianson; Anil Nichani; Celine Nadon; Ana Paccagnella; Linda Hoang; Linda Chui; Paul N. Levett; Ryan R. McDonald; John L. Wylie; David C. Alexander; Vanessa Allen; Anne Maki; Sadjia Bekal; Ross J. Davidson; Elspeth Nickerson; Janet Reid; Laura Gilbert; Greg German; Moe Elmufti; Sean Quinlan; Cathy Carrillo; Ray Allain
Salmonella serotyping remains the gold-standard tool for the classification of Salmonella isolates and forms the basis of Canada’s national surveillance program for this priority foodborne pathogen. Public health officials have been increasingly looking toward whole genome sequencing (WGS) to provide a large set of data from which all the relevant information about an isolate can be mined. However, rigorous validation and careful consideration of potential implications in the replacement of traditional surveillance methodologies with WGS data analysis tools is needed. Two in silico tools for Salmonella serotyping have been developed, the Salmonella in silico Typing Resource (SISTR) and SeqSero, while seven gene MLST for serovar prediction can be adapted for in silico analysis. All three analysis methods were assessed and compared to traditional serotyping techniques using a set of 813 verified clinical and laboratory isolates, including 492 Canadian clinical isolates and 321 isolates of human and non-human sources. Successful results were obtained for 94.8, 88.2, and 88.3% of the isolates tested using SISTR, SeqSero, and MLST, respectively, indicating all would be suitable for maintaining historical records, surveillance systems, and communication structures currently in place and the choice of the platform used will ultimately depend on the users need. Results also pointed to the need to reframe serotyping in the genomic era as a test to understand the genes that are carried by an isolate, one which is not necessarily congruent with what is antigenically expressed. The adoption of WGS for serotyping will provide the simultaneous collection of information that can be used by multiple programs within the current surveillance paradigm; however, this does not negate the importance of the various programs or the role of serotyping going forward.
Journal of Clinical Microbiology | 2016
Catherine Yoshida; Simone Gurnik; Aaminah Ahmad; Travis M. Blimkie; Stephanie A. Murphy; Andrew M. Kropinski; John H. E. Nash
ABSTRACT Classification by serotyping is the essential first step in the characterization of Salmonella isolates and is important for surveillance, source tracking, and outbreak detection. To improve detection and reduce the burden of salmonellosis, several rapid and high-throughput molecular Salmonella serotyping methods have been developed. IMPORTANCE The aim of this study was to compare three commercial kits, Salm SeroGen (Salm Sero-Genotyping AS-1 kit), Check&Trace (Check-Points), and xMAP (xMAP Salmonella serotyping assay), to the Salmonella genoserotyping array (SGSA) developed by our laboratory. They were assessed using a panel of 321 isolates that represent commonly reported serovars from human and nonhuman sources globally. The four methods correctly identified 73.8% to 94.7% of the isolates tested. The methods correctly identified 85% and 98% of the clinically important Salmonella serovars Enteritidis and Typhimurium, respectively. The methods correctly identified 75% to 100% of the nontyphoidal, broad host range Salmonella serovars, including Heidelberg, Hadar, Infantis, Kentucky, Montevideo, Newport, and Virchow. The sensitivity and specificity of Salmonella serovars Typhimurium and Enteritidis ranged from 85% to 100% and 99% to 100%, respectively. IMPORTANCE It is anticipated that whole-genome sequencing will replace serotyping in public health laboratories in the future. However, at present, it is approximately three times more expensive than molecular methods. Until consistent standards and methodologies are deployed for whole-genome sequencing, data analysis and interlaboratory comparability remain a challenge. The use of molecular serotyping will provide a valuable high-throughput alternative to traditional serotyping. This comprehensive analysis provides a detailed comparison of commercial kits available for the molecular serotyping of Salmonella.
Diagnostic Microbiology and Infectious Disease | 2014
Catherine Yoshida; Erika J. Lingohr; Friederike Trognitz; Nikki MacLaren; Andrea Rosano; Stephanie A. Murphy; Andre Villegas; Marlies Polt; Kristyn Franklin; Tanja Kostić; Andrew M. Kropinski; Roderick M. Card
Salmonella serotyping is an essential first step for identification of isolates associated with disease outbreaks. The Salmonella genoserotyping array (SGSA) is a microarray-based alternative to standard serotyping designed to rapidly identify 57 of the most commonly reported serovars through detection of the genes encoding surface O and H antigens and reporting the corresponding serovar in accordance with the existing White-Kaufmann-Le Minor serotyping scheme. In this study, we evaluated the SGSA at 4 laboratories in 3 countries by testing 1874 isolates from human and non-human sources. The SGSA correctly identified 96.7% of isolates from the target 57 serovars. For the prevalent and clinically important Salmonella serovars Enteritidis and Typhimurium, test specificity and sensitivity were greater than 98% and 99%, respectively. Due to its high-throughput nature, the SGSA is a rapid and cost-effective alternative to standard serotyping for identifying the most prevalent serovars of Salmonella.
Microbial Genomics | 2018
James Robertson; Catherine Yoshida; Peter Kruczkiewicz; Celine Nadon; Anil Nichani; Eduardo N. Taboada; John H. E. Nash
Public health and food safety institutions around the world are adopting whole genome sequencing (WGS) to replace conventional methods for characterizing Salmonella for use in surveillance and outbreak response. Falling costs and increased throughput of WGS have resulted in an explosion of data, but questions remain as to the reliability and robustness of the data. Due to the critical importance of serovar information to public health, it is essential to have reliable serovar assignments available for all of the Salmonella records. The current study used a systematic assessment and curation of all Salmonella in the sequence read archive (SRA) to assess the state of the data and their utility. A total of 67 758 genomes were assembled de novo and quality-assessed for their assembly metrics as well as species and serovar assignments. A total of 42 400 genomes passed all of the quality criteria but 30.16 % of genomes were deposited without serotype information. These data were used to compare the concordance of reported and predicted serovars for two in silico prediction tools, multi-locus sequence typing (MLST) and the Salmonella in silico Typing Resource (SISTR), which produced predictions that were fully concordant with 87.51 and 91.91 % of the tested isolates, respectively. Concordance of in silico predictions increased when serovar variants were grouped together, 89.25 % for MLST and 94.98 % for SISTR. This study represents the first large-scale validation of serovar information in public genomes and provides a large validated set of genomes, which can be used to benchmark new bioinformatics tools.
Genome Announcements | 2016
Catherine Yoshida; Stephanie L. Brumwell; Erika J. Lingohr; Aaminah Ahmad; Travis M. Blimkie; Benjamin A. Kogan; Jessica Pilsworth; Muhammad Attiq Rehman; Krista L. Schleicher; Jenitta Shanmugaraj; Andrew M. Kropinski; John H. E. Nash
ABSTRACT We report the draft genome sequences of 25 Salmonella enterica strains representing 24 different serotypes, many of which were not available in public repositories during our selection process. These draft genomes will provide useful reference for the genetic variation between serotypes and aid in the development of molecular typing tools.
Genome Announcements | 2018
James Robertson; Catherine Yoshida; Simone Gurnik; John H. E. Nash
ABSTRACT We report here the completed closed genome sequences of strains representing 36 serotypes of Salmonella. These genome sequences will provide useful references for understanding the genetic variation between serotypes, particularly as references for mapping of raw reads or to create assemblies of higher quality, as well as to aid in studies of comparative genomics of Salmonella.
Current Clinical Microbiology Reports | 2017
Gitanjali Arya; Robert Holtslander; James Robertson; Catherine Yoshida; Janet Harris; Jane Parmley; Anil Nichani; Roger P. Johnson; Cornelis Poppe
Purpose of reviewNon-typhoidal Salmonella (NTS) are among the most commonly reported cause of bacterial foodborne zoonoses. In this review, we discuss the current status of non-typhoidal salmonellosis with respect to its epidemiology, pathogenesis, antimicrobial resistance, and prevention and control measures.Recent findingsAmong the NTS, a relatively small group, which includes S. Typhimurium and S. Enteritidis, is responsible for the majority of human salmonellosis. Multidrug-resistant NTS is an emerging threat in food-animal production. Whole genome sequencing is being rapidly adopted to provide the highest possible resolution of Salmonella for outbreak investigations and routine surveillance. New advances in the study of host–pathogen interactions during Salmonella infections highlight the role of Salmonella pathogenicity islands, type III secretion systems and effectors in pathogenesis.SummaryA good understanding of the epidemiology, pathogenesis, host–pathogen interactions and emergence of virulent types of NTS will aid in the development and implementation of vaccine and public health strategies to control Salmonella from farm to fork.