Congratulations to Kara Tsang for winning the 2018 Michael G. DeGroote Institute for Infectious Disease Research (IIDR) Michael Kamin Hart Memorial Scholarship (MSc), the highest academic honour for graduate students in the IIDR. Awarded during the 2018 IIDR Trainee Day, the award was accompanied by a talk by Kara on her Ph.D. research: (Machine) Learning about antibiotic resistance genotype- phenotype relationships”. Well done Kara!

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Dr. McArthur has been busy doing some Government outreach. In early 2018 he was a Panellist on Artificial Intelligence in Healthcare at Norwegian Health Ministry & Government of Canada Round Table hosted by Hamilton Health Sciences and then in May 2018 represented McMaster University at Research Canada’s Health Research Caucus – Reshaping Health Research and Innovation: Artificial Intelligence and Machine Learning at Parliament Hill, Ottawa.

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The Comprehensive Antibiotic Resistance Database has been updated, http://card.mcmaster.ca

CARD Curation: Addition of HERA, TRU, & ACI beta-lactamases, sul4, and new quinolone efflux pumps.

Antibiotic Resistance Ontology: Expanded to include an entirely new branch describing AMR phenotypic testing methods. ARO additionally now officially available at the OBO Foundry, allowing formal integration with other ontological resources, most notably the Genomic Epidemiology Application Ontology (GenEpiO), https://github.com/genepio/genepio.

Resistance Gene Identifier: Resistome prediction for low quality or low coverage assemblies, merged metagenomics reads, and small plasmids or assembly contigs. Includes prediction of partial AMR genes. Support added for Docker operating-system-level virtualization (i.e. containerization).

Prevalence, Resistomes, & Variants: Expanded to 67 important pathogens, with a focus on ESKAPEs, WHO Priority Pathogens, and agents of sepsis.

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The Comprehensive Antibiotic Resistance Database has been updated, http://card.mcmaster.ca

This February 2018 release is our largest to date and includes new data types, a new classification system, an entirely new version of the Resistance Gene Identifier, and website improvements.

CARD Curation: 37 new ADC beta-lactamases, 21 PDC beta-lactamases, new MCR proteins, 23 rRNA mutations, resistant isoleucyl-tRNA synthetases, hundreds of new resistance mutations, and more. While in past releases all curated AMR mutations were those characterized from clinical isolates, CARD now additionally includes mutations discovered via in vitro selection experiments. Ontological improvements have been made to enable an entirely new classification system for CARD data and RGI results: resistance determinants are now systematically categorized by AMR Gene Family, Drug Class, and Resistance Mechanism. The Antibiotic Resistance Ontology is now additionally available via GitHub, https://github.com/arpcard.

Resistance Gene Identifier: Entirely new codebase, compatible with CARD data (card.json) version 2.0.0 and up (download separately). Open Reading Frame (ORF) prediction using Prodigal, homolog detection using BLAST (default) or DIAMOND, and Strict significance based on CARD curated bitscore cut-offs. Addition of rRNA mutation and efflux over-expression models. Hits of 95% identity or better are automatically listed as Strict. All results organized by revised ARO classification: AMR Gene Family, Drug Class, and Resistance Mechanism. Revised documentation, command line menu, and website graphical interface. The Resistance Gene Identifier is now additionally available via GitHub, https://github.com/arpcard.

Prevalence, Genomes, & Variants: Expansion of our computer-generated data set on the prevalence of AMR genes and variants among the sequenced genomes, plasmids, and whole-genome shotgun assemblies available at NCBI for clinically important pathogens. CARD Prevalence 2.0.0 is based on sequence data acquired from NCBI on August 28, 2017, analyzed using RGI 4.0.0 (DIAMOND homolog detection) and CARD 2.0.0. Now includes results for protein overexpression models and rRNA mutations. All results organized by the revised ARO classification: AMR Gene Family, Drug Class, and Resistance Mechanism. Download files now include 35000+ genome annotations and all predicted sequence variants.

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Congratulations to our 3rd year Biochemistry & Biomedical Sciences students upon completion of their research projects! Both will be staying on as summer research students.

 

Tammy Lau – The Importance of Protocol Design for RNA-Seq in the Ongoing Development of a Novel Technology for Tissue Specific Gene Expression Profiling in C. elegans

Arjun Sharma – The Glycopeptide Resistance Predictor

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Congratulations to 4th Year Biomedical Discovery & Commercialization student and McArthur lab member Suman Virdee for her CIHR Undergraduate Summer Studentship Award for her summer project “Development and implementation of computational tools to dissect cancer stem cell circuitry”, a joint project between our laboratory and that of Dr. Kristin Hope!

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genomecanadacolorThe McArthur lab and the Comprehensive Antibiotic Resistance Database are proud to have contributed to the Genome Canada – Canadian Food Inspection Agency Forum on Genomics and Antimicrobial Resistance. The two-day event brought together over sixty leading experts from academic, government, industry and commodities groups to address the challenge of AMR and discuss a path forward. A summary of the Forum and the Workshop Report are now online.

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genome-canada-1A cross-national research consortia co-led by McMaster’s Andrew McArthur is receiving two of 16 federal grants to further develop a big data solution to the growing problem of antimicrobial resistance (AMR). The government’s investment, totaling more than $4M, is the result of Genome Canada’s 2015 Bioinformatics and Computational Biology Competition, a partnership with the Canadian Institutes of Health Research (CIHR). McArthur and his colleagues will receive $500,000 over two years. McArthur will work closely with researchers from the University of British Columbia, Simon Fraser University, Dalhousie University and the Public Health Agency of Canada to design and develop novel software and database systems that will empower public health agencies and the agri-food sector to rapidly respond to threats posed by infectious disease outbreaks and food-borne illnesses.

Full Coverage: Faculty of Health Sciences, Genome Canada, Newswire, Hamilton Spectator

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