Tammy Lau has been awarded a prestigious Michael G. DeGroote Institute for Infectious Disease Research (IIDR) Summer Student Fellowship for her work on development of k-mer approaches to predicting pathogen-of-origin for metagenomics antimicrobial resistance gene sequences. More details here.
The McArthur lab welcomes Pardeep Gill, who will be performing a Biochem 3R06 project on the phylogenetic origins of AraC and NeuB proteins in collaboration with the Knodler lab at Washington State University and the Berti lab of McMaster’s Chemistry & Chemical Biology department, respectively.
Tammy Lau is continuing her k-mer algorithm development for AMR gene pathogen-of-origin prediction thesis work as a summer student (as part of the IRIDA consortium) and Bhavya Singh and Alexandra Florescu will be volunteering part-time on ontology development (as part of the GenEpiO consortium).
Congratulations to Jonsson Lui & Kirill Pankov, both alumni of the McArthur, for being awarded Biogen Scholarships as part of their Masters in Biomedical Discovery & Commercialization. Well done! (Jonsson Liu shown)
Florescu, A., B. Alcock, A. Raphenya, & A.G. McArthur. 2018. Incorporating phenotypic testing into ontological data sharing paradigms. Presentation at Ontario Biology Day, Waterloo, Ontario, Canada.
Lau, T. & A.G. McArthur. 2018. The optimization of antimicrobial resistance surveillance tools. Poster presentation at Ontario Biology Day, Waterloo, Ontario, Canada.
Singh, B., A.G. McArthur, & J. Stone. 2018. Ontological classification of resistance gene annotations for antimicrobial surveillance. Presentation at Ontario Biology Day, Waterloo, Ontario, Canada.
Jenny, M.J., K. Srinivasan, B. O’Shields, & A.G. McArthur. 2018. Sex and age-related differences in cadmium-induced global transcriptomic profiles in adult zebrafish eye tissues. Presentation at the Society of Toxicology 57th Annual Meeting, San Antonio, Texas.
Srinivasan, K., M.J. Jenny, & A.G. McArthur. 2018. Global changes in gene expression in human lens epithelial cells in response to cadmium exposure. Poster presentation at the Society of Toxicology 57th Annual Meeting, San Antonio, Texas
Lau, T. & A.G. McArthur. 2018. The optimization of antimicrobial resistance surveillance tools. Presentation at McMaster Women in Science and Engineering (WISE) Current Research in Engineering, Science & Technology (CREST) Meeting, Hamilton, Ontario, Canada.
Singh, B., A.G. McArthur, & J. Stone. 2018. Ontological classification of resistance gene annotations for antimicrobial surveillance. Presentation at McMaster Women in Science and Engineering (WISE) Current Research in Engineering, Science & Technology (CREST) Meeting, Hamilton, Ontario, Canada.
4th year Bachelor of Health Sciences student Alexandra Florescu has joined us for her Biochem 3A03 (Biochemical Research Practice) course. Alexandra will be collaborating with colleagues in the Genomic Epidemiology Ontology Consortium (genepio.org) on developing ontological terminology for phenotypic tests of antimicrobial resistance and microbial virulence via our ongoing Genome Canada Bioinformatics & Computational Biology funding.
Tsang, K.K. & A.G. McArthur. 2017. Encoding the efflux pump phenomena. Oral presentation at the Second American Society for Microbiology Meeting on Rapid Applied Microbial Next-Generation Sequencing and Bioinformatics Pipelines, Washington, D.C.
Background: Efflux pumps are a major mechanism for intrinsic and acquired resistance to our current antibiotic armamentarium. Efflux mechanisms interplay synergistically with other resistance mechanisms, including drug permeability, degradation and inactivation, to strengthen pathogen antimicrobial resistance levels. Despite their clinical relevance, there is no resource that seeks to understand and predict the contribution of efflux pumps in antimicrobial resistance from genome sequence. This has resulted in limited prediction of the full potential of all resistance determinants in a bacterial cell.
Methods: The Comprehensive Antibiotic Resistance Database (CARD, https://card.mcmaster.ca/) and Resistance Gene Identifier (RGI) were optimized for E. coli and P. aeruginosa efflux pump detection through extensive curation and algorithmic development. Literature was mined and analyzed to curate all published information on E. coli and P. aeruginosa efflux pumps into CARD. Algorithmic development of RGI involved creating bioinformatics detection models and refining their parameters. The Efflux Pump Identifier (EPI) was developed to predict efflux pumps and antimicrobial resistance based on RGI results generated using CARD and tested using genome sequences of characterized, clinical multi-drug resistant E. coli and P. aeruginosa isolates.
Results: The Efflux Pump Identifier (EPI) analyzed 124 E. coli and 94 P. aeruginosa clinical multi-drug resistant samples to predict efflux pumps and their complex regulatory networks under three paradigms: 1) Perfect, 2) Partial, and 3) Putative. The Perfect paradigm identifies perfect matches to known efflux pumps curated into CARD. The Partial algorithm detects efflux pumps where at least one or more components of the efflux pump is not a perfect match to an efflux pump component in CARD, but likely a functional homolog. Lastly, the Putative algorithm discovers potential efflux pumps where all components are not perfect matches to previously curated components in CARD.
Conclusions: The development of the Efflux Pump Identifier (EPI) devotes effort to an area in antimicrobial resistance where insufficient attention has been paid in the past. This is a step towards answering the long-standing question in the efflux pump phenomena; is the detected efflux pump genotype being expressed to present a specific phenotype? Using the Efflux Pump Identifier (EPI) in tandem with the existing repertoire of detection tools for dedicated and mutational resistance determinants leads to the complete prediction of antibiogram from genome sequence.
Building upon her successful Biochem 3A03 project, Tammy Lau is staying in the lab for 2017-2018 as part of her Biochem 4T15 Research Thesis. Tammy’s research will be focussed on developing new classification and visualization tools for our Resistance Gene Identifier (RGI), plus extending the RGI towards k-mer approaches for predicting pathogen-of-origin for metagenomics antimicrobial resistance gene sequences.
Today we say farewell to Arjun Sharma & Suman Virdee. Arjun joined the lab as a second year volunteer, staying to perform a Biochem 3R06 research project. He has been very active in our Comprehensive Antibiotic Resistance Database project, co-developing our CARD*Shark text mining tools for computer-guided curation of literature in PubMed, pipelines for our clinical isolate genome sequencing work, and developing novel algorithms for predicting glycopeptide resistance from genome assemblies. He was the recipient of an IIDR Summer Student Fellowship and leaves the Biochemistry program to enter medical school at the University of Toronto. Suman joined the lab in the 4th year of the Biomedical Discovery & Commercialization program, performing her thesis research on RNA-Seq bioinformatics workflows in a collaboration between our lab and the laboratory of Dr. Kristen Hope (McMaster Stem Cell and Cancer Research Institute), extending her research into the summer by winning a CIHR Summer Undergraduate Research Award. Suman finished her degree and this September starts in the McMaster Master of Science in Global Health program. Bon chance Suman & Arjun!
Anastasia joins us & the IIDR for Summer 2017 from the Center for Genomic Sciences, UNAM, Cuernavaca, Mexico as part of her successful competition for a Mitacs Globalink Internship. Throughout the summer, she will be working on data and algorithm development for antimicrobial resistance genomic surveillance. Welcome Anastasia!
Well done Kara! The OGS is a provincial merit-based scholarship, with awards available to graduate students in all disciplines of academic study, while the MacDATA Graduate Fellowship Program is part of McMaster’s new MacDATA Institute. Learn more about Kara’s Masters research on antimicrobial resistance genomics here.