INN_CFI_ENB_2C_RGBThe McArthurLab is receives funding from the Canadian Foundation for Innovation: Twelve McMaster research projects receive more than $2.4-million

 

 

fwiDr. McArthur to be a @McMasterU Learning Portfolio Fellow! Continuing the collaboration with @TweetDrD & @McMaster_MIIETL: Meet the 2015/2016 Learning Portfolio Fellows

 

 

blue301logoDr. McArthur will be spending August 2015 at the Woods Hole Oceanographic Institution as a Guest Investigator of Dr. Mark Hahn, continuing a long standing collaboration in ecotoxicogenomics.

 

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S13695274Authors: McArthur AG, Wright GD. Curr Opin Microbiol. 2015 Jul 31;27:45-50.

Antimicrobial resistance is a global health challenge and has an evolutionary trajectory ranging from proto-resistance in the environment to untreatable clinical pathogens. Resistance is not static, as pathogenic strains can move among patient populations and individual resistance genes can move among pathogens. Effective treatment of resistant infections, antimicrobial stewardship, and new drug discovery increasingly rely upon genotype information, powered by decreasing costs of DNA sequencing. These new approaches will require advances in microbial informatics, particularly in development of reference databases of molecular determinants such as our Comprehensive Antibiotic Resistance Database and clinical metadata, new algorithms for prediction of resistome and resistance phenotype from genotype, and new protocols for global collection and sharing of high-throughput molecular epidemiology data.

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UnknownThe McArthur lab is proud to collaborate with colleagues in the Faculty of Science on the metabolic and transcriptional responses to human inactivity and aging under the leadership of Dr. Stuart Phillips (pictured) of the Department of Kinesiology’s Exercise Metabolism Research Group. Dr. Phillips successfully competed in Faculty of Science Call for Interdisciplinary Projects 2015 to obtain funding for this project, which also includes Dr. Martin Gibala (Department of Kinesiology) and Dr. Philip Britz‐McKibbin of the Department of Chemistry.

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I spent July travelling to two great meetings in the British Isles. First was the Galaxy Community Conference in Norwich, UK which provided a crash course on the Galaxy Platform for data analysis – data intensive biology for everyone! We will definitely be using Galaxy for projects in 2015-2016. Second was the 2015 Annual Conference on Intelligent Systems for Molecular Biology / European Conference on Computational Biology joint meeting in Dublin, Ireland. This meeting covers a very broad spectrum of computational biology and our work on the CARD was well received. I also got a change to attend the Bio-Ontologies SIG for the first time, which provided a lot of perspective for our ontology development efforts. And yes, I had a few pints with colleagues…

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  • McArthur, A.G. 2015. Flash Update – The Antibiotic Resistance Ontology. Presentation at Bio-Ontologies 2015, Dublin, Ireland.
  • McArthur, A.G., Waglechner, N., Nizam, F., Pereira, S.K., Jia, B., Sardar, D., Westman, E.L., Pawlowski, A.C., Johnson, T., Lo, R., Courtot, M., Brinkman, F.S., Williams, L.E., Frye, J.G., & Wright, G.D. 2015. The Comprehensive Antibiotic Resistance Database. Poster Presentation at the 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Ireland.
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W1.coverAuthors: Dhillon BK, Laird MR, Shay JA, Winsor GL, Lo R, Nizam F, Pereira SK, Waglechner N, McArthur AG, Langille MG, Brinkman FS.

Nucleic Acids Res. 2015 Jul 1;43(W1):W104-8.

IslandViewer (http://pathogenomics.sfu.ca/islandviewer) is a widely used web-based resource for the prediction and analysis of genomic islands (GIs) in bacterial and archaeal genomes. GIs are clusters of genes of probable horizontal origin, and are of high interest since they disproportionately encode genes involved in medically and environmentally important adaptations, including antimicrobial resistance and virulence. We now report a major new release of IslandViewer, since the last release in 2013. IslandViewer 3 incorporates a completely new genome visualization tool, IslandPlot, enabling for the first time interactive genome analysis and gene search capabilities using synchronized circular, horizontal and vertical genome views. In addition, more curated virulence factors and antimicrobial resistance genes have been incorporated, and homologs of these genes identified in closely related genomes using strict filters. Pathogen-associated genes have been re-calculated for all pre-computed complete genomes. For user-uploaded genomes to be analysed, IslandViewer 3 can also now handle incomplete genomes, with an improved queuing system on compute nodes to handle user demand. Overall, IslandViewer 3 represents a significant new version of this GI analysis software, with features that may make it more broadly useful for general microbial genome analysis and visualization.

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amos pearl

Amos Raphenya and Pearl Guo have joined the McArthur Lab! Amos graduated from McMaster with Bachelor of Computer Engineering in 2008 and joins the lab as a core software engineer, for both our drug resistance and ecotoxicogenomics projects. Pearl just finished her second year at the University of Waterloo’s Computer Science co-op program, with a minor in Bioinformatics. Pearl will be performing a 3 month co-op position in the lab, with a focus on algorithms for prediction of glycopeptide resistance.

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spectrum

One of the themes in the McArthurLab is research at the intersection of academia, government, and industry. We endeavour to work with government agencies and industrial partners as much as with fellow academics. This is in part a reflection of our emphasis upon applied research but also my history of starting and owning my own bioinformatics company between being a professor in the United States (until 2006) and starting my faculty position at McMaster (in late 2014). This weekend I had the opportunity to participate in @Mac_Spectrum’s Summer Startup where student teams worked to create a start-up company in 36 hours. I got to meet with a lot of the teams and discuss their start-up strategies as well as give a talk on “Software in Science Entrepreneurship” where I discussed our efforts to partner our antibiotic resistance software with government and industry partners. It was a great weekend and impressive competition. Congratulations to Clear Roots, Avaro, and E-Dopa on their awards!

 

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amr_web_banner3.7McArthur, A.G., Waglechner, N., Nizam, F., Pereira, S.K., Jia, B., Sardar, D., Westman, E.L., Pawlowski, A.C., Johnson, T., Lo, R., Courtot, M., Brinkman, F.S., Williams, L.E., Frye, J.G., & Wright, G.D. 2015. The Comprehensive Antibiotic Resistance Database. Presentation at the 4th ASM Conference on Antimicrobial Resistance in Zoonotic Bacteria and Foodborne Pathogens, Washington, District of Columbia.

Antimicrobial resistance (AMR) is among the most pressing public health crises of the 21st Century. Despite the importance of resistance to health, this field has been slow to take advantage of genome scale tools. Rather, phenotype based criteria dominate the epidemiology of antibiotic action and effectiveness. As a result, there is a poor understanding of which antibiotic resistance genes are in circulation, which ones are a threat, and how clinicians and public health workers can manage the crisis of resistance. However, DNA sequencing is rapidly decreasing in cost and as such we are on the cusp of an age of high-throughput molecular epidemiology. What are needed are tools for rapid, accurate analysis of DNA sequence data for the genetic underpinnings of antibiotic resistance. In an effort to address this problem, we have created the Comprehensive Antibiotic Resistance Database (arpcard.mcmaster.ca). This database is a rigorously curated collection of known antibiotics, targets, and resistance determinants. It integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in raw genome sequences using the novel Resistance Gene Identifier (RGI). Here we review the current state of the CARD, particularly recent advances in the curation of resistance determinants and the structure of the ARO. We will also present our plans for development of semi- and fully-automated text mining algorithms for curation of broader AMR data, construction of Probabilistic Graphic Models for improved AMR phenotype prediction, and development of portable command-line genome analysis tools.

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“A global network of millions of genomes could be medicine’s next great advance.” See the full article at the MIT Tech Review: Internet of DNA.

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