Wright, G.D. & A.G. McArthur. 2015. A bioinformatic platform for the characterization of antibiotic resistance in bacterial genomes and metagenomes. Presentation at the 2015 Interscience Conference of Antimicrobial Agents and Chemotherapy, San Diego, California.
The increasingly routine sequencing of bacterial genomes in biomedical research and the clinical lab requires access to easy to use, efficient, and accurate bioinformatic tools for analysis of bacterial traits from virulence to drug resistance. To contribute to this growing need, we have developed a platform for the investigation of antibiotic resistance elements, the Comprehensive Antibiotic Resistance Database (http://arpcard.mcmaster.ca/). This resource includes a manually curated database of over 3000 resistance genes and associated literature, protein structures, and target antibiotics. Associated with this platform are tools to aid in the study of resistance including the Resistance Gene Identifier (RGI) that can analyze genomic data for the presence of resistance elements. Our goal is to accurately predict resistance phenotype from genomic data. Our analysis of many genomes and associated antibiograms reveals a reservoir of ‘silent’ resistance genes that are predicted to encode viable resistance elements yet the phenotype is drug sensitive. Our efforts to manage these issues along with identifying and adding new resistance genes will be presented.
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…
- 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.
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!
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. 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.
Smith, E.M., A.G. McArthur, M. Galus, S. Higgins, N. Kirischian, J. Jeyaranjaan, & J.Y. Wilson. 2014. Transcriptional responses of zebrafish to pharmaceutical and wastewater exposure: are single compound exposures predictive of mixtures? Keynote presentation at the Aquatic Toxicology Workshop 2014, Ottawa, Canada.
Human pharmaceuticals have been well documented in receiving waters yet their impacts on aquatic species are not clear. We have exposed adult zebrafish for 6 weeks to waterborne acetaminophen, gemfibrozil, venlafaxine, and carbamazepine at two doses (0.5 and 10 μg L-1). Fish were then exposed to a mixture of all four pharmaceuticals or wastewater effluent (5 and 25%) to assess whether transcriptional responses are similar with mixtures.. For all exposures, reproduction was significantly reduced and histopathological changes induced in kidney with at least the high dose exposure. Livers were pooled to provide sufficient RNA for microarray analyses. Hepatic transcriptional responses were determined with a modified Agilent 44K zebrafish microarry using a single channel approach. Significantly different probes were identified with a 2-way ANOVA (sex and treatment) and rank product analyses with a 10% false discovery rate. Transcriptional responses were particularly marked with acetaminophen exposure and there was broad overlap in the significant probes found between doses and across gender for this compound. 52 probes were at least 20 fold up- or down- regulated in acetaminophen exposed fish; 3 probes were 100 fold up-regulated (apolipoprotein Eb precursor, cdc73, and a hypothetical protein). Unique probes were identified for all exposures suggesting a unique transcriptional response may occur for each pharmaceutical, the pharmaceutical mixture, and wastewater effluent. Interestingly, there was almost no overlap in the transcriptional response found with single pharmaceutical exposure and either the mixture or wastewater effluent exposure. Indeed, the large transcriptional response from acetaminophen exposure was largely absent in fish exposed to the pharmaceutical mixture and wastewater effluent. This suggests that identifying individual or clusters of genes that may be useful in effects based monitoring may be difficult for pharmaceutical compounds.
Williams, L.E., A.G. McArthur, N. Waglechner, F. Nizam, P.T. Desai, M. McClelland, G.M. Weinstock, J.B. Barrett, L.M. Hiott, C.R. Jackson, & J.G. Frye. 2014. Genetic variation and genomic context of antibiotic resistance genes and mobile genetic elements in Salmonella from non-human animals. Presentation at the 114th General Meeting of the American Society for Microbiology, Boston, Massachusetts.
Zittermann, S.I., A.G. McArthur, N.V. Fittipaldi, V. Braun, L. Vrbova, D. Middleton, G. Mallo, R. Ahmed, P. Huk, M. Lombos, V.G. Allen. 2014. Whole genome sequencing of Salmonella Enteritidis for public health investigation. Presentation at the 114th General Meeting of the American Society for Microbiology, Boston, Massachusetts.
Karchner, S.I., D.G. Franks, A.R. Timme-Laragy, A.G. McArthur, & M.E. Hahn. 2013. Chemical-specific oxidative stress response in zebrafish embryos. Presentation at the Pollutant Responses in Marine Organisms (PRIMO 17) Meeting, Faro, Portugal. Exposure to natural and anthropogenic stressors often leads to oxidative stress—a disruption in the regulation of intracellular redox conditions. Animals have evolved protective responses to mitigate damage caused by oxidative stress. However, the mechanisms by which the oxidative stress response is regulated during development are poorly understood. Oxidants, electrophiles, and some phenolic anti-oxidants initiate this response by activating NF-E2-related factor 2 (NRF2) and related cap’n’collar (CNC)- basic-leucine zipper (bZIP) family proteins, which bind to the anti-oxidant response element (ARE) and activate transcription of genes such as glutathione S-transferases (GST), NAD(P)H-quinone oxidoreductase (NQO1), glutamate-cysteine ligase (GCL), and superoxide dismutase (SOD). In order to determine the genes that are induced or repressed in response to oxidative stress during development, and whether there is a “core” set of oxidant responsive genes that is induced by structurally distinct activators of NRF2, zebrafish (Danio rerio) larvae (96 hours post-fertilization) were exposed to model oxidants (tert-butylhydroquinone (tBHQ), tert-butylhydroperoxide (tBOOH), diquat (DQ) or sulforaphane (SFN)) and gene expression was measured 6 hr later by microarray and Q-RT-PCR. There was a robust response to oxidative stress by all chemicals, with a total of 1281 probes significantly altered in expression. The compounds caused overlapping but distinct patterns of altered gene expression. A core set of genes responded to all oxidants. However, other genes exhibited oxidant-specific changes in expression. Principal components analysis revealed that the changes in gene expression caused by SFN, a sulfhydryl-reactive agent, were distinct from those produced by the other oxidants. The results demonstrate that the oxidative stress response in developing animals is dependent upon the nature of the oxidative stress.