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.
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!
We haven’t been travelling much this year, but our collaborators have been busy!
Dearborn, D.C., A.B. Gager, A.G. McArthur, M.E. Gilmour, E. Mandzhukova, R.A. Mauck. 2017. How to get diverse MHC genotypes without disassortative mating. Presentation at the 2017 Annual Meeting of the Society for Integrative and Comparative Biology, New Orleans, Louisiana.
McLean, M., D. Theriault, M. Kelley, B.A. Lago, A.G. McArthur, & L. Williams. 2017. Role of Nfe2 and pro-oxidant exposure in inner ear development in zebrafish. Presentation at the Society of Toxicology 56rd Annual Meeting, Baltimore, Maryland.
Williams, L.M., B.A. Lago, A.G. McArthur, A.R. Raphenya, N. Pray, N. Saleem, S. Salas, K. Paulson, R.S. Mangar, Y. Liu, A.H. Vo, & J.A. Shavit. 2017. The transcription factor, Nuclear factor, erythroid 2 (Nfe2), is a regulator of the oxidative stress response during Danio rerio development. Presentation at the Society of Toxicology 56rd Annual Meeting, Baltimore, Maryland.
Winsor, G.L., C. Bertelli, K.K. Tsang, B. Alcock, A.G. McArthur, & F.S.L. Brinkman. 2017. Pseudomonas Genome Database 2017: Improved gene/AMR/VF/genomic island annotations, comparative genome analyses, and a platform for facilitating public health genomic epidemiology. Presentation at the 16th International Conference on Pseudomonas, Liverpool, United Kingdom.
Suman Virdee – Developing a Galaxy based Pipeline for RNA-Seq Analysis in Stem Cell Biology
Kirill Pankov – The Cytochrome P450 (CYP) Superfamily in the Cnidarian Phylum
Jonsson Liu – Clinical virulence detection and Clostridium difficile clonality
Annie Cheng – Predicting Plasmid-Mediated Antimicrobial Resistance from Whole Genome Sequencing
Godwin Chan – Using the Galaxy Platform to Increase Accessibility for Structure Determination via Cryo-Electron Microscopy
The loss of effective antimicrobials is reducing our ability to protect the global population from infectious disease. However, the field of antibiotic drug discovery and the public health monitoring of antimicrobial resistance (AMR) is beginning to exploit the power of genome and metagenome sequencing. The creation of novel AMR bioinformatics tools and databases and their continued development will advance our understanding of the molecular mechanisms and threat severity of antibiotic resistance, while simultaneously improving our ability to accurately predict and screen for antibiotic resistance genes within environmental, agricultural, and clinical settings. To do so, efforts must be focused toward exploiting the advancements of genome sequencing and information technology. Currently, AMR bioinformatics software and databases reflect different scopes and functions, each with its own strengths and weaknesses. A review of the available tools reveals common approaches and reference data but also reveals gaps in our curated data, models, algorithms, and data-sharing tools that must be addressed to conquer the limitations and areas of unmet need within the AMR research field before DNA sequencing can be fully exploited for AMR surveillance and improved clinical outcomes.
3rd year Biochemistry & Biomedical Sciences student Tammy Lau has joined us for her Biochem 3A03 (Biochemical Research Practice) course. Tammy will be collaborating with Dr. Lesley MacNeil in development of a bioinformatics pipeline for a new technology for tissue-specific expression profiling in the important model organism C. elegans. Support from this project comes from a new Michael G. DeGroote Institute for Infectious Disease Research (McMaster) Research Grant. Welcome Tammy!
Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, Lago BA, Dave BM, Pereira S, Sharma AN, Doshi S, Courtot M, Lo R, Williams LE, Frye JG, Elsayegh T, Sardar D, Westman EL, Pawlowski AC, Johnson TA, Brinkman FS, Wright GD, & McArthur AG.
The Comprehensive Antibiotic Resistance Database (CARD; http://arpcard.mcmaster.ca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR. CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance. It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization. Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence. Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats. CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis.
This month we say farewell to Briony Lago as she returns to her undergraduate studies in Chemical Biology at McMaster. Briony joined us as part of her Chemical Biology Co-Op program and worked on both human muscle atrophy and zebrafish toxicology transcriptome studies, as well a curation of the Comprehensive Antibiotic Resistance Database. Her publications are below, with more on the way. Briony was also awarded a 2016 IIDR Summer Student Fellowship for her work. Good luck Briony!
- Jia, B., A.R. Raphenya, B. Alcock, N. Waglechner, P. Guo, K.K. Tsang, B.A. Lago, B.M. Dave, S. Pereira, A.N. Sharma, S. Doshi, M. Courtot, R. Lo, L.E. Williams, J.G. Frye, T. Elsayegh, D. Sardar, E.L. Westman, A.C. Pawlowski, T.A. Johnson, F.S.L. Brinkman, G.D. Wright, & A.G. McArthur. 2017. CARD 2017: expansion and model-centric curation of the Comprehensive Antibiotic Resistance Database. Nucleic Acids Research, 45, D566-573.
- Williams, L.M, B.A. Lago, A.G. McArthur, A.R. Raphenya, N. Pray, N. Saleem, S. Salas, K. Paulson, R.S. Mangar, Y. Liu, A.H. Vo, & J.A. Shavit. 2016. The transcription factor, Nuclear factor, erythroid 2 (Nfe2), is a regulator of the oxidative stress response during Danio rerio development. Aquatic Toxicology, 180, 141-154.
Three of our undergraduate students gave poster presentations in the last month. Arjun Sharma (Biochemistry & Biomedical Sciences 3rd year) outlined his work on developing the Comprehensive Antibiotic Resistance Database’s (arpcard.mcmaster.ca) CARD*Shark text mining algorithms at the Michael G. DeGroote Institute for Infectious Disease Research (IIDR) Trainee Day while Kirill Pankov (Biomedical Discovery & Commercialization 4th year) presented the results of his summer NSERC Undergraduate Student Research Award (USRA) research in the Laboratory of Dr. Joanna Wilson into the origin of Cnidarian P450 enzymes, work he is continuing in our lab as part of his thesis research. Mohammad Khan (Biomedical Discovery & Commercialization 4th year), a thesis student in the Laboratory of Dr. Eric Brown that collaborates with our group, also presented a poster at IIDR Trainee Day on his work on chemical-genetic interaction database design.
Sharma, A.N., S. Doshi, A.R. Raphenya, B. Alcock, B.M. Dave, B.A. Lago, K.K. Tsang, & A.G. McArthur. 2016. CARDShark: Computer-assisted biocuration of the Comprehensive Antibiotic Resistance Database. Poster presentation at the 2016 Michael G. DeGroote Institute for Infectious Disease Research (IIDR) Trainee Day, Hamilton, Ontario, Canada.
Pankov, K., A.G. McArthur & J.Y. Wilson. 2016. The Cytochrome P450 (CYP) superfamily in the Cnidarian phylum. Poster presentation at the 2016 Undergraduate Student Research Awards (USRA) Poster Session, Hamilton, Ontario, Canada.
Khan, M.A., S. French, B. Aubie, A.G McArthur & E.D. Brown. 2016. Challenging common screening filters through analysis of a chemical-genetic screening database. Poster presentation at the 2016 Michael G. DeGroote Institute for Infectious Disease Research (IIDR) Trainee Day, Hamilton, Ontario, Canada.