arjun-at-iidr-trainee-daykirill-usra-poster

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.

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17-coverNi X, Davis JH, Jain N, Razi A, Benlekbir S, McArthur AG, Rubinstein JL, Britton RA, Williamson JR, Ortega J.

Nucleic Acids Res. 2016 Sep 30;44(17):8442-55.

YphC and YsxC are GTPases in Bacillus subtilis that facilitate the assembly of the 50S ribosomal subunit, however their roles in this process are still uncharacterized. To explore their function, we used strains in which the only copy of the yphC or ysxC genes were under the control of an inducible promoter. Under depletion conditions, they accumulated incomplete ribosomal subunits that we named 45SYphC and 44.5SYsxC particles. Quantitative mass spectrometry analysis and the 5-6 Å resolution cryo-EM maps of the 45SYphC and 44.5SYsxC particles revealed that the two GTPases participate in the maturation of the central protuberance, GTPase associated region and key RNA helices in the A, P and E functional sites of the 50S subunit. We observed that YphC and YsxC bind specifically to the two immature particles, suggesting that they represent either on-pathway intermediates or that their structure has not significantly diverged from that of the actual substrate. These results describe the nature of these immature particles, a widely used tool to study the assembly process of the ribosome. They also provide the first insights into the function of YphC and YsxC in 50S subunit assembly and are consistent with this process occurring through multiple parallel pathways, as it has been described for the 30S subunit.

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s0166445xWilliams LM, Lago BA, McArthur AG, Raphenya AR, Pray N, Saleem N, Salas S, Paulson K, Mangar RS, Liu Y, Vo AH, Shavit JA.

Aquat Toxicol. 2016 Oct 1;180:141-154.

Development is a complex and well-defined process characterized by rapid cell proliferation and apoptosis. At this stage in life, a developmentally young organism is more sensitive to toxicants as compared to an adult. In response to pro-oxidant exposure, members of the Cap’n’Collar (CNC) basic leucine zipper (b-ZIP) transcription factor family (including Nfe2 and Nfe2-related factors, Nrfs) activate the expression of genes whose protein products contribute to reduced toxicity. Here, we studied the role of the CNC protein, Nfe2, in the developmental response to pro-oxidant exposure in the zebrafish (Danio rerio). Following acute waterborne exposures to diquat or tert-buytlhydroperoxide (tBOOH) at one of three developmental stages, wildtype (WT) and nfe2 knockout (KO) embryos and larvae were morphologically scored and their transcriptomes sequenced. Early in development, KO animals suffered from hypochromia that was made more severe through exposure to pro-oxidants; this phenotype in the KO may be linked to decreased expression of alas2, a gene involved in heme synthesis. WT and KO eleutheroembryos and larvae were phenotypically equally affected by exposure to pro-oxidants, where tBOOH caused more pronounced phenotypes as compared to diquat. Comparing diquat and tBOOH exposed embryos relative to the WT untreated control, a greater number of genes were up-regulated in the tBOOH condition as compared to diquat (tBOOH: 304 vs diquat: 148), including those commonly found to be differentially regulated in the vertebrate oxidative stress response (OSR) (e.g. hsp70.2, txn1, and gsr). When comparing WT and KO across all treatments and times, there were 1170 genes that were differentially expressed, of which 33 are known targets of the Nrf proteins Nrf1 and Nrf2. More specifically, in animals exposed to pro-oxidants a total of 968 genes were differentially expressed between WT and KO across developmental time, representing pathways involved in coagulation, embryonic organ development, body fluid level regulation, erythrocyte differentiation, and oxidation-reduction, amongst others. The greatest number of genes that changed in expression between WT and KO occurred in animals exposed to diquat at 2h post fertilization (hpf). Across time and treatment, there were six genes (dhx40, cfap70, dnajb9b, slc35f4, spi-c, and gpr19) that were significantly up-regulated in KO compared to WT and four genes (fhad1, cyp4v7, nlrp12, and slc16a6a) that were significantly down-regulated. None of these genes have been previously identified as targets of Nfe2 or the Nrf family. These results demonstrate that the zebrafish Nfe2 may be a regulator of both primitive erythropoiesis and the OSR during development.

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coverAuthors: Dearborn DC, Gager AB, McArthur AG, Gilmour ME, Mandzhukova E, Mauck RA.

Mol Ecol. 2016 Sep;25(17):4355-67.

Genes of the major histocompatibility complex (MHC) exhibit heterozygote advantage in immune defence, which in turn can select for MHC-disassortative mate choice. However, many species lack this expected pattern of MHC-disassortative mating. A possible explanation lies in evolutionary processes following gene duplication: if two duplicated MHC genes become functionally diverged from each other, offspring will inherit diverse multilocus genotypes even under random mating. We used locus-specific primers for high-throughput sequencing of two expressed MHC Class II B genes in Leach’s storm-petrels, Oceanodroma leucorhoa, and found that exon 2 alleles fall into two gene-specific monophyletic clades. We tested for disassortative vs. random mating at these two functionally diverged Class II B genes, using multiple metrics and different subsets of exon 2 sequence data. With good statistical power, we consistently found random assortment of mates at MHC. Despite random mating, birds had MHC genotypes with functionally diverged alleles, averaging 13 amino acid differences in pairwise comparisons of exon 2 alleles within individuals. To test whether this high MHC diversity in individuals is driven by evolutionary divergence of the two duplicated genes, we built a phylogenetic permutation model. The model showed that genotypic diversity was strongly impacted by sequence divergence between the most common allele of each gene, with a smaller additional impact of monophyly of the two genes. Divergence of allele sequences between genes may have reduced the benefits of actively seeking MHC-dissimilar mates, in which case the evolutionary history of duplicated genes is shaping the adaptive landscape of sexual selection.

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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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Arjun Sharmakirill-pankov suman annie jonsson godwin

Biochem 3R06 Project Students – Arjun Sharma

BiomedDC 4A15 Thesis Students – Kirill Pankov, Suman Virdee, Annie Cheng, Jonsson Liu, Godwin Chan

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Kara Tsang krishna

Kara Tsang (graduate, McMaster BDC) – Kara did her BiomedDC 4A15 thesis in the lab, focused on Pseudomonas resistome prediction and cystic fibrosis-associated metagenomic sequencing and starts September 2016 as MSc student in the area of clinical AMR analytics, particularly metagenomics. Her work will be part of our recently funded Genome Canada grants, as well as part of McMaster’s clinical genome sequencing efforts.

Krishna Srinivasan (graduate, McMaster Biology) – Krishna just finished his undergraduate degree in McMaster’s Biology department, with a thesis in environmental toxicology. He starts as a MSc student September 2016, collaborating with the Jenny lab (UAlabama) on our recently funded NIH grant examining the role of MTF-1 in lens development and cataractogenesis.

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Sachin Biren Dave

The McArthur Lab bids farewell and good luck to Biren Dave and Sachin Doshi! Sachin left mid-summer for a fellowship at Harvard and now is off to the UToronto Medical School! Biren finished his 3rd year Biochemistry Co-Op position and joins McMaster’s Stem Cell and Cancer Research Institute for his fourth year thesis. Thanks to you both!

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McArthur, A.G.B. Jia, A.R. Raphenya, P. Guo, K. Tsang, B. Dave, B. Alcock, B. Lago, N. Waglechner, & G.D. Wright. 2016. The Comprehensive Antibiotic Resistance Database – A Platform for Antimicrobial Resistance Surveillance. Invited presentation at the 2nd Conference Rapid Microbial NGS and Bioinformatics: Translation Into Practice, Hamburg, Germany.

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. Phenotype based criteria dominate the epidemiology of antibiotic action and effectiveness. There is a poor understanding of which antibiotic resistance genes are in circulation, which 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 (card.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 meta-models for improved AMR phenotype prediction, and release of portable command-line genome analysis tools.

 

* presenter underlined, trainees in bold
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