The McArthur lab welcomes new Curator-Developer William Huynh to the Comprehensive Antibiotic Resistance Database staff. Looking forward to pushing CARD forward with William’s help!

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The McArthur lab welcomes back summer students Rachel Tran & Arman Edalatmand plus first timers Marcel Jansen & Emily Panousis! These four will be covering a lot of ground this summer, including AMR transmission dynamics, machine learning for automated bio curation, prediction of antibiotic production in Streptomycetes, algorithm development, and data harmonization.

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Welcome Ashraf Bazan, who has joined the lab and the McMaster Biochemistry & Biomedical Sciences graduate program! A familiar face in the IIDR as he started if the Coombes lab, Ashraf joins us to lead an antimicrobial resistance (AMR) metagenomics investigation of azithromycin treatment of childhood diarrheal disease in Botswana, in collaboration with Dr. Jeffrey Pernica. Welcome Ashraf!

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COVID19 kept us from celebrating together, but we are very proud of the work you have accomplished!

Rachel Tran | Biochem 4T15 – Exploring the diversity of clinical multidrug resistance in Hamilton, Canada

Arman Edalatmand | Biochem 4T15 – Improving upon CARD*Shark and contextualizing antimicrobial resistance genes

Marcel Jansen | Biochem 4T15 – Translating the Comprehensive Antimicrobial Resistance Database to act as a stopgap for MEGARes

William Huynh | Biochem 4T15 – Expansion of Resistance Gene Identifier allows the identification of putative and novel frameshift mutations

Sohaib Syed | BiomedDC 4A15 – Expanding the scope of antimicrobial resistance surveillance of Mycobacterium tuberculosis in the Comprehensive Antibiotic Resistance Database

Thanks also goes to our 3rd year students Corie Niu (Biochem 3R06), Hamna Imtiaz (Biochem 3R06), Anna-Lisa Nguyen (HthSci 4D03), Sarah Yaqoob (Science 3RP3), & Hafsa Omer (LifeSci 3RP3)!

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Quick update on the status of the McArthur Lab and the Comprehensive Antibiotic Resistance Database. While our home institution McMaster University is closed to on-site research and undergraduate/graduate teaching, all McArthur Lab members and CARD staff are working from home. However, like many genomics labs in Canada we are directly helping our clinical colleagues in analysis of SARS-CoV-2 sequences, lending processing power, staff time, and expertise. Response time for CARD might be a bit slow as we are stretched a bit thin. But on May 1st, 2020 we will be joined by William Huynh as Junior CARD Curator & Help Desk manager. We are excited to have William join us and expect to come back strong supporting the AMR research community in May.

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Chen CY, Clark CG, Langner S, Boyd DA, Bharat A, McCorrister SJ, McArthur AG, Graham MR, Westmacott GR, Van Domselaar G

Proteomics Clin Appl. 2019 Dec 24 [Epub ahead of print]

PURPOSE: Antimicrobial resistance (AMR), especially multidrug resistance, is one of the most serious global threats facing public health. We performed a proof of concept study assessing the suitability of shotgun proteomics as a complementary approach to whole-genome sequencing (WGS) for detecting AMR determinants.

EXPERIMENTAL DESIGN: We used previously published shotgun proteomics and WGS data on four isolates of Campylobacter jejuni to perform AMR detection by searching the Comprehensive Antibiotic Resistance Database, and we assessed their detection ability relative to genomics screening and traditional phenotypic testing measured by minimum inhibitory concentration.

RESULTS: Both genomic and proteomic approaches identified the wild type and variant molecular determinants responsible for resistance to tetracycline and ciprofloxacin, in agreement with phenotypic testing. In contrast, the genomic method identified the presence of the β-lactamase gene, blaOXA-61 , in three isolates. However, its corresponding protein product was detected in only a single isolate, consistent with results obtained from phenotypic testing.

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Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, Huynh W, Nguyen A-LV, Cheng AA, Liu S, Min SY, Miroshnichenko A, Tran H-K, Werfalli RE, Nasir JA, Oloni M, Speicher DJ, Florescu A, Singh B, Faltyn M, Hernandez-Koutoucheva A, Sharma AN, Bordeleau E, Pawlowski AC, Zubyk HL, Dooley D, Griffiths E, Maguire F, Winsor GL, Beiko RG, Brinkman FSL, Hsiao WWL, Van Domselaar G, McArthur AG.

Nucleic Acids Research 2019 Oct 29. [Epub ahead of print]

The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

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Guitor AK, Raphenya AR, Klunk J, Kuch M, Alcock B, Surette MG, McArthur AG, Poinar HN, Wright GD.

Editor’s Pick! Antimicrobial Agents and Chemotherapy 2019 Oct 14. [Epub ahead of print]

The identification and association of the nucleotide sequences encoding antibiotic resistance elements is critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, which are both heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probeset on DNA libraries generated from multi-drug resistant bacteria to selectively capture resistance genes reproducibly produced higher reads on-target at greater length of coverage when compared to shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables sensitive gene detection in diverse environments where antibiotic resistance represents less than 0.1% of the metagenome.

Download the Baits & Protocol at the Comprehensive Antibiotic Resistance Database!

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Waglechner N, McArthur AG, Wright GD.

Nat Microbiol. 2019 Aug 12. [Epub ahead of print]

Glycopeptide antibiotics are produced by Actinobacteria through biosynthetic gene clusters that include genes supporting their regulation, synthesis, export and resistance. The chemical and biosynthetic diversities of glycopeptides are the product of an intricate evolutionary history. Extracting this history from genome sequences is difficult as conservation of the individual components of these gene clusters is variable and each component can have a different trajectory. We show that glycopeptide biosynthesis and resistance in Actinobacteria maps to approximately 150-400 million years ago. Phylogenetic reconciliation reveals that the precursors of glycopeptide biosynthesis are far older than other components, implying that these clusters arose from a pre-existing pool of genes. We find that resistance appeared contemporaneously with biosynthetic genes, raising the possibility that the mechanism of action of glycopeptides was a driver of diversification in these gene clusters. Our results put antibiotic biosynthesis and resistance into an evolutionary context and can guide the future discovery of compounds possessing new mechanisms of action, which are especially needed as the usefulness of the antibiotics available at present is imperilled by human activity.

More details at McMaster’s Brighter World.

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