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.
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.
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.
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.
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.
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.
David Braley Centre for Antibiotic Discovery gives researchers a fighting chance against antimicrobial resistance.
A forward-looking McMaster donor is investing $7 million in a new research centre dedicated specifically to tackling the growing global threat of antimicrobial resistance.
David Braley, whose gifts to the university include a $50-million investment in McMaster teaching, learning and health-care research and delivery, has allocated $7 million from that 2007 gift towards the new David Braley Centre for Antibiotic Discovery.
The centre will operate from the Michael G. DeGroote Institute for Infectious Disease Research, whose labs and offices are located on campus in the Michael G. DeGroote Centre for Learning and Discovery.
Dr. McArthur and PhD student Kara Tsang taught together at the 2019 MacData Institute Summer School, with Dr. McArthur reviewing biocuration and bioinformatics for genomic surviellence of antimicrobial resistance and Kara following up with a lecture on machine learning techniques to predict clinical antimicrobial resistance from raw genomic sequence.
Also congratulations to Kara for being awarded a 2019 Faculty of Health Sciences Graduate Programs Excellence Award!
Updated August 6, 2019: Congratulations to Kara for also winning an Ontario Graduate Scholarship!
The Comprehensive Antibiotic Resistance Database has been updated, http://card.mcmaster.ca
CARD Curation: Expanded MCR, OXA & IMP beta-lactamase, and macrolide phosphotransferase (MPH) sequence curation. Updated nomenclature for MPHs and drug resistant dihydrofolate reductases (dfr). Updated classification of ADC beta-lactamases.
Ontologies: Addition of 518 draft virulence ontology (VIRO) terms.
Prevalence, Resistomes, & Variants: Expansion to 82 pathogens (more Brucella species), 81,000+ resistomes, and 173,000+ AMR allele sequences based on sequence data acquired from NCBI on 28-Feb-2019, analyzed using RGI 4.2.2 (DIAMOND homolog detection) and CARD 3.0.1.
During McMaster Spring Mid-Term Recess (February 18-24), the McArthur lab is pleased to present a series of lectures, demonstrations, and training sessions for the Comprehensive Antibiotic Resistance Database (card.mcmaster.ca) and its associated Resistance Gene Identifier (RGI) software, sponsored by the Michael G. DeGroote Institute for Infectious Disease Research (IIDR).
Questions? Email firstname.lastname@example.org
Workshop & Lecture material will be available here: https://github.com/arpcard/state-of-the-card-2019