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The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Diagnosing antimicrobial resistance (AMR) in the clinic is based on empirical evidence and current gold standard laboratory phenotypic methods. Genotypic methods have the potential advantages of being faster and cheaper, and having improved mechanistic resolution over phenotypic methods. We generated and applied rule-based and logistic regression models to predict the AMR phenotype from Escherichia coli and Pseudomonas aeruginosa multidrug-resistant clinical isolate genomes. By inspecting and evaluating these models, we identified previously unknown β-lactamase substrate activities. In total, 22 unknown β-lactamase substrate activities were experimentally validated using targeted gene expression studies. Our results demonstrate that generating and analysing predictive models can help guide researchers to the mechanisms driving resistance and improve annotation of AMR genes and phenotypic prediction, and suggest that we cannot solely rely on curated knowledge to predict resistance phenotypes.

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 Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

One of the main challenges in the search for new antibiotics from natural product extracts is the re-discovery of common compounds. To address this challenge, dereplication, which is the process of identifying known compounds, is performed on samples of interest. Methods for dereplication such as analytical separation followed by mass spectrometry are time-consuming and resource-intensive. To improve the dereplication process, we have developed the antibiotic resistance platform (ARP). The ARP is a library of approximately 100 antibiotic resistance genes that have been individually cloned into Escherichia coli. This strain collection has many applications, including a cost-effective and facile method for antibiotic dereplication. The process involves the fermentation of antibiotic-producing microbes on the surface of rectangular Petri dishes containing solid medium, thereby allowing for the secretion and diffusion of secondary metabolites through the medium. After a 6 day fermentation period, the microbial biomass is removed, and a thin agar-overlay is added to the Petri dish to create a smooth surface and enable the growth of the E. coli indicator strains. Our collection of ARP strains is then pinned onto the surface of the antibiotic-containing Petri dish. The plate is next incubated overnight to allow for E. coli growth on the surface of the overlay. Only strains containing resistance to a specific antibiotic (or class) grow on this surface enabling rapid identification of the produced compound. This method has been successfully used for the identification of producers of known antibiotics and as a means to identify those producing novel compounds.

Lipid A phosphoethanolamine (PEtN) transferases render bacteria resistant to the last resort antibiotic colistin. The recent discoveries of pathogenic bacteria harboring plasmid-borne PEtN transferase ( mcr) genes have illustrated the serious potential for wide dissemination of these resistance elements. The origin of mcr-1 is traced to Moraxella species co-occupying environmental niches with Enterobacteriaceae. Here, we describe the crystal structure of the catalytic domain of the chromosomally encoded colistin resistance PEtN transferase, ICR Mc (for intrinsic colistin resistance) of Moraxella catarrhalis. The ICR Mc structure in complex with PEtN reveals key molecular details including specific residues involved in catalysis and PEtN binding. It also demonstrates that ICR Mc catalytic domain dimerization is required for substrate binding. Our structure-guided phylogenetic analysis provides sequence signatures defining potentially colistin-active representatives in this enzyme family. Combined, these results advance the molecular and mechanistic understanding of PEtN transferases and illuminate their origins.

Rifamycin monooxygenases (Rox) are present in a variety of environmental bacteria and are associated with decomposition of the clinically utilized antibiotic rifampin. Here we report the structure and function of a drug-inducible rox gene from Streptomyces venezuelae, which encodes a class A flavoprotein monooxygenase that inactivates a broad range of rifamycin antibiotics. Our findings describe a mechanism of rifamycin inactivation initiated by monooxygenation of the 2-position of the naphthyl group, which subsequently results in ring opening and linearization of the antibiotic. The result is an antibiotic that no longer adopts the basket-like structure essential for binding to the RNA exit tunnel of the target RpoB, thereby providing the molecular logic of resistance. This unique mechanism of enzymatic inactivation underpins the broad spectrum of rifamycin resistance mediated by Rox enzymes and presents a new antibiotic resistance mechanism not yet seen in microbial antibiotic detoxification., (Copyright © 2018 Elsevier Ltd. All rights reserved.)