CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

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 ß-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.

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database.

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.

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline.

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

A standardized nomenclature for resistance-modifying agents in the Comprehensive Antibiotic Resistance Database.

IMPORTANCE: While increasing rates of antimicrobial resistance undermine our current arsenal of antibiotics, resistance-modifying agents (RMAs) hold promise to extend the lifetime of these important molecules. We here provide a standardized nomenclature for RMAs within the Comprehensive Antibiotic Resistance Database in aid of RMA discovery, data curation, and genome mining.

Exploring the mobilome and resistome of Enterococcus faecium in a One Health context across two continents.

Enterococcus faecium is a ubiquitous opportunistic pathogen that is exhibiting increasing levels of antimicrobial resistance (AMR). Many of the genes that confer resistance and pathogenic functions are localized on mobile genetic elements (MGEs), which facilitate their transfer between lineages. Here, features including resistance determinants, virulence factors and MGEs were profiled in a set of 1273 E. faecium genomes from two disparate geographic locations (in the UK and Canada) from a range of agricultural, clinical and associated habitats. Neither lineages of E. faecium, type A and B, nor MGEs are constrained by geographic proximity, but our results show evidence of a strong association of many profiled genes and MGEs with habitat. Many features were associated with a group of clinical and municipal wastewater genomes that are likely forming a new human-associated ecotype within type A. The evolutionary dynamics of E. faecium make it a highly versatile emerging pathogen, and its ability to acquire, transmit and lose features presents a high risk for the emergence of new pathogenic variants and novel resistance combinations. This study provides a workflow for MGE-centric surveillance of AMR in Enterococcus that can be adapted to other pathogens.

A Comparison of Whole Genome Sequencing of SARS-CoV-2 Using Amplicon-Based Sequencing, Random Hexamers, and Bait Capture.

Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex PCR and bait capture enrichment. Each method has advantages and disadvantages but a direct comparison with different viral RNA concentrations has not been performed to assess the performance of these approaches. Here we compare Liverpool amplification, ARTIC amplification, and bait capture using clinical diagnostics samples. All libraries were sequenced using an Illumina MiniSeq with data analyzed using a standardized bioinformatics workflow (SARS-CoV-2 Illumina GeNome Assembly Line; SIGNAL). One sample showed poor SARS-CoV-2 genome coverage and consensus, reflective of low viral RNA concentration. In contrast, the second sample had a higher viral RNA concentration, which yielded good genome coverage and consensus. ARTIC amplification showed the highest depth of coverage results for both samples, suggesting this protocol is effective for low concentrations. Liverpool amplification provided a more even read coverage of the SARS-CoV-2 genome, but at a lower depth of coverage. Bait capture enrichment of SARS-CoV-2 cDNA provided results on par with amplification. While only two clinical samples were examined in this comparative analysis, both the Liverpool and ARTIC amplification methods showed differing efficacy for high and low concentration samples. In addition, amplification-free bait capture enriched sequencing of cDNA is a viable method for generating a SARS-CoV-2 genome sequence and for identification of amplification artifacts.

Dynamic expression profiles of virus-responsive and putative antimicrobial peptide-encoding transcripts during Atlantic cod (Gadus morhua) embryonic and early larval development.

Early life stage mortality is one of the problems faced by Atlantic cod aquaculture. However, our understanding of immunity in early life stage fish is still incomplete, and the information available is restricted to a few species. In the present work we investigated the expression of immune-relevant transcripts in Atlantic cod during early development. The transcripts subjected to QPCR analysis in the present study were previously identified as putative anti-viral or anti-bacterial genes in Atlantic cod using suppression subtractive hybridization (SSH) libraries, QPCR, and/or microarrays. Of the 11 genes involved in this study, only atf3, cxc chemokine and gaduscidin-1 were not detected at the transcript level in all developmental stages investigated from unfertilized egg to early larval stage. Adam22, hamp, il8, irf1, irf7, lgp2, sacsin, and stat1 transcripts were detected in unfertilized egg and 7h post-fertilization (~2-cell stage) embryos, showing maternal contribution of these immune-relevant transcripts to the early embryonic transcriptome. The Atlantic cod genes included in this study presented diverse transcript expression profiles throughout embryonic and early larval development. For example, adam22 and sacsin transcripts rose abruptly during blastula/gastrula stage and were then expressed at relatively high levels through subsequent embryonic and early larval developmental stages. A peak in irf1 and irf7 transcript expression during early segmentation suggests that these interferon pathway genes play developmental stage-specific roles during cod embryogenesis. Stat1 had increasing transcript expression throughout blastula/gastrula, segmentation, and early larval developmental stages. Atf3, cxc chemokine, gaduscidin-1, and il8 transcripts rose approximately 2-3 fold during hatching, supporting the hypothesis that there is preparation at the immune-relevant transcript expression level to deal with environmental pathogens that may be encountered during early larval development. The specific roles that interferon pathway and other immune-relevant genes play in early life stage cod, and the potential impact of their dynamic transcript expression on immune competence of Atlantic cod embryos and larvae, remain unclear and warrant further study.