CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database
TL;DR: A new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes, able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants.
Abstract: 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.
Citations
More filters
TL;DR: In this article, the authors applied computational saturation mutagenesis to three important drug-targets in Mycobacterium leprae (M. leparae) for the drugs dapsone, rifampin and ofloxacin namely Dihydropteroate Synthase (DHPS), RNA Polymerase (RNAP) and DNA Gyrase (GYR), respectively.
Abstract: Computational Saturation Mutagenesis is an in-silico approach that employs systematic mutagenesis of each amino acid residue in the protein to all other amino acid types, and predicts changes in thermodynamic stability and affinity to the other subunits/protein counterparts, ligands and nucleic acid molecules. The data thus generated are useful in understanding the functional consequences of mutations in antimicrobial resistance phenotypes. In this study, we applied computational saturation mutagenesis to three important drug-targets in Mycobacterium leprae (M. leprae) for the drugs dapsone, rifampin and ofloxacin namely Dihydropteroate Synthase (DHPS), RNA Polymerase (RNAP) and DNA Gyrase (GYR), respectively. M. leprae causes leprosy and is an obligate intracellular bacillus with limited protein structural information associating mutations with phenotypic resistance outcomes in leprosy. Experimentally solved structures of DHPS, RNAP and GYR of M. leprae are not available in the Protein Data Bank, therefore, we modelled the structures of these proteins using template-based comparative modelling and introduced systematic mutations in each model generating 80,902 mutations and mutant structures for all the three proteins. Impacts of mutations on stability and protein-subunit, protein-ligand and protein-nucleic acid affinities were computed using various in-house developed and other published protein stability and affinity prediction software. A consensus impact was estimated for each mutation using qualitative scoring metrics for physicochemical properties and by a categorical grouping of stability and affinity predictions. We developed a web database named HARP (a database of Hansen's Disease Antimicrobial Resistance Profiles), which is accessible at the URL - https://harp-leprosy.org and provides the details to each of these predictions.
12 citations
TL;DR: In this article , metagenomic assembly and cross-sample mapping were used to comprehensively decipher the common resistome and its potential mobility and hosts in animal manure and composts.
Abstract: Antibiotics and antibiotic resistance genes (ARGs) used in intensive animal farming threaten human health worldwide; however, the common resistome, ARG mobility, and ARG host composition in different animal manures and mixed manure composts remain unclear. In the present study, metagenomic assembly and cross-sample mapping were used to comprehensively decipher the common resistome and its potential mobility and hosts in animal manure and composts.In total, 201 ARGs were shared among different animal (layer, broiler, swine, beef cow, and dairy cow) manures and accounted for 86-99% of total relative abundance of ARGs. Except for multidrug, sulfonamide, and trimethoprim resistance genes, the relative abundance of most ARGs in composts was significantly lower than that in animal manure. Procrustes analysis indicated that antibiotic residues positively correlated with ARG composition in manure but not in composts. More than 75% ARG subtypes were shared between plasmids and chromosomes in our samples. Transposases could play a pivotal role in mediating the transfer of ARGs between different phyla in animal manure and composting. Cross-sample mapping to contigs carrying ARGs showed that the hosts of common resistome in manure had preference on animal species, and the dominant genus of ARG host shifted from Enterococcus in manure to Pseudomonas in composts. The broad host range and linking with diverse mobile genetic elements (MGEs) were two key factors for ARGs, such as sul1 and aadA, which could survive during composting. The multidrug resistance genes represented the dominant ARGs in pathogenic antibiotic-resistant bacteria in manure but could be effectively controlled by composting.Our experiments revealed the common resistome in animal manure, classified and relative quantified the ARG hosts, and assessed the mobility of ARGs. Composting can mitigate ARGs in animal manure by altering the bacterial hosts; however, persistent ARGs can escape from the removal because of diverse host range and MGEs. Our findings provide an overall background for source tracking, risk assessment, and control of livestock ARGs.
12 citations
TL;DR: The results showed medical waste accumulation significantly enriched the contents of Cu, Cr, Pb, and As in the tested soil samples, and the comparatively higher abundance and diversity of ARGs in contaminated soil pose a potential risk to human health.
12 citations
TL;DR: An original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments.
Abstract: Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs) and spread to humans. Here, we performed a longitudinal study in a large-scale commercial poultry farm in China, collecting E. coli isolates from both farm and slaughterhouse; targeting animals, carcasses, workers and their households and environment. By using whole-genome phylogenetic analysis and network analysis based on single nucleotide polymorphisms (SNPs), we found highly interrelated non-pathogenic and pathogenic E. coli strains with phylogenetic intermixing, and a high prevalence of shared multidrug resistance profiles amongst livestock, human and environment. Through an original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, we investigated the resistance to 26 different antimicrobials and identified 361 genes associated to antimicrobial resistance (AMR) phenotypes; 58 of these were known AMR-associated genes and 35 were associated to multidrug resistance. We uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments. We also found several human, livestock and environmental isolates sharing closely related mobile genetic elements carrying ARGs across host species and environments. In a scenario where no consensus exists on how antibiotic use in the livestock may affect antibiotic resistance in the human population, our findings provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming. Moreover, our original data analysis method has the potential to uncover AMR transmission pathways when applied to the study of other pathogens active in other anthropogenic environments characterised by complex interconnections between host species.
12 citations
TL;DR: High susceptibility to amikacin and apramycin suggests that aminoglycosides may remain an effective second-line treatment of ventilator-associated bacterial pneumonia, provided efficacious drug exposure in lungs can be achieved.
Abstract: Background Bacterial superinfections associated with COVID-19 are common in ventilated ICU patients and impact morbidity and lethality. However, the contribution of antimicrobial resistance to the manifestation of bacterial infections in these patients has yet to be elucidated. Methods We collected 70 Gram-negative bacterial strains, isolated from the lower respiratory tract of ventilated COVID-19 patients in Zurich, Switzerland between March and May 2020. Species identification was performed using MALDI-TOF; antibiotic susceptibility profiles were determined by EUCAST disk diffusion and CLSI broth microdilution assays. Selected Pseudomonas aeruginosa isolates were analyzed by whole-genome sequencing. Results P. aeruginosa (46%) and Enterobacterales (36%) comprised the two largest etiologic groups. Drug resistance in P. aeruginosa isolates was high for piperacillin/tazobactam (65.6%), cefepime (56.3%), ceftazidime (46.9%) and meropenem (50.0%). Enterobacterales isolates showed slightly lower levels of resistance to piperacillin/tazobactam (32%), ceftriaxone (32%), and ceftazidime (36%). All P. aeruginosa isolates and 92% of Enterobacterales isolates were susceptible to aminoglycosides, with apramycin found to provide best-in-class coverage. Genotypic analysis of consecutive P. aeruginosa isolates in one patient revealed a frameshift mutation in the transcriptional regulator nalC that coincided with a phenotypic shift in susceptibility to β-lactams and quinolones. Conclusions Considerable levels of antimicrobial resistance may have contributed to the manifestation of bacterial superinfections in ventilated COVID-19 patients, and may in some cases mandate consecutive adaptation of antibiotic therapy. High susceptibility to amikacin and apramycin suggests that aminoglycosides may remain an effective second-line treatment of ventilator-associated bacterial pneumonia, provided efficacious drug exposure in lungs can be achieved.
12 citations
References
More filters
TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
88,255 citations
"CARD 2020: antibiotic resistome sur..." refers background in this paper
...The latter is described by CARD’s Model Ontology (MO, Supplementary Figure S1), which includes reference nucleotide and protein sequences, as well as additional search parameters including mutations conferring AMR (if applicable) and curated BLAST(P/N) (34,35) bit score cut-offs....
[...]
TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals.
Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package.
Availability: http://maq.sourceforge.net
Contact: [email protected]
43,862 citations
TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
37,898 citations
"CARD 2020: antibiotic resistome sur..." refers methods in this paper
...Metagenomics analysis (i.e. RGI bwt) uses Bowtie2 (40) or BWA (41) mapping of sequencing reads to CARD’s PHM reference sequences only, while annotation of genomes or assembly contigs predicts resistome using four of CARD’s AMR detection models: PHM, PVM, RVM and POM (note: RGI currently only scans for nonsynonymous substitutions; not frameshifts, deletions or insertions)....
[...]
...RGI bwt) uses Bowtie2 (40) or BWA (41) mapping of sequencing reads to CARD’s PHM reference sequences only, while annotation of genomes or assembly contigs predicts resistome using four of CARD’s AMR detection models: PHM, PVM, RVM and POM (note: RGI currently only scans for nonsynonymous substitutions; not frameshifts, deletions or insertions)....
[...]
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Abstract: The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
34,239 citations
"CARD 2020: antibiotic resistome sur..." refers methods in this paper
...In 2017, we described the CARD*Shark text-mining algorithm (26) for computer-assisted literature triage, which we have expanded based on the new ARO Drug Class classification tags....
[...]
TL;DR: The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences.
Abstract: Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
13,223 citations
"CARD 2020: antibiotic resistome sur..." refers background or methods in this paper
...The website also includes a built-in BLAST instance for comparing sequences to CARD reference sequences and a web instance of RGI for resistome prediction with data visualization tools (https:// card.mcmaster.ca/analyze)....
[...]
...The RVM is functionally similar to the PVM, except it works for rRNA mutations and therefore uses a nucleotide reference sequence and a BLASTN bit score cut-off....
[...]
...Briefly, RGI algorithmically predicts AMR genes and mutations from submitted genomes using a combination of open reading frame prediction with Prodigal (38), sequence alignment with BLAST (35) or DIAMOND (39), and curated resistance mutations included with the AMR detection model....
[...]
...In the same time period, the CARD website hosted ∼45 000 BLAST analyses, ∼220 000 RGI analyses, ∼64 000 data file downloads, and ∼10,000 RGI software downloads....
[...]
...We had determined that the asymptotic nature of the BLAST expectation value (E) gave it very low discriminatory power between different -lactamase gene families (nearly 13 of CARD’s content), but that the linear nature of the BLAST bit score (S′) allowed this level of discrimination....
[...]