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.
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TL;DR: In this paper , the authors used PromethION to determine the whole genome sequence of R. anatipestifer RCAD0416, a multidrug-resistant isolate from China.
4 citations
TL;DR: The findings of this report may serve as baseline information for laboratory studies leading to the discovery of drugs for use against C. ureolyticus infections and help identify potential risks associated with the selected compounds.
Abstract: Campylobacter ureolyticus is a Gram-negative, anaerobic, non-spore-forming bacteria that causes gastrointestinal infections. Being the most prevalent cause of bacterial enteritis globally, infection by this bacterium is linked with significant morbidity and mortality in children and immunocompromised patients. No information on pan-therapeutic drug targets for this species is available yet. In the current study, a pan-genome analysis was performed on 13 strains of C. ureolyticus to prioritize potent drug targets from the identified core genome. In total, 26 druggable proteins were identified using subtractive genomics. To the best of the authors’ knowledge, this is the first report on the mining of drug targets in C. ureolyticus. UDP-3-O-acyl-N-acetylglucosamine deacetylase (LpxC) was selected as a promiscuous pharmacological target for virtual screening of two bacterial-derived natural product libraries, i.e., postbiotics (n = 78) and streptomycin (n = 737) compounds. LpxC inhibitors from the ZINC database (n = 142 compounds) were also studied with reference to LpxC of C. ureolyticus. The top three docked compounds from each library (including ZINC26844580, ZINC13474902, ZINC13474878, Notoginsenoside St-4, Asiaticoside F, Paraherquamide E, Phytoene, Lycopene, and Sparsomycin) were selected based on their binding energies and validated using molecular dynamics simulations. To help identify potential risks associated with the selected compounds, ADMET profiling was also performed and most of the compounds were considered safe. Our findings may serve as baseline information for laboratory studies leading to the discovery of drugs for use against C. ureolyticus infections.
4 citations
TL;DR: Evidence is provided for a gut–metabolism–kidney axis in the metabolism of db/db mice, in which the gut microbiome and circulating metabolomics interact, and suggests that information from this axis may contribute to the understanding of T2D and DKD pathogenesis.
Abstract: Evidence has demonstrated that either metabolites or intestinal microbiota are involved in the pathogenesis of type 2 diabetes (T2D) and diabetic kidney disease (DKD). To explore the interaction between plasma metabolomics and intestinal microbiome in the progress of T2D-DKD, in the current study, we analyzed metabolomics in the plasma of db/db mice with liquid chromatography–mass spectrometry and also examined intestinal prokaryotes and entire gut microbiome dysbiosis at the genus level with both 16S rDNA and metagenomic sequencing techniques. We found that Negativibacillus and Rikenella were upregulated, while Akkermansia, Candidatus, Erysipelatoclostridium and Ileibacterium were downregulated in the colon of db/db mice compared with non-diabetic controls. In parallel, a total of 91 metabolites were upregulated, while 23 were downregulated in the plasma of db/db mice. The top five upregulated metabolites included D-arabinose 5-phosphate, estrone 3-sulfate, L-theanine, 3′-aenylic acid and adenosine 5′-monophosphate, and the five most significantly downregulated metabolites were aurohyocholic acid sodium salt, calcium phosphorylcholine chloride, tauro-alpha-muricholic acid sodium salt, galactinol and phosphocholine. These plasma metabolites were interacted with intestinal microbiomes, which are mainly involved in the pathways related to the biosynthesis of unsaturated fatty acids, fatty acid elongation, steroid biosynthesis, and D-arginine and D-ornithine metabolism. In the differential metabolites, N-acetyl-L-ornithine, ornithine and L-kyn could be metabolized by the correspondingly differential ontology genes in the intestinal metagenome. The current study thereby provides evidence for a gut–metabolism–kidney axis in the metabolism of db/db mice, in which the gut microbiome and circulating metabolomics interact, and suggests that information from this axis may contribute to our understanding of T2D and DKD pathogenesis.
4 citations
TL;DR: The aim of this review is to highlight the updated knowledge of AMR genes in the mobilome of Salmonella and related enteric bacteria to identify and verification of emerging multidrug resistance.
Abstract: The foodborne pathogen Salmonella enterica is considered a global public health risk. Salmonella enterica isolates can develop resistance to several antimicrobial drugs due to the rapid spread of antimicrobial resistance (AMR) genes, thus increasing the impact on hospitalization and treatment costs, as well as the healthcare system. Mobile genetic elements (MGEs) play key roles in the dissemination of AMR genes in S. enterica isolates. Multiple phenotypic and molecular techniques have been utilized to better understand the biology and epidemiology of plasmids including DNA sequence analyses, whole genome sequencing (WGS), incompatibility typing, and conjugation studies of plasmids from S. enterica and related species. Focusing on the dynamics of AMR genes is critical for identification and verification of emerging multidrug resistance. The aim of this review is to highlight the updated knowledge of AMR genes in the mobilome of Salmonella and related enteric bacteria. The mobilome is a term defined as all MGEs, including plasmids, transposons, insertion sequences (ISs), gene cassettes, integrons, and resistance islands, that contribute to the potential spread of genes in an organism, including S. enterica isolates and related species, which are the focus of this review.
4 citations
23 Sep 2021
TL;DR: Escherichia phage 590B, which was isolated from community sewage water in Chandigarh, India, exhibited lytic activity against an extensively drug-resistant uropathogenic E coli isolate as mentioned in this paper.
Abstract: Escherichia phage 590B, which was isolated from community sewage water in Chandigarh, India, exhibited lytic activity against an extensively drug-resistant uropathogenic Escherichia coli isolate. The genome of the phage is linear, double stranded, and 44.39 kb long. Phage 590B is a member of the Siphoviridae family and is closest to phage vB_EcoS_XY2, which was isolated in China.
4 citations
References
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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....
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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)....
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...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)....
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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....
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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)....
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...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....
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...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....
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...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....
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...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....
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