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: With the strain predicted as non-human pathogen, coupled with many other identified desired features, L. reuteri PNW1 stands a chance of making good and safe candidates for probiotic, though further in-vivo investigations are still necessary.
Abstract: This study evaluates whole-genome sequence of Lactobacillus reuteri PNW1 and identifies its safety genes that may qualify it as a putative probiotic. It further extracted the bacteriocin produced by the strain and tested its effectiveness against pathogenic STEC E. coli O177. The genomic DNA was sequenced on illuminal Miseq instrument and the sequenced data was assessed for quality reads before assembled with SPAdes. The draft assembly was annotated with Prokaryotic Genome Annotation Pipeline (PGAP) and Rapid Annotations using Subsystems Technology (RAST). Further downstream analyses were carried out using appropriate bioinformatic tools. Production of biogenic amines was biochemically confirmed through HPLC analysis. The assembled genome was 2,430,215 bp long in 420 contigs with 39% G+C content. Among all known genes, putatively responsible for the production of toxic biochemicals, only arginine deiminase (EC3.5.3.6) was spotted. Coding sequences (CDS) putative for D-lactate dehydrogenase (EC1.1.1.28), L-lactate dehydrogenase (EC1.1.1.27) and bacteriocin helveticin J were found within the genome together with plethora of other probiotic important genes. The strain harbours only resistant genes putative for Lincosamide (lnuC) and Tetracycline resistant genes (tetW). There was no hit found for virulence factors and probability of the strain being a human pathogen was zero. Two intact prophage regions were detected within the genome of L. reuteri PNW1 and nine CDS were identified for insertion sequence by OASIS which are belong to seven different families. Five putative CDS were identified for the CRISPR, each associated with Cas genes. Maximum zone of inhibition exhibited by the bacteriocin produced L. reuteri PNW1 is 20.0±1.00 mm (crude) and 23.3±1.15 mm (at 0.25 mg/ml) after being partially purified. With the strain predicted as non-human pathogen, coupled with many other identified desired features, L. reuteri PNW1 stands a chance of making good and safe candidates for probiotic, though further in-vivo investigations are still necessary.
31 citations
TL;DR: Gut metagenomes from previously under-represented Asian countries, Korea, India, and Japan are developed to generate an expanded microbiome catalog, the Human Reference Gut Microbiome (HRGM), which suggested that bacterial taxa with high cross-reactivity potential may contribute more to the pathogenesis of gut microbiome-associated diseases than those with low cross- reactivity potential by promoting inflammatory condition.
Abstract: Metagenome sampling bias for geographical location and lifestyle is partially responsible for the incomplete catalog of reference genomes of gut microbial species. Thus, genome assembly from currently under-represented populations may effectively expand the reference gut microbiome and improve taxonomic and functional profiling. We assembled genomes using public whole-metagenomic shotgun sequencing (WMS) data for 110 and 645 fecal samples from India and Japan, respectively. In addition, we assembled genomes from newly generated WMS data for 90 fecal samples collected from Korea. Expecting genome assembly for low-abundance species may require a much deeper sequencing than that usually employed, so we performed ultra-deep WMS (> 30 Gbp or > 100 million read pairs) for the fecal samples from Korea. We consequently assembled 29,082 prokaryotic genomes from 845 fecal metagenomes for the three under-represented Asian countries and combined them with the Unified Human Gastrointestinal Genome (UHGG) to generate an expanded catalog, the Human Reference Gut Microbiome (HRGM). HRGM contains 232,098 non-redundant genomes for 5414 representative prokaryotic species including 780 that are novel, > 103 million unique proteins, and > 274 million single-nucleotide variants. This is an over 10% increase from the UHGG. The new 780 species were enriched for the Bacteroidaceae family, including species associated with high-fiber and seaweed-rich diets. Single-nucleotide variant density was positively associated with the speciation rate of gut commensals. We found that ultra-deep sequencing facilitated the assembly of genomes for low-abundance taxa, and deep sequencing (e.g., > 20 million read pairs) may be needed for the profiling of low-abundance taxa. Importantly, the HRGM significantly improved the taxonomic and functional classification of sequencing reads from fecal samples. Finally, analysis of human self-antigen homologs on the HRGM species genomes suggested that bacterial taxa with high cross-reactivity potential may contribute more to the pathogenesis of gut microbiome-associated diseases than those with low cross-reactivity potential by promoting inflammatory condition. By including gut metagenomes from previously under-represented Asian countries, Korea, India, and Japan, we developed a substantially expanded microbiome catalog, HRGM. Information of the microbial genomes and coding genes is publicly available (
www.mbiomenet.org/HRGM/
). HRGM will facilitate the identification and functional analysis of disease-associated gut microbiota.
31 citations
Cites methods from "CARD 2020: antibiotic resistome sur..."
...With the protein sequences predicted by Prokka, the antibiotic resistance genes were annotated using RGI v5....
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...We predicted and annotated non-coding RNAs and functional peptides, using Prokka [30]; antibiotic resistance genes, using RGI [31] (Additional file 2: Fig....
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TL;DR: In this paper, the authors explore the feasibility of using a machine learning approach, random forests (RF's), to identify the strength of associations between ARGs and bacterial taxa in metagenomic datasets from the activated sludge of WWTPs.
30 citations
TL;DR: The removal of both bacteria and ARGs was higher during summer compared to winter, and the season had no effect on the removal pattern of ARGs; combination of the serial plantation with substrate having high surface area is a potential strategy that can be used to improve the performance of CWs.
30 citations
TL;DR: This study augments the present knowledge that WGS can help predict resistance genotypes and eventual correlation with phenotypes, enabling the chance to spot AMR determinants for fast diagnosis and prioritize antibiotic use directly from sequence.
Abstract: The development of multidrug resistance in Salmonella enterica serovar Typhi currently forms a major roadblock for the treatment of enteric fever. This poses a major health problem in endemic regions and extends to travellers returning from developing countries. The appearance of fluoroquinolone non-susceptible strains has resulted in use of ceftriaxone as drug of choice with azithromycin being recommended for uncomplicated cases of typhoid fever. A recent sporadic instance of decreased susceptibility to the latest drug regime has necessitated a detailed analysis of antimicrobial resistance genes and possible relationships with their phenotypes to facilitate selection of future treatment regimes. Whole genome sequencing (WGS) was conducted for 133 clinical isolates from typhoid patients. Sequence output files were processed for pan-genome analysis and prediction of antimicrobial resistance genes. The WGS analyses disclosed the existence of fluoroquinolone resistance conferring mutations in gyrA, gyrB, parC and parE genes of all strains. Acquired resistance determining mechanisms observed included catA1 genes for chloramphenicol resistance, dfrA7, dfrA15, sul1 and sul2 for trimethoprim-sulfamethoxazole and blaTEM-116/blaTEM-1B genes for amoxicillin. No resistance determinants were found for ceftriaxone and cefixime. The genotypes were further correlated with their respective phenotypes for chloramphenicol, ampicillin, co-trimoxazole, ciprofloxacin and ceftriaxone. A high correlation was observed between genotypes and phenotypes in isolates of S. Typhi. The pan-genome analysis revealed that core genes were enriched in metabolic functions and accessory genes were majorly implicated in pathogenesis and antimicrobial resistance. The pan-genome of S. Typhi appears to be closed (Bpan = 0.09) as analysed by Heap’s law. Simpson’s diversity index of 0.51 showed a lower level of genetic diversity among isolates of S. Typhi. Overall, this study augments the present knowledge that WGS can help predict resistance genotypes and eventual correlation with phenotypes, enabling the chance to spot AMR determinants for fast diagnosis and prioritize antibiotic use directly from sequence.
30 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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