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Journal Article•DOI•

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

Brian Alcock1, Amogelang R. Raphenya1, Tammy T. Y. Lau1, Kara K. Tsang1, Mégane Bouchard1, Arman Edalatmand1, William Huynh1, Anna-Lisa V. Nguyen1, Annie A. Cheng1, Sihan Liu1, Sally Y. Min1, Anatoly Miroshnichenko1, Hiu-Ki R Tran1, Rafik El Werfalli1, Jalees A. Nasir1, Martins Oloni1, David Speicher1, Alexandra Florescu1, Bhavya Singh1, Mateusz Faltyn1, Anastasia Hernández-Koutoucheva2, Arjun N. Sharma1, Emily Bordeleau1, Andrew C. Pawlowski3, Haley L. Zubyk1, Damion M. Dooley4, Emma Griffiths5, Finlay Maguire6, Geoffrey L. Winsor5, Robert G. Beiko6, Fiona S. L. Brinkman5, William W. L. Hsiao5, William W. L. Hsiao4, Gary Van Domselaar7, Gary Van Domselaar8, Andrew G. McArthur1 •
McMaster University1, National Autonomous University of Mexico2, Harvard University3, University of British Columbia4, Simon Fraser University5, Dalhousie University6, Public Health Agency of Canada7, University of Manitoba8
29 Oct 2019-Nucleic Acids Research (Oxford University Press)-Vol. 48
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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Citations
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Journal Article•DOI•
Antibiotic resistance in the environment.

[...]

D. G. Joakim Larsson1, Carl-Fredrik Flach1•
University of Gothenburg1
04 Nov 2021-Nature Reviews Microbiology
TL;DR: In this article, the authors present the current understanding of the roles of the environment, including antibiotic pollution, in resistance evolution, in transmission and as a mere reflection of the regional antibiotic resistance situation in the clinic.
Abstract: Antibiotic resistance is a global health challenge, involving the transfer of bacteria and genes between humans, animals and the environment. Although multiple barriers restrict the flow of both bacteria and genes, pathogens recurrently acquire new resistance factors from other species, thereby reducing our ability to prevent and treat bacterial infections. Evolutionary events that lead to the emergence of new resistance factors in pathogens are rare and challenging to predict, but may be associated with vast ramifications. Transmission events of already widespread resistant strains are, on the other hand, common, quantifiable and more predictable, but the consequences of each event are limited. Quantifying the pathways and identifying the drivers of and bottlenecks for environmental evolution and transmission of antibiotic resistance are key components to understand and manage the resistance crisis as a whole. In this Review, we present our current understanding of the roles of the environment, including antibiotic pollution, in resistance evolution, in transmission and as a mere reflection of the regional antibiotic resistance situation in the clinic. We provide a perspective on current evidence, describe risk scenarios, discuss methods for surveillance and the assessment of potential drivers, and finally identify some actions to mitigate risks.

383 citations

Journal Article•DOI•
Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome.

[...]

Stephen Nayfach1, David Paez-Espino2, David Paez-Espino1, Lee Call1, Lee Call2, Soo Jen Low3, Hila Sberro4, Natalia Ivanova2, Natalia Ivanova1, Amy D Proal, Michael A. Fischbach4, Ami S. Bhatt4, Philip Hugenholtz3, Nikos C. Kyrpides2, Nikos C. Kyrpides1 •
Lawrence Berkeley National Laboratory1, United States Department of Energy2, University of Queensland3, Stanford University4
24 Jun 2021-Nature microbiology
TL;DR: The Metagenomic Gut Virus catalogue as discussed by the authors contains 189,680 genomes from 11,810 publicly available human stool metagenomes and identified 54,118 candidate viral species, 92% of which were not found in existing databases.
Abstract: Bacteriophages have important roles in the ecology of the human gut microbiome but are under-represented in reference databases. To address this problem, we assembled the Metagenomic Gut Virus catalogue that comprises 189,680 viral genomes from 11,810 publicly available human stool metagenomes. Over 75% of genomes represent double-stranded DNA phages that infect members of the Bacteroidia and Clostridia classes. Based on sequence clustering we identified 54,118 candidate viral species, 92% of which were not found in existing databases. The Metagenomic Gut Virus catalogue improves detection of viruses in stool metagenomes and accounts for nearly 40% of CRISPR spacers found in human gut Bacteria and Archaea. We also produced a catalogue of 459,375 viral protein clusters to explore the functional potential of the gut virome. This revealed tens of thousands of diversity-generating retroelements, which use error-prone reverse transcription to mutate target genes and may be involved in the molecular arms race between phages and their bacterial hosts.

159 citations

Journal Article•DOI•
Raw Cow Milk Bacterial Consortium as Bioindicator of Circulating Anti-Microbial Resistance (AMR).

[...]

Cristian Piras1, Viviana Greco2, Viviana Greco3, Enrico Gugliandolo4, Alessio Soggiu5, Bruno Tilocca1, Luigi Bonizzi5, Alfonso Zecconi5, Rainer Cramer6, Domenico Britti1, Andrea Urbani3, Andrea Urbani2, Paola Roncada1 •
Magna Græcia University1, Agostino Gemelli University Polyclinic2, Catholic University of the Sacred Heart3, University of Messina4, University of Milan5, University of Reading6
11 Dec 2020-Animal
TL;DR: (meta)proteomics analysis of bacterial compartment of raw milk is applied to obtain a method that provides a measurement of circulating AMR involved proteins and gathers information about the whole bacterial composition.
Abstract: The environment, including animals and animal products, is colonized by bacterial species that are typical and specific of every different ecological niche. Natural and human-related ecological pressure promotes the selection and expression of genes related to antimicrobial resistance (AMR). These genes might be present in a bacterial consortium but might not necessarily be expressed. Their expression could be induced by the presence of antimicrobial compounds that could originate from a given ecological niche or from human activity. In this work, we applied (meta)proteomics analysis of bacterial compartment of raw milk in order to obtain a method that provides a measurement of circulating AMR involved proteins and gathers information about the whole bacterial composition. Results from milk analysis revealed the presence of 29 proteins/proteoforms linked to AMR. The detection of mainly β-lactamases suggests the possibility of using the milk microbiome as a bioindicator for the investigation of AMR. Moreover, it was possible to achieve a culture-free qualitative and functional analysis of raw milk bacterial consortia.

121 citations

Cites methods from "CARD 2020: antibiotic resistome sur..."

  • ...Among other proteins with AMR potential identified using the CARD15 database there is an isoform of the Aminoglycoside N(6’)-acetyltransferase of Enterococcus hirae....

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  • ...In order to identify the whole bacterial proteome, the obtained MS datasets were analyzed using different databases: UniProt KB/Swiss-Prot restricted to all reviewed Bacteria protein sequences (UniProt KB) and the Comprehensive Antibiotic Resistance Database (CARD) [14]....

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  • ...Figure 3 shows the Venn diagram of the proteins identified in the two extractions using the CARD 15 database....

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  • ...The same raw MS dataset was then searched against the CARD 15 database....

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  • ...The qualitative identification of proteins was obtained by searching two different databases: (i) bacteria (UniProt KB/Swiss-Prot Protein Knowledgebase restricted to all Bacteria taxonomy) and (ii) The Comprehensive AMR Database (CARD, https://card.mcmaster.ca/) as FASTA files [13,14]....

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Journal Article•DOI•
Majorbio Cloud: A one‐stop, comprehensive bioinformatic platform for multiomics analyses

[...]

Yi Ren, Guo Yu, Caiping Shi, Linmeng Liu, Quan Guo, Chang Pei Han, Dan Zhang, Lei Zhang, Binxu Liu, Jing Zeng, Yong-xiang Zhou, Yuhan Qiu, Jian Wei, Yanchun Luo, Fengjuan Zhu, Xiaojie Li, Qinxu Wu, Bing Li, Wenyao Fu, Yanli Tong, Jie Meng, J. Dong, Yi Feng, Shichang Xie, Qian-Ru Yang, Hui Yang, Yan Wang, Junbiao Zhang, Haidong Gu, Hongdong Xuan, Guanqing Zou, Chunshou Luo, Longjie Huang, Bing Yang, Yachen Dong, Jianhua Zhao, Jichen Han, Xianglin Zhang, Huasheng Huang 
16 Mar 2022-iMeta
TL;DR: In this paper , the authors present a platform consisting of three modules, which are preconfigured bioinformatic pipelines, cloud toolsets, and online omics' courses, which combine analytic tools for metagenomics, genomes, transcriptome, proteomics and metabolomics.
Abstract: The platform consists of three modules, which are pre-configured bioinformatic pipelines, cloud toolsets, and online omics' courses. The pre-configured bioinformatic pipelines not only combine analytic tools for metagenomics, genomes, transcriptome, proteomics and metabolomics, but also provide users with powerful and convenient interactive analysis reports, which allow them to analyze and mine data independently. As a useful supplement to the bioinformatics pipelines, a wide range of cloud toolsets can further meet the needs of users for daily biological data processing, statistics, and visualization. The rich online courses of multi-omics also provide a state-of-art platform to researchers in interactive communication and knowledge sharing.

121 citations

Journal Article•DOI•
Antibiotic resistance in microbes: History, mechanisms, therapeutic strategies and future prospects.

[...]

Tanvir Mahtab Uddin1, Arka Jyoti Chakraborty1, Ameer Khusro2, Bm Redwan Matin Zidan1, Saikat Mitra1, Talha Bin Emran3, Kuldeep Dhama4, Kamal Hossain Ripon5, Márió Gajdács6, Muhammad Umar Khayam Sahibzada7, Jamal Hossain8, Niranjan Koirala9 •
University of Dhaka1, Loyola University Chicago2, BGC Trust University Bangladesh3, Indian Veterinary Research Institute4, Mawlana Bhashani Science and Technology University5, University of Szeged6, Sarhad University of Science & IT, Ring Road (Hayatabad Link) Peshawar7, State University of Bangladesh8, Kathmandu9
23 Oct 2021-Journal of Infection and Public Health
TL;DR: Antibiotics have been used to cure bacterial infections for more than 70 years, and these low-molecular-weight bioactive agents have also been used for a variety of other medicinal applications.

99 citations

References
More filters
Journal Article•DOI•
Basic Local Alignment Search Tool

[...]

Stephen F. Altschul1, Warren Gish1, Webb Miller2, Eugene W. Myers3, David J. Lipman1 •
National Institutes of Health1, Pennsylvania State University2, University of Arizona3
01 Oct 1990-Journal of Molecular Biology
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....

    [...]

Journal Article•DOI•
Fast and accurate short read alignment with Burrows–Wheeler transform

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Heng Li1, Richard Durbin1•
Wellcome Trust Sanger Institute1
01 Jul 2009-Bioinformatics
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

Journal Article•DOI•
Fast gapped-read alignment with Bowtie 2

[...]

Ben Langmead1, Steven L. Salzberg2, Steven L. Salzberg1, Steven L. Salzberg3•
University of Maryland, College Park1, Johns Hopkins University School of Medicine2, Johns Hopkins University3
01 Apr 2012-Nature Methods
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)....

    [...]

Journal Article•DOI•
The Protein Data Bank

[...]

Helen M. Berman1, John D. Westbrook, Zukang Feng, Gary L. Gilliland, Talapady N. Bhat, Helge Weissig, Ilya N. Shindyalov, Philip E. Bourne •
Rutgers University1
01 Jan 2000-Nucleic Acids Research
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....

    [...]

Journal Article•DOI•
BLAST+: architecture and applications.

[...]

Christiam Camacho1, George Coulouris1, Vahram Avagyan1, Ning Ma1, Jason S. Papadopoulos1, Kevin Bealer1, Thomas L. Madden1 •
National Institutes of Health1
15 Dec 2009-BMC Bioinformatics
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....

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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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