CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database
Brian Alcock,Amogelang R. Raphenya,Tammy T. Y. Lau,Kara K. Tsang,Mégane Bouchard,Arman Edalatmand,William Huynh,Anna-Lisa V. Nguyen,Annie A. Cheng,Sihan Liu,Sally Y. Min,Anatoly Miroshnichenko,Hiu-Ki R Tran,Rafik El Werfalli,Jalees A. Nasir,Martins Oloni,David Speicher,Alexandra Florescu,Bhavya Singh,Mateusz Faltyn,Anastasia Hernández-Koutoucheva,Arjun N. Sharma,Emily Bordeleau,Andrew C. Pawlowski,Haley L. Zubyk,Damion M. Dooley,Emma Griffiths,Finlay Maguire,Geoffrey L. Winsor,Robert G. Beiko,Fiona S. L. Brinkman,William W. L. Hsiao,William W. L. Hsiao,Gary Van Domselaar,Gary Van Domselaar,Andrew G. McArthur +35 more
TLDR
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.read more
Citations
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Of Cockroaches and Symbionts: Recent Advances in the Characterization of the Relationship between Blattella germanica and Its Dual Symbiotic System
TL;DR: The German cockroach Blattella germanica is a good model for the study of symbiotic interactions, as it can be maintained in the laboratory in controlled populations, allowing the perturbations of the two symbiotic systems in order to study the communication and integration of the tripartite organization of the host–endosymbiont–microbiota.
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Genome Analysis and Antibiofilm Activity of Phage 590B against Multidrug-Resistant and Extensively Drug-Resistant Uropathogenic Escherichia coli Isolates, India
TL;DR: In this paper , a lytic phage (590B) was isolated from community sewage in Chandigarh, which was active against multiple MDR and XDR biofilm-forming UPEC strains.
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Metagenomic Analysis Reveals Changes in Bacterial Communities and Antibiotic Resistance Genes in an Eye Specialty Hospital and a General Hospital Before and After Wastewater Treatment
Xueli Ma,Xuyang Dong,Jiabei Cai,Chunyan Fu,Jing Yang,Yuan Liu,Yan Jun Zhang,Tian Wan,Shudan Lin,Yongliang Lou,Mei-Qin Zheng +10 more
TL;DR: In this article , high-throughput metagenomic sequencing was used to analyze the bacterial community composition and ARGs in two hospitals exposed to different antibiotic use conditions (an eye specialty hospital and a general hospital) before and after wastewater treatment.
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Ontology-Aware Deep Learning Enables Novel Antibiotic Resistance Gene Discovery Towards Comprehensive Profiling of ARGs
TL;DR: In this paper, an ontology-aware deep learning model, ONN4ARG (http://onn4arg.xfcui.com/), is proposed for the discovery of novel ARGs based on multi-level annotations.
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Extended genomic analyses of the broad-host-range phages vB_KmiM-2Di and vB_KmiM-4Dii reveal slopekviruses have highly conserved genomes
TL;DR: In this article , the authors characterized two phages, vB_KmiM-2Di and vB-Kmi-M-4Dii, that were isolated from sewage water against two GES-5-positive Klebsiella michiganensis strains (PS_Koxy2 and PS-Koxy4, respectively) and found that they belonged to the genus Slopekvirus.
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