Introduction to the database card of resistance gene

With the discovery and use of antibiotic drugs, more and more drug resistant strains are produced. The development of drug-resistant strains will increase the difficulty and cost of treatment, so the study of resistant microorganisms is particularly important. At present, through the identification of drug resistance gene excavation can help us to uncover the mechanism of resistance, for the treatment of diseases, drug research and development to provide reference. ARDB is the first database to integrate the anti-drug genes in various microorganisms, but it has not been updated since 2009. The comprehensive Antibiotic research database contains all the resistance information in the ARDB database and builds a data sharing platform based on the contribution of volunteers, so that real-time updates ensure the effectiveness of the data. Currently, the card database collects more than 1600 known antibiotic resistance genes.

Database description

Card Database (http://arpcard.mcmaster.ca) core is aro (antibiotic resistance Ontology), ARO contains the antibiotic resistance genes, resistance mechanisms, antibiotics and target-related term,. Published in 2017, the database has been updated with relevant functions, including other ontologies, such as Mo, which describes the module and parameters for the prediction of antibiotic resistance genes, the definition of RO for different term relationship types, and the ncbitaxon of species and strains in the description card.

Drug resistance Gene prediction

On the Card database website, click on the Analyze option to enter the drug resistant gene prediction interface. The predictive analysis of resistant genes can be achieved by choosing two modes, blast and RGi (resistance gene Identifier). Blast is dependent on the blast software in NCBI, and the sequence is compared with the card reference sequence to obtain relevant annotation information; RGi is a software developed by the card database team based on protein predictive resistance gene sequences that predict resistance gene sequences through protein homology and protein mutation. At present, RGi can only analyze protein sequences, if there are genomic sequences or assembled Contigs submitted, then the first need to use software prodigal to predict the open reading box, and then rgi analysis of the predicted protein sequence.

Figure 1

RGi accepts data in a variety of formats, including: GenBank accession, GI, Fasta sequence information, etc., as shown in Figure 2. In the prediction of resistance genes, three algorithms were provided, namely perfect, Strict, and Loose. RGi General default Perfect, Strict. RGi results can be visualized by resistance wheel, as shown in Figure 3. The inner ring represents the resistance classification, the outer ring represents the antibiotic resistance gene, such as the resistance gene orf0_267 expression aminoglycoside (aminoglycoside) antibiotic resistance.

Figure 2

Figure 3

Database download

All ARO, targets, sequences, etc. can be downloaded for http://arpcard.mcmaster.ca/download. 4, ARO exists in OBO format, each term contains term ID number, antibiotic classification information, antibiotic description information, and so on; sequence data exists in FASTA format, 5.

Figure 4 ARO

Figure 5 Nucleotide_fasta_protein_homolog_model

After the card database is downloaded, the gene sequence can be compared to the card database by BLASTP, thus the resistance gene is annotated. If the scaffold sequence is given, it is necessary to make a genetic prediction and then compare the predicted protein sequence to the card database to obtain the resistance gene.

Reference documents:

Mcarthur,a.g., Waglechner,n, Nizam,f., Yan,a., Azad,m.a., BAYLAY,A.J., Bhullar,k., canova,m.j., de pascale,g., Ejim,L. E T al. The comprehensive antibiotic resistance database. Antimicrob. Agents Chemother., 57, 3348–3357.

2. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, Lago BA, Dave BM, Pereira S, Sharma An.et al. 2017:expansion and Model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Volume p.d566-d573

Introduction to the database card of resistance gene