Biology:MEGARes
| Content | |
|---|---|
| Description | MEGARes is an antimicrobial resistance database made for high throughput sequencing based at collaborating centers |
| Data types captured | Antimicrobial resistance genes and phenotypes |
| Organisms | Bacteria |
| Contact | |
| Research centre | Texas A&M University, University of Minnesota, University of Florida, Colorado State Uninversity |
| Primary citation | PMID 27899569 |
| Access | |
| Website | http://meglab.org |
| Download URL | Download |
| Miscellaneous | |
| Bookmarkable entities | yes |
MEGARes is a hand-curated antibiotic resistance database which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 3.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 59 classes, 223 mechanisms of resistance, and 1,448 gene groups that classify the 8,733 gene accessions. [1][2][3] This works in conjunction with the AMR++ bioinformatics pipelin (version 3.0) to classify resistome sequences directly from FASTA.[citation needed]
The database focuses on the analysis of large-scale, ecological sequence datasets with an annotation structure that allows for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes annotation consists of three hierarchical levels when looking at AMR genes: drug class, mechanism, and group. The comprehensive MEGARes content was compiled from all published sequences included various other databases: Resfinder, ARG-ANNOT, Comprehensive Antibiotic Resistance Database (CARD), and the National Center for Biotechnology Information (NCBI) Lahey Clinic beta-lactamase archive.[citation needed]
MEGARes allows users to analyze antimicrobial resistance on a population-level, similar to a microbiome analysis, from a FASTA sequence. Furthermore, users can access AMR++, a bioiinformatics pipeline for resistome analysis of metagenomic datasets that can be integrated with the MEGARes database.[citation needed]
See also
References
- ↑ Lakin SM, Dean C, Noyes NR, Dettenwanger A, Ross AS, Doster E, Rovira P, Abdo Z, Jones KL, Ruiz J, Belk KE, Morley PS, Boucher C. MEGARes: an antimicrobial resistance database for high throughput sequencing. Nucleic Acids Res. 2017 Jan 4;45(D1):D574-D580. https://doi.org/10.1093/nar/gkw1009.
- ↑ Doster E, Lakin SM, Dean CJ, Wolfe C, Young JG, Boucher C, Belk KE, Noyes NR, Morley PS. MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data. Nucleic Acids Res. 2020 Jan 8;48(D1):D561-D569. https://doi.org/10.1093/nar/gkz1010
- ↑ Bonin N, Doster E, Worley H, Pinnell LJ, Bravo J, Ferm P, Marini S, Prosperi M, Noyes NR, Morley PS, Boucher C. MEGARes and AMR++, v3.0: An updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing. Nucleic Acids Res 2022 gkac1047. https://doi.org/10.1093/nar/gkac1047.
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