Read the recent publication (PMID: 31427293) on the AMRFinder, a tool that identifies antimicrobial resistance (AMR) genes in bacterial genome sequences using a high-quality curated AMR gene reference database. We use the AMRFinder to identify AMR genes in the hundreds of bacterial genomes that NCBI receives every day, and the results of AMRFinder are used in NCBI’s Isolates Browser to provide accurate assessments of AMR gene content. You can install AMRFinder locally and run it yourself. Follow the instructions on our GitHub site.
Since the publication we have upgraded AMRFinder to AMRFinderPlus. The enhanced tool now
- supports searches based on protein annotations, nucleotide sequences, or both for best results
- identifies point mutations in Campylobacter, E. coli, Shigella, and Salmonella
- optionally identifies many genes involved in biocide, heat, metal, and stress resistance, as well as many antigenicity and virulence genes
- provides information about gene function, including resistance to individual antibiotics and other phenotypes
You can learn more about NCBI’s role in helping to combat antimicrobial resistance at the National Database of Antibiotic Resistant Organisms.
The latest improvement in the NCBI search experience is designed to help you quickly find microbial proteins. Now when you search for a prokaryotic protein name such as recombinase RecA in NCBI’s sequence databases or in the All databases search, a high-quality representative protein sequence is highlighted in a panel at the top of the results page (Figure 1).
The result panel also allows you to quickly link to related resources such as NCBI’s new pages for protein family models, Identical Protein Groups, and SPARCLE, NCBI’s protein domain architecture resource. We also provide as-you-type suggestions so you don’t have to type out some of the long names.
Figure 1. The result for a search with recombinase RecA. The panel provides access to analysis tools, downloads, and relevant links to the protein family, the RefSeq protein, the identical protein group, and citations in PubMed.
Try these protein name searches, or your own, and use the as-you-type suggestions to assist your searches.
Please let us know how you like these results!
We are now showing the curated evidence used for assigning names and, if possible, gene symbols, publications, and Enzyme Commission numbers on nearly 70% (83 million) microbial RefSeq proteins. This evidence includes a hierarchical collection of curated Hidden Markov Model (HMM)-based and BLAST-based protein families, and conserved domain architectures.
As of March 2018, there were 141,000 prokaryotic genomes in the Assembly database. As this database grows, misassigned prokaryotic genomes becomes a serious problem. Taxonomy misassignment can occur through simple submission error or can accumulate as new information adds greater specification to the taxonomic tree.
A paper in the International Journal of Systematic and Evolutionary Microbiology presents the method NCBI scientists used to verify taxonomic identities in prokaryotic genomes. The authors used an Average Nucleotide Identity method with optimum threshold ranges for prokaryotic taxa to review all prokaryotic genome assemblies in GenBank. This method relies on Type strain information and is one outcome of a 2015 workshop involving several important parties in the bacteriology community.