Three critical regions of the erythromycin resistance methyltransferase, ErmE, are required for function supporting a model for the interaction of Erm family enzymes with substrate rRNA

Two dynamic N-terminal regions are required for function in ribosomal RNA adenine dimethylase family members

Prominent members of the ribosomal RNA adenine dimethylase (RRAD) family of enzymes facilitate ribosome maturation by dimethylating 2 nt of small subunit rRNA, including the human DIMT1 and bacterial KsgA enzymes. A subgroup of RRAD enzymes, named erythromycin resistance methyltransferases (Erm), dimethylate a specific nucleotide in large subunit rRNA to confer antibiotic resistance. How these enzymes regulate methylation so that it only occurs on the specific substrate is not fully understood. While performing random mutagenesis on the catalytic domain of ErmE, we discovered that mutants in an N-terminal region of the protein that is disordered in the ErmE crystal structure are associated with a loss of antibiotic resistance. By subjecting site-directed mutants of ErmE and KsgA to phenotypic and in vitro assays, we found that the N-terminal region is critical for activity in RRAD enzymes: The N-terminal basic region promotes rRNA binding, and the conserved motif likely assists in juxtaposing the adenosine substrate and the S-adenosylmethionine cofactor. Our results and emerging structural data suggest that this dynamic, N-terminal region of RRAD enzymes becomes ordered upon rRNA binding, forming a cap on the active site required for methylation.

Curation of the AMRFinderPlus databases: applications, functionality and impact

Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed to identify these genomic elements. Most of those tools rely on reference databases of nucleotide or protein sequences and collections of models and rules for analysis. While the tools are critical for the identification of AMR genes, the databases themselves also provide significant utility for researchers, for applications ranging from sequence analysis to information about AMR phenotypes. Additionally, these databases can be evaluated by domain experts and others to ensure their accuracy. Here we describe how we curate the genes, point mutations and blast rules, and hidden Markov models used in NCBI’s AMRFinderPlus, along with the quality-control steps we take to ensure database quality. We also describe the web interfaces that display the full structure of the database and their newly developed cross-browser relationships. Then, using the Reference Gene Catalog as an example, we detail how the databases, rules and models are made publicly available, as well as how to access the software. In addition, as part of the Pathogen Detection system, we have analysed over 1 million publicly available genomes using AMRFinderPlus and its databases. We discuss how the computed analyses generated by those tools can be accessed through a web interface. Finally, we conclude with NCBI’s plans to make these databases accessible over the long-term.