IBR   13079
INSTITUTO DE BIOLOGIA MOLECULAR Y CELULAR DE ROSARIO
Unidad Ejecutora - UE
artículos
Título:
A standard numbering scheme for class C β-lactamases
Autor/es:
BARNES MD; HUJER KM; HAFT D; VILA AJ; PAPP-WALLACE KM; DOCQUIER JD; HANSON ND; POIREL L; JACOBY GA; MACK AR; HUJER AM; FELDGARDEN M; VAN DER AKKER F; HAIDER S; ROSSOLINI GM; GALLENI M; PLESIAT P; PALZKILL TG ; BONOMO RA; TARACILA MA; CABOT G; KLIMKE W; SMANIA AM; BRADFORD PA; FRERE JM; OLIVER A; NORDMANN P; BUSH K; BARNES MD; HUJER KM; HAFT D; VILA AJ; PAPP-WALLACE KM; DOCQUIER JD; HANSON ND; POIREL L; JACOBY GA; MACK AR; HUJER AM; FELDGARDEN M; VAN DER AKKER F; HAIDER S; ROSSOLINI GM; GALLENI M; PLESIAT P; PALZKILL TG ; BONOMO RA; TARACILA MA; CABOT G; KLIMKE W; SMANIA AM; BRADFORD PA; FRERE JM; OLIVER A; NORDMANN P; BUSH K
Revista:
ANTIMICROBIAL AGENTS AND CHEMOTHERAPY
Editorial:
AMER SOC MICROBIOLOGY
Referencias:
Lugar: Washington; Año: 2020 vol. 64
ISSN:
0066-4804
Resumen:
Unlike the class A and class B β-lactamases, a standardized amino acid residue numbering system for the class C (AmpC) β-lactamases has not been proposed. This lack of standardization can lead to ambiguity when referencing the same residue with different numbers and complicates comparisons between diverse AmpC β-lactamases. Having a standardized numbering system would eliminate this ambiguity, facilitate communication within the field, and greatly simplify comparisons between families of AmpC β-lactamases. Here, we propose a standardized numbering system for AmpC β-lactamases which is based on a multiple sequence alignment of 32 diverse enzymes and accounts for secondary structure of the enzymes. We outline a simple, straightforward, and comprehensive system for assigning amino residue numbers to AmpC β-lactamases that preserves the traditional numbering of key residues (Ser64, Lys67, Tyr150, and Lys315) and defines a means of assigning residue numbers for AmpC β-lactamases with novel insertions and deletions. In addition to a structural numbering scheme, we describe a companion approach for genetic and epidemiological applications. Finally, we provide a protein profile Hidden Markov Model (HMM) which can be used to largely automate the process of assigning residue numbers to novel AmpC families or substantially different variants of existing families that may evolve or be discovered in the future.