Dataset Information

Genomics of antibiotic-resistance prediction in Pseudomonas aeruginosa.

ABSTRACT: Antibiotic resistance is a worldwide health issue spreading quickly among human and animal pathogens, as well as environmental bacteria. Misuse of antibiotics has an impact on the selection of resistant bacteria, thus contributing to an increase in the occurrence of resistant genotypes that emerge via spontaneous mutation or are acquired by horizontal gene transfer. There is a specific and urgent need not only to detect antimicrobial resistance but also to predict antibiotic resistance in silico. We now have the capability to sequence hundreds of bacterial genomes per week, including assembly and annotation. Novel and forthcoming bioinformatics tools can predict the resistome and the mobilome with a level of sophistication not previously possible. Coupled with bacterial strain collections and databases containing strain metadata, prediction of antibiotic resistance and the potential for virulence are moving rapidly toward a novel approach in molecular epidemiology. Here, we present a model system in antibiotic-resistance prediction, along with its promises and limitations. As it is commonly multidrug resistant, Pseudomonas aeruginosa causes infections that are often difficult to eradicate. We review novel approaches for genotype prediction of antibiotic resistance. We discuss the generation of microbial sequence data for real-time patient management and the prediction of antimicrobial resistance.

SUBMITTER: Jeukens J

PROVIDER: S-EPMC7379567 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Genomics of antibiotic-resistance prediction in Pseudomonas aeruginosa.

Jeukens Julie J Freschi Luca L Kukavica-Ibrulj Irena I Emond-Rheault Jean-Guillaume JG Tucker Nicholas P NP Levesque Roger C RC

Annals of the New York Academy of Sciences 20170602 1

Antibiotic resistance is a worldwide health issue spreading quickly among human and animal pathogens, as well as environmental bacteria. Misuse of antibiotics has an impact on the selection of resistant bacteria, thus contributing to an increase in the occurrence of resistant genotypes that emerge via spontaneous mutation or are acquired by horizontal gene transfer. There is a specific and urgent need not only to detect antimicrobial resistance but also to predict antibiotic resistance in silico ...[more]

PMID: 28574575

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Project description:UnlabelledElongation factor P (EF-P) is a ubiquitous bacterial protein that is required for the synthesis of poly-proline motifs during translation. In Escherichia coli and Salmonella enterica, the posttranslational ?-lysylation of Lys34 by the PoxA protein is critical for EF-P activity. PoxA is absent from many bacterial species such as Pseudomonas aeruginosa, prompting a search for alternative EF-P posttranslation modification pathways. Structural analyses of P. aeruginosa EF-P revealed the attachment of a single cyclic rhamnose moiety to an Arg residue at a position equivalent to that at which ?-Lys is attached to E. coli EF-P. Analysis of the genomes of organisms that both lack poxA and encode an Arg32-containing EF-P revealed a highly conserved glycosyltransferase (EarP) encoded at a position adjacent to efp. EF-P proteins isolated from P. aeruginosa ?earP, or from a ?rmlC::acc1 strain deficient in dTDP-L-rhamnose biosynthesis, were unmodified. In vitro assays confirmed the ability of EarP to use dTDP-L-rhamnose as a substrate for the posttranslational glycosylation of EF-P. The role of rhamnosylated EF-P in translational control was investigated in P. aeruginosa using a Pro4-green fluorescent protein (Pro4GFP) in vivo reporter assay, and the fluorescence was significantly reduced in ?efp, ?earP, and ?rmlC::acc1 strains. ?rmlC::acc1, ?earP, and ?efp strains also displayed significant increases in their sensitivities to a range of antibiotics, including ertapenem, polymyxin B, cefotaxim, and piperacillin. Taken together, our findings indicate that posttranslational rhamnosylation of EF-P plays a key role in P. aeruginosa gene expression and survival.ImportanceInfections with pathogenic Salmonella, E. coli, and Pseudomonas isolates can all lead to infectious disease with potentially fatal sequelae. EF-P proteins contribute to the pathogenicity of the causative agents of these and other diseases by controlling the translation of proteins critical for modulating antibiotic resistance, motility, and other traits that play key roles in establishing virulence. In Salmonella spp. and E. coli, the attachment of ?-Lys is required for EF-P activity, but the proteins required for this posttranslational modification pathway are absent from many organisms. Instead, bacteria such as P. aeruginosa activate EF-P by posttranslational modification with rhamnose, revealing a new role for protein glycosylation that may also prove useful as a target for the development of novel antibiotics.

Dataset Information

Genomics of antibiotic-resistance prediction in Pseudomonas aeruginosa.

Publications

Genomics of antibiotic-resistance prediction in Pseudomonas aeruginosa.

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