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1.
Microbiology (Reading) ; 168(8)2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35943884

RESUMO

The discovery of penicillin by Alexander Fleming marked a new era for modern medicine, allowing not only the treatment of infectious diseases, but also the safe performance of life-saving interventions, like surgery and chemotherapy. Unfortunately, resistance against penicillin, as well as more complex ß-lactam antibiotics, has rapidly emerged since the introduction of these drugs in the clinic, and is largely driven by a single type of extra-cytoplasmic proteins, hydrolytic enzymes called ß-lactamases. While the structures, biochemistry and epidemiology of these resistance determinants have been extensively characterized, their biogenesis, a complex process including multiple steps and involving several fundamental biochemical pathways, is rarely discussed. In this review, we provide a comprehensive overview of the journey of ß-lactamases, from the moment they exit the ribosomal channel until they reach their final cellular destination as folded and active enzymes.


Assuntos
Penicilinas , beta-Lactamases , Antibacterianos/farmacologia , Antibacterianos/uso terapêutico , Inibidores de beta-Lactamases , beta-Lactamases/genética , beta-Lactamases/metabolismo
2.
Microlife ; 3: uqac013, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-37223348

RESUMO

Neisseria gonorrhoeae causes the sexually transmitted disease gonorrhoea. The treatment of gonorrhoea is becoming increasingly challenging, as N. gonorrhoeae has developed resistance to antimicrobial agents routinely used in the clinic. Resistance to penicillin is wide-spread partly due to the acquisition of ß-lactamase genes. How N. gonorrhoeae survives an initial exposure to ß-lactams before acquiring resistance genes remains to be understood. Here, using a panel of clinical isolates of N. gonorrhoeae we show that the ß-lactamase enzyme is packaged into outer membrane vesicles (OMVs) by strains expressing blaTEM-1B or blaTEM-106, which protects otherwise susceptible clinical isolates from the ß-lactam drug amoxycillin. We characterized the phenotypes of these clinical isolates of N. gonorrhoeae and the time courses over which the cross-protection of the strains is effective. Imaging and biochemical assays suggest that OMVs promote the transfer of proteins and lipids between bacteria. Thus, N. gonorrhoeae strains secret antibiotic degrading enzymes via OMVs enabling survival of otherwise susceptible bacteria.

3.
mBio ; 12(3): e0130221, 2021 06 29.
Artigo em Inglês | MEDLINE | ID: mdl-34154411

RESUMO

The cell envelope of Gram-negative bacteria consists of two membranes surrounding the periplasm and peptidoglycan layer. ß-Lactam antibiotics target the periplasmic penicillin-binding proteins that synthesize peptidoglycan, resulting in cell death. The primary means by which bacterial species resist the effects of ß-lactam drugs is to populate the periplasmic space with ß-lactamases. Resistance to ß-lactam drugs is spread by lateral transfer of genes encoding ß-lactamases from one species of bacteria to another. However, the resistance phenotype depends in turn on these "alien" protein sequences being recognized and exported across the cytoplasmic membrane by either the Sec or Tat protein translocation machinery of the new bacterial host. Here, we examine BKC-1, a carbapenemase from an unknown bacterial source that has been identified in a single clinical isolate of Klebsiella pneumoniae. BKC-1 was shown to be located in the periplasm, and functional in both K. pneumoniae and Escherichia coli. Sequence analysis revealed the presence of an unusual signal peptide with a twin arginine motif and a duplicated hydrophobic region. Biochemical assays showed this signal peptide directs BKC-1 for translocation by both Sec and Tat translocons. This is one of the few descriptions of a periplasmic protein that is functionally translocated by both export pathways in the same organism, and we suggest it represents a snapshot of evolution for a ß-lactamase adapting to functionality in a new host. IMPORTANCE Bacteria can readily acquire plasmids via lateral gene transfer (LGT). These plasmids can carry genes for virulence and antimicrobial resistance (AMR). Of growing concern are LGT events that spread ß-lactamases, particularly carbapenemases, and it is important to understand what limits this spread. This study provides insight into the sequence features of BKC-1 that exemplify the limitations on the successful biogenesis of ß-lactamases, which is one factor limiting the spread of AMR phenotypes by LGT. With a very simple evolutionary adaptation, BKC-1 could become a more effective carbapenemase, underscoring the need to understand the evolution, adaptability, and functional assessment of newly reported ß-lactamases rapidly and thoroughly.


Assuntos
Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismo , Produtos do Gene tat/genética , Klebsiella pneumoniae/genética , Canais de Translocação SEC/genética , beta-Lactamases/genética , beta-Lactamases/metabolismo , Antibacterianos/farmacologia , Transporte Biológico , Escherichia coli/genética , Humanos , Infecções por Klebsiella/microbiologia , Klebsiella pneumoniae/efeitos dos fármacos , Klebsiella pneumoniae/enzimologia , Testes de Sensibilidade Microbiana , Periplasma/metabolismo , beta-Lactamas/farmacologia
4.
Brief Bioinform ; 22(4)2021 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-33212503

RESUMO

Beta-lactamases (BLs) are enzymes localized in the periplasmic space of bacterial pathogens, where they confer resistance to beta-lactam antibiotics. Experimental identification of BLs is costly yet crucial to understand beta-lactam resistance mechanisms. To address this issue, we present DeepBL, a deep learning-based approach by incorporating sequence-derived features to enable high-throughput prediction of BLs. Specifically, DeepBL is implemented based on the Small VGGNet architecture and the TensorFlow deep learning library. Furthermore, the performance of DeepBL models is investigated in relation to the sequence redundancy level and negative sample selection in the benchmark dataset. The models are trained on datasets of varying sequence redundancy thresholds, and the model performance is evaluated by extensive benchmarking tests. Using the optimized DeepBL model, we perform proteome-wide screening for all reviewed bacterium protein sequences available from the UniProt database. These results are freely accessible at the DeepBL webserver at http://deepbl.erc.monash.edu.au/.


Assuntos
Biologia Computacional , Bases de Dados de Proteínas , Aprendizado Profundo , Proteoma , Software , beta-Lactamases/genética
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