Literature DB >> 30247120

Disrupting folate metabolism reduces the capacity of bacteria in exponential growth to develop persisters to antibiotics.

Jasmine Morgan1, Matthew Smith2, Mark T Mc Auley3, J Enrique Salcedo-Sora4.   

Abstract

Bacteria can survive high doses of antibiotics through stochastic phenotypic diversification. We present initial evidence that folate metabolism could be involved with the formation of persisters. The aberrant expression of the folate enzyme gene fau seems to reduce the incidence of persisters to antibiotics. Folate-impaired bacteria had a lower generation rate for persisters to the antibiotics ampicillin and ofloxacin. Persister bacteria were detectable from the outset of the exponential growth phase in the complex media. Gene expression analyses tentatively showed distinctive profiles in exponential growth at times when bacteria persisters were observed. Levels of persisters were assessed in bacteria with altered, genetically and pharmacologically, folate metabolism. This work shows that by disrupting folate biosynthesis and usage, bacterial tolerance to antibiotics seems to be diminished. Based on these findings there is a possibility that bacteriostatic antibiotics such as anti-folates could have a role to play in clinical settings where the incidence of antibiotic persisters seems to drive recalcitrant infections.

Entities:  

Keywords:  ampicillin; antibiotic persistence; antifolates; folates; ofloxacin; recurrent infections

Mesh:

Substances:

Year:  2018        PMID: 30247120     DOI: 10.1099/mic.0.000722

Source DB:  PubMed          Journal:  Microbiology        ISSN: 1350-0872            Impact factor:   2.777


  2 in total

Review 1.  Strategic Moves of "Superbugs" Against Available Chemical Scaffolds: Signaling, Regulation, and Challenges.

Authors:  Bikash Baral; M R Mozafari
Journal:  ACS Pharmacol Transl Sci       Date:  2020-04-13

2.  Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in Escherichia coli and Unravel the Underlying Metabolic Adaptation Mechanisms.

Authors:  Nicole Pearcy; Yue Hu; Michelle Baker; Alexandre Maciel-Guerra; Ning Xue; Wei Wang; Jasmeet Kaler; Zixin Peng; Fengqin Li; Tania Dottorini
Journal:  mSystems       Date:  2021-08-03       Impact factor: 6.496

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.