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Review
. 2020 Jun 16;11(3):e00817-20.
doi: 10.1128/mBio.00817-20.

A Physiological Basis for Nonheritable Antibiotic Resistance

Affiliations
Review

A Physiological Basis for Nonheritable Antibiotic Resistance

Mauricio H Pontes et al. mBio. .

Abstract

Antibiotics constitute one of the cornerstones of modern medicine. However, individuals may succumb to a bacterial infection if a pathogen survives exposure to antibiotics. The ability of bacteria to survive bactericidal antibiotics results from genetic changes in the preexisting bacterial genome, from the acquisition of genes from other organisms, and from nonheritable phenomena that give rise to antibiotic tolerance. Nonheritable antibiotic tolerance can be exhibited by a large fraction of the bacterial population or by a small subpopulation referred to as persisters. Nonheritable resistance to antibiotics has been ascribed to the activity of toxins that are part of toxin-antitoxin modules, to the universal energy currency ATP, and to the signaling molecule guanosine (penta) tetraphosphate. However, these molecules are dispensable for nonheritable resistance to antibiotics in many organisms. By contrast, nutrient limitation, treatment with bacteriostatic antibiotics, or expression of genes that slow bacterial growth invariably promote nonheritable resistance. We posit that antibiotic persistence results from conditions promoting feedback inhibition among core cellular processes, resulting phenotypically in a slowdown or halt in bacterial growth.

Keywords: antibiotic tolerance; growth feedback regulation; persister.

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Figures

FIG 1
FIG 1
Effect of a bactericidal antibiotic on killing kinetics among susceptible, tolerant, and resistant bacteria. (A) Schematic representation of antibiotic killing during the population growth of susceptible, tolerant, and resistant bacteria (top left). Resistant cells (red line) are unaffected and are able to grow in the presence of the antibiotic. Tolerant cells (yellow line) are susceptible to the antibiotic but display slower killing kinetics than susceptible cells (green line). Schematic representation of antibiotic killing during the population growth of genetically susceptible bacteria (top right). Cells within this population can be partitioned into phenotypically susceptible cells, which comprise the majority of the population (green line), and a small fraction of phenotypically tolerant, persister cells (yellow line). Cartoon representation of antibiotic killing during the population growth of a genetically susceptible bacterium (bottom). Phenotypically susceptible (green) and phenotypically tolerant, persister cells (yellow) are depicted. (B) Cartoon schematics depicting the inferred action of an antibiotic (kanamycin) on susceptible, tolerant, and resistant cells. Ribosome cartoons were modified from Servier Medical Art, licensed under a Creative Common Attribution 3.0 Generic License.
FIG 2
FIG 2
Cartoon depicting the three core cellular processes (chromosome replication, transcription, and translation) and coregulatory relationships among them.
FIG 3
FIG 3
Schematic representation of antibiotic killing in a growing population of susceptible bacteria following inhibition of a core biosynthetic process (top). Feedback regulation promotes the inhibition of other major cellular processes, leading to multidrug tolerance. Cartoons depicting processes outlined in the top schematic (bottom).

References

    1. Aminov RI. 2010. A brief history of the antibiotic era: lessons learned and challenges for the future. Front Microbiol 1:134. doi:10.3389/fmicb.2010.00134. - DOI - PMC - PubMed
    1. Naylor NR, Atun R, Zhu N, Kulasabanathan K, Silva S, Chatterjee A, Knight GM, Robotham JV. 2018. Estimating the burden of antimicrobial resistance: a systematic literature review. Antimicrob Resist Infect Control 7:58. doi:10.1186/s13756-018-0336-y. - DOI - PMC - PubMed
    1. Ma C, Yang X, Lewis PJ. 2016. Bacterial transcription as a target for antibacterial drug development. Microbiol Mol Biol Rev 80:139–160. doi:10.1128/MMBR.00055-15. - DOI - PMC - PubMed
    1. van Hoek AH, Mevius D, Guerra B, Mullany P, Roberts AP, Aarts HJ. 2011. Acquired antibiotic resistance genes: an overview. Front Microbiol 2:203. doi:10.3389/fmicb.2011.00203. - DOI - PMC - PubMed
    1. Mira A, Ochman H, Moran NA. 2001. Deletional bias and the evolution of bacterial genomes. Trends Genet 17:589–596. doi:10.1016/s0168-9525(01)02447-7. - DOI - PubMed

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