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      Pharmacodynamic considerations of collateral sensitivity in design of antibiotic treatment regimen

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          Abstract

          Introduction

          Antibiotics have greatly reduced the morbidity and mortality due to infectious diseases. Although antibiotic resistance is not a new problem, its breadth now constitutes a significant threat to human health. One strategy to help combat resistance is to find novel ways to use existing drugs, even those that display high rates of resistance. For the pathogens Escherichia coli and Pseudomonas aeruginosa, pairs of antibiotics have been identified for which evolution of resistance to drug A increases sensitivity to drug B and vice versa. These research groups have proposed cycling such pairs to treat infections, and similar treatment strategies are being investigated for various cancer forms as well. While an exciting treatment prospect, no cycling experiments have yet been performed with consideration of pharmacokinetics and pharmacodynamics. To test the plausibility of such schemes and optimize them, we create a mathematical model with explicit pharmacokinetic/pharmacodynamic considerations.

          Materials and methods

          We evaluate antibiotic cycling protocols using pairs of such antibiotics and investigate the speed of ascent of multiply resistant mutants.

          Results

          Our analyses show that when using low concentrations of antibiotics, treatment failure will always occur due to the rapid ascent and fixation of resistant mutants. However, moderate to high concentrations of some combinations of bacteriostatic and bactericidal antibiotics with multiday cycling prevent resistance from developing and increase the likelihood of treatment success.

          Conclusion

          Our results call for guarded optimism in application and development of such treatment protocols.

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          Most cited references 16

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          Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing.

          Knowledge of the rate and nature of spontaneous mutation is fundamental to understanding evolutionary and molecular processes. In this report, we analyze spontaneous mutations accumulated over thousands of generations by wild-type Escherichia coli and a derivative defective in mismatch repair (MMR), the primary pathway for correcting replication errors. The major conclusions are (i) the mutation rate of a wild-type E. coli strain is ~1 × 10(-3) per genome per generation; (ii) mutations in the wild-type strain have the expected mutational bias for G:C > A:T mutations, but the bias changes to A:T > G:C mutations in the absence of MMR; (iii) during replication, A:T > G:C transitions preferentially occur with A templating the lagging strand and T templating the leading strand, whereas G:C > A:T transitions preferentially occur with C templating the lagging strand and G templating the leading strand; (iv) there is a strong bias for transition mutations to occur at 5'ApC3'/3'TpG5' sites (where bases 5'A and 3'T are mutated) and, to a lesser extent, at 5'GpC3'/3'CpG5' sites (where bases 5'G and 3'C are mutated); (v) although the rate of small (≤4 nt) insertions and deletions is high at repeat sequences, these events occur at only 1/10th the genomic rate of base-pair substitutions. MMR activity is genetically regulated, and bacteria isolated from nature often lack MMR capacity, suggesting that modulation of MMR can be adaptive. Thus, comparing results from the wild-type and MMR-defective strains may lead to a deeper understanding of factors that determine mutation rates and spectra, how these factors may differ among organisms, and how they may be shaped by environmental conditions.
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            Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development.

            New drug deployment strategies are imperative to address the problem of drug resistance, which is limiting the management of infectious diseases and cancers. We evolved resistance in Escherichia coli toward 23 drugs used clinically for treating bacterial infections and mapped the resulting collateral sensitivity and resistance profiles, revealing a complex collateral sensitivity network. On the basis of these data, we propose a new treatment framework--collateral sensitivity cycling--in which drugs with compatible collateral sensitivity profiles are used sequentially to treat infection and select against drug resistance development. We identified hundreds of such drug sets and demonstrated that the antibiotics gentamicin and cefuroxime can be deployed cyclically such that the treatment regimen selected against resistance to either drug. We then validated our findings with related bacterial pathogens. These results provide proof of principle for collateral sensitivity cycling as a sustainable treatment paradigm that may be generally applicable to infectious diseases and cancer.
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              Collateral sensitivity as a strategy against cancer multidrug resistance.

              While chemotherapy remains the most effective treatment for disseminated tumors, acquired or intrinsic drug resistance accounts for approximately 90% of treatment failure. Multidrug resistance (MDR), the simultaneous resistance to drugs that differ both structurally and mechanistically, often results from drug efflux pumps in the cell membrane that reduce intracellular drug levels to less than therapeutic concentrations. Expression of the MDR transporter P-glycoprotein (P-gp, MDR1, ABCB1) has been shown to correlate with overall poor chemotherapy response and prognosis. This review will focus on collateral sensitivity (CS), the ability of compounds to kill MDR cells selectively over the parental cells from which they were derived. Insights into CS may offer an alternative strategy for the clinical resolution of MDR, as highly selective and potent CS agents may lead to drugs that are effective at MDR cell killing and tumor resensitization. Four main mechanistic hypotheses for CS will be reviewed, followed by a discussion on quantitative and experimental evaluation of CS. Published by Elsevier Ltd.
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                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                1177-8881
                2018
                23 July 2018
                : 12
                : 2249-2257
                Affiliations
                [1 ]Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden, klas.udekwu@ 123456su.se
                [2 ]Department of Mathematics, Georgia Institute of Technology, Atlanta, GA, USA
                Author notes
                Correspondence: Klas I Udekwu, Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University Building F, Room 556, SE 10691 Stockholm, Sweden, Tel +46 8 164 189, Email klas.udekwu@ 123456su.se
                [*]

                These authors contributed equally to this work

                Article
                dddt-12-2249
                10.2147/DDDT.S164316
                6061756
                © 2018 Udekwu and Weiss. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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                Original Research

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