Drug detoxification dynamics explain the postantibiotic effect

Cell-cell interactions play an important role in bacterial antibiotic resistance. Here, we asked whether neighbor proximity is sufficient to generate single-cell variation in antibiotic resistance due to local differences in antibiotic concentrations. To test this, we focused on multidrug efflux pumps because recent studies have revealed that expression of pumps is heterogeneous across populations. Efflux pumps can export antibiotics, leading to elevated resistance relative to cells with low or no pump expression. In this study, we co-cultured cells with and without AcrAB-TolC pump expression and used single-cell time-lapse microscopy to quantify growth rate as a function of a cell’s neighbors. In inhibitory concentrations of chloramphenicol, we found that cells lacking functional efflux pumps (ΔacrB) grow more slowly when they are surrounded by cells with AcrAB-TolC pumps than when surrounded by ΔacrB cells. To help explain our experimental results, we developed an agent-based mathematical model, which demonstrates the impact of neighbors based on efflux efficiency. Our findings hold true for co-cultures of Escherichia coli with and without pump expression and also in co-cultures of E. coli and Salmonella typhumirium. These results show how drug export and local microenvironments play a key role in defining single-cell level antibiotic resistance.

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“…The biomass equation has a term for the toxicity of the environment, which is derived from Van Impe et al . 15 , 35 , 36 . …”

Section: Methodsmentioning

confidence: 99%

Antibiotic export by efflux pumps affects growth of neighboring bacteria

Wen

Langevin

Dunlop

2018

Sci Rep

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“…To illustrate this, we coupled a pharmacokinetic model describing different modes ampicillin administration in patients and predict the pathogen load in infected tissues based on the realistic, fluctuating antibiotic concentrations (S1 Text, S13 and S14 Figs and S5 Table). They can also explain complicated phenomena such as biphasic kill curves, the post-antibiotic effect, or the inoculum effect [20,21,52] that often complicate the clinical phase of drug development. COMBAT has similar characteristics that allow capturing these complex phenomena.…”

Section: Plos Computational Biologymentioning

confidence: 99%

Drug-target binding quantitatively predicts optimal antibiotic dose levels in quinolones

et al. 2020

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Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that can quantitatively predict antibiotic dose-response relationships. Our goal is dual: We address a fundamental biological question and investigate how drug-target binding shapes antibiotic action. We also create a tool that can predict antibiotic efficacy a priori. COMBAT requires measurable biochemical parameters of drugtarget interaction and can be directly fitted to time-kill curves. As a proof-of-concept, we first investigate the utility of COMBAT with antibiotics belonging to the widely used quinolone class. COMBAT can predict antibiotic efficacy in clinical isolates for quinolones from drug affinity (R 2 >0.9). To further challenge our approach, we also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We overexpress target molecules to infer changes in antibiotic-target binding from changes in antimicrobial efficacy of ciprofloxacin with 92-94% accuracy. To test the generality of our approach, we use the beta-lactam ampicillin to predict target molecule occupancy at MIC from antimicrobial action with 90% accuracy. Finally, we apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations. Using ciprofloxacin and ampicillin as well defined test cases, our work demonstrates that drug-target binding is a major predictor of bacterial responses to antibiotics. This is surprising because antibiotic action involves many additional effects downstream of drug-target binding. In addition, COMBAT provides a framework to inform optimal antibiotic dose levels that maximize efficacy and minimize the rise of resistant mutants.

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“…The kanamycin-propagated Tn5A7 supernatant resulted in a significant reduction in bacterial burdens relative to the non-kanamycin supernatant but the magnitude of this effect was significantly less than that achieved by the kanamycin-propagated Tn5A7 cell suspension ( Fig 3B), indicating that the molecules responsible for the enhanced bacterial clearance are present in the supernatant. Aminoglycoside antibiotics are known to exhibit a post-antibiotic effect [29,30]. It is possible that, despite washing, kanamycin is liberated from the kanamycin-propagated strain and the released kanamycin kills the kanamycin-susceptible WT strain when the strains are mixed prior to co-inoculation of mice.…”

Section: Aminoglycoside Exposure Results In Enhanced Clearance Of Amimentioning

confidence: 99%

Broad-spectrum suppression of bacterial pneumonia by aminoglycoside-propagated Acinetobacter baumannii

et al. 2020

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Antimicrobial resistance is increasing in pathogenic bacteria. Yet, the effect of antibiotic exposure on resistant bacteria has been underexplored and may affect pathogenesis. Here we describe the discovery that propagation of the human pathogen Acinetobacter baumannii in an aminoglycoside antibiotic results in alterations to the bacterium that interact with lung innate immunity resulting in enhanced bacterial clearance. Co-inoculation of mice with A. baumannii grown in the presence and absence of the aminoglycoside, kanamycin, induces enhanced clearance of a non-kanamycin-propagated strain. This finding can be replicated when kanamycin-propagated A. baumannii is killed prior to co-inoculation of mice, indicating the enhanced bacterial clearance results from interactions with innate host defenses in the lung. Infection with kanamycin-propagated A. baumannii alters the kinetics of phagocyte recruitment to the lung and reduces pro-and anti-inflammatory cytokine and chemokine production in the lung and blood. This culminates in reduced histopathologic evidence of lung injury during infection despite enhanced bacterial clearance. Further, the antibacterial response induced by killed aminoglycoside-propagated A. baumannii enhances the clearance of multiple clinically relevant Gram-negative pathogens from the lungs of infected mice. Together, these findings exemplify cooperation between antibiotics and the host immune system that affords protection against multiple antibiotic-resistant bacterial pathogens. Further, these findings highlight the potential for the development of a broadspectrum therapeutic that exploits a similar mechanism to that described here and acts as an innate immunity modulator.

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Drug detoxification dynamics explain the postantibiotic effect

Cited by 29 publications

References 69 publications

Antibiotic export by efflux pumps affects growth of neighboring bacteria

Antibiotic export by efflux pumps affects growth of neighboring bacteria

Drug-target binding quantitatively predicts optimal antibiotic dose levels in quinolones

Broad-spectrum suppression of bacterial pneumonia by aminoglycoside-propagated Acinetobacter baumannii

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