Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Feder, Alison F.; Harper, Kristin N.; Brumme, Chanson J.; Pennings, Pleuni S.

doi:10.1101/807560

Cited by 10 publications

(19 citation statements)

References 113 publications

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“…Whether multi-resistance can arise during combination therapy, or even during monotherapy as suggested here, needs to be established. The observation of multi-resistance arising during combination therapies for HIV raises this as a possibility 42,87 (albeit at a mutation rate that exceeds even that of typical mutators 88 ).…”

Section: Discussionmentioning

confidence: 99%

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Mutators drive evolution of multi-resistance to antibiotics

Gifford¹,

Berríos-Caro

Joerres³

et al. 2019

Preprint

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Combination therapy aims to prevent growth of organisms not resistant to all component drugs, making it an obvious strategy for countering the global rise of multi-drug resistance. However, success relies on preventing resistance from arising to all component drugs before full inhibition is reached during treatment. Here, we investigated whether bacterial populations can overcome combination therapy by evolving 'multi-resistance', i.e. independent resistance mutations to multiple drugs, during single-drug and combination antibiotic treatment. Using both experimental evolution and in silico stochastic simulations, we studied resistance evolution in a common laboratory strain of bacteria (Escherichia coli K-12 BW25113). Populations were exposed to either single-drug or combination treatments involving rifampicin and nalidixic acid, with concentrations increasing through time. For wild-type populations, multi-resistance was not detected in any of the experimental populations, and simulations predict its evolution should be rare.However, populations comprising mixtures of wild-type and 'mutator' strains were readily capable of evolving multi-resistance. Increasing the initial frequency of mutators resulted in a higher proportion of populations evolving multi-resistance. Experiments and simulations produced the same qualitative-and in many cases, quantitative-insights about the association between resistance, mutators and antibiotic treatment. In particular, both approaches demonstrated that multi-resistance can arise through sequential acquisition of independent resistance mutations, without a need to invoke multi-drug resistance mechanisms. Crucially, we found multi-resistance evolved even when not directly favoured by natural selection, i.e. under single-drug treatments. Simulations revealed this resulted from elevated mutation supply caused by genetic hitch-hiking of the mutator allele on single-drug resistant backgrounds. Our results suggest that combination therapy does not necessarily prevent sequential acquisition of multiple drug resistances via spontaneous mutation when mutators are present. Indeed both combination and single-drug treatments actively promoted multi-resistance, meaning that combination therapy will not be a panacea for the antibiotic resistance crisis. inference, stochastic simulations, individual-based model, Markov chains W , K. B., 2016 Pairwise interactions and the battle against combinatorics in multidrug therapies.

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Section: Discussionmentioning

confidence: 99%

“…Concentration gradients are expected to facilitate the evolution of resistance 40,41 , particularly if multiple mutations are required [42][43][44][45] .…”

Section: Introductionmentioning

confidence: 99%

Mutators drive evolution of multi-resistance to antibiotics

Gifford¹,

Berríos-Caro

Joerres³

et al. 2019

Preprint

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“…The second scenario entails logistic growth for each strain, but with no competition between individuals of different strains. This describes situations where resources are limited, but each strain exploits a different resource (such as may occur if a resistance mutation allows a strain to occupy a new ecological or spatial niche, Moreno-Gamez et al (2015); Feder et al (2019)). The growth of any one strain is then limited by the number of individuals of that strain, but not by individuals of other strains.…”

Section: Specific Growth Lawsmentioning

confidence: 99%

Competition delays multi-drug resistance evolution during combination therapy

Berríos-Caro

Gifford

Galla

2020

Preprint

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A R T I C L E I N F O Keywords: probability of drug resistance combination therapy simulation of individual-based models stochastic processes A B S T R A C T Combination therapies have shown remarkable success in preventing the evolution of resistance to multiple drugs, including HIV, tuberculosis, and cancer. Nevertheless, the rise in drug resistance still remains an important challenge. The capability to accurately predict the emergence of resistance, either to one or multiple drugs, may help to improve treatment options. Existing theoretical approaches often focus on exponential growth laws, which may not be realistic when scarce resources and competition limit growth. In this work, we study the emergence of single and double drug resistance in a model of combination therapy of two drugs. The model describes a sensitive strain, two types of single-resistant strains, and a double-resistant strain. We compare the probability that resistance emerges for three growth laws: exponential growth, logistic growth without competition between strains, and logistic growth with competition between strains. Using mathematical estimates and numerical simulations, we show that between-strain competition only affects the emergence of single resistance when resources are scarce. In contrast, the probability of double resistance is affected by between-strain competition over a wider space of resource availability. This indicates that competition between different resistant strains may be pertinent to identifying strategies for suppressing drug resistance, and that exponential models may overestimate the emergence of resistance to multiple drugs. A by-product of our work is an efficient strategy to evaluate probabilities of single and double resistance in models with multiple sequential mutations. This may be useful for a range of other problems in which the probability of resistance is of interest.

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“…Incomplete viral suppression of HIV because of treatment interruptions (1-7), and lowered drug levels in some anatomical compartments (8)(9)(10)(11)(12) contribute to the selection of drug resistance mutations (13,14). Drug resistance mutations enable HIV to replicate in the face of what should be suppressive ART concentrations if sufficient mutations are accumulated and result in multidrug resistance (10,15). The prevalence of drug resistance mutations in HIV infected individuals on ART is about 10% (16,17), (see also the WHO HIV Drug Resistance Report 2019 at https://www.who.int/hiv/pub/drugresistance/ hivdr-report-2019/en/).…”

Section: Introductionmentioning

confidence: 99%

“…EFV monotherapy occurs in the clinical setting during treatment interruptions, as EFV has a longer half-life relative to FTC and the reverse transcriptase inhibitor tenofovir which are usually co-formulated with it(2,48,(50)(51)(52)(53). Monotherapy provides the opportunity for HIV to accumulate drug resistance mutations in a stepwise fashion(10,15). If HIV evolves more rapidly by cell-free infection relative to cell-to-cell spread, infection by cell-free virus would allow it to quickly evolve drug resistance to the single drug during a window of monotherapy.…”

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confidence: 99%

HIV cell-to-cell spread slows evolution of drug resistance

Hunter

Cele

Jackson

et al. 2020

Preprint

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Many enveloped viruses such as HIV have evolved to transmit by two infection modes: cell-free infection and cell-to-cell spread. Cell-to-cell spread is highly efficient as it involves directed viral transmission from the infected to the uninfected cell. In contrast, cell-free infection relies on chance encounters between the virion and cell. Despite the higher efficiency of cell-to-cell spread, there is substantial transmission by cell-free infection in conjunction with cell-to-cell spread. A possible reason is that cell-free infection offers a selective advantage by increasing sensitivity to factors interfering with infection, hence accelerating evolution of resistance relative to cell-to-cell spread alone. Here we investigated whether a combination of cell-free infection and cell-to-cell spread confers a selective advantage in experimental evolution to an antiretroviral drug. We maintained HIV infection using coculture of infected with uninfected cells in the face of moderate inhibition by the reverse transcriptase inhibitor efavirenz. We tested the effect on the rate of drug resistance evolution of replacing one coculture infection cycle with an infection cycle involving cell-free infection only, and observed earlier evolution of drug resistance mutations to efavirenz. When we increased selective pressure by adding a second reverse transcriptase inhibitor, emtricitabine, infection with the cell-free step consistently evolved multidrug resistance to both drugs and was able to replicate. In contrast, infection without a cell-free step mostly failed to evolve multidrug resistance. Therefore, HIV cell-to-cell spread decreases the ability of HIV to rapidly evolve resistance to inhibitors, which is conferred by cell-free infection.

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Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Cited by 10 publications

References 113 publications

Mutators drive evolution of multi-resistance to antibiotics

Mutators drive evolution of multi-resistance to antibiotics

Competition delays multi-drug resistance evolution during combination therapy

HIV cell-to-cell spread slows evolution of drug resistance

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