Correction: Rational Design of Antibiotic Treatment Plans: A Treatment Strategy for Managing Evolution and Reversing Resistance

Mira, Portia; Crona, Kristina; Greene, Devin; Meza, Juan C.; Sturmfels, Bernd; Barlow, Miriam

doi:10.1371/journal.pone.0139387

Cited by 3 publications

(16 citation statements)

References 1 publication

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“…In E. coli, the wild-type bla TEM-1 gene coding for β-lactamase needs four amino acid substitutions to become bla TEM-50 , which is resistant to cephalosporins and inhibitor combined therapies. Mira et al [9] created all 16 possible genotypes and measured their growth rates as proxies of fitness under 15 different β-lactam antibiotics, creating 15 different fitness landscapes. Each genotype has a range of growth rates depending on the antibiotic, suggesting the potential for successful reversion of resistance given the right antibiotic sequence (Table S1).…”

Section: Empirical Fitness Landscapesmentioning

confidence: 99%

“…mutation and v has a higher fitness than u ( Fig. 1) [9]. Each fitness graph under an antibiotic, A, was mapped to a 16 × 16 transition matrix M (A) with rows and columns corresponding to all possible genotypes.…”

Section: Markov Model For Evolutionmentioning

confidence: 99%

“…One optimization strategy is to calculate the probability of returning to the initial sensitive genotype after every possible sequence of k unique antibiotics and then select the sequence that maximizes the frequency of the sensitive genotype [9]. If M seq is the transition matrix for a single cycle of an antibiotic sequence, then (M seq ) n is the matrix giving the transition probabilities after n cycles, and p n = p 0 M n seq (4) gives the genotype frequency distribution p n after n cycles of the sequence.…”

Section: Effects Of Long-term Cycling Treatment Length and Immigrationmentioning

confidence: 99%

“…One proposed method to limit the evolution of resistance, especially in healthcare settings, is antibiotic cycling [6][7][8][9][10][11][12]. The idea is to treat all patients in a hospital ward with the same antibiotic for a given period, and then with a second antibiotic, and so on, eventually cycling back to the first.…”

Section: Introductionmentioning

confidence: 99%

“…In pursuit of this goal, the fitnesses of different E. coli genotypes were previously enumerated for each of 15 β-lactam antibiotics and used to identify optimal sequences for antibiotic cycling [9,25]. These fitnesses, measured by growth rates in the presence of each antibiotic, were obtained for the wild-type, "sensitive" genotype (known as TEM-1) and a more broadly resistant genotype (known as TEM-50) and all permutations (TEM-1 or TEM-50) at each of the four loci that differ between the genotypes, i.e., for 16 genotypes in total.…”

Section: Introductionmentioning

confidence: 99%

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Fitness Landscapes Reveal Simple Strategies for Steering Evolution to Minimize Antibiotic Resistance

Smith

Cobey

2016

Preprint

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The evolution of antibiotic resistance presents a practical and theoretical challenge: the design of strategies that limit the risk of evolved resistance while effectively treating current patients. Sequentially cycling antibiotics has been proposed as a way to slow the evolution of resistance by reducing the extent of adaptation to a given drug, and clinical trials have demonstrated its effectiveness in some settings. Empirical fitness landscapes in theory allow the sequence of drugs to be refined to maximize tradeoffs between drugs and thereby slow adaptation even further. Using the measured growth rates of 16 genotypes of Escherichia coli in the presence of 15 β-lactam antibiotics, we test an adaptive strategy, based on a Markov chain transition matrix, to select drug sequences that continuously minimize resistance. Cycling is never selected over the long term. Instead, monotherapy with the antibiotic that permits the least growth in its landscape's absorbing state is rapidly selected from different starting conditions. Analysis of a synthetic fitness landscape shows that cycling drugs that induce sensitivity to one other could, in theory, outperform monotherapy. These results underscore the importance of considering the specific topologies of fitness landscape in determining whether to cycle drugs and suggest a general computational approach to identify high-performing, practical strategies to manage resistance.

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Section: Empirical Fitness Landscapesmentioning

confidence: 99%

Section: Markov Model For Evolutionmentioning

confidence: 99%

Section: Effects Of Long-term Cycling Treatment Length and Immigrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fitness Landscapes Reveal Simple Strategies for Steering Evolution to Minimize Antibiotic Resistance

Smith

Cobey

2016

Preprint

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Adaptive Landscapes in the Age of Synthetic Biology

Xiao

Dean

2019

Molecular Biology and Evolution

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For nearly a century adaptive landscapes have provided overviews of the evolutionary process and yet they remain metaphors. We redefine adaptive landscapes in terms of biological processes rather than descriptive phenomenology. We focus on the underlying mechanisms that generate emergent properties such as epistasis, dominance, trade-offs and adaptive peaks. We illustrate the utility of landscapes in predicting the course of adaptation and the distribution of fitness effects. We abandon aged arguments concerning landscape ruggedness in favor of empirically determining landscape architecture. In so doing, we transform the landscape metaphor into a scientific framework within which causal hypotheses can be tested.

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Microbiological Air Quality and Drug Resistance in Airborne Bacteria Isolated from a Waste Sorting Plant Located in Poland―A Case Study

2020

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International interests in biological air pollutants have increased rapidly to broaden the pool of knowledge on their identification and health impacts (e.g., infectious, respiratory diseases and allergies). Antibiotic resistance and its wider implications present us with a growing healthcare crisis, and an increased understanding of antibiotic-resistant bacteria populations should enable better interpretation of bioaerosol exposure found in the air. Waste sorting plant (WSP) activities are a source of occupational bacterial exposures that are associated with many health disorders. The objectives of this study were (a) to assess bacterial air quality (BAQ) in two cabins of a WSP: preliminary manual sorting cabin (PSP) and purification manual sorting cabin (quality control) (QCSP), (b) determine the particle size distribution (PSD) of bacterial aerosol (BA) in PSP, QCSP, and in the outdoor air (OUT), and (c) determine the antibiotic resistance of isolated strains of bacteria. Bacterial strains were identified on a Biolog GEN III (Biolog, Hayward, CA, USA), and disc diffusion method for antimicrobial susceptibility testing was carried out according to the Kirby–Bauer Disk Diffusion Susceptibility Test Protocol. A large share of fecal bacteria, Enterococcus faecalis and Alcaligenes faecalis spp. feacalis, was found in the tested indoor air, which is a potential health hazard to the workers of the monitored WSP. Our results demonstrate the necessity to take into account fecal air pollution levels to avoid making erroneous assumptions regarding the environmental selection of antibiotic resistance. Total elimination of many anthropogenic sources is not possible, but important findings of this study can be used to develop realistic management policies methods to improve BAQ.

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Correction: Rational Design of Antibiotic Treatment Plans: A Treatment Strategy for Managing Evolution and Reversing Resistance

Cited by 3 publications

References 1 publication

Fitness Landscapes Reveal Simple Strategies for Steering Evolution to Minimize Antibiotic Resistance

Fitness Landscapes Reveal Simple Strategies for Steering Evolution to Minimize Antibiotic Resistance

Adaptive Landscapes in the Age of Synthetic Biology

Microbiological Air Quality and Drug Resistance in Airborne Bacteria Isolated from a Waste Sorting Plant Located in Poland―A Case Study

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