Predicting trajectories and mechanisms of antibiotic resistance evolution

Pinheiro, Fernanda; Warsi, Omar; Andersson, Dan I.; Lässig, Michael

doi:10.1101/2020.07.02.184622

Cited by 3 publications

(4 citation statements)

References 56 publications

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“…Full JDFEs could differ substantially from the koJDFEs that we examined here. Finally, the availability and the type of resistance mutations depend on drug concentrations, other environmental conditions and on the bacterial species and strain (Lindsey et al, 2013;Das et al, 2020;Pinheiro et al, 2020;Card et al, 2020). All these factors could significantly affect the JDFE shape.…”

Section: Discussionmentioning

confidence: 99%

“…Some of the inconsistencies can be attributed to the fact that resistance mutations vary between bacterial strains, drug dosages, etc. (Mira et al, 2015;Das et al, 2020;Pinheiro et al, 2020;Card et al, 2020). However, these factors cannot explain the wide variation in the pleiotropic outcomes of adaptation that are observed in replicate populations in the same experiment (Oz et al, 2014;Nichol et al, 2019).…”

Section: Introductionmentioning

confidence: 98%

“…Modeling evolution using the DFE and the JDFE is justified by the fact that there are usually many mutations that can improve the fitness of an organism in the home environment. These adaptive mutations affect a variety of genetic targets (Lang et al, 2013;Tenaillon et al, 2012;Kryazhimskiy et al, 2014;Venkataram et al, 2016;Good et al, 2017;Blundell et al, 2019) and provide fitness benefits of various magnitudes (Rees and Bataillon, 2006;MacLean and Buckling, 2009;Khan et al, 2011;Chou et al, 2011;Levy et al, 2015;Venkataram et al, 2016) via diverse physiological mechanisms (Travisano and Lenski, 1996;Jerison et al, 2020;Pinheiro et al, 2020;Kinsler et al, 2020). As a consequence, different mutations also have diverse pleiotropic effects on fitness in non-home environments (Lenski, 1988;Ostrowski et al, 2005;Qian et al, 2012;Hietpas et al, 2013;Rodríguez-Verdugo et al, 2014;Jerison et al, 2020;Kinsler et al, 2020;Card et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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The Population Genetics of Collateral Resistance and Sensitivity

Ardell

Kryazhimskiy

2020

Preprint

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Pleiotropic fitness trade-offs and their opposite, buttressing pleiotropy, underlie many important phenomena in ecology and evolution. Yet, predicting whether a population adapting to one ("home") environment will concomitantly gain or lose fitness in another ("non-home") environment remains challenging, especially when adaptive mutations have diverse pleiotropic effects. Here, we address this problem using the concept of the joint distribution of fitness effects (JDFE), a local measurable property of the fitness landscape. We derive simple statistics of the JDFE that predict the expected slope, variance and covariance of non-home fitness trajectories. We estimate these statistics from published data from the Escherichia coli knock-out collection in the presence of antibiotics. We find that, for some drug pairs, the average trend towards collateral sensitivity may be masked by large uncertainty, even in the absence of epistasis. We provide simple theoretically grounded guidelines for designing robust sequential drug protocols.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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The Population Genetics of Collateral Resistance and Sensitivity

Ardell

Kryazhimskiy

2020

Preprint

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“…Antibiotic was an important discovery which treats many infections and prevents the spread of infectious diseases. However, bacteria can rapidly evolve resistance to antibiotics (Pinheiro et al 2020). In 2015, World Health Organization (WHO) established a Global Antimicrobial Resistance Surveillance System (GLASS) to act against antibiotic resistance (WHO 2015;WHO 2020a).…”

Section: Introductionmentioning

confidence: 99%

A comprehensive bibliometric overview: antibiotic resistance and Escherichia coli in natural water

Şahin

Sivri

Akpınar

et al. 2021

Environ Sci Pollut Res

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The environment is the most important reservoir for both resistance mechanisms and gene transfer in biological science studies. This study gives a bibliometric overview of studies of “antibiotic resistance” and “Escherichia coli” in the field of “Agricultural and Biological Sciences” from 2015 to 2019 to assess both research trends and scholarly networks in diverse research disciplines. The two keywords of “antibiotic resistance” and “Escherichia coli” were selected to search in the Scopus database. Each review article was categorized into materials, natural waters (i.e., seawater, freshwater) and wastewater, journal name, and quartile in category of the journal, the year of publication, and the country. Bibliometric indicators and visualization maps were utilized to analyse the retrieved data quantitatively and qualitatively. A total of 1376 publications in the field of agricultural and biological sciences over the last 5 years were obtained using the keywords of antibiotic resistance and Escherichia coli. With additional keywords of freshwater and wastewater, 4 and 24 studies were obtained, respectively. Wastewater was found to be the most common working environment for the keywords of antibiotic resistance and Escherichia coli. It is also found that the studies of antibiotic resistance are mainly conducted in wastewater environments, focusing on human and food health. Working under “One Health” consisting of human, animal and agriculture, and environmental health could be the only permanent and effective approach to solving antibiotic resistance-related issues.

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Choice of β-Lactam Resistance Pathway Depends Critically on Initial Antibiotic Concentration

Ruelens

Visser

2021

Antimicrob Agents Chemother

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Antibiotic-resistance trajectories with different final resistance may critically depend on the first mutation due to epistatic interactions. Here, we study the effect of mutation bias and concentration-dependent fitness effects of two clinically important mutations in TEM-1 β-lactamase initiating alternative trajectories to cefotaxime resistance. We show that mutation R164S, conferring relatively low resistance, is competitively superior over larger-effect mutation G238S at low cefotaxime concentrations, highlighting a critical influence of antibiotic concentration on long-term resistance evolution.

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Predicting trajectories and mechanisms of antibiotic resistance evolution

Cited by 3 publications

References 56 publications

The Population Genetics of Collateral Resistance and Sensitivity

The Population Genetics of Collateral Resistance and Sensitivity

A comprehensive bibliometric overview: antibiotic resistance and Escherichia coli in natural water

Choice of β-Lactam Resistance Pathway Depends Critically on Initial Antibiotic Concentration

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