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Antibiotic resistance: Insights from evolution experiments and mathematical modeling

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TLDR
A new strategy for observing, predicting, and ultimately controlling resistance evolution is emerging, based on advances in quantitative cell physiology and predictive theoretical models of resistance.
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This article is published in Current Opinion in Systems Biology.The article was published on 2021-12-01 and is currently open access. It has received 1 citations till now.

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Quantitative approaches to study phenotypic effects of large-scale genetic perturbations.

TL;DR: A review of recent advances in this field, and applications to the study of gene-drug interactions can be found in this article , where newly developed techniques for the rapid generation of genome-wide mutant libraries and the high-throughput measurement of more complex phenotypes and other observables, such as cell morphology or thermal stability of the proteome.
References
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Antibiotic resistance and its cost: is it possible to reverse resistance?

TL;DR: The findings suggest that the fitness costs of resistance will allow susceptible bacteria to outcompete resistant bacteria if the selective pressure from antibiotics is reduced, and that the rate of reversibility will be slow at the community level.
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Mobile Genetic Elements Associated with Antimicrobial Resistance

TL;DR: The characteristics of the major types of mobile genetic elements involved in acquisition and spread of antibiotic resistance in both Gram-negative and Gram-positive bacteria are outlined, focusing on the so-called ESKAPEE group of organisms, which have become the most problematic hospital pathogens.
Journal ArticleDOI

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection

TL;DR: A selection device, the 'morbidostat', that continuously monitors bacterial growth and dynamically regulates drug concentrations, such that the evolving population is constantly challenged, shows that parallel populations evolved similar mutations and acquired them in a similar order.
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Phenotypic Landscape of a Bacterial Cell

TL;DR: This work shows that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery, and highlights new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides.
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Trending Questions (2)
How do antibiotic-resistant organisms evolve?

The paper discusses that antibiotic-resistant organisms evolve through a combination of systematic experimental and theoretical approaches, including evolution experiments, next-generation sequencing techniques, laboratory automation, and mathematical modeling.

Is there any mathematical model developed to better understand antimicrobial resistance ?

Yes, the paper discusses the development of predictive theoretical models of resistance to better understand antimicrobial resistance.