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Journal ArticleDOI

Empirical fitness landscapes and the predictability of evolution

TLDR
This work reviews recent empirical and theoretical developments of the genotype–fitness map, identifies methodological issues and organizing principles, and discusses possibilities to develop more realistic fitness landscape models.
Abstract
A central topic in biology concerns how genotypes determine phenotypes and functions of organisms that affect their evolutionary fitness. This Review discusses recent advances in the development of empirical fitness landscapes and their contribution to theoretical analyses of the predictability of evolution. The genotype–fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

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The Role of Epidemic Resistance Plasmids and International High-Risk Clones in the Spread of Multidrug-Resistant Enterobacteriaceae

TL;DR: Escherichia coli sequence type 131 (ST131) and Klebsiella pneumoniae ST258 emerged in the 2000s as important human pathogens, have spread extensively throughout the world, and are responsible for the rapid increase in antimicrobial resistance among E. coli and K. pneumoniae strains.
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Contingency and determinism in evolution: Replaying life's tape.

TL;DR: The authors' review of many such experiments indicates that responses across replicate populations are often repeatable to some degree, although divergence increases as analyses move from overall fitness to underlying phenotypes and genetic changes.
Journal ArticleDOI

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

TL;DR: Improving enzymes by directed evolution requires the navigation of very large search spaces; this work surveys how to do this intelligently.
References
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Journal ArticleDOI

Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance

TL;DR: The evolution of antibiotic resistance can now be rapidly tracked with high-throughput technologies for bacterial genotyping and phenotyping, and the genomic and evolutionary insights they provide could transform the diagnosis, treatment and predictability of antibiotics resistance in bacterial infections.
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The rate at which asexual populations cross fitness valleys.

TL;DR: This work calculates the rate at which a population crosses a fitness valley or plateau of arbitrary width, as a function of the mutation rates, the population size, and the fitnesses of the intermediates, and finds that when intermediates are close to neutral, a large population can cross even wide fitness valleys remarkably quickly, so that valley-crossing dynamics may be common even when mutations that directly increase fitness are also possible.
Journal ArticleDOI

The biochemical architecture of an ancient adaptive landscape.

TL;DR: The genotype-phenotype-fitness map shows that NAD use is a global optimum, and mediates between these two phenotypic extremes show that each amino acid contributes additively to enzyme function, with epistatic contributions confined to fitness.
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Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design

TL;DR: Using computational models, an approach is developed to translate available viral sequence data into quantitative landscapes of viral fitness as a function of the amino acid sequences of its constituent proteins that inform the design of immunogens and therapies that can target regions of the virus most vulnerable to selection pressure.
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