A Comprehensive, High-Resolution Map of a Gene’s Fitness Landscape

Firnberg, Elad; Labonte, Jason W.; Gray, Jeffrey J.; Ostermeier, Marc

doi:10.1093/molbev/msu081

Cited by 317 publications

(314 citation statements)

References 65 publications

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“…Although synonymous mutations are not necessarily neutral [95][96][97]436], the ratio of non-synonymous over synonymous codon replacement rates, v ¼ dN/dS, is commonly used to detect adaptation in a given phylogenetic tree of related gene sequences. In such studies, most mutations do not show any signs of adaptation, with v % 1, and are thus considered 'neutral'; v .…”

Section: Synergy Between Biophysics and The Study Of Protein Evolutionmentioning

confidence: 99%

Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

224

207

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The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

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Section: Synergy Between Biophysics and The Study Of Protein Evolutionmentioning

confidence: 99%

Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

224

207

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“…Specifically, Firnberg et al (2014) created nearly all possible amino acid mutants of TEM-1 beta-lactamase and then used antibiotic selection to enrich for functional variants at various antibiotic concentrations. Next, they used high-throughput sequencing to examine how the frequencies of mutations changed during this functional selection.…”

Section: Resultsmentioning

confidence: 99%

An Experimentally Informed Evolutionary Model Improves Phylogenetic Fit to Divergent Lactamase Homologs

Bloom

2014

Molecular Biology and Evolution

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Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene’s fitness landscape. Mol Biol Evol. 31:1581–1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.

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“…Ostermeier and colleagues accomplished this by utilizing specialized protocols based on uracil-containing template DNA 3 , while Wrenbeck and Whitehead selectively degrade the WT strand using single-strand nicking endonucleases 6 . Such methods have been used to generate nearly comprehensive libraries of genes for exploring the entirety of the fitness landscape 21 , and to comprehensively examine the possible evolutionary pathways leading from one allele to another 22 .…”

Section: Resultsmentioning

confidence: 99%

Rapid and Programmable Protein Mutagenesis Using Plasmid Recombineering

2017

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Comprehensive and programmable protein mutagenesis is critical for understanding structure-function relationships and improving protein function. However, current techniques enabling comprehensive protein mutagenesis are based on PCR and require in vitro reactions involving specialized protocols and reagents. This has complicated efforts to rapidly and reliably produce desired comprehensive protein libraries. Here we demonstrate that plasmid recombineering is a simple and robust in vivo method for the generation of protein mutants for both comprehensive library generation as well as programmable targeting of sequence space. Using the fluorescent protein iLOV as a model target, we build a complete mutagenesis library and find it to be specific and comprehensive, detecting 99.8% of our intended mutations. We then develop a thermostability screen and utilize our comprehensive mutation data to rapidly construct a targeted and multiplexed library that identifies significantly improved variants, thus demonstrating rapid protein engineering in a simple protocol.

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A Comprehensive, High-Resolution Map of a Gene’s Fitness Landscape

Cited by 317 publications

References 65 publications

Biophysics of protein evolution and evolutionary protein biophysics

Biophysics of protein evolution and evolutionary protein biophysics

An Experimentally Informed Evolutionary Model Improves Phylogenetic Fit to Divergent Lactamase Homologs

Rapid and Programmable Protein Mutagenesis Using Plasmid Recombineering

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