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Record W1945992259 · doi:10.7554/elife.06492

Reverse evolution leads to genotypic incompatibility despite functional and active site convergence

2015· article· en· W1945992259 on OpenAlexafffund
Miriam Kaltenbach, Colin J. Jackson, E.C. Campbell, Florian Hollfelder, Nobuhiko Tokuriki

Bibliographic record

VenueeLife · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersBiotechnology and Biological Sciences Research CouncilEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaAustralian Research CouncilEuropean Commission
KeywordsDirected evolutionEpistasisDirected Molecular EvolutionBiologyGeneticsMolecular evolutionFitness landscapeActive siteSequence (biology)Experimental evolutionComputational biologyEnzymeBiochemistryMutantGenomeGenePopulation

Abstract

fetched live from OpenAlex

Understanding the extent to which enzyme evolution is reversible can shed light on the fundamental relationship between protein sequence, structure, and function. Here, we perform an experimental test of evolutionary reversibility using directed evolution from a phosphotriesterase to an arylesterase, and back, and examine the underlying molecular basis. We find that wild-type phosphotriesterase function could be restored (>10(4)-fold activity increase), but via an alternative set of mutations. The enzyme active site converged towards its original state, indicating evolutionary constraints imposed by catalytic requirements. We reveal that extensive epistasis prevents reversions and necessitates fixation of new mutations, leading to a functionally identical sequence. Many amino acid exchanges between the new and original enzyme are not tolerated, implying sequence incompatibility. Therefore, the evolution was phenotypically reversible but genotypically irreversible. Our study illustrates that the enzyme's adaptive landscape is highly rugged, and different functional sequences may constitute separate fitness peaks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.253
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations82
Published2015
Admission routes2
Has abstractyes

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