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Record W3092862293 · doi:10.1021/acsomega.0c03508

Phage-Assisted Continuous Evolution (PACE): A Guide Focused on Evolving Protein–DNA Interactions

2020· review· en· W3092862293 on OpenAlexafffund
Serban C. Popa, Ichiro Inamoto, B W. Thuronyi, Jumi A. Shin

Bibliographic record

VenueACS Omega · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsPaceSelection (genetic algorithm)Directed Molecular EvolutionDirected evolutionComputer scienceComputational biologyBiologyGeneticsArtificial intelligenceGene

Abstract

fetched live from OpenAlex

evolution, where the protein under selective pressure undergoes continuous mutagenesis with little-to-no input from the researcher once the system is started. However, continuous evolution methods can be challenging to implement and a daunting investment of time and resources. Our intent is to provide basic information and helpful suggestions that we have gained from our experience with bacterial phage-assisted continuous evolution (PACE) toward the evolution of proteins that bind to a specific DNA target. We discuss factors to consider before adopting PACE for a given evolution scheme with focus on the PACE bacterial one-hybrid selection system and what optimization of a PACE selection circuit may look like using the evolution of the DNA-binding protein ME47 as a case study. We outline different types of selection circuits and techniques that may be added onto a basic PACE setup. With this information, researchers will be better equipped to determine whether PACE is a valid strategy to adopt for their research program and how to set up a valid selection circuit.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.333
Teacher spread0.314 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2020
Admission routes2
Has abstractyes

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