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Record W2973118395 · doi:10.1101/769422

Green, orange, red, and far-red optogenetic tools derived from cyanobacteriochromes

2019· preprint· en· W2973118395 on OpenAlexaff
Jaewan Jang, Sherin McDonald, Maruti Uppalapati, G. Andrew Woolley

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of SaskatchewanUniversity of Toronto
Fundersnot available
KeywordsPhycocyanobilinChromophoreBiliverdinOptogeneticsFar-redOrange (colour)LimitingChemistryProtein engineeringSynechocystisRed lightBiophysicsPhycocyaninBiologyPhotochemistryCyanobacteriaBiochemistryGeneticsGeneBacteriaBotanyHeme

Abstract

fetched live from OpenAlex

Abstract Existing optogenetic tools for controlling protein-protein interactions are available in a limited number of wavelengths thereby limiting opportunities for multiplexing. The cyanobacteriochrome (CBCR) family of photoreceptors responds to an extraordinary range of colors, but light-dependent binding partners for CBCR domains are not currently known. We used a phage-display based approach to develop small (~50-residue) monomeric binders selective for the green absorbing state (Pg), or for the red absorbing state (Pr) of the CBCR Am1_c0023g2 with a phycocyanobilin chromophore and also for the far-red absorbing state (Pfr) of Am1_c0023g2 with a biliverdin chromophore. These bind in a 1:1 mole ratio with K D s for the target state from 0.2 to 2 μM and selectivities from 10 to 500-fold. We demonstrate green, orange, red, and far-red light-dependent control of protein-protein interactions in vitro and also in vivo where these multicolor optogenetic tools are used to control transcription in yeast.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.198
Teacher spread0.180 · 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 designBench or experimental
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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

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