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Record W3048786791 · doi:10.3390/plants9081018

Identification of Three Monofunctional Diterpene Synthases with Specific Enzyme Activities Expressed during Heartwood Formation in Western Redcedar (Thuja plicata) Trees

2020· article· en· W3048786791 on OpenAlexafffund
Sifat Tasnim, Regine Gries, Jim Mattsson

Bibliographic record

VenuePlants · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThujaDiterpeneBiologyEnzymeIdentification (biology)BotanyBiochemistry

Abstract

fetched live from OpenAlex

Upon harvest, Western redcedar (WRC; Thuja plicata) trees have a high incidence and extent of heartwood rot. While monoterpenoids and lignans have been linked to rot resistance in this species, other specialized metabolites, such as diterpenes, are likely to contribute to rot resistance. Here we report the cloning and functional assessment of three putative diterpene synthase (TpdiTPS) genes expressed during heartwood formation in WRC. The predicted proteins of the three genes lack either of the two catalytically independent active sites typical of most diTPS, indicating monofunctional rather than bifunctional activity. To identify potential catalytic activities of these proteins, we expressed them in genetically engineered Escherichia coli strains that produce four potential substrates, geranylgeranyl diphosphate (GGDP), ent, syn, and normal stereoisomers of copalyl diphosphate (CDP). We found that TpdiTPS3 used GGDP to produce CDP. TpdiTPS2 used normal CDP to produce levopimaradiene. TpdiTPS1 showed stereoselectivity as it used normal CDP to produce sandaracopimaradiene and syn-CDP to produce syn-stemod-13(17)-ene. These genes and protein enzymatic activities have not been previously reported in WRC and provide an opportunity to assess their potential roles in heartwood rot resistance in this economically important species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.471

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 head0.018
GPT teacher head0.206
Teacher spread0.188 · 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 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

Citations9
Published2020
Admission routes2
Has abstractyes

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