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Record W2625367194 · doi:10.3390/plants6020023

The Unique Role of the ECERIFERUM2-LIKE Clade of the BAHD Acyltransferase Superfamily in Cuticular Wax Metabolism

2017· review· en· W2625367194 on OpenAlexafffund
Tegan M. Haslam, Wesley K. Gerelle, Sean W. Graham, Ljerka Kunst

Bibliographic record

VenuePlants · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArabidopsisBiologyAcyltransferaseWaxMutantSiliqueHeterologous expressionBiochemistryFunction (biology)AcyltransferasesSaccharomyces cerevisiaeEnzymeGeneCell biologyBiosynthesis

Abstract

fetched live from OpenAlex

The elongation of very-long-chain fatty acids is a conserved process used for the production of many metabolites, including plant cuticular waxes. The elongation of precursors of the most abundant cuticular wax components of some plants, however, is unique in requiring ECERIFERUM2-LIKE (CER2-LIKE) proteins. CER2-LIKEs are a clade within the BAHD superfamily of acyltransferases. They are known to be required for cuticular wax production in both Arabidopsis and maize based on mutant studies. Heterologous expression of Arabidopsis and rice CER2-LIKEs in Saccharomyces cerevisiae has demonstrated that they modify the chain-length specificity of elongation when paired with particular condensing enzymes. Despite sequence homology, CER2-LIKEs are distinct from the BAHD superfamily in that they do not appear to use acyl transfer activity to fulfill their biological function. Here, we review the discovery and characterization of CER2-LIKEs, propose several models to explain their function, and explore the importance of CER2-LIKE proteins for the evolution of plant cuticles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.058
GPT teacher head0.259
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations51
Published2017
Admission routes2
Has abstractyes

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