MétaCan
Menu
Back to cohort
Record W4388566519 · doi:10.1038/s41467-023-42917-9

Biosynthesis of barley wax β-diketones: a type-III polyketide synthase condensing two fatty acyl units

2023· article· en· W4388566519 on OpenAlexafffund
Yulin Sun, Alberto Ruiz Orduna, Zhonghang Zhang, Sarah J. Feakins, Reinhard Jetter

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsUniversity of British Columbia
FundersRWTH Aachen UniversityChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsPolyketide synthaseEnzymeBiochemistryWax esterBiosynthesisAcyl carrier proteinWaxPolyketideHordeum vulgareChemistryBiologyStereochemistryPoaceaeBotany

Abstract

fetched live from OpenAlex

Abstract The surface coatings of cereal plants are dominated by waxy β-diketones crucial for drought resistance and, therefore, grain yield. Here, barley ( Hordeum vulgare ) wax analyses reveal β-diketone and associated 2-alkanol ester profiles suggesting a common C 16 3-ketoacid precursor. Isotope analysis further shows that the major (C 31 ) diketone is synthesized from two plastidial C 16 acyl units. Previous studies identified a gene cluster encoding enzymes responsible for β-diketone formation in barley, but left their biochemical functions unknown. Various assays now characterize one of these enzymes as a thioesterase producing long-chain (mainly C 16 ) 3-ketoacids, and another one as a polyketide synthase (PKS) condensing the 3-ketoacids with long-chain (mainly C 16 ) acyl-CoAs into β-diketones. The two enzymes are localized to the plastids and Endoplasmic Reticulum (ER), respectively, implying substrate transfer between these two sub-cellular compartments. Overall, our findings define a two-step pathway involving an unprecedented PKS reaction leading directly to the β-diketone products.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.062
GPT teacher head0.288
Teacher spread0.226 · 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

Citations14
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicPlant Surface Properties and TreatmentsFrench-language works237,207