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Record W4319827015 · doi:10.1111/pbi.14027

Protein interactomes for plant lipid biosynthesis and their biotechnological applications

2023· review· en· W4319827015 on OpenAlexafffund
Yang Xu, Stacy D. Singer, Guanqun Chen

Bibliographic record

VenuePlant Biotechnology Journal · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of AlbertaUniversity of Guelph
FundersAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of AlbertaAgriculture and Agri-Food CanadaUniversity of Guelph
KeywordsInteractomeBiologyBiosynthesisBiochemistryLipid metabolismProteomicsLipid dropletMetabolic pathwayComputational biologyCell biologyEnzymeGene

Abstract

fetched live from OpenAlex

Plant lipids have essential biological roles in plant development and stress responses through their functions in cell membrane formation, energy storage and signalling. Vegetable oil, which is composed mainly of the storage lipid triacylglycerol, also has important applications in food, biofuel and oleochemical industries. Lipid biosynthesis occurs in multiple subcellular compartments and involves the coordinated action of various pathways. Although biochemical and molecular biology research over the last few decades has identified many proteins associated with lipid metabolism, our current understanding of the dynamic protein interactomes involved in lipid biosynthesis, modification and channelling is limited. This review examines advances in the identification and characterization of protein interactomes involved in plant lipid biosynthesis, with a focus on protein complexes consisting of different subunits for sequential reactions such as those in fatty acid biosynthesis and modification, as well as transient or dynamic interactomes formed from enzymes in cooperative pathways such as assemblies of membrane-bound enzymes for triacylglycerol biosynthesis. We also showcase a selection of representative protein interactome structures predicted using AlphaFold2, and discuss current and prospective strategies involving the use of interactome knowledge in plant lipid biotechnology. Finally, unresolved questions in this research area and possible approaches to address them are also discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.001
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 head0.040
GPT teacher head0.285
Teacher spread0.246 · 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 designOther design
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

Citations33
Published2023
Admission routes2
Has abstractyes

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