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Record W4297237807 · doi:10.1111/pbi.13935

Metabolic engineering of <i>p</i>‐hydroxybenzoate in poplar lignin

2022· article· en· W4297237807 on OpenAlexaff
Yaseen Mottiar, Steven D. Karlen, Robyn E. Goacher, John Ralph, Shawn D. Mansfield

Bibliographic record

VenuePlant Biotechnology Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
FundersGreat Lakes Bioenergy Research CenterBiological and Environmental ResearchOffice of ScienceU.S. Department of Energy
KeywordsLigninXylemMetabolic engineeringCell wallHydrolysisBiologyBiochemistryPhenylpropanoidBiomass (ecology)BotanyEnzymeBiosynthesisAgronomy

Abstract

fetched live from OpenAlex

Ester-linked p-hydroxybenzoate occurs naturally in poplar lignin as pendent groups that can be released by mild alkaline hydrolysis. These 'clip-off' phenolics can be separated from biomass and upgraded into diverse high-value bioproducts. We introduced a bacterial chorismate pyruvate lyase gene into transgenic poplar trees with the aim of producing more p-hydroxybenzoate from chorismate, itself a metabolic precursor to lignin. By driving heterologous expression specifically in the plastids of cells undergoing secondary wall formation, this strategy achieved a 50% increase in cell-wall-bound p-hydroxybenzoate in mature wood and nearly 10 times more in developing xylem relative to control trees. Comparable amounts also remained as soluble p-hydroxybenzoate-containing xylem metabolites, pointing to even greater engineering potential. Mass spectrometry imaging showed that the elevated p-hydroxybenzoylation was largely restricted to the cell walls of fibres. Finally, transgenic lines outperformed control trees in assays of saccharification potential. This study highlights the biotech potential of cell-wall-bound phenolate esters and demonstrates the importance of substrate supply in lignin engineering.

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 score0.017
Threshold uncertainty score0.556

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 integrity0.0000.001
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 head0.004
GPT teacher head0.154
Teacher spread0.150 · 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

Citations38
Published2022
Admission routes1
Has abstractyes

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