Laccases Direct Lignification in the Discrete Secondary Cell Wall Domains of Protoxylem
Bibliographic record
Abstract
Plants precisely control lignin deposition in spiral or annular secondary cell wall domains during protoxylem tracheary element (TE) development. Because protoxylem TEs function to transport water within rapidly elongating tissues, it is important that lignin deposition is restricted to the secondary cell walls in order to preserve the plasticity of adjacent primary wall domains. The Arabidopsis (Arabidopsis thaliana) inducible VASCULAR NAC DOMAIN7 (VND7) protoxylem TE differentiation system permits the use of mutant backgrounds, fluorescent protein tagging, and high-resolution live-cell imaging of xylem cells during secondary cell wall development. Enzymes synthesizing monolignols, as well as putative monolignol transporters, showed a uniform distribution during protoxylem TE differentiation. By contrast, the oxidative enzymes LACCASE4 (LAC4) and LAC17 were spatially localized to secondary cell walls throughout protoxylem TE differentiation. These data support the hypothesis that precise delivery of oxidative enzymes determines the pattern of cell wall lignification. This view was supported by lac4lac17 mutant analysis demonstrating that laccases are necessary for protoxylem TE lignification. Overexpression studies showed that laccases are sufficient to catalyze ectopic lignin polymerization in primary cell walls when exogenous monolignols are supplied. Our data support a model of protoxylem TE lignification in which monolignols are highly mobile once exported to the cell wall, and in which precise targeting of laccases to secondary cell wall domains directs lignin deposition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".