Fasciclin-like arabinogalactan proteins: specialization for stem biomechanics and cell wall architecture in Arabidopsis and Eucalyptus
Bibliographic record
Abstract
The ancient cell adhesion fasciclin (FAS) domain is found in bacteria, fungi, algae, insects and animals, and occurs in a large family of fasciclin-like arabinogalactan proteins (FLAs) in higher plants. Functional roles for FAS-containing proteins have been determined for insects, algae and vertebrates; however, the biological functions of the various higher-plant FLAs are not clear. Expression of some FLAs has been correlated with the onset of secondary-wall cellulose synthesis in Arabidopsis stems, and also with wood formation in the stems and branches of trees, suggesting a biological role in plant stems. We examined whether FLAs contribute to plant stem biomechanics. Using phylogenetic, transcript abundance and promoter-GUS fusion analyses, we identified a conserved subset of single FAS domain FLAs (group A FLAs) in Eucalyptus and Arabidopsis that have specific and high transcript abundance in stems, particularly in stem cells undergoing secondary-wall deposition, and that the phylogenetic conservation appears to extend to other dicots and monocots. Gene-function analyses revealed that Arabidopsis T-DNA knockout double mutant stems had altered stem biomechanics with reduced tensile strength and a reduced tensile modulus of elasticity, as well as altered cell-wall architecture and composition, with increased cellulose microfibril angle and reduced arabinose, galactose and cellulose content. Using materials engineering concepts, we relate the effects of these FLAs on cell-wall composition with stem biomechanics. Our results suggest that a subset of single FAS domain FLAs contributes to plant stem strength by affecting cellulose deposition, and to the stem modulus of elasticity by affecting the integrity of the cell-wall matrix.
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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) | 0.000 | 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".