Expression of fungal acetyl xylan esterase in <i>Arabidopsis thaliana</i> improves saccharification of stem lignocellulose
Bibliographic record
Abstract
Cell wall hemicelluloses and pectins are O-acetylated at specific positions, but the significance of these substitutions is poorly understood. Using a transgenic approach, we investigated how reducing the extent of O-acetylation in xylan affects cell wall chemistry, plant performance and the recalcitrance of lignocellulose to saccharification. The Aspergillus niger acetyl xylan esterase AnAXE1 was expressed in Arabidopsis under the control of either the constitutively expressed 35S CAMV promoter or a woody-tissue-specific GT43B aspen promoter, and the protein was targeted to the apoplast by its native signal peptide, resulting in elevated acetyl esterase activity in soluble and wall-bound protein extracts and reduced xylan acetylation. No significant alterations in cell wall composition were observed in the transgenic lines, but their xylans were more easily digested by a β-1,4-endoxylanase, and more readily extracted by hot water, acids or alkali. Enzymatic saccharification of lignocellulose after hot water and alkali pretreatments produced up to 20% more reducing sugars in several lines. Fermentation by Trametes versicolor of tissue hydrolysates from the line with a 30% reduction in acetyl content yielded ~70% more ethanol compared with wild type. Plants expressing 35S:AnAXE1 and pGT43B:AnAXE1 developed normally and showed increased resistance to the biotrophic pathogen Hyaloperonospora arabidopsidis, probably due to constitutive activation of defence pathways. However, unintended changes in xyloglucan and pectin acetylation were only observed in 35S:AnAXE1-expressing plants. This study demonstrates that postsynthetic xylan deacetylation in woody tissues is a promising strategy for optimizing lignocellulosic biomass for biofuel production.
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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 | 0.001 |
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".