Direct and up-close views of plant cell walls show a leading role for lignin-modifying enzymes on ensuing xylanases
Bibliographic record
Abstract
BACKGROUND: A key barrier that limits the full potential of biological processes to create new, sustainable materials and fuels from plant fibre is limited enzyme accessibility to polysaccharides and lignin that characterize lignocellulose networks. Moreover, the heterogeneity of lignocellulosic substrates means that different enzyme combinations might be required for efficient transformation of different plant resources. Analytical techniques with high chemical sensitivity and spatial resolution that permit direct characterization of solid samples could help overcome these challenges by allowing direct visualization of enzyme action within plant fibre, thereby identify barriers to enzyme action. RESULTS: In the current study, the high spatial resolution (about 30 nm) of scanning transmission X-ray microscopy (STXM), and the detection sensitivity (ppm) of time-of-flight secondary ion mass spectrometry (ToF-SIMS), were harnessed for the first time to investigate the progression of laccase, cellulase and xylanase activities through wood samples, and to evaluate complementary action between lignin-modifying and polysaccharide-degrading enzymes. In particular, complementary insights from the STXM and ToF-SIMS analyses revealed the key role of laccase in promoting xylanase activity throughout and between plant cell walls. CONCLUSIONS: The spatial resolution of STXM clearly revealed time-dependent progression and spatial distribution of laccase and xylanase activities, whereas ToF-SIMS analyses confirmed that laccase promoted protein penetration into fibre samples, leading to an overall increase in polysaccharide degradation. Spectromicroscopic visualizations of plant cell wall chemistry allowed simultaneous tracking of changes to lignin and polysaccharide contents, which provides new possibilities for investigating the complementary roles of lignin-modifying and carbohydrate-active enzymes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".