Illuminating Glucomannan Synthases to Explore Cell Wall Synthesis Bottlenecks
Bibliographic record
Abstract
ABSTRACT Hemicelluloses are important dietary fibers and a key component of lignocellulosic biomass. Despite numerous observations for fluorescently tagged cellulose synthases, the subcellular journeys and biochemical activities of intracellular cellulose synthase-like enzymes such as β-mannan synthases (ManS) remain largely unexplored. This study identifies C-terminal fluorescent protein tags that maintain ManS activity in the yeast to accelerate the Design, Build, Test, Learn cycles for polysaccharide biosynthesis. Using the Amorphophallus konjac ManS as a case study, we demonstrate that the enzyme co-localizes with a known yeast marker for the Golgi apparatus despite the toxic effects of plant glucomannan accumulation in Pichia pastoris . The ManS first transmembrane domain was found to be critical for the punctate localization of the enzyme, its overall expression level and its function. Additionally, we explored how fluorescently tagged ManS is influenced by genetic or chemical perturbations of native yeast cell wall components, such as reducing protein mannosylation and severely disrupting β-1,3-glucans. Finally, we identified alternative feeding strategies and episomal vectors for Pichia , which were extended to Saccharomyces cerevisiae , to accelerate hemicellulose research. We propose that expanding the Plant MoClo-compatible plasmid repertoire is essential to swiftly prototype carbohydrate-active enzymes in yeast before proceeding with more time-intensive analyses in plants. Requiring only hours or days instead of weeks or months for plant transformation/regeneration, our yeast prototyping strategies can de-risk the bioengineering of 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".