Phylogenetically distinct fungal expansins show different binding preferences towards cellulosic materials and enhance cellulase activity
Bibliographic record
Abstract
Expansins and expansin-like proteins are found in plants and microbes, and can disrupt the cellulosic fiber network of plant cell walls. While plant expansins play a role in cell wall formation, microbial expansin-like proteins reportedly enhance the activity of cellulases. Herein, two novel fungal expansin-like proteins, Ama EXLX1 from Allomyces macrogynus and Apu EXLX1 from Aureobasidium pullulans , were recombinantly produced in Pichia pastoris . While both Ama EXLX1 and Apu EXLX1 retain typical expansin structure, they share low sequence identity (22.5 %) and different predicted pI values (5.8 and 8.8, respectively), which was expected to impact their action on cellulosic substrates. Accordingly, adsorption of the proteins on cellulose nanofibers (CNF) and the impact of the expansin-like proteins on the hydrolysis of CNF by an endoglucanase (Cel7B) was investigated using quartz crystal microbalance with dissipation (QCM-D). Ama EXLX1 showed higher affinity towards cellulose compared to Apu EXLX1, which was correlated to missing key aromatic residues in the polysaccharide binding surface of Apu EXLX1. The pretreatment of a CNF film with Ama EXLX1 and Apu EXLX1 increased the initial rate of Cel7B activity. This study underscores similarities between the impacts that bacterial and fungal expansin-like proteins can have on the enzymatic deconstruction of cellulose, and sequence properties that could impact expansin performance.
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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".