Analysis of Enzymatic Degradation of Cellulose Microfibrils by Quantitative Surface Plasmon Resonance Imaging
Bibliographic record
Abstract
Cellulose is the most plentiful biopolymer on the planet, and as such, is a large potential energy source. Converting cellulose into ethanol first requires the disruption of the crystallinity of cellulose fibers and subsequent hydrolysis into glucose. The glucose can then be fermented, producing ethanol. The conversion of cellulose fibers to glucose is an energy intensive and costly step, which is a barrier to industrial production of cellulosic ethanol. The use of enzymes to facilitate this conversion is a promising approach. In the present study, the action of individual enzymes and combinations of enzymes from the Hypocrea jecorina secretome on bacterial cellulose fibers has been studied, to better understand their individual and synergistic action.\nI have used a custom Surface Plasmon Resonance imaging (SPRi) device to measure changes in the thickness of cellulose fiber coverage of a thioglucose-functionalized gold substrate upon exposure to enzymes. The cellulose fibers were deposited using a Langmuir-Blodgett technique, resulting in non-uniform cellulose coverage of the substrate. By defining local Regions of Interest (ROIs) of the cellulose-covered gold film, and by measuring the SPR curves at elevated temperature for the ROIs as a function of time, we are able to determine the rate and extent of degradation of the cellulose fibers within individual ROIs. We have fit the change in SPR angle over time after exposure to enzyme to an exponential decay function that allows us to determine the average time constant of action of these enzymes on the deposited cellulose fibers.\nWe have used the above procedure to measure the average time constants of action and the average degradation fraction (the change in average thickness divided by the initial average thickness) of cellulose fibers exposed to CBH-1, CBH-2, and EG-1, as well as combinations of these enzymes. We have measured an increase in the average degradation fraction and a decrease in the average time constants of action for cellulose fibers exposed to 23 μg/mL CBH-2 compared to fibers exposed to the same concentration of CBH-1. Additionally, for concurrent exposure of CBH-1 and EG-1 (with individual concentrations of 23 μg/mL), as well as concurrent introduction of CBH-1, CBH-2 and EG-1, we observed increases in the average degradation fraction and decreases in average time constants relative to the values measured for the individual enzymes. These measurements allow us to determine the relative activity of these enzymes and they demonstrate cooperativity and complementarity of action of the different 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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".