Unraveling the Supramolecular Structure and Nanoscale Dislocations of Bacterial Cellulose Ribbons Using Correlative Super-Resolution Light and Electron Microscopy
Bibliographic record
Abstract
Cellulose is a structural linear polysaccharide that is naturally produced by plants and bacteria, making it the most abundant biopolymer on Earth. The hierarchical structure of cellulose from the nano- to microscale is intimately linked to its biosynthesis and the ability to process this sustainable resource for materials applications. Despite this, the morphology of bacterial cellulose microfibrils and their assembly into higher order structures, as well as the structural origins of the alternating crystalline and disordered supramolecular structure of cellulose, have remained elusive. In this work, we employed high-resolution transmission electron and atomic force microscopies to study the morphology of bacterial cellulose ribbons at different levels of its structural hierarchy and provide direct visualization of nanometer-wide microfibrils. The non-persistent twisting of cellulose ribbons was characterized in detail, and we found that twists are associated with nanostructural defects at the bundle and microfibril levels. To investigate the structural origins of the persistent disordered regions that are present along cellulose ribbons, we employed a correlative super-resolution light and electron microscopy workflow and observed that the disordered regions that can be seen in super-resolution fluorescence microscopy largely correlated with the ribbon twisting observed in electron microscopy. Unraveling the hierarchical assembly of bacterial cellulose and the ultrastructural basis of its disordered regions provides insights into its biosynthesis and susceptibility to hydrolysis. These findings are important to understand the cell-directed assembly of cellulose, develop new cellulose-based nanomaterials, and develop more efficient biomass conversion strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".