Diverse specificity of cellulosome attachment to the bacterial cell surface
Bibliographic record
Abstract
During the course of evolution, the cellulosome, one of Nature's most intricate multi-enzyme complexes, has been continuously fine-tuned to efficiently deconstruct recalcitrant carbohydrates. To facilitate the uptake of released sugars, anaerobic bacteria use highly ordered protein-protein interactions to recruit these nanomachines to the cell surface. Dockerin modules located within a non-catalytic macromolecular scaffold, whose primary role is to assemble cellulosomal enzymatic subunits, bind cohesin modules of cell envelope proteins, thereby anchoring the cellulosome onto the bacterial cell. Here we have elucidated the unique molecular mechanisms used by anaerobic bacteria for cellulosome cellular attachment. The structure and biochemical analysis of five cohesin-dockerin complexes revealed that cell surface dockerins contain two cohesin-binding interfaces, which can present different or identical specificities. In contrast to the current static model, we propose that dockerins utilize multivalent modes of cohesin recognition to recruit cellulosomes to the cell surface, a mechanism that maximises substrate access while facilitating complex assembly.
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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 | 0.000 |
| 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".