Mechanism of bacterial cell-surface attachment revealed by the structure of cellulosomal type II cohesin-dockerin complex
Bibliographic record
Abstract
Bacterial cell-surface attachment of macromolecular complexes maintains the microorganism in close proximity to extracellular substrates and allows for optimal uptake of hydrolytic byproducts. The cellulosome is a large multienzyme complex used by many anaerobic bacteria for the efficient degradation of plant cell-wall polysaccharides. The mechanism of cellulosome retention to the bacterial cell surface involves a calcium-mediated protein-protein interaction between the dockerin (Doc) module from the cellulosomal scaffold and a cohesin (Coh) module of cell-surface proteins located within the proteoglycan layer. Here, we report the structure of an ultra-high-affinity (K(a) = 1.44 x 10(10) M(-1)) complex between type II Doc, together with its neighboring X module from the cellulosome scaffold of Clostridium thermocellum, and a type II Coh module associated with the bacterial cell surface. Identification of X module-Doc and X module-Coh contacts reveal roles for the X module in Doc stability and enhanced Coh recognition. This extremely tight interaction involves one face of the Coh and both helices of the Doc and comprises significant hydrophobic character and a complementary extensive hydrogen-bond network. This structure represents a unique mechanism for cell-surface attachment in anaerobic bacteria and provides a rationale for discriminating between type I and type II Coh modules.
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 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".