Bioinformatics analysis of diversity in bacterial glycan chain-termination chemistry and organization of carbohydrate-binding modules linked to ABC transporters
Bibliographic record
Abstract
The structures of bacterial cell surface glycans are remarkably diverse. In spite of this diversity, the general strategies used for their assembly are limited. In one of the major processes, found in both Gram-positive and Gram-negative bacteria, the glycan is polymerized in the cytoplasm on a polyprenol lipid carrier and exported from the cytoplasm by an ATP-binding cassette (ABC) transporter. The ABC transporter actively participates in determining the chain length of the glycan substrate, which impacts functional properties of the glycoconjugate products. A subset of these systems employs an additional elaborate glycan capping strategy that dictates the size distribution of the products. The hallmarks of prototypical capped glycan systems are a chain-terminating enzyme possessing a coiled-coil molecular ruler and an ABC transporter possessing a carbohydrate-binding module, which recognizes the glycan cap. To date, detailed investigations are limited to a small number of prototypes, and here, we used our current understanding of these processes for a bioinformatics census of other examples in available genome sequences. This study not only revealed additional instances of existing terminators but also predicted new chemistries as well as systems that diverge from the established prototypes. These analyses enable some new functional hypotheses and offer a roadmap for future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".