A polysaccharide deacetylase enhances bacterial adhesion in high-ionic-strength environments
Bibliographic record
Abstract
Differences in ionic strength, pH, temperature, shear forces, and other environmental factors impact adhesion, and organisms have evolved various strategies to optimize their adhesins for their specific environmental conditions. Many species of Alphaproteobacteria, including members of the order Caulobacterales, use a polar adhesin, called holdfast, for surface attachment and subsequent biofilm formation in both freshwater and marine environments. Hirschia baltica, a marine member of Caulobacterales, produces a holdfast adhesin that tolerates a drastically higher ionic strength than the holdfast produced by its freshwater relative, Caulobacter crescentus . In this work, we show that the holdfast polysaccharide deacetylase HfsH plays an important role in adherence in high-ionic-strength environments. We show that increasing expression of HfsH improves holdfast binding in high-ionic-strength environments. We conclude that HfsH plays a role in modulating holdfast binding at high ionic strength and hypothesize that this modulation occurs through varied deacetylation of holdfast polysaccharides.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".