Pilin antigenic variants impact gonococcal lifestyle and antibiotic tolerance by modulating interbacterial forces
Bibliographic record
Abstract
Type 4 pili (T4P) are multifunctional filaments involved in adhesion, surface motility, biofilm formation, and horizontal gene transfer. These extracellular polymers are surface-exposed and, therefore, act as antigens. The human pathogen Neisseria gonorrhoeae uses pilin antigenic variation to escape immune surveillance, yet it is unclear how antigenic variation impacts most other functions of T4P. Here, we addressed this question by replacing the major pilin of a laboratory strain with pilins from clinical isolates. We reveal that the resulting strains vary substantially in their attractive forces. Strongly interacting bacteria form microcolonies while weakly interacting bacteria retain a planktonic lifestyle. In mixed microcolonies, different variant strains segregate in agreement with the differential strength of adhesion hypothesis. By combining structural predictions and laser tweezers experiments, we show that the C-terminal region of the pilin is crucial for attraction. Lifestyle affects growth kinetics and antibiotic tolerance. In the presence of ceftriaxone or ciprofloxacin, the killing kinetics indicate strongly increased tolerance of aggregating strains. We propose that pilin antigenic variation produces a mixed population containing variants optimized for growth, colonization, or survivability under external stress. Different environments select different variants, ensuring the survival and reproduction of the population as a whole.
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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) | 0.001 | 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".