Interaction between bacterial adhesins leads to coaggregation by the oral bacteria <i>Veillonella parvula</i> and <i>Streptococcus gordonii</i>
Bibliographic record
Abstract
ABSTRACT Veillonella parvula is an unusual diderm firmicute that plays a central role in the formation of dental biofilm formation through coaggregation with many other oral bacteria. However, the molecular interactions leading to oral biofilm formation are largely unknown. In a recent study (L. Dorison, N. Béchon, C. Martin-Gallausiaux, S. Chamorro-Rodriguez, et al., mBio 15:e02171-24, 2024, https://doi.org/10.1128/mbio.02171-24 ), coaggregation by V. parvula was shown to be mediated by trimeric autotransporter adhesins (TAAs), which are large, fibrous surface proteins widespread in Gram-negative bacteria. Importantly, this study identified the binding partner protein on a coaggregating bacterium, Streptococcus gordonii , which the authors called VisA. This finding is the first time a TAA mediating coaggregation with a different type of protein has been established and suggests that specifically interacting protein partners may have coevolved multiple times to allow complex biofilm formation, as exemplified by the development of dental plaque. Understanding these interactions might lead to innovations to reduce build-up of dental plaque and associated oral diseases.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".