Conformation Change in a Self-recognizing Autotransporter Modulates Bacterial Cell-Cell Interaction
Bibliographic record
Abstract
Bacteria mostly live as multicellular communities, although they are unicellular organisms, yet the mechanisms that tie individual bacteria together are often poorly understood. The adhesin involved in diffuse adherence (AIDA-I) is an adhesin of diarrheagenic Escherichia coli strains. AIDA-I also mediates bacterial auto-aggregation and biofilm formation and thus could be important for the organization of communities of pathogens. Using purified protein and whole bacteria, we provide direct evidence that AIDA-I promotes auto-aggregation by interacting with itself. Using various biophysical and biochemical techniques, we observed a conformational change in the protein during AIDA-AIDA interactions, strengthening the notion that this is a highly specific interaction. The self-association of AIDA-I is of high affinity but can be modulated by sodium chloride. We observe that a bile salt, sodium deoxycholate, also prevents AIDA-I oligomerization and bacterial auto-aggregation. Thus, we propose that AIDA-I, and most likely other similar autotransporters such as antigen 43 (Ag43) and TibA, organize bacterial communities of pathogens through a self-recognition mechanism that is sensitive to the environment. This could permit bacteria to switch between multicellular and unicellular lifestyles to complete their infection.
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 | 0.000 | 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".