Glycosylation of the Escherichia coli TibA Self-Associating Autotransporter Influences the Conformation and the Functionality of the Protein
Bibliographic record
Abstract
The self-associating autotransporters (SAATs) are multifunctional secreted proteins of Escherichia coli, comprising the AIDA-I, TibA and Ag43 proteins. One of their characteristics is that they can be glycosylated. Glycosylation of AIDA-I and Ag43 have been investigated, but not that of TibA. It is still not clear whether glycosylation of the SAATs affect their structure or their functionality. Therefore, we have looked at the effects of glycosylation on the TibA adhesin/invasin. TibA is glycosylated by TibC, a specific glycosyltransferase, and the two genes are encoded in an operon. In this study, we have found that the glycosylation of TibA is not limited to the extracellular functional domain, as previously observed with AIDA-I and Ag43. We have determined that unglycosylated TibA is not able to promote the adhesion of bacteria on cultured epithelial cell, even though it is still able to promote invasion, biofilm formation and autoaggregation of bacteria. We have purified the glycosylated and unglycosylated forms of TibA, and determined that TibA is less stable when not glycosylated. We finally observed that glycosylation affects the oligomerisation of TibA and that unglycosylated TibA is locked in a conformation that is not suited for adhesion. Our results suggest that the effect of glycosylation on the functionality of TibA is indirect.
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".