Repeats-In-Toxin Adhesion Proteins: What Makes Them Stick?
Bibliographic record
Abstract
Bacteria use adhesion proteins (adhesins) to bind substrates on biotic and abiotic surfaces to initiate biofilm formation. These bacterial communities can be detrimental to a host when, for example, they cause teeth plaques, chronic infections, and the contamination of food products. On the other hand, they can also promote plant growth and the degradation of oils, depending on the organism. Characterizing adhesin interactions may present opportunities to inhibit destructive biofilms and reinforce the advantageous ones. A subgroup of these proteins called Repeats-In-Toxin adhesins are exported by a type 1 secretion system and are retained on the outer membrane of some Gram-negative bacteria. This thesis examined C-terminal ligand-binding domains from three different adhesins: 1) The large adhesion protein from the oil- degrading bacterium Marinobacter hydrocarbonoclasticus, contains a PA14 domain with the ability to bind specific carbohydrates. This 20-kDa domain was tested as a dextran-affinity tag for purification of recombinant proteins on dextran-based size-exclusion resins. The tag bound to Superdex, Sephadex, and Sephacryl, and proved to be superior to nickel-affinity chromatography. 2) A medium adhesion protein from Pseudomonas fluorescens, which contributes to biofilm formation on plant root surfaces, contains a von Willebrand Factor A domain in the C-terminal region that was characterized by X-ray crystallography. While human integrin contains a homologue of this domain to bind extracellular matrix proteins, including collagen, the binding partner for Pseudomonas fluorescens is still unknown. Lastly, 3) the flagellum-regulated hemagglutinin A, which binds to epithelial cells and erythrocytes in the pathogenic lifecycle of Vibrio cholerae, does so through a peptide-binding domain. This protein was produced with its neighboring domain and co-crystallized with nanomolar-affinity pentapeptide ligands. These peptides successfully inhibited attachment of V. cholerae to erythrocytes and could potentially be used for anti-adhesion therapy against cholera.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".