Disulfide Bonds: A Key Modification in Bacterial Extracytoplasmic Proteins
Bibliographic record
Abstract
Disulfide bonds are a common posttranslational modification that contributes to the folding and stability of extracytoplasmic proteins. Almost all organisms, from eukaryotes to prokaryotes, have evolved enzymes to make and break these bonds. Accurate and efficient disulfide bond formation can be vital for protein function; therefore, the enzymes that catalyze disulfide bond formation are involved in multiple biological processes. Recent advances clearly show that oral bacteria also have the ability to from disulfide bonds, and this ability has an effect on a range of dental plaque-related phenotypes. In the gram-positive Streptococcus gordonii, the ability to form disulfide bonds affected autolysis, extracellular DNA release, biofilm formation, genetic competence, and bacteriocin production. In Actinomyces oris, disulfide bond formation is needed for pilus assembly, coaggregation, and biofilm formation. In other gram-positive bacteria, such as Enterococcus faecalis, disulfide bonds are formed in secreted bacteriocins and required for activity. In these oral bacteria, the enzymes that catalyze the disulfide bonds are quite diverse and share little sequence homology, but all contain a CXXC catalytic active site motif and a conserved C-terminal cis-proline, signature features of a thiol-disulfide oxidoreductase. Emerging evidence also indicates that gram-negative oral bacteria, such as Porphyromonas gingivalis and Tannerella forsythia, use disulfide bonds to stabilize their outer membrane porin proteins. Bioinformatic screens reveal that these gram-negative bacteria carry genes coding for thiol-disulfide oxidoreductases in their genomes. In conclusion, disulfide bond formation in oral bacteria is an emerging field, and the ability to form disulfide bonds plays an important role in dental plaque formation and fitness for the bacteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".