Foreign signal peptides can constitute a barrier to functional expression of periplasmic proteins in Haemophilus influenzae
Bibliographic record
Abstract
To study the periplasmic branch of iron (ferric ion) uptake systems in Gram-negative bacteria, genetic reconstitution experiments were initiated in Haemophilus influenzae involving exchange of the periplasmic iron-binding protein. The expression of many of the heterologous periplasmic ferric-binding proteins (FbpAs) was quite limited. Transformation experiments with the fbpA gene from Neisseria gonorrhoeae yielded two colony sizes with different phenotypic characteristics. The small colonies contained the intact N. gonorrhoeae fbpA gene and were deficient in utilization of transferrin iron. The large colonies contained hybrid H. influenzae/N. gonorrhoeae fbpA genes, were proficient in transferrin iron utilization and had enhanced levels of expression of FbpA. These hybrid genes included several that encoded the mature N. gonorrhoeae FbpA with the H. influenzae signal peptide. To more fully evaluate the effect of foreign signal peptides, a series of hybrid genes were prepared that exchanged the signal peptides from H. influenzae FbpA, N. gonorrhoeae FbpA and the TEM-1 beta-lactamase. The presence of the H. influenzae leader was required for functional expression of FbpAs and was shown to dramatically increase the level of beta-lactamase activity.
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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 | 0.000 | 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) | 0.000 | 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".