The Hem and Has haem uptake systems in Serratia marcescens
Bibliographic record
Abstract
Serratia marcescens, like several other Gram-negative bacteria, possesses two functional haem uptake systems. The first, referred to as the Hem system, can transport haem present at a concentration equal to or above 10(-6) M. It requires an active outer-membrane receptor which uses proton-motive force energy transmitted by the inner-membrane TonB protein. The other system, Has, takes up haem at lower concentrations and utilizes a small secreted haem-binding protein (haemophore) and its cognate TonB-dependent outer-membrane receptor HasR. Various combinations of mutations were used to examine haem uptake activity by the two systems in S. marcescens. The Hem uptake system enables S. marcescens to take up haem at a concentration of 10(-6) M in the presence of various levels of iron depletion. The Has system, which enables such uptake even in the presence of lower haem concentrations, requires higher iron depletion conditions for function. Has haem uptake requires the presence of HasB, a TonB paralogue encoded by the has operon. These two systems enable S. marcescens to take up haem under various conditions from different sources, reflecting its capacity to confront conditions encountered in natural biotopes.
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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".