Essential genes from Arctic bacteria used to construct stable, temperature-sensitive bacterial vaccines
Bibliographic record
Abstract
All bacteria share a set of evolutionarily conserved essential genes that encode products that are required for viability. The great diversity of environments that bacteria inhabit, including environments at extreme temperatures, place adaptive pressure on essential genes. We sought to use this evolutionary diversity of essential genes to engineer bacterial pathogens to be stably temperature-sensitive, and thus useful as live vaccines. We isolated essential genes from bacteria found in the Arctic and substituted them for their counterparts into pathogens of mammals. We found that substitution of nine different essential genes from psychrophilic (cold-loving) bacteria into mammalian pathogenic bacteria resulted in strains that died below their normal-temperature growth limits. Substitution of three different psychrophilic gene orthologs of ligA, which encode NAD-dependent DNA ligase, resulted in bacterial strains that died at 33, 35, and 37 degrees C. One ligA gene was shown to render Francisella tularensis, Salmonella enterica, and Mycobacterium smegmatis temperature-sensitive, demonstrating that this gene functions in both Gram-negative and Gram-positive lineage bacteria. Three temperature-sensitive F. tularensis strains were shown to induce protective immunity after vaccination at a cool body site. About half of the genes that could be tested were unable to mutate to temperature-resistant forms at detectable levels. These results show that psychrophilic essential genes can be used to create a unique class of bacterial temperature-sensitive vaccines for important human pathogens, such as S. enterica and Mycobacterium tuberculosis.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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 teacher head, 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".