Identification of <i>Campylobacter jejuni</i> Genes Contributing to Acid Adaptation by Transcriptional Profiling and Genome-Wide Mutagenesis
Bibliographic record
Abstract
In order to cause disease, the food- and waterborne pathogen Campylobacter jejuni must face the extreme acidity of the host stomach as well as cope with pH fluctuations in the intestine. In the present study, C. jejuni NCTC 11168 was grown under mildly acidic conditions mimicking those encountered in the intestine. The resulting transcriptional profiles revealed how this bacterium fine-tunes gene expression in response to acid stress. This adaptation involves the differential expression of respiratory pathways, the induction of genes for phosphate transport, and the repression of energy generation and intermediary metabolism genes. We also generated and screened a transposon-based mutant library to identify genes required for wild-type levels of growth under mildly acidic conditions. This screen highlighted the important role played by cell surface components (flagella, the outer membrane, capsular polysaccharides, and lipooligosaccharides) in the acid stress response of C. jejuni. Our data also revealed that a limited correlation exists between genes required for growth under acidic conditions and genes differentially expressed in response to acid. To gain a comprehensive picture of the acid stress response of C. jejuni, we merged transcriptional profiles obtained from acid-adapted cells and cells subjected to acid shock. Genes encoding the transcriptional regulator PerR and putative oxidoreductase subunits Cj0414 and Cj0415 were among the few up-regulated under both acid stress conditions. As a Cj0415 mutant was acid sensitive, it is likely that these genes are crucial to the acid stress response of C. jejuni and consequently are important for host colonization.
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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 | 0.000 | 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 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".