Effects of cell signalling on survival and virulence of Campylobacter jejuni
Bibliographic record
Abstract
'Campylobacter jejuni' is the leading bacterial cause of food-borne illness worldwide. The regulation of survival and virulence mechanisms are not fully characterized in 'C. jejuni', however, the molecular basis for both survival and virulence traits of many bacteria is thought to involve cell-cell communication via autoinducers. There are three known autoinducer types allegedly produced by Gram-negative bacteria, designated AI-1, AI-2 and AI-3. This study investigated production of these molecules by 'C. jejuni', and then determined the effect of these signalling systems on selected survival and virulence characteristics. The AI-1 and AI-3 molecules and mimics investigated increased the transition rate to a viable but non culturable (VBNC) state, and decreased the organisms ability to form biofilms. These molecules and mimics were also involved to some degree in either up- or down-regulating the 5 virulence genes studied, as well as effecting an increase of interleukin-8 secretion in INT407 cells. Previous reports established that 'C. jejuni' produces an AI-2 molecule via the 'luxS' gene, so a 'luxS' mutant was generated, and the above survival and virulence determinants examined. Complementation studies showed that the 'luxS' mutation altered the wild-type phenotype, but these effects were not reversed when complemented with an AI-2 precursor. Finally, a range of defined as well as complex media and solutions were trialled to assess the ability to transform 'C. jejuni' VBNC cells to a culturable state, but all were found to be unsatisfactory. In conclusion, 'C. jejuni' may not produce classical AI-1 or AI-3 molecules, but is able to utilize these signals and mimics in gene regulation for both survival and virulence mechanisms. While ' C. jejuni' produces an AI-2 molecule, this might be a byproduct of metabolism and not involved in gene regulation. It also appears that ' C. jejuni' requires live animal models and specific hosts to transform from a VBNC state to a culturable state. These results give insight into cell-signalling utilization in survival and virulence mechanisms as well as having implications in developing new standard detection methods to replace the existing protocols which are not able to detect VBNC cells of 'C. jejuni '.
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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 | 0.001 |
| 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".