The Transcriptional Landscape of Campylobacter jejuni under Iron Replete and Iron Limited Growth Conditions
Bibliographic record
Abstract
The genome-wide Campylobacter jejuni transcriptional response under iron replete and iron limited conditions was characterized using RNA-seq. We have identified 111 novel C. jejuni 5'UTRs and mapped 377 co-transcribed genes into 230 transcriptional operons. In contrast to previous microarray results, the C. jejuni iron stimulon is less extensive than previously believed and consists of 77 iron activated genes and 50 iron repressed genes. As anticipated, the iron repressed genes are primarily those involved in iron acquisition or oxidative stress defense. Interestingly, these experiments have revealed that iron is an important modulator of flagellar biogenesis with almost all the components of the flagella found to be iron activated. Given that motility is a well-known C. jejuni colonization factor, this suggests that there is an important regulatory coupling of flagellar biogenesis and iron level in C. jejuni. In addition we have identified several consensus mutations in the C. jejuni NCTC11168 strain that are widespread in the Campylobacter research community and which may explain conflicting phenotypic reports for this strain. Comparative analysis of iron responsive genes with the known Fur regulon indicates that many iron responsive genes are not Fur responsive; suggesting that additional iron regulatory factors remain to be characterized in C. jejuni. Further analysis of the RNA-seq data identified multiple novel transcripts including 19 potential ncRNAs. The expression of selected ncRNAs was confirmed and quantified with qRT-PCR. The qRT-PCR results indicate that several of these novel transcripts are either Fur and/or iron responsive. The fact that several of these ncRNAs are iron responsive or Fur regulated suggests that they may perform regulatory roles in iron homeostasis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".