Bacteriophage-encoded 24B_1 molecule resembles herpesviral microRNAs and plays a crucial role in the development of both the virus and its host
Bibliographic record
Abstract
The 24B_1 small non-coding RNA molecule has been identified in Escherichia coli after induction of Shiga toxin-converting bacteriophage Φ24B. In this work, we focused on its direct role during phage and bacterial host development. We observed that in many aspects, this phage sRNA resembles herpesviral microRNAs. Similar to microRNAs, the mature 24B_1 is a short molecule, consisting of just 20 nucleotides. It is generated by cleaving the 80-nt long precursor transcript, and likely it undergoes a multi-step maturation process in which the Hfq protein plays an important role, as confirmed by demonstration of its binding to the 24B_1 precursor, but not to the 24B_1 mature form. Moreover, 24B_1 plays a significant role in maintaining the prophage state and reprogramming the host's energy metabolism. We proved that overproduction of this molecule causes the opposite physiological effects to the mutant devoid of the 24B_1 gene, and thus, favors the lysogenic pathway. Furthermore, the 24B_1 overrepresentation significantly increases the efficiency of expression of phage genes coding for proteins CI, CII, and CIII which are engaged in the maintenance of the prophage. It seems that through binding to mRNA of the sdhB gene, coding for the succinate dehydrogenase subunit, the 24B_1 alters the central carbon metabolism and causes a drop in the ATP intracellular level. Interestingly, a similar effect, called the Warburg switch, is caused by herpesviral microRNAs and it is observed in cancer cells. The advantage of the Warburg effect is still unclear, however, it was proposed that the metabolism of cancer cells, and all rapidly dividing cells, is adopted to convert nutrients such as glucose and glutamine faster and more efficiently into biomass. The availability of essential building blocks, such as nucleotides, amino acids, and lipids, is crucial for effective cell proliferation which in turn is essential for the prophage and its host to stay in the lysogenic state.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".