Unexpected modulation of Hna phage defense activity by the symbiotic regulator NolR
Bibliographic record
Abstract
ABSTRACT The Hna phage defense system is one of many systems that protect bacteria against bacterial viruses (phages). Hna was first discovered in the nitrogen-fixing alphaproteobacterium Sinorhizobium meliloti , which forms root nodules on leguminous plants. We report that the efficacy of the Hna system depends on NolR, a transcriptional regulator known to regulate expression of nodulation genes. Strains carrying a mutant nolR gene (e.g., the widely used laboratory strain Rm1021) display dramatically reduced Hna-mediated phage resistance compared to those with the wild-type nolR gene. hna expression is approximately doubled in nolR + (wild-type) compared to nolR – strains. Integration of a second copy of hna increased phage resistance in a nolR – strain >1,000-fold, indicating that a moderate hna expression difference is sufficient to affect the Hna phage resistance phenotype. NolR does not appear to directly regulate hna , as there is no predicted NolR binding site upstream of hna , and purified NolR protein does not bind to the hna upstream sequence. Other genes whose transcription is regulated by NolR were identified through RNA-seq experiments. These include the lipopolysaccharide sulfotransferase gene lpsS , which is located downstream of a NolR binding site. This work illustrates how modest differences in expression between strains can dramatically alter the protective phenotype of a defense system. IMPORTANCE The ability of a bacterial culture to survive phage infection is significant in both medical (phage therapy) and industrial (e.g., cheese production) contexts. This study describes a factor that influences the efficacy of a recently discovered phage defense system (Hna) in the agriculturally relevant soil bacterium Sinorhizobium meliloti . Like other phage defense systems, Hna systems undergo extensive horizontal transfer and must be able to maintain functionality across different genetic backgrounds. Our work demonstrates that host factor differences can significantly impact the performance of phage defense systems.
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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".