High allelic diversity in the methyltransferase gene of a phase variable type III restriction-modification system has implications for the fitness of Haemophilus influenzae
Bibliographic record
Abstract
Phase variable restriction-modification (R-M) systems are widespread in Eubacteria. Haemophilus influenzae encodes a phase variable homolog of Type III R-M systems. Sequence analysis of this system in 22 non-typeable H.influenzae isolates revealed a hypervariable region in the central portion of the mod gene whereas the res gene was conserved. Maximum likelihood (ML) analysis indicated that most sites outside this hypervariable region experienced strong negative selection but evidence of positive selection for a few sites in adjacent regions. A phylogenetic analysis of 61 Type III mod genes revealed clustering of these H.influenzae mod alleles with mod genes from pathogenic Neisseriae and, based on sequence analysis, horizontal transfer of the mod-res complex between these species. Neisserial mod alleles also contained a hypervariable region and all mod alleles exhibited variability in the repeat tract. We propose that this hypervariable region encodes the target recognition domain (TRD) of the Mod protein and that variability results in alterations to the recognition sequence of this R-M system. We argue that the high allelic diversity and phase variable nature of this R-M system have arisen due to selective pressures exerted by diversity in bacteriophage populations but also have implications for other fitness attributes of these bacterial species.
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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 | 0.000 |
| 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".