A genomic approach to understand interactions between Streptococcus pneumoniae and its bacteriophages
Bibliographic record
Abstract
BACKGROUND: Bacteriophage replication depends on bacterial proteins and inactivation of genes coding for such host factors should interfere with phage infection. To gain further insights into the interactions between S. pneumoniae and its pneumophages, we characterized S. pneumoniae mutants selected for resistance to the virulent phages SOCP or Dp-1. RESULTS: S. pneumoniae R6-SOCP(R) and R6-DP1(R) were highly resistant to the phage used for their selection and no cross-resistance between the two phages was detected. Adsorption of SOCP to R6-SOCP(R) was partly reduced whereas no difference in Dp-1 adsorption was noted on R6-DP1(R). The replication of SOCP was completely inhibited in R6-SOCP(R) while Dp-1 was severely impaired in R6-DP1(R). Genome sequencing identified 8 and 2 genes mutated in R6-SOCP(R) and R6-DP1(R), respectively. Resistance reconstruction in phage-sensitive S. pneumoniae confirmed that mutations in a GntR-type regulator, in a glycerophosphoryl phosphodiesterase and in a Mur ligase were responsible for resistance to SOCP. The three mutations were additive to increase resistance to SOCP. In contrast, resistance to Dp-1 in R6-DP1(R) resulted from mutations in a unique gene coding for a type IV restriction endonuclease. CONCLUSION: The characterization of mutations conferring resistance to pneumophages highlighted that diverse host genes are involved in the replication of phages from different families.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".