Identification of <i>Streptococcus pneumoniae</i> genes specifically induced in mouse lung tissues
Bibliographic record
Abstract
To identify Streptococcus pneumoniae genes expressed specifically during infections, a selection system based on the in vivo expression technology (IVET) was established. galU, which is critical for capsular polysaccharide biosynthesis, and lacZY encoding beta-galactosidase were employed as dual reporter genes to screen in-vivo-induced (ivi) genes of S. pneumoniae. The galU-deficient mutant of S. pneumoniae is incapable of utilizing galactose, thus failing to synthesize capsular polysaccharide, and therefore loses its ability to survive in the host. A promoter-trap library was constructed in S. pneumoniae, which was used to infect BALB/c mice in an intranostril model. Those strains recovered from lung tissue of mice and exhibiting a white colony phenotype on tryptic soy agar containing X-gal (5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside) were collected and identificated. A total of 15 unique sequences were obtained through in vivo screening. The ivi genes of S. pneumoniae are involved in many processes, such as colonization and adherence, energy metabolism, nutrient substance transport, transcription regulation, DNA metabolism, and cell wall synthesis. There are some hypothetical proteins whose functions are not clear. This novel IVET is a useful tool for identifying ivi genes in S. pneumoniae.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".