Microarray analysis of Streptococcus pneumoniae gene expression changes to human lung epithelial cells
Bibliographic record
Abstract
Streptococcus pneumoniae infection starts from the respiratory tract where interaction with host epithelial cells occurs. To gain more insights on pneumococcal pathogenesis, an oligonucleotide (oligo)-based microarray was used to investigate gene expression changes of one serotype 3 encapsulated pathogenic S. pneumoniae strain 82 and one unencapsulated avirulent S. pneumoniae strain R6 upon exposure to human lung epithelial cells (A549) for 1 and 3 h, respectively. We observed that genes associated with many functional categories were differentially regulated in strain 82, such as genes in pathogenesis, cell envelope, transcription, translation, transport, metabolism, and unknown functions. In contrast, few genes were changed in strain R6 except for genes in ribonucleotide biosynthesis and unknown functions. Quantitative real-time PCR analysis confirmed the microarray results for most of the genes tested. To further characterize functions of the selected genes, knockout mutants were constructed in strain R6. We demonstrated that 2 genetic loci, SP_2170 (AdcB, zinc ABC transporter) and SP_0157 (hypothetical protein), were involved in adherence to A549 cells. These data suggest that divergent gene expression changes occur in S. pneumoniae pathogenic and avirulent strains during interaction with human lung epithelial cells. Some of those genes are involved in pneumococcal pathogenesis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".