Phenotypic rescue of<i>Chlamydia trachomatis</i>growth in IFN-γ treated mouse cells by irradiated<i>Chlamydia muridarum</i>
Bibliographic record
Abstract
Chlamydia trachomatis and C. muridarum, human and mouse pathogens, respectively, share more than 99% of open reading frames (ORFs) but differ in a cytotoxin locus. Presence or absence of cytotoxin gene(s) in these strains correlates with their ability to grow in IFN-gamma treated mouse cells. Growth of toxin-positive C. muridarum is not affected in IFN-gamma treated cells, whereas growth of toxin-negative C. trachomatis is inhibited. We previously reported that this difference in IFN-gamma sensitivity is important to the in vivo infection tropism of these pathogens. Here we describe a phenotypic rescue assay that utilizes C. muridarum gamma irradiated killed elementary bodies (iEB) to rescue C. trachomatis infectivity in IFN-gamma treated mouse cells. Rescue by iEB was temporal, maximal early post infection, directly related to multiplicity of iEB infection, and was independent of de novo chlamydial transcription. Lastly, C. muridarum iEB vacuoles and C. trachomatis inclusions were not fusogenic, suggesting the factor(s) responsible for rescue was secreted or exposed to the cytosol where it inactivated IFN-gamma induced effectors. Chlamydial phenotypic rescue may have broader utility for the study of other EB associated virulence factors that function early in the interaction of chlamydiae with host cells.
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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 | 0.000 |
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".