Airway Delivery of Soluble Mycobacterial Antigens Restores Protective Mucosal Immunity by Single Intramuscular Plasmid DNA Tuberculosis Vaccination: Role of Proinflammatory Signals in the Lung
Bibliographic record
Abstract
Protection by parenteral immunization with plasmid DNA vaccines against pulmonary tuberculosis (TB) is very modest. In this study, we have investigated the underlying mechanisms for the poor mucosal protective efficacy and the avenues and mechanisms to improve the efficacy of a single i.m. immunization with a monogenic plasmid DNA TB vaccine in a murine model. We show that i.m. DNA immunization fails to elicit accumulation of Ag-specific T cells in the airway lumen despite robust T cell responses in the spleen. Such systemically activated T cells cannot be rapidly mobilized into the airway lumen upon Mycobacterium tuberculosis exposure. However, airway deposition of low doses of soluble mycobacterial Ags in previously immunized mice effectively mobilizes the systemically activated T cells into the airway lumen. A fraction of such airway luminal T cells can persist in the airway lumen, undergo quick, robust expansion and activation and provide marked immune protection upon airway M. tuberculosis exposure. Airway mucosal deposition of soluble mycobacterial Ags was found to create a tissue microenvironment rich in proinflammatory molecules including chemokines and hence conducive to T cell recruitment. Thus, in vivo neutralization of MIP-1alpha or IFN-inducible protein-10 markedly inhibited the accumulation of Ag-specific T cells in the airway lumen. Our data suggest that immunoprotective efficacy on the mucosal surface by i.m. plasmid DNA immunization could be substantially improved by simple mucosal soluble Ag inoculation and restoration of mucosal luminal T cells. Our study holds implication for the future design of DNA vaccination strategies against intracellular infections.
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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 | 0.001 | 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".