A porcine ex vivo lung perfusion model to investigate bacterial pathogenesis
Bibliographic record
Abstract
ABSTRACT The use of animal infection models is essential to understand microbial pathogenesis and to develop and test treatments. Insects, and 2D and 3D tissue models are increasingly being used as surrogate for mammalian models. However, there are concerns whether these models recapitulate the complexity of host-pathogen interactions. Here, we developed the ex vivo lung perfusion (EVLP) model of infection using porcine lungs to investigate Klebsiella pneumoniae -triggered pneumonia as model of respiratory infections. The porcine EVLP model recapitulates features of K. pneumoniae -induced pneumonia lung injury. This model is also useful to assess the pathogenic potential of K. pneumoniae as we observed that the attenuated Klebsiella capsule mutant strain caused less pathological tissue damage with a concomitant decrease in the bacterial burden compare to lungs infected with the wild type. The porcine EVLP model allows assessment of inflammatory responses following infection; similar to the mouse pneumonia model, we observed an increase of il-10 in the lungs infected with the wild type and an increase of ifn-γ in lungs infected with the capsule mutant. This model also allows monitoring phenotypes at the single-cell level. Wild-type K. pneumoniae skews macrophages towards an M2-like state. In vitro experiments probing pig bone marrow-derived macrophages uncovered the role of the M2 transcriptional factor STAT6, and that Klebsiella -induced il10 expression is controlled by p38 and ERK. Klebsiella -induced macrophage polarization is dependent on the capsule. Altogether, this study support the utility of the EVLP model using pig lungs as platform to investigate the infection biology of respiratory pathogens. IMPORTANCE The implementation of infection models that approximate human disease is essential to understand infections and for testing new therapies before they enter into clinical stages. Rodents are used in most of pre-clinical studies, although the differences between mouse and man have fuelled the conclusion that murine studies are unreliable predictors of human outcomes. Here, we have developed a whole lung porcine model of infection using the established ex vivo lung perfusion (EVLP) system established to re-condition human lungs for transplant. As a proof-of-principle, we provide evidence demonstrating that infection of the porcine EVLP with the human pathogen K. pneumoniae recapitulates the known features of Klebsiella -triggered pneumonia. Moreover, our data revealed the porcine EVLP model is useful to reveal features of the virulence of K. pneumoniae including the manipulation of immune cells. Altogether, this study supports the utility of the EVLP model using pig lungs as surrogate host for assessing respiratory infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".