<i>Pseudomonas aeruginosa</i> supports the survival of <i>Prevotella melaninogenica</i> in a cystic fibrosis lung polymicrobial community through metabolic cross-feeding
Bibliographic record
Abstract
Abstract Cystic fibrosis (CF) is a multi-organ genetic disorder that affects more than 100,000 individuals worldwide. Chronic respiratory infections are among the hallmark complications associated with CF lung disease, and these infections are often due to polymicrobial communities that colonize the airways of persons with CF (pwCF). Such infections are a significant cause of morbidity and mortality, with studies indicating that pwCF who are co-infected with more than one organism experience more frequent pulmonary exacerbations, leading to a faster decline in lung function. Previous work established an in vitro CF-relevant polymicrobial community model composed of P. aeruginosa , S. aureus , S. sanguinis , and P. melaninogenica . P. melaninogenica cannot survive in monoculture in this model. In this study, we leverage this model to investigate the interactions between P. aeruginosa and P. melaninogenica , allowing us to understand the mechanisms by which the two microbes interact to support the growth of P. melaninogenica specifically in the context of the polymicrobial community. We demonstrate a cross-feeding mechanism whereby P. melaninogenica metabolizes mucin into short-chain fatty acids that are in turn utilized by P. aeruginosa and converted into metabolites (succinate, acetate) that are cross-fed to P. melaninogenica , supporting the survival of this anaerobe in the CF lung-relevant model. Importance Polymicrobial interactions impact disease outcomes in pwCF who suffer from chronic respiratory infections. Previous work established a CF-relevant polymicrobial community model that allows experimental probing of these microbial interactions to achieve a better understanding of the factors that govern the mechanisms by which CF lung microbes influence each other. In this study, we investigate the interaction between P. aeruginosa and P. melaninogenica , which are two highly prevalent and abundant CF lung microbes. We uncover a cross-feeding mechanism that requires the metabolism of mucin by P. melaninogenica to generate short-chain fatty acids that are cross-fed to P. aeruginosa , and into metabolized into metabolites which are then cross-fed back to P. melaninogenica to support the growth of this anaerobe.
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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 | 0.001 |
| 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".