3D mapping of host-parasite-microbiome interactions reveals metabolic determinants of tissue tropism and disease tolerance in Chagas disease
Bibliographic record
Abstract
Abstract Chagas disease (CD) is a parasitic infection caused by Trypanosoma cruzi protozoa. Over 8 million people worldwide are T. cruzi -positive, 20-30% of which will develop cardiomyopathy, megaoesophagus and/or megacolon. The mechanisms leading to gastrointestinal (GI) symptom development are however poorly understood. To address this issue, we systematically characterized the spatial impact of experimental T. cruzi infection on the microbiome and metabolome across the GI tract. The largest microbiota perturbations were observed in the proximal large intestine in both acute and chronic disease, with chronic-stage effects also observed in the cecum. Strikingly, metabolomic impact of acute-to-chronic stage transition differed depending on the organ, with persistent large-scale effects of infection primarily in the oesophagus and large intestine, providing a potential mechanism for GI pathology tropism in CD. Infection particularly affected acylcarnitine and lipid metabolism. Building on these observations, treatment of infected mice with carnitine-supplemented drinking water prevented acute-stage mortality with no changes in parasite burden. Overall, these results identified a new mechanism of disease tolerance in CD, with potential for the development of new therapeutic regimens. More broadly, these results highlight the potential of spatially-resolved metabolomic approaches to provide insight into disease pathogenesis, with translational applications for infectious disease drug development.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".