Metabolite profiling of experimental cutaneous leishmaniasis lesions demonstrates significant perturbations in tissue phospholipids
Bibliographic record
Abstract
Abstract Each year 700,000 to 1.2 million new cases of cutaneous leishmaniasis (CL) are reported and yet CL remains one of thirteen diseases classified as neglected tropical diseases (NTDs). Leishmania major is one of several different species of that same genus that can cause CL. Current CL treatments are limited by adverse effects and rising resistance. Studying disease metabolism at the site of infection can lead to new drug targets. In this study, samples were collected from mice infected in the ear and footpad with L. major and analyzed by untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). Significant differences in overall metabolite profiles were noted in the ear at the site of the lesion. Interestingly, lesion-adjacent, macroscopically healthy sites also showed alterations in specific metabolites, including select phosphocholines (PCs). Host-derived PCs in the lower m/z range ( m/z 200-799) showed an increase with infection in the ear at the lesion site, while those in the higher m/z range ( m/z 800-899) were decreased with infection at the lesion site. Overall, our results expanded our understanding of the mechanisms of CL pathogenesis through the host metabolism and may lead to new curative measures against infection with Leishmania . Author summary Cutaneous leishmaniasis (CL) is one of thirteen neglected tropical diseases in the world today. It is an infectious disease with a wide distribution spanning five continents, with increasing distribution expected due to climate change. CL manifests as skin lesions and ulcers that are disabling and stigmatized. With the current treatment options being limited, studying host-pathogen metabolism can uncover mechanisms of disease pathogenesis that may lead to new curative measures against infection. In this paper we used untargeted metabolomics to address molecular-level changes occurring in vivo in experimental skin lesions of Leishmania major . Distinct global metabolic profiles were observed. Total phosphocholines (PCs) and those in the lower m/z ranges were significantly higher at the site of the skin lesion in the ear. In addition, specific PCs as well as PCs of varied m/z ranges were also affected at healthy-appearing lesion-adjacent sites, indicating that infection-induced metabolic perturbations are not restricted to the lesion site. Ultimately, these results provide essential clues to the metabolic pathways affected by CL.
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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 | 0.000 |
| 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".