A combined proteomic and transcriptomic approach to the study of stage differentiation in <b><i>Leishmania infantum</i></b>
Bibliographic record
Abstract
Protozoan parasites of the genus Leishmania are found as promastigotes in the sandfly vector and as amastigotes in mammalian macrophages. Mechanisms controlling stage-regulated gene expression in these organisms are poorly understood. Here, we applied a comprehensive approach consisting of protein prefractionation, global proteomics and targeted DNA microarray analysis to the study of stage differentiation in Leishmania. By excluding some abundant structural proteins and reducing complexity, we detected and identified numerous novel differentially expressed protein isoforms in L. infantum. Using 2-D gels, over 2200 protein isoforms were visualized in each developmental stage. Of these, 6.1% were strongly increased or appeared unique in the promastigote stage, while the relative amounts of 12.4% were increased in amastigotes. Amastigote-specific protein isoform and mRNA expression trends correlated modestly (53%), while no correlation was found for promastigote-specific spots. Even where direction of regulation was similar, fold-changes were more modest at the RNA than protein level. Many proteins were present in multiple spots, suggesting that PTM is extensive in this organism. In several cases, different isoforms appeared to be specific to different life stages. Our results suggest that post-transcriptional controls at translational and post-translational levels could play major roles in differentiation in Leishmania parasites.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".