Genome-wide gene expression profiling analysis of Leishmania major and Leishmania infantum developmental stages reveals substantial differences between the two species
Bibliographic record
Abstract
BACKGROUND: Leishmania parasites cause a diverse spectrum of diseases in humans ranging from spontaneously healing skin lesions (e.g., L. major) to life-threatening visceral diseases (e.g., L. infantum). The high conservation in gene content and genome organization between Leishmania major and Leishmania infantum contrasts their distinct pathophysiologies, suggesting that highly regulated hierarchical and temporal changes in gene expression may be involved. RESULTS: We used a multispecies DNA oligonucleotide microarray to compare whole-genome expression patterns of promastigote (sandfly vector) and amastigote (mammalian macrophages) developmental stages between L. major and L. infantum. Seven per cent of the total L. infantum genome and 9.3% of the L. major genome were differentially expressed at the RNA level throughout development. The main variations were found in genes involved in metabolism, cellular organization and biogenesis, transport and genes encoding unknown function. Remarkably, this comparative global interspecies analysis demonstrated that only 10-12% of the differentially expressed genes were common to L. major and L. infantum. Differentially expressed genes are randomly distributed across chromosomes further supporting a posttranscriptional control, which is likely to involve a variety of 3'UTR elements. CONCLUSION: This study highlighted substantial differences in gene expression patterns between L. major and L. infantum. These important species-specific differences in stage-regulated gene expression may contribute to the disease tropism that distinguishes L. major from L. infantum.
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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) | 0.001 | 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".