<i>In vivo</i> selection for <i>Leishmania donovani</i> miniexon genes that increase virulence in <i>Leishmania major</i><sup>†</sup>
Bibliographic record
Abstract
Different species of Leishmania are responsible for the diverse pathologies associated with leishmaniasis including Leishmania donovani which results in fatal visceral infection and Leishmania major which causes non-fatal cutaneous infection. In an attempt to identify genotypic differences between these related Old World Leishmania species which contribute to their distinct phenotypic characteristics, we have introduced a L. donovani cosmid library into L. major to select for L. donovani sequences which may increase L. major virulence in BALB/c mice. Through this approach, we have identified a region of the L. donovani genome which increased virulence in both visceral and cutaneous sites and was divergent from the corresponding region of the L. major genome. When these L. donovani sequences were reintroduced into L. major, they enhanced the overall virulence of L. major, increasing its ability to survive in both visceral and cutaneous sites. The region responsible for increased infection levels was determined to be the miniexon gene array derived from chromosome 36 of L. donovani. Pulse field electrophoresis revealed that L. donovani contained miniexon gene sequences in several chromosome locations as opposed to L. major which contains miniexon gene sequences only in chromosome 2. Because of the requirement for miniexon-derived transcripts in maturation of pre-mRNAs in trypanosomatids, this observation suggests that the increased expression of miniexon genes is associated with increased virulence. As the genome sequence for Leishmania becomes available, the in vivo selection procedure described within will be useful to identify additional species-specific sequences responsible for different pathogenic phenotypes associated with Leishmania infection.
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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 | 0.001 |
| 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".