Modulation of gene expression in Leishmania drug resistant mutants as determined by targeted DNA microarrays
Bibliographic record
Abstract
In the protozoan parasite Leishmania, drug resistance can be a complex phenomenon. Several metabolic pathways and membrane transporters are implicated in the resistance phenotype. To monitor the expression of these genes, we generated custom DNA microarrays with PCR fragments corresponding to 44 genes involved with drug resistance. Transcript profiling of arsenite and antimony resistant mutants with these arrays pinpointed a number of genes overexpressed in mutants, including the ABC transporter PGPA, the glutathione biosynthesis genes gamma-glutamylcysteine synthetase (GSH1) and the glutathione synthetase (GSH2). Competitive hybridisations with total RNA derived from sensitive and methotrexate resistant cells revealed the overexpression of genes coding for dihydrofolate reductase (DHFR-TS), pteridine reductase (PTR1) and S-adenosylmethionine synthase (MAT2) and a down regulation of one gene of the folate transporter (FT) family. By labelling the DNA of sensitive and resistant parasites we could also detect several gene amplification events using DNA microarrays including the amplification of the S-adenosyl homocysteine hydrolase gene (SAHH). Alteration in gene expression detected by microarrays was validated by northern blot analysis, while Southern blots indicated that most genes overexpressed were also amplified, although other mechanisms were also present. The microarrays were useful in the study of resistant parasites to pinpoint several genes linked to drug resistance.
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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".