<i>Leishmania donovani</i> 's protein tyrosine phosphatases interact with <scp>DUF</scp> 21 and respond to environmental magnesium
Bibliographic record
Abstract
Leishmania donovani is a causative agent of the neglected tropical disease known as visceral leishmaniasis or Kala Azar. This disease is lethal when untreated, with more than 90 000 cases annually. Little is known about magnesium regulation in these parasites despite magnesium being the second most abundant intracellular cation and universally required for normal cell function. L. donovani contains two protein tyrosine phosphatase (PTP) proteins (PTP1 and PTP2) and a DUF21 protein (domain of unknown function 21), which are respectively homologous to mammalian PRL [phosphatases of regenerating liver; also known as protein tyrosine phosphatase type IVA (PTP4A)] and mammalian transmembrane protein CNNM (cyclin M family). In mammalian cells, the PRL and CNNM multiprotein complex has been shown to sense and modulate intracellular magnesium levels. Herein, we revealed that L. donovani PTP1 and DUF21 can also form a specific protein complex. Using CRISPR-Cas9 gene editing, four L. donovani knockouts, LdΔPTP1, LdΔPTP2, a double knockout termed LdΔPTP1/2, and LdΔDUF21 have been generated. Magnesium-dependent growth curves demonstrated that the LdΔPTP1/2 mutant could not survive in low magnesium and had a reduced level of survival in infected macrophages. In contrast, LdΔDUF21 is sensitive to high levels of magnesium and has an increased level of intracellular magnesium and an increased survival in macrophages compared to wild-type L. donovani. Taken together, these observations provide evidence that, similar to the PRL and CNNM proteins in mammalian cells, PTP and DUF21 homologs in L. donovani have the ability to complex and respond to environmental changes in magnesium.
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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 | 0.001 |
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".