Identification of <i>Leishmania‐</i> specific protein phosphorylation sites by LC‐ESI‐MS/MS and comparative genomics analyses
Bibliographic record
Abstract
Human pathogenic protozoa of the genus Leishmania undergo various developmental transitions during the infectious cycle that are triggered by changes in the host environment. How these parasites sense, transduce, and respond to these signals is only poorly understood. Here we used phosphoproteomic approaches to monitor signaling events in L. donovani axenic amastigotes, which may be important for intracellular parasite survival. LC-ESI-MS/MS analysis of IMAC-enriched phosphoprotein extracts identified 445 putative phosphoproteins in two independent biological experiments. Functional enrichment analysis allowed us to gain insight into parasite pathways that are regulated by protein phosphorylation and revealed significant enrichment in our data set of proteins whose biological functions are associated with protein turn-over, stress response, and signal transduction. LC-ESI-MS/MS analysis of TiO(2)-enriched phosphopeptides confirmed these results and identified 157 unique phosphopeptides covering 181 unique phosphorylation sites in 126 distinct proteins. Investigation of phosphorylation site conservation across related trypanosomatids and higher eukaryotes by multiple sequence alignment and cluster analysis revealed L. donovani-specific phosphoresidues in highly conserved proteins that share significant sequence homology to orthologs of the human host. These unique phosphorylation sites reveal important differences between host and parasite biology and post-translational protein regulation, which may be exploited for the design of novel anti-parasitic interventions.
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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".