New potential eukaryotic substrates of the mycobacterial protein tyrosine phosphatase PtpA: hints of a bacterial modulation of macrophage bioenergetics state
Bibliographic record
Abstract
The bacterial protein tyrosine phosphatase PtpA is a key virulence factor released by Mycobacterium tuberculosis in the cytosol of infected macrophages. So far only two unrelated macrophage components (VPS33B, GSK3α) have been identified as PtpA substrates. As tyrosine phosphatases are capable of using multiple substrates, we developed an improved methodology to pull down novel PtpA substrates from an enriched P-Y macrophage extract using the mutant PtpA D126A. This methodology reduced non-specific protein interactions allowing the identification of four novel putative PtpA substrates by MALDI-TOF-MS and nano LC-MS: three mitochondrial proteins - the trifunctional enzyme (TFP), the ATP synthase, and the sulfide quinone oxidoreductase - and the cytosolic 6-phosphofructokinase. All these proteins play a relevant role in cell energy metabolism. Using surface plasmon resonance, PtpA was found to bind immunopurified human TFP through its catalytic site since TFP-PtpA association was inhibited by a specific phosphatase inhibitor. Moreover, PtpA wt was capable of dephosphorylating immunopurified human TFP in vitro supporting that TFP may be a bona fide PtpA susbtrate. Overall, these results suggest a novel scenario where PtpA-mediated dephosphorylation may affect pathways involved in cell energy metabolism, particularly the beta oxidation of fatty acids through modulation of TFP activity and/or cell distribution.
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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".