Serine Phosphorylation Marks Proteins for Degradation By the Mitochondrial Serine Protease Complex, Clpxp
Bibliographic record
Abstract
ClpXP, a serine protease located in the mitochondrial matrix, regulates mitochondrial proteostasis by degrading damaged or aggregated proteins, including respiratory chain subunits. ClpXP is a bipartite protein complex comprised of the ClpX regulatory particle that caps each end of the ClpP degradation chamber. ClpX recognizes substrates, unfolds them, and feeds them into ClpP for proteolysis. Genetic or chemical inhibition of ClpXP leads to impaired oxidative phosphorylation function and leukemic cell death in vitro and in vivo. Importantly, however, the degradation marker of human ClpXP remains elusive. Since the bacterial homologue of ClpXP recognizes phosphorylated arginine (pArg)-tagged protein for degradation, we hypothesized that human ClpXP might also recognize phosphorylated amino acids as degrons. We first investigated whether phosphorylation influences substrate degradation by ClpXP using a model substrate, α-casein. Recombinant human ClpXP preferentially degraded phosphorylated α-casein compared to dephosphorylated α-casein. To further elucidate the effects of phosphorylation, we screened a panel of phosphorylated amino acids for their ability to impede ClpXP-mediated degradation of FITC-tagged α-casein. Phosphorylated serine (pSer) and phosphorylated threonine (pThr) free amino acids, or short peptides containing pSer or pThr, inhibited α-casein degradation by ClpXP in a dose-dependent manner. In contrast, phosphorylated pArg, and phosphorylated tyrosine (pTyr), as well as free unmodified Ser or Thr, did not impact ClpXP protease activity. Next, we applied a thermal shift assay to measure the binding capabilities of pSer and pThr to ClpX. We discovered that these phosphorylated amino acids, whether free or incorporated into short peptides, successfully associated with ClpX. In contrast, their dephosphorylated counterparts did not exhibit the same binding activity. Notably, pSer did not affect enzyme activity of the related LonP1 mitochondrial matrix serine protease, thereby demonstrating the specificity of pSer for ClpXP. Extending our studies to intact cells, we analyzed a proteomic dataset of post-translational modifications in Jurkat cells with and without treatment with bortezomib (1 µM), a proteasome inhibitor that inhibits ClpXP at this concentration. Notably, a global enrichment of phosphorylation was observed for mitochondrial proteins upon bortezomib treatment. We overlaid observed phosphorylated proteins with the ClpXP interactome as determined by BioID, and identified 9 phosphorylated mitochondrial proteins that also interact with ClpXP. Of these proteins, respiratory chain II complex subunit, SDHA, was the top hit, where serine phosphorylation was increased over 4 folds. Next we determined how depletion of ClpXP affected levels of phosphorylated substrate in intact cells. Knockdown of ClpX or ClpP in OCI-AML2 cells increased levels of serine phosphorylated SDHA (pSer-SDHA). We then added recombinant ClpXP protein to mitochondrial lysates and observed selective degradation of pSer-SDHA. To determine if pSer-SDHA are damaged proteins, we partitioned mitochondria into soluble and insoluble fractions using digitonin. pSer-SDHA was enriched in the detergent-insoluble fraction. In addition, we induced mitochondrial proteolytic stress by treating OCI-AML2 cells with antimycin to increase mitochondrial ROS or through heat shock by culturing cells at 42 oC. Both antimycin and heat shock increased pSer-SDHA in the detergent-insoluble fraction, further supporting pSer marking damaged proteins. Finally, we developed small molecule pSer mimics. We showed that these compounds bound ClpX in thermal shift assays. In addition, these compounds inhibited ClpXP protease activity in cell-free enzymatic assays. In summary, ClpXP recognizes serine phosphorylation as a degradation marker for damaged mitochondrial proteins. Small molecules that inhibit ClpX could be leads for novel anti-cancer agents.
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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".