Global Interactome Mapping of Mitochondrial Intermembrane Space Proteases Identifies a Novel Function for HTRA2
Bibliographic record
Abstract
A number of unique proteases localize to specific sub-compartments of the mitochondria, but the functions of these enzymes are poorly defined. Here, in vivo proximity-dependent biotinylation (BioID) is used to map the interactomes of seven proteases localized to the mitochondrial intermembrane space (IMS). In total, 802 high confidence proximity interactions with 342 unique proteins are identified. While all seven proteases co-localized with the IMS markers OPA1 and CLPB, 230 of the interacting partners are unique to just one or two protease bait proteins, highlighting the ability of BioID to differentiate unique interactomes within the confined space of the IMS. Notably, high-temperature requirement peptidase 2 (HTRA2) interacts with eight of 13 components of the mitochondrial intermembrane space bridging (MIB) complex, a multiprotein assembly essential for the maintenance of mitochondrial cristae structure. Knockdown of HTRA2 disrupts cristae in HEK 293 and OCI-AML2 cells, and leads to increased intracellular levels of the MIB subunit IMMT. Using a cell-free assay it is demonstrated that HTRA2 can degrade recombinant IMMT but not two other core MIB complex subunits, SAMM50 and CHCHD3. The IMS protease interactome thus represents a rich dataset that can be mined to uncover novel IMS protease biology.
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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".