An endogenous PI3K interactome promoting astrocyte-mediated neuroprotection identifies a novel association with RNA-binding protein ZC3H14
Bibliographic record
Abstract
Astrocytes can support neuronal survival through a range of secreted signals that protect against neurotoxicity, oxidative stress, and apoptotic cascades. Thus, analyzing the effects of the astrocyte secretome may provide valuable insight into these neuroprotective mechanisms. Previously, we characterized a potent neuroprotective activity mediated by retinal astrocyte conditioned media (ACM) on retinal and cortical neurons in metabolic stress models. However, the molecular mechanism underlying this complex activity in neuronal cells has remained unclear. Here, a chemical genetics screen of kinase inhibitors revealed phosphoinositide 3-kinase (PI3K) as a central player transducing ACM-mediated neuroprotection. To identify additional proteins contributing to the protective cascade, endogenous PI3K was immunoprecipitated from neuronal cells exposed to ACM or control media, followed by MS/MS proteomic analyses. These data pointed toward a relatively small number of proteins that coimmunoprecipitated with PI3K, and surprisingly only five were regulated by the ACM signal. These hits included expected PI3K interactors, such as the platelet-derived growth factor receptor A (PDGFRA), as well as novel RNA-binding protein interactors ZC3H14 (zinc finger CCCH-type containing 14) and THOC1 (THO complex protein 1). In particular, ZC3H14 has recently emerged as an important RNA-binding protein with multiple roles in posttranscriptional regulation. In validation studies, we show that PI3K recruitment of ZC3H14 is necessary for PDGF-induced neuroprotection and that this interaction is present in primary retinal ganglion cells. Thus, we identified a novel non-cell autonomous neuroprotective signaling cascade mediated through PI3K that requires recruitment of ZC3H14 and may present a promising strategy to promote astrocyte-secreted prosurvival signals.
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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".