Pharmacological inhibition of astrocytic transglutaminase 2 facilitates the expression of a neurosupportive astrocyte reactive phenotype in association with increased histone acetylation
Bibliographic record
Abstract
Abstract Astrocytes play critical roles in supporting structural and metabolic homeostasis in the central nervous system (CNS). CNS injury leads to the development of a range of reactive phenotypes in astrocytes whose molecular determinants are poorly understood. Finding ways to modulate astrocytic injury responses and leverage a pro-recovery phenotype holds promise in treating CNS injury. Recently, it has been demonstrated that ablation of astrocytic transglutaminase 2 (TG2) modulates the phenotype of reactive astrocytes in a way that improves neuronal injury outcomes both in vitro and in vivo . In an in vivo mouse model, pharmacological inhibition of TG2 with the irreversible inhibitor VA4 phenocopies the neurosupportive effects of TG2 deletion in astrocytes. In this study, we provide insights into the mechanisms by which TG2 deletion or inhibition result in a more neurosupportive astrocytic phenotype. Using a neuron-astrocyte co-culture model, we show that VA4 treatment improves the ability of astrocytes to support neurite outgrowth on an injury-relevant matrix. To better understand how pharmacologically altering TG2 affects its ability to regulate reactive astrocyte phenotypes, we assessed how VA4 inhibition impacts TG2’s interaction with Zbtb7a, a transcription factor we have previously identified as a functionally relevant TG2 nuclear interactor. The results of these studies demonstrate that VA4 significantly decreases the interaction of TG2 and Zbtb7a. TG2’s interactions with Zbtb7a, as well as a wide range of other transcription factors and chromatin regulatory proteins, suggest that TG2 may act as an epigenetic regulator to modulate gene expression. To begin to understand if TG2-mediated epigenetic modification may impact astrocytic phenotypes in our models, we interrogated the effect of TG2 deletion and VA4 treatment on histone acetylation and found significantly greater acetylation in both experimental groups. Consistent with these findings, previous RNA-sequencing and our present proteomic analysis also supported a predominant transcriptionally suppressive role of TG2 in astrocytes. Our proteomic data additionally unveiled pronounced changes in lipid and antioxidant metabolism in astrocytes with TG2 deletion or inhibition, which likely contribute to the enhanced neurosupportive function of these astrocytes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".