Extracellular Histones as Exosome Membrane Proteins Regulated by Cell Stress
Bibliographic record
Abstract
Histones are conserved nuclear proteins that function as part of the nucleosome in the regulation of chromatin structure and gene expression. Interestingly, extracellular histones populate biofluids from healthy individuals, and when elevated, may contribute to various acute and chronic diseases. It is generally assumed that most extracellular histones exist as nucleosomes, as components of extracellular chromatin. We analysed cell culture models under normal and stressed conditions to identify pathways of histone secretion. We report that core and linker histones localize to extracellular vesicles (EVs) and are secreted via the multivesicular body/exosome pathway. Upregulation of EV histone secretion occurs in response to cellular stress, with enhanced vesicle secretion and a shift towards a population of smaller EVs. Most histones were membrane associated with the outer surface of EVs. Degradation of EV-DNA did not impact significantly on EV-histone association. Individual histones and histone octamers bound strongly to liposomes and EVs, but nucleosomes did not, showing histones do not require DNA for EV binding. Histones colocalized to tetraspanin positive EVs but using genetic or pharmacological intervention, we found that all known pathways of exosome biogenesis acted positively on histone secretion. Inhibition of autophagy and lysosomal degradation had a strong positive effect on EV histone release. Unexpectedly, EV-associated histones lacked the extensive post-translational modification of their nuclear counterparts, suggesting loss of PTMs may be involved in their trafficking or secretion. Our data does not support a significant role for EV-histones existing as nucleosomes. We show for the first time that histones are secreted from cells as membrane proteins via EVs/exosomes. This fundamental discovery provides support for further investigation of the biological activity of exosome associated histones and their role in disease.
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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".