Mitochondrial Fragmentation Promotes Inflammation Resolution Responses in Macrophages via Histone Lactylation
Bibliographic record
Abstract
During the inflammatory response, macrophage phenotypes can be broadly classified as pro-inflammatory/classically activated "M1", or pro-resolving/alternatively "M2" macrophages. Although the classification of macrophages is general and assumes there are distinct phenotypes, in reality macrophages exist across a spectrum and must transform from a pro-inflammatory state to a proresolving state following an inflammatory insult. To adapt to changing metabolic needs of the cell, mitochondria undergo fusion and fission, which have important implications for cell fate and function. We hypothesized that mitochondrial fission and fusion directly contribute to macrophage function during the pro-inflammatory and proresolving phases. In the present study, we find that mitochondrial length directly contributes to macrophage phenotype, primarily during the transition from a pro-inflammatory to a proresolving state. Phenocopying the elongated mitochondrial network (by disabling the fission machinery using siRNA) leads to a baseline reduction in the inflammatory marker IL-1β, but a normal inflammatory response to LPS, similar to control macrophages. In contrast, in macrophages with a phenocopied fragmented phenotype (by disabling the fusion machinery using siRNA) there is a heightened inflammatory response to LPS and increased signaling through the ATF4/c-Jun transcriptional axis compared to control macrophages. Importantly, macrophages with a fragmented mitochondrial phenotype show increased expression of proresolving mediator arginase 1 and increased phagocytic capacity. Promoting mitochondrial fragmentation caused an increase in cellular lactate, and an increase in histone lactylation which caused an increase in arginase 1 expression. These studies demonstrate that a fragmented mitochondrial phenotype is critical for the proresolving response in macrophages and specifically drive epigenetic changes via lactylation of histones following an inflammatory insult.
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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 | 0.000 | 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) | 0.000 | 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".