High-parameter Cytometry Unmasks Microglial Cell Spatio-temporal Response Kinetics in Severe Neuroinflammatory Disease.
Bibliographic record
Abstract
Abstract Background:Differentiating infiltrating myeloid cells from resident microglia in neuroinflammatory disease is challenging, because bone marrow-derived inflammatory monocytes infiltrating the inflamed brain adopt a ‘microglia-like’ phenotype. This precludes the accurate identification of either cell type without genetic manipulation, which is important to understand their temporal contribution to disease and inform effective intervention in its pathogenesis. During West Nile virus (WNV) encephalitis, widespread neuronal infection drives substantial CNS infiltration of inflammatory monocytes, causing severe immunopathology and/or death, but the role of microglia in this remains unclear. Methods:Using high-parameter cytometry and dimensionality-reduction, we devised a simple, novel gating strategy to identify microglia and infiltrating myeloid cells under extreme inflammatory conditions. Validating our strategy we 1) blocked the entry of infiltrating myeloid populations from peripheral blood using monoclonal blocking antibodies, 2) adoptively transferred BM-derived monocytes and tracked their phenotypic changes after infiltration and 3) labelled peripheral leukocytes that infiltrate into the brain with an intravenous dye. We demonstrated that myeloid immigrants populated only the identified macrophage gates, while PLX5622 depletion reduced all 4 subsets defined by the microglial gates. Results:Using this novel gating approach, we identified four consistent microglia subsets in the homeostatic and WNV-infected brain. These were P2RY12hiCD86-, P2RY12hiCD86+, and P2RY12loCD86- P2RY12loCD86+. During infection, 2 further populations were identified as inflammatory and microglia-like macrophages, recruited from the bone marrow. Detailed kinetic analysis showed significant increases in the proportions of both P2RY12lo microglia subsets in all anatomical areas, largely at the expense of the P2RY12hiCD86- subset, with the latter undergoing compensatory proliferation, suggesting replenishment of, and differentiation from this subset in response to infection. Microglia altered their morphology early in infection, with all cells adopting temporal and regional disease-specific phenotypes. Late in disease, microglia produced IL-12, downregulated CX3CR1, F4/80 and TMEM119 and underwent apoptosis. Infiltrating macrophages expressed both TMEM119 and P2RY12 de novo, with the microglia-like subset notably exhibiting the highest proportional myeloid population death. Conclusions:Our approach enables detailed kinetic analysis of resident vs infiltrating myeloid cells in a wide range of neuroinflammatory models without non-physiological manipulation. This will more clearly inform potential therapeutic approaches that specifically modulate these cells.
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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 | 0.001 |
| 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".