Isolation and RNA Extraction of Neurons, Macrophages and Microglia from Larval Zebrafish Brains
Bibliographic record
Abstract
To gain a detailed understanding of the role of different CNS cells during development or the establishment and progression of brain pathologies, it is important to isolate these cells without changing their gene expression profile. The zebrafish model provides a large number of transgenic fish lines in which specific cell types are labelled; for example neurons in the NBT:DsRed line or macrophages/microglia in the mpeg1:eGFP line. Furthermore, antibodies have been developed to stain specific cells, such as microglia with the 4C4 antibody. Here, we describe the isolation of neurons, macrophages and microglia from larval zebrafish brains. Central to this protocol is the avoidance of an enzymatic tissue digestion at 37 °C, which could modify cellular profiles. Instead a mechanical system of tissue homogenization at 4 °C is used. This protocol entails homogenization of brains into cell suspension, their immuno-staining and the isolation of neurons, macrophages and microglia by FACS. Afterwards, we extracted RNA from those cells and evaluated their quality/quantity. We managed to obtain RNA of high quality (RNA Integrity Number (RIN) > 7) to perform qPCR on macrophages/microglia and neurons, and transcriptomic analysis on microglia. This approach enables a better characterization of these cells, as well as a clearer understanding about their role in development and pathologies.
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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".