Application of CRISPR/Cas9 editing and digital droplet PCR in human iPSCs to generate novel knock-in reporter lines to visualize dopaminergic neurons
Bibliographic record
Abstract
Human induced pluripotent stem cells (hiPSCs) have become indispensable for disease modelling. They are an important resource to access patient cells harbouring disease-causing mutations. Derivation of midbrain dopaminergic (DAergic) neurons from hiPSCs of PD patients represents the only option to model physiological processes in a cell type that is not otherwise accessible from human patients. However, differentiation does not produce a homogenous population of DA neurons and contaminant cell types may interfere with the readout of the in vitro system. Here, we use CRISPR/Cas9 to generate novel knock-in reporter lines for DA neurons, engineered with an endogenous fluorescent tyrosine hydroxylase - enhanced green fluorescent protein (TH-eGFP) reporter. We present a reproducible knock-in strategy combined with a highly specific homologous directed repair (HDR) screening approach using digital droplet PCR (ddPCR). The knock-in cell lines that we created show a functioning fluorescent reporter system for DA neurons that are identifiable by flow cytometry.
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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".