Creation of an in-vitro¬ Co-culture Model of Microglia and Retinal Pigment Epithelium Cells for Investigating the Innate Immune Mechanisms of the Retina
Bibliographic record
Abstract
Background: The immune mechanisms of the retina in response to gene therapy have been previously understudied due to assumptions of ocular immune privilege. Ocular immune privilege is the concept that there is a tolerance or reduced immune response to antigen exposure in the eye. With the recent FDA and Health Canada approvals of the first ocular gene therapy, Luxturna, there has been a resurgence of interest in viral vector-based gene therapies for treating of ocular pathologies. Inherited retinal dystrophies (IRDs), in particular, of the outer retina may be treated through masking for the loss of function of the mutated gene with the introduction of the Wild Type (WT) copy. In treatment for IRDs such as choroideremia, adeno-associated virus serotype 2 (AAV-2) viral vector is delivered to the inner retina through a sub-retinal injection with the intent of targeting the retinal pigment epithelium (RPE) cells. Recent studies and clinical trials have reported poor outcomes as a result of this procedure for WT gene delivery which included inflammation causing unwanted damage to ocular tissues. Purpose: The aim of this study was to create and test the immunological activity in an in vitro co-culture model using induced pluripotent stem cell (iPSC) derived RPE cells and SV-40 immortalized microglia to model interactions of two resident immune cells found in the retina. I hypothesize that the model will respond to treatment with pro-inflammatory master regulators IL-1β and TNF-α in a dose dependent matter including the secretion of pro-inflammatory cytokines. Methods: iPSC RPE cells were grown on cell culture plates until the demonstration of pigmentation, polarization, polygonal morphology, and markers characteristic of RPE. SV-40 microglia cells were grown on permeable supports until mature. The cell types were combined by moving the permeable inserts into the cell culture plates with iPSC RPE cells to form the co-culture model. The model was treated with a series of pro-inflammatory stimulants including IL-1β, TNF-α and Poly(I:C) and inflammatory response was measured using an enzyme-linked immunosorbent assay (ELISA) and RT-qPCR to quantify secreted pro-inflammatory cytokines IL-6, IL-8 and CCL-2. Medium was sampled for ELISA analysis across 5 timepoints: at the time of treatment, 3 hours, 24 hours, 72 hours and 168 hours post treatment. Results: Techniques were established in this study which increased the survival and maintenance of the mature monolayer of the RPE cells in both the presence and absence of microglial cells. These improvements were observed through visual inspection of cultured RPE cells using an EVOS cell Imaging System with images captured at 10x magnification. Upon testing the co-cultured RPE and microglia model with pro-inflammatory stimuli and using an ELISA assay and RT-qPCR to measure the secretion of pro-inflammatory cytokines (IL-6, IL-8 and CCL-2), no statistically significant differences were found between the untreated controls and pro-inflammatory treatments at each time point. Levels of IL-6, IL-8 and CCL-2 increased across timepoints, although treatment at all levels did not yield significant differences. Conclusions: The model and alterations to RPE growth established in this study will aid in future iterations of study using this model. Further testing of the immunological features of this proposed model is required in order to establish whether or not it may provide insight into the immune mechanisms of the retina. It may be advisable to use co-stimulatory treatments or other pro-inflammatory stimulus to further test the immunological capabilities of this system in vitro.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".