Human glial müller and umbilical vein endothelial cell coculture as an in vitro model to investigate retinal oxidative damage. A morphological and molecular assessment.
Gloria AstolfiCarmen CiavarellaSabrina ValenteChiara CosloviDanilo IannettaLuigi FontanaGianandrea PasquinelliPiera VersuraPublished in: Microscopy research and technique (2022)
The aim of this study was to optimize a coculture in vitro model established between the human Müller glial cells and human umbilical vein endothelial cells, mimicking the inner blood-retinal barrier, and to explore its resistance to damage induced by oxidative stress. A spontaneously immortalized human Müller cell line MIO-M1 and human umbilical vein endothelial cells (HUVEC) were plated together at a density ratio 1:1 and maintained up to the 8th passage (p8). The MIO-M1/HUVECs p1 through p8 were treated with increasing concentrations (range 200-800 μM) of H 2 O 2 to evaluate oxidative stress induced damage and comparing data with single cell cultures. The following features were assayed p1 through p8: doubling time maintenance, cell viability using MTS assay, ultrastructure of cell-cell contacts, immunofluorescence for Vimentin and GFAP, molecular biology (q-PCR) for GFAP and CD31 mRNA. MIO-M1/HUVECs cocultures maintained distinct cell cytotype up to p8 as shown by flow cytometry analysis, without evidence of cross activation, displaying cell-cell tight junctions mimicking those found in human retina, only acquiring a slight resistance to oxidative stress induction over the passages. This MIO-M1/HUVECs coculture represents a simple, reproducible and affordable model for in vitro studies on oxidative stress-induced retinal damages.
Keyphrases
- endothelial cells
- single cell
- oxidative stress
- cell therapy
- high glucose
- rna seq
- diabetic retinopathy
- induced apoptosis
- optical coherence tomography
- induced pluripotent stem cells
- pluripotent stem cells
- stem cells
- single molecule
- blood brain barrier
- signaling pathway
- machine learning
- ischemia reperfusion injury
- spinal cord
- cell death
- deep learning
- heat stress
- case control