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Filipe A Muhale, Aram Asatryan, Jessica Heap, Marie-Audrey Ines Kautzmann, Nicolas Guillermo Bazan; Single human retinal pigmented epithelial cells (hRPE) transcriptome analysis reveals upregulation of a subset of autophagy-related genes in response to uncompensated oxidative stress (UOS). Invest. Ophthalmol. Vis. Sci. 2017;58(8):5261.
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© ARVO (1962-2015); The Authors (2016-present)
To date there is a lack of understanding at the single cell level of the differential expression of genes regulating autophagy following insults to RPE cells. This study was designed to determine if following UOS, changes in the transcriptome for autophagy-related genes occurs as an homogenous group or subpopulations of individual cells.
hRPE cells were grown and maintained in MEM medium supplemented with 10% FBS, 5 % NCS, NEAA and incubated at 37°C with a constant supply of 5% CO2. hRPE cells were subjected to four hours UOS (600μM H2O2/10ng/ml TNFα) then trypsinized and loaded on a C1 chip (Fluidigm) for separation in automated C1 system utilizing microfluidics technologies. Cells were lysed in micro-chambers and pre-amplified with human autophagy gene-panel (34 genes and controls). Pre-amplified samples were transferred into Biomark HD 96x96 chip for a RT-qPCR amplification. Results were analyzed using Fluidigm Real-Time PCR analysis software.
Heatmap analysis shows a first cluster of hRPE cells characterized by high expression genes. The remaining individual cells cluster into two major groups displaying differential gene expression relative to the first control cluster. Interestingly within these subpopulations most individual cells, cluster either in treated- or control-type of autophagy expression pattern. The violin plot shows most of the individual cells display a bimodal expression type for the gene panel. In these subgroups bimodal gene expression is different between controls and treatments. Differential expression of genes ATG12, ATG16, ATG9A, ATG7, SIRT1, ATG2A, ATG2B, ATG9B, MAP1LC3A, ATG5 highlights the power and potential of this novel technology.
Our study indicates that analysis of transcriptome at the single cell level for autophagy-related genes shows clear segmentation between control and UOS treated groups of cells. Therefore our approach resulted in the generation of a subpopulation of cells displaying upregulation of autophagy-related genes that provides an opportunity to define networks and molecular principles involved.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.
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