Supplementary Materials12035_2016_9974_MOESM1_ESM: Supplemental Figure 1. additive effect on endothelial gene expression by qPCR in either Lacosamide inhibitor astrocytes (a) or neural precursor cells (b). Baseline oxygen conditions were used a reference values for gene expression changes. Supplemental Figure 4. Gene ontology of biological processes based on up-regulated genes (FDR 0.01). Supplemental Figure 5. Gene ontology of biological processes based on down-regulated genes (FDR 0.01). Supplemental Figure 6. Analysis of the common transcription factors between serum-deprived cardiac fibroblasts and astrocytes. Of the 49 shared transcription factors (FDR 0.1), 12 were up-regulated (logFC 0) in both cell populations (a, pHyper = 0.08596) and 10 were Lacosamide inhibitor down-regulated (logFC 0) in both cell populations (b, pHyper = 0.18349). Enrichr pathway analysis using the PPI Hub Protein database of each gene list indicates that EP300 (p=0.00014 (up); p=0.0008 (down) and CREBBP (p=0.00002 (down) transcription regulatory system is common linker pathway in the both up- (b) and down-regulated (d) transcription factors. Notably, this system works to activate p53 further implicating this Rabbit Polyclonal to MPRA molecular system in the cellular plasticity observed in serum-deprived astrocytes. Supplemental Figure 7. miR-194 inhibition reduces endothelial gene expression in serum-deprived astrocytes. Endothelial gene qPCR array demonstrates significantly decreased gene expression after 48 h of serum deprivation in the presence of miR-194 inhibitor (log10 of 2?Ct) compared to vehicle only serum-deprived astrocytes. Lines represent 2-fold regulation changes. Four of eight endothelial genes were down-regulated compared to empty transfected serum deprived astrocytes (green circles). NIHMS801560-supplement-12035_2016_9974_MOESM1_ESM.docx (5.8M) GUID:?A9F87DB0-9573-4DD8-BD49-F1834DA2AEE6 12035_2016_9974_MOESM2_ESM: Supplemental Table 1 Primer sequences for qPCR NIHMS801560-supplement-12035_2016_9974_MOESM2_ESM.docx (62K) GUID:?FE93603B-B198-434B-8BC3-9CC14E58ACDE 12035_2016_9974_MOESM3_ESM. NIHMS801560-supplement-12035_2016_9974_MOESM3_ESM.pdf (298K) GUID:?469F2B1D-6A8E-490F-A162-0B981A869206 12035_2016_9974_MOESM4_ESM. NIHMS801560-supplement-12035_2016_9974_MOESM4_ESM.pdf (37K) GUID:?BF5A53D9-4811-4752-9AF1-5FE8E1AFD0F5 Abstract Astrocytes respond to a variety of CNS injuries by cellular enlargement, process outgrowth, and upregulation of extracellular matrix proteins that function to prevent expansion of the injured region. This astrocytic response, though critical to the acute injury response, results in the formation of a glial scar that inhibits neural repair. Scar forming cells (fibroblasts) in the heart can undergo mesenchymal-endothelial transition into endothelial cell fates following cardiac injury in a process dependent on p53 that can be modulated to augment cardiac repair. Here, we sought to determine whether astrocytes, as the primary scar-forming cell of the CNS, are able to undergo a similar cellular phenotypic transition and adopt endothelial cell fates. Serum deprivation of differentiated astrocytes resulted in a change in cellular morphology and upregulation of endothelial cell marker genes. In a tube formation assay, serum deprived astrocytes showed a substantial increase in vessel-like morphology that was comparable to human umbilical vein endothelial cells and dependent on p53. RNA-sequencing of serum-deprived astrocytes demonstrated an expression profile that mimicked an endothelial rather than astrocyte transcriptome and identified p53 and angiogenic pathways as specifically up-regulated. Inhibition of Lacosamide inhibitor p53 with genetic or pharmacologic strategies inhibited astrocyte-endothelial transition. Astrocyte-endothelial cell transition could also be modulated by miR-194, a microRNA downstream of p53 that affects expression of genes regulating angiogenesis. Together, these studies demonstrate that differentiated astrocytes retain a stimulus-dependent mechanism for cellular transition into an endothelial phenotype that may modulate formation of the glial scar and promote injury-induced angiogenesis. pathway analysis was performed using both up- and down-regulated gene lists [19]. For cell type enrichment analysis, expression values for different cells types were downloaded [20]. For each cell type, enrichment index was calculated log2([FPKM_one_cell_type]/[FPKM_avg_all_other_cell_types]). Top 500 cell specific genes were selected and plotted against log2 fold change from serum deprived astrocytes compared to control..