Abstract
Purpose :
The shortage of donors is the principal handicap in the treatment of corneal endothelium diseases. In addition, expansion of corneal endothelial cells (CEC) is difficult due to its low mitotic activity. A possible solution is the use of stem cells as an extraocular-tissue source. Nevertheless, there is none successful protocol for differentiating stem cells towards CEC. Our aim is to differentiate stem cells by overexpression of key transcriptional factors.
Methods :
To identify transcriptional factors CEC-specific, we already implemented different bioinformatical algorithms. Using data from GEO/NCBI, differential expression between a pull of non-CEC tissue and CEC tissue data was calculated. With the Top30 TFs differential expressed, we performed Co-expression and Network Interaction Analysis (CNIA) using public platforms (Metascape and STRING). A Gen Set Enrichment Analysis (GSEA) was conducted in R environment to identify enriched pathways. For experimental model, stem cell lines were acquired from ATCC and cultivated following recommendation’s supplier. sgRNA were designed for each TF in GPP web portal from Broad Institute. sgRNA were cloned into PB-UniSAM plasmid (Addgene) and transfected to stem cells with GeneXPlus reagent (ATCC). Primers for qPCR were designed in BlastPrimer tool/NCBI.
Results :
445 samples, 136 tissues represented and 1,408 TFs annotated were used for differential expression. Four TFs were selected after literature curation (ERG, ZFHX4, POUF6F2 and PITX2) and four were identified with CNIA (LMX1B, TFAP2B, MEIS2, and YY1), Subsequent GSEA showed pathways positive associated to TFs, such as “rhodopsin pathway” (q-value<0.001), and negative correlation association, for instance “regulation of mitotic cell cycle” (q-value<0.001). We will show the results of cells exposed to vectors expressing sgRNA’s directed to promotor of TFs identified in order to modified its basal expression. Evidence of characterization of experimental model and assessment of CEC-specific markers (TJP1 and Na/K-ATPse pump) by qPCR will be presented.
Conclusions :
Bioinformatic algorithms represent valuable tools for prediction of tissue-specific TF since can save time and resources. Using our computational approaches, we have achieved to identify TF as potential key masters in corneal endothelial cell fate. This is the first project that tries to differentiate stem cells towards CEC by guided genetic induction.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.