Concurrent Group III

ISSCR 2018 Plenary and Concurrent

3 - USING A PREDICTIVE COMPUTATIONAL ALGORITHM TO ESTABLISH A UNIVERSAL TRANSCRIPTION FACTOR ENHANCED DIFFERENTIATION FRAMEWORK

6/22/2018
13:45 - 14:00

The ability of pluripotent stem cells (PSCs) to generate virtually any cell type in the body holds great promise in regenerative medicine and disease modeling. Many strategies, adapted from our understanding of developmental biology, have aided us in optimizing specific culture conditions that facilitate the differentiation of target cell types. However, in recent years, a number of studies suggested the use of transcription factors (TFs), master regulators of cell identity, to improve the yield, speed and/or specificity of differentiation. These novel TF-based strategies were discovered through empirical testing of a large number of TF combinations that have been associated with the target cell type, a very complex, laborious and inefficient process. Unfortunately, the identification of key TFs to enhance differentiation of PSCs is currently limited to specific cell lineages which have been extensively studied (e.g. neurons, blood and muscle). In spite of this, we and others have previously developed computational frameworks to accurately predict the TFs required for cell conversion into target cell types. We adopted our predictive algorithm, Mogrify, to predict TFs which will enhance the differentiation of PSCs into cells of all three germ layers. We show that co-expression of the predicted key TFs for PSC to keratinocyte differentiation gave rise to cells acquiring keratinocyte-like morphologies and expressing keratinocyte markers (K1 and K14) in half the time compared to the standard baseline differentiation method. Similarly, enhanced differentiation into cells of other germ layers using separate sets of predicted TFs yielded the desired cells in less than half the time compared to control cultures. Through this approach, we have established new enhanced differentiation protocols for a variety of lineages and cell types which were previously unreported. Accordingly, Mogrify enables the identification of key TFs that can enable cell fate conversion as well as develop enhanced differentiation protocols for the generation and enrichment of target cell types from pluripotent stem cells for potential therapeutic downstream applications.


 

Joseph Chen

Monash University, VIC, Australia

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3 - USING A PREDICTIVE COMPUTATIONAL ALGORITHM TO ESTABLISH A UNIVERSAL TRANSCRIPTION FACTOR ENHANCED DIFFERENTIATION FRAMEWORK



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