AI-guided miniproteins driving the production and functional endurance of pancreatic islet tissue from pluripotent stem cells.

Summary Stem cell (SC)-based replacement therapy is emerging as promising cure for diabetes. However, population-wide applicability of this approach remains constrained by the limited efficiency of current protocols in controlling the state of pluripotency and/or patient-specific propensity of SC lines to respond to morphogens and inductive factors, thereby yielding

heterogenous islet cell preparations containing variable proportions of endocrine and immature cell types. In this RC2 project we integrate knowledge from a team of Investigators with a complementary expertise to exploit the power of Artificial Intelligence (AI)-designed mini-proteins (EpiBinders) in

controlling SC ability to more efficiently differentiate into functional islet cells. This approach is based on our recent work demonstrating that EpiBinders are capable of erasing repressive histone methylation marks and activate select genes of interest, thus fostering the activation of downstream developmental programs. Building on this preliminary work, our hypothesis is that

the newly discovered regulatory function of AI-designed EpiBinders on gene expression can be harnessed to drive a more efficient differentiation of multiple SC lines into functional islet tissue. Hence our collaborative project will focus on the following specific aims: Aim 1. Develop and in- cell validate a toolbox of Al-designed mini-proteins targeting epigenetic regulators of islet cell

development and function beyond PRC2 inhibitor in multiple iPSC lines. Aim 2. Apply and validate the toolbox of EpiBinders for the regulation of islet cell development and function at specific stages of SC differentiation. Aim 3. Characterize states of differentiation, functional maturation and metabolic endurance of epigenetically manipulated SC-derived islet cells, in vitro and in vivo in

transplantation models. We anticipate that our interdisciplinary efforts will produce new knowledge and resources that will be readily shared with the scientific community, and that will advance collective efforts to broaden the future therapeutic potential of SC-based treatments by developing a radically new

approach to enhance efficiency of islet tissue derivation from SC.