Title: Single cell profiling to define biomarkers of photoreceptor dysfunction after gene editing within PCS-derived organoids
Legend: A. tSNE plot of edited and non-edited cells colored by cluster. Cell types annotated for a cluster via gene marker enrichment are shown. B. tSNE plot of cells positive and negative for Chr14_safe (safe targeting region); positive and negative for RDH12 (involved in retinoid recycling and visual cycle); and untransduced cells. Colors indicate different cells based on transduction status. C. Subnetworks for photoreceptor cells showing shared edges between all networks in yellow and differential edges in blue.
Citation: Sunnie Grace McCalla, Katie Mueller, Matt Stone, Alireza Fotuhi Siahpirani, Junha Shin, Bikash Pattnaik, Divya Sinha, Ben Steyer, Elizabeth Capowski, Pawan Shahi, Amr Abdeen, Shivani Saxena, Rupa Sridharan, Melissa Skala, David Gamm, Krishanu Saha, Sushmita Roy. In process.
Abstract: Genome editors make targeted changes in the genome and hold great promise in both basic and translational research. Unfortunately, they often produce unwanted adverse effects, including genotoxicity, immune response, and reductions in cellular function. Therefore, screening for adverse events is essential for the development of safe genome editing therapies. Here we are developing a generalizable and scalable approach to define biomarkers for adverse events after delivery of a genome editor. Our strategy uses single-cell transcriptomic profiling (scRNA-seq) and regulatory network-based methods to analyze single-cell data. The inferred gene regulatory networks can be used to develop a small (~50) set of biomarkers for adverse events within functional cells. Proof-of-concept studies will focus on the retina, specifically on rod and cone photoreceptors (PR) within 3D optic vesicle (OV) organoids derived from human pluripotent stem cells (PSCs). The creation of this dataset and validation of this approach will leverage these bioengineering technologies toward the development of safer genome editing therapeutics. By tackling a 3D, heterogeneous organoid culture, our approach will extend to more complex cultures. Thus, the impact of this work could be broad, with the potential to advance the development of genome editors administered to any tissue.
About the Lab: The Saha Lab is affiliated with several multi-disciplinary centers including the Waisman Center, Wisconsin Institute for Discovery and the Stem Cell and Regenerative Medicine Center at UW-Madison. Our research dedicated to using human stem cells together with emerging engineering methods in material science and synthetic biology to make smarter therapeutics, model human disease, and advance personalized medicine. As a part of our effort to develop new prognosis and diagnosis tools together with Audra Sterling, Jan Greenberg and Marsha Mailick of the Waisman Center, we investigate methods that can improve our understanding of the genotype-phenotype correlation between various genes and the outcomes such as linguistic and cognitive phenotypes.