How wonderful would it be if you could deposit your skin cells at a medical facility and get an organ you need within weeks, ready to be transplanted? For decades, scientists have relentlessly worked to recapitulate functionally and physiologically relevant human organs in the lab. Some approaches rely on engineering an unfeasible number of genes in cells or on external cues like growth factors and mechanical signals. But these organs are far from overcoming the barriers of complexity, reproducibility, and time sensitivity, and are thus not ready to be applied in the real world.
In an episode of Science Rehashed, McGowan Institute for Regenerative Medicine affiliated faculty member Mo Ebrahimkhani, MD, Associate Professor in the Department of Pathology, School of Medicine, University of Pittsburgh, and a member of the Division of Experimental Pathology and the Pittsburgh Liver Research Center, discusses with the podcast’s hosts Mehdi Jorfi and Shen Ning, how his team used a machine-learning algorithm (called CellNet) to engineer genetic nodes in the stem cells, resulting in the generation of human liver organoids in less than three weeks. Importantly, these organoids were able to capture the complexity of a mature liver.
In the Laboratory for Synthetic Biology and Regenerative Medicine, Dr. Ebrahimkhani’s team of researchers combines systems and synthetic biology-based approaches to program development of induced pluripotent stem cells across the developmental trajectories and towards human designer liver organoids and hematopoietic niches. This approach will open novel opportunities for next generation genomically engineered human tissues, personalized disease modeling and more effective regenerative therapies. His vision is to advance regenerative medicine through integrating systems and synthetic biology.