A systems biology pipeline identifies regulatory networks for stem cell engineering

• Main Authors: Kinney, Melissa A. (Author), Vo, Linda T. (Author), Frame, Jenna M. (Author), Barragan, Jessica (Author), Conway, Ashlee J. (Author), Li, Shuai (Author), Wong, Kwok-Kin (Author), Collins, James J. (Author), Cahan, Patrick (Author), North, Trista E. (Author), Lauffenburger, Douglas A (Author), Daley, George Q. (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Broad Institute of MIT and Harvard (Contributor), Harvard University- (Contributor)
• Format: Article
• Language: English
• Published: Springer Science and Business Media LLC, 2020-06-22T19:47:30Z.
• Subjects: Article
• Online Access: Get fulltext

 A major challenge for stem cell engineering is achieving a holistic understanding of the molecular networks and biological processes governing cell differentiation. To address this challenge, we describe a computational approach that combines gene expression analysis, previous knowledge from proteomic pathway informatics and cell signaling models to delineate key transitional states of differentiating cells at high resolution. Our network models connect sparse gene signatures with corresponding, yet disparate, biological processes to uncover molecular mechanisms governing cell fate transitions. This approach builds on our earlier CellNet and recent trajectory-defining algorithms, as illustrated by our analysis of hematopoietic specification along the erythroid lineage, which reveals a role for the EGF receptor family member, ErbB4, as an important mediator of blood development. We experimentally validate this prediction and perturb the pathway to improve erythroid maturation from human pluripotent stem cells. These results exploit an integrative systems perspective to identify new regulatory processes and nodes useful in cell engineering.