A systems biology pipeline identifies regulatory networks for stem cell engineering.
Melissa A KinneyLinda T VoJenna M FrameJessica BarraganAshlee J ConwayShuai LiKwok-Kin WongJames J CollinsPatrick CahanTrista E NorthDouglas A LauffenburgerGeorge Q DaleyPublished in: Nature biotechnology (2019)
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.
Keyphrases
- cell fate
- stem cells
- pluripotent stem cells
- genome wide
- single cell
- cell therapy
- high resolution
- genome wide identification
- transcription factor
- endothelial cells
- copy number
- induced apoptosis
- squamous cell carcinoma
- growth factor
- bone marrow
- gene expression
- mass spectrometry
- magnetic resonance
- oxidative stress
- artificial intelligence
- radiation therapy
- cell proliferation
- induced pluripotent stem cells
- sentinel lymph node
- neural network
- early stage