The broad long-term objective of our work is to determine the molecular mechanism of induced pluripotency. The ability to induce pluripotency in differentiated cells has revolutionized the field of stem cell biology and presents great potential for therapeutic application. However, there are many unanswered questions regarding the mechanisms that establish and maintain pluripotency, including how the various genetic, epigenetic and signaling reprogramming factors interact with transcriptional regulators to induce pluripotency. The highly interconnected and multidimensional nature of the reprogramming factors necessitates a systems biology approach, where the role of each factor is considered within the context of the entire network. A tightly integrated experimental and statistical modeling approach is proposed to predict connections among transcription factors involved in the reprogramming network. The result will provide a strong basis for mechanistic investigation of this process and information for enhancing the safety and efficiency of reprogramming methods. Specifically, the aims of this project are: 1. To generate a large data set comprised of transcriptional and pluripotency responses under a broad range of reprogramming cues;2. To use Bayesian network analysis methods to predict transcriptional control mechanisms that mediate reprogramming;and 3. To experimentally validate the computational predictions. Our exciting, integrated experimental and computational approach applies a systems biology paradigm to open questions in stem cell biology and promises to yield progress in an important problem with direct impact on the use of stem cells in regenerative medicine. Relevance Recently, the ability to reprogram adult skin cells into embryonic-like stem cells by the introduction of four genes has been discovered. This technology has the potential to revolutionize regenerative medicine, but the viral vectors used to deliver the four genes are not safe for human use. By studying the network of interactions between the four genes and other reprogramming factors, it may be possible to identify methods to reprogram cells without the use of viral vectors.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM088978-02
Application #
7916566
Study Section
Special Emphasis Panel (ZRG1-F05-K (20))
Program Officer
Bender, Michael T
Project Start
2009-08-01
Project End
2011-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
2
Fiscal Year
2010
Total Cost
$52,154
Indirect Cost
Name
University of California Berkeley
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704