center for systems

& synthetic biology

an NIGMS national systems biology center


about us


understanding the design principles of biological systems

The UCSF Center for Systems and Synthetic Biology was funded in September 2010 as part of the NIGMS national centers for systems biology. This center serves as a nucleus at UCSF for interdisciplinary and quantitative explorations into how biological systems function. The center also serves as one node within a network of 15 national centers for systems biology. Major goals of our center are to expand the systems biology community at UCSF and, scientifically, to understand the design principles of cellular networks.


expanding systems biology at UCSF

We have established a Systems Biology Fellows program as a mechanism to bring in outstanding young scientists from non-traditional, non-biological backgrounds into the strong medical and biology-oriented community at UCSF. These Fellows are able to partner with any faculty of interest at UCSF, also serving to better integrate our center within the broader community.


we are trying to understand how cells make decisions using genetically encoded molecular networks

The UCSF Center for Systems and Synthetic Biology aims to understand the design principles by which cells solve problems. Our philosophy is to use a combination of network perturbation/analysis, network engineering, and theoretical enumeration to more comprehensively understand the underlying algorithmic principles that cells use to make particular classes of regulatory decisions. We also aim to use our increasing knowledge of network design principles and mechanism to develop innovative therapeutic strategies. More broadly, the center aims to play a leadership and catalytic role in the development of this transformative field, both at our own institution, but also in the greater scientific and educational community.


Current Projects


project 1: networks that control and use time

This project is motivated by the fundamental problem of how cells make so many diverse decisions using a limited set of regulatory pathways. We and others hypothesize that cellular networks must be able to encode and decode different information in the temporal patterns of pathway activation. We are using optogenetic temporal perturbations to directly and systematically ask how cells interpret different dynamic signals, exploring 3 distinct systems (yeast stress response, mammalian cell proliferation, and stem cell differentiation) that are postulated to utilize temporal encoding. In parallel we are using computational and synthetic biology approaches to elucidate the bottom-up design principles of networks that are gated by input dynamics (pulse width or frequency).


project 2: networks that organize space

The goal of this project is understanding how cellular networks can program self-organized spatial outputs, such as formation of asymmetric intracellular structure, as well as the higher level of formation of complex multicellular morphologies. We are using a combination of quantitative analysis, computational circuit exploration, and synthetic reconstitution/perturbation to understand how networks can regulate intracellular structures such as the formation of cell polarity or the homeostasis of organelle size. At the multicellular level, we are using a parallel combination of approaches to understand how cellular networks can control core morphological behaviors such as cell sorting, cyst formation, tubule formation, tubule branching, and asymmetric cell differentiation. 


project 3: applications - network rewiring in t cells

This project is motivated by the longer-term goal of using systems and synthetic biology approaches to both understand and engineer therapeutically important cellular networks. We have chosen to focus on the regulatory network of T lymphocytes because of two important therapeutic goals: i) T cells are the target of HIV infection, thus we want to understand how HIV rewires the network, and how we can manipulate the network in anti-viral therapy; ii) engineered, adoptively transferred T cells have recently emerged as a viable and effective platform for treatment of cancer, yet their activities are still only crudely controllable. We want to understand how we can synthetically manipulate the T cell network to yield more precise therapeutic actions and improved therapeutic outcomes.