Difference between revisions of "Team:William and Mary/Description"

 
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A fundamental goal of synthetic biology is the ability to create synthetic systems capable of effectively interfacing with natural systems. From synthetic organs to the production of biomaterials, the applications of synthetic biology require that synthetic systems are capable interacting with and interpreting the signals used by natural systems. However, the field of synthetic biology currently lacks in the ability to interact with the rich dynamical encoding systems present in natural systems. This fundamentally limits our abilities to create interactive synthetic systems.</div>
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A fundamental goal of synthetic biology is the ability to create synthetic systems capable of effectively interfacing with natural systems. From synthetic organs to the production of biomaterials, the applications of synthetic biology require that synthetic systems are capable of interacting with and interpreting the signals used by natural systems. However, the field of synthetic biology currently lacks the ability to interact with the rich dynamical encoding systems present in natural systems. This fundamentally limits our abilities to create interactive synthetic systems.</div>
 
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Latest revision as of 03:11, 18 October 2018

Page Title

Background

Motivation
A fundamental goal of synthetic biology is the ability to create synthetic systems capable of effectively interfacing with natural systems. From synthetic organs to the production of biomaterials, the applications of synthetic biology require that synthetic systems are capable of interacting with and interpreting the signals used by natural systems. However, the field of synthetic biology currently lacks the ability to interact with the rich dynamical encoding systems present in natural systems. This fundamentally limits our abilities to create interactive synthetic systems.
In natural systems, information is usually transmitted dynamically; that is, information is transmitted based upon how the system changes over time, rather than by the system’s value at any given point in time. One prominent example of dynamical information transmission is the p53 mediated response to DNA damage. In this system, the dynamics of p53 encode both the source and severity of the DNA damage (Figure 1).
Figure 1: Different types of DNA damage lead to different dynamics of P53. Gamma radiation (left) leads to fixed height pulses, with increasing strength leading to a greater number of pulses. UV radiation (right) leads to a single pulse, with increasing strength leading to longer duration and greater amplitude. Figure from [1]
Importantly, different sources of DNA damage lead to information being encoded in the dynamics of p53 in a qualitatively distinct manner. When the source of DNA damage is ultraviolet radiation, information is encoded in the form of a single pulse of variable amplitude and duration, whereas when the damage results from gamma radiation, information is encoded in a variable number of fixed height pulses [1,2]. Since these two different encoding schemes lead to radically different pathways (cell cycle arrest and apoptosis respectively), any synthetic system that aims to interact with this or any of the millions of other dynamical signaling pathways will need to be able to appropriately distinguish and process the different types of encoding schemes.
This phenomenon of dynamic information encoding is not restricted to p53. In fact, it is wide spread throughout natural systems, with information being encoded in this manner in systems as varied as amoeba development, yeast stress response, immune function, and the maintenance of stem cells. This presents an obstacle for synthetic biologists hoping to study or interact with these systems, as there are currently no synthetic systems explicitly designed to distinguish and process information encoded in this dynamic manner. Further, if synthetic systems are to emulate the diversity and complexity of natural systems, they will need to be able to harness the power inherent in dynamic information processing. To address this problem, our project this year focused on the design and creation of a synthetic circuit capable of converting the dynamic information present in natural systems into a form usable by existing synthetic circuits. This circuit, which we term the decoder, would be of great use to field, enabling more effective integration of synthetic and natural systems. Click to read about our results.
References
[1] Purvis, J.E., and Lahav, G. (2013). Encoding and decoding cellular information through signaling dynamics. Cell 152, 945–956.
[2] Kracikova, M., Akiri, G., George, A., Sachidanandam, R., and Aaronson, S.A. (2013). A threshold mechanism mediates p53 cell fate decision between growth arrest and apoptosis. Cell Death Differ. 20, 576–588.