Synthetic Physiology: Strategies for Adapting Tools from Nature for Genetically Targeted Control of Fast Biological Processes [Chapter 18]
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Boyden_Synthetic physiology.pdf
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Author(s)
Chow, Brian Yichiun
Chuong, Amy S.
Klapoetke, Nathan Cao
Boyden, Edward Stuart
Date Issued
May 2011
Journal
Synthetic Biology, Part A
Publisher
Elsevier
Citation
Chow, Brian Y., Amy S. Chuong, Nathan C. Klapoetke, and Edward S. Boyden. "Synthetic Physiology: Strategies for Adapting Tools from Nature for Genetically Targeted Control of Fast Biological Processes." Methods in Enzymology, Synthetic Biology, Part A., Volume 497, Pages 2-662, (2011).
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Author's final manuscript
Abstract
The life and operation of cells involve many physiological processes that take place over fast timescales of milliseconds to minutes. Genetically encoded technologies for driving or suppressing specific fast physiological processes in intact cells, perhaps embedded within intact tissues in living organisms, are critical for the ability to understand how these physiological processes contribute to emergent cellular and organismal functions and behaviors. Such “synthetic physiology” tools are often incredibly complex molecular machines, in part because they must operate at high speeds, without causing side effects. We here explore how synthetic physiology molecules can be identified and deployed in cells, and how the physiology of these molecules in cellular contexts can be assessed and optimized. For concreteness, we discuss these methods in the context of the “optogenetic” light-gated ion channels and pumps that we have developed over the past few years as synthetic physiology tools and widely disseminated for use in neuroscience for probing the role of specific brain cell types in neural computations, behaviors, and pathologies. We anticipate that some of the insights revealed here may be of general value for the field of synthetic physiology, as they raise issues that will be of importance for the development and use of high-performance, high-speed, side-effect free physiological control tools in heterologous expression systems.
MIT Department
Massachusetts Institute of Technology. Synthetic Neurobiology Group
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/b978-0-12-385075-1.00018-4
