Journal
SCIENCE
Volume 353, Issue 6297, Pages 363-+Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.aad8559
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Funding
- Ford Foundation Pre-doctoral Fellowships Program and Molecular Biophysics Training Grant [NIH/NIGMS T32 GM008313]
- NSF Alan T. Waterman Award [1249349]
- Center for Microbiome Informatics and Therapeutics
- NIH [DP2 OD008435, P50 GM098792]
- Office of Naval Research [N00014-13-1-0424, N0001411110725]
- NSF [MCB-1350625]
- NSF Expeditions in Computing Program Award [1522074]
- Defense Advanced Research Projects Agency [HR0011-15-C-0091]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [1521925] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1522074] Funding Source: National Science Foundation
- Div Of Molecular and Cellular Bioscience
- Direct For Biological Sciences [1350625] Funding Source: National Science Foundation
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State machines underlie the sophisticated functionality behind human-made and natural computing systems that perform order-dependent information processing. We developed a recombinase-based framework for building state machines in living cells by leveraging chemically controlled DNA excision and inversion operations to encode states in DNA sequences. This strategy enables convenient readout of states (by sequencing and/or polymerase chain reaction) as well as complex regulation of gene expression. We validated our framework by engineering state machines in Escherichia coli that used one, two, or three chemical inputs to control up to 16 DNA states. These state machines were capable of recording the temporal order of all inputs and performing multi-input, multi-output control of gene expression. We also developed a computational tool for the automated design of gene regulation programs using recombinase-based state machines. Our scalable framework should enable new strategies for recording and studying how combinational and temporal events regulate complex cell functions and for programming sophisticated cell behaviors.
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