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<li><a href="https://2018.igem.org/Team:Fudan/Model#War_Predictor">Model: war predictor</a></li> | <li><a href="https://2018.igem.org/Team:Fudan/Model#War_Predictor">Model: war predictor</a></li> | ||
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− | + | Figure 2. Previous designs with single element are not able to handle transmembrane signal processing task. The input-output relationship of a single element is characterized by Hill Equation, which comes with a 'detection range' defined by Kd and n. When the input range does not match the detection range, the system cannot faithfully represent the on and off of the input. | |
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<h2 style="margin: 0;padding: 10px 0;">Abstract</h2> | <h2 style="margin: 0;padding: 10px 0;">Abstract</h2> | ||
− | <p style="margin:0 | + | <p style="margin: 0">Contact-dependent signaling is critical for multicellular biological |
events, yet customizing contact-dependent signal transduction between | events, yet customizing contact-dependent signal transduction between | ||
cells remains challenging. Here we have developed the ENABLE toolbox, a | cells remains challenging. Here we have developed the ENABLE toolbox, a | ||
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<li><a href="https://2018.igem.org/Team:Fudan/Results">Transmembrane logic</a></li> | <li><a href="https://2018.igem.org/Team:Fudan/Results">Transmembrane logic</a></li> | ||
<li><a href="https://2017.igem.org/Team:Fudan">2017.iGEM</a></li> | <li><a href="https://2017.igem.org/Team:Fudan">2017.iGEM</a></li> | ||
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<li><a href="https://2018.igem.org/Team:Fudan/Model#Transcriptional_Amplifer">Model: transcriptional amplifer</a></li> | <li><a href="https://2018.igem.org/Team:Fudan/Model#Transcriptional_Amplifer">Model: transcriptional amplifer</a></li> | ||
<li><a href="https://2018.igem.org/Team:Fudan/Model#War_Predictor">Model: war predictor</a></li> | <li><a href="https://2018.igem.org/Team:Fudan/Model#War_Predictor">Model: war predictor</a></li> | ||
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Revision as of 10:52, 17 October 2018
Our notebook
Figure 2. Previous designs with single element are not able to handle transmembrane signal processing task. The input-output relationship of a single element is characterized by Hill Equation, which comes with a 'detection range' defined by Kd and n. When the input range does not match the detection range, the system cannot faithfully represent the on and off of the input.
Abstract
Contact-dependent signaling is critical for multicellular biological events, yet customizing contact-dependent signal transduction between cells remains challenging. Here we have developed the ENABLE toolbox, a complete set of transmembrane binary logic gates. Each gate consists of 3 layers: Receptor, Amplifier, and Combiner. We first optimized synthetic Notch receptors to enable cells to respond to different signals across the membrane reliably. These signals, individually amplified intracellularly by transcription, are further combined for computing. Our engineered zinc finger-based transcription factors perform binary computation and output designed products. In summary, we have combined spatially different signals in mammalian cells, and revealed new potentials for biological oscillators, tissue engineering, cancer treatments, bio-computing, etc. ENABLE is a toolbox for constructing contact-dependent signaling networks in mammals. The 3-layer design principle underlying ENABLE empowers any future development of transmembrane logic circuits, thus contributes a foundational advance to Synthetic Biology.