User:Andrew Yang/Notebook/MURI MIT

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Project Description/Abstract

  • Micro-bio-robotic communication: Multicellular pattern formation and detection with visible and ultraviolet light

Project Summary: Programmable Bacteria
MBRs will execute sophisticated algorithms that will enable them to sense, compute, amplify, and communicate their internal state, as well as directly sense and modify their environment. We will focus on designing an extendable platform of synthetic biology components and gene network modules. While bacteria can serve as simple and robust environmental biosensors by linking natural two-component signaling motifs and promoters to reporter genes like green fluorescent protein, we will engineer richer signal processing and programmed behavior using novel, engineered biomolecular sensors (e.g., two-component signaling motifs) targeted against a panel of key analytes (e.g., explosives, toxins, environmental cues, light, salinity, etc.), and then use their output to drive synthetic gene networks. We will establish sensor profiles indicative of particular environmental conditions and use these to drive synthetic gene networks, creating programmable bacteria specific to operational conditions. These gene networks will enable signal processing and communication within living systems. For example, digital processing is possible using memory [1], multi-input logic [2], and specialized circuits such as counters [3] and edge detectors [4]. Analog circuits can enable an even broader set of processing functions, such as filters [5] and timers [6]. A potential processor could, for example, combine multiple inputs, such as salinity, temperature, light, and mechanical stress, via NOT and AND gates to gauge sea depth and conditions. Depending upon the environment’s profile, there will likely be situations for data acquired where a ratio of two sensor activities, not absolute activities, is indicative of an interesting or relevant environmental condition. We will create ratio calculator circuits to respond to these environments. Alternatively, where the order of environmental cues is important, we will create sequential signal detection networks to respond to specific sequences of sensor activation. Novel signal processing and logic gene circuits have been developed by our labs, as well as intercellular communication circuits [7, 8], and we will integrate these modules to form subroutines in more advanced algorithms. These programs will allow our MBRs to conduct autonomous decision-making, and thus modify their behavior in a swarm. As an example, engineered promoters can drive memory units, such as genetic toggle switches [1] or invertase memory modules [3], for the purpose of adaptation, a fundamental computational step that allows for a broad range of decision making and self-regulation.

Notes

Please refer to the calender to see each day's workflow. Contact acyang@mit.edu or dollizzy@gmail.com for questions.


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