EAGER: Hybrid Analog-Digital Automata in Microbial Cells

EAGER：微生物细胞中的混合模拟数字自动机

• 批准号: 1348519
• 负责人: Rahul Sarpeshkar
• 金额: $ 30万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1348519&HistoricalAwards=false
• 关键词: EAGER; Hybrid; Analog; Digital; Automata

Molecular computation by cells helps them process signals in their environment to make important decisions. Such computation in cells is both analog, which uses signals with shades of grey and operations that are probabilistic or graded, and also digital, which uses "on" and "off" signals and operations that are logical. The hybrid analog-digital computation in the cell is an extremely important reason for why it is highly efficient in its use of energy and molecular parts (proteins, RNA, and DNA molecules), which are severely limited in number compared with artificial computational systems. For example, current digital microprocessors have nearly a billion electronic parts and a relatively plentiful supply of energy. The cell is several orders of magnitude more energy and part-count efficient than even the best digital computers of the far future are ever expected to be. For advancing the foundations of computer science beyond its boundaries, and for the future of biotechnology and medicine, it is important to understand and to artificially engineer hybrid analog-digital computation in living cells. The proposal focuses on how to engineer a hybrid analog-digital computational automaton in microbial cells that can enable it to sense, amplify, and process analog input molecular signals into pulsatile digital output molecular signals.Intellectual Merit: This work combines innovations and knowledge from several disciplines to potentially create a paradigm-changing capability in the fields of synthetic biology, systems biology, molecular programming, biotechnology, computer science, and medicine: 1) Hybrid analog-digital automata can perform complex computations with very few parts and little energy, and the research here can help advance fundamental work in computer science in this area; 2) The highly efficient instantiation of a spiking-neuron-like automaton with only four genes in a microbe creates a fundamental new computational motif that can be ported to a wide range of molecular implementations including in-vitro molecular systems, in-vivo microbial, yeast, and mammalian cells; 3) The microbial fuel cell automaton enables sensitive and continuous molecular sensing to be built in a wide range of hosts without the need for bulky, expensive, non-continuous and toxic photo-bleaching optical systems; 4) By creating molecular cellular automata that serve to implement sophisticated molecular sensing, pattern recognition, and collective computation, the proposal could enable very large scale molecular computational systems to become practical.Broader Impact: The hybrid analog-digital automata is a computational motif that could be widely applied to synthetic cell-based treatments in medicine. Microbial sensing and computational systems that are capable of sensing, amplifying, digitizing and classifying minute concentrations of input molecules could have wide application in the food, biotechnology, pharmaceutical, environmental, and security industries. PI participates in the Society of Women Engineers, MIT Summer Research Program, Saturday Engineering Enrichment Discovery Program, and computational and systems biology recruitment programs at MIT, which actively target women and underrepresented minorities.

细胞的分子计算帮助它们处理环境中的信号，以做出重要的决定。单元格中的这种计算既是模拟的，它使用带有灰色阴影的信号和概率或分级的操作，也是数字的，它使用“开”和“关”的信号和逻辑操作。细胞中的模拟-数字混合计算是其高效利用能量和分子部分(蛋白质、RNA和DNA分子)的一个极其重要的原因，与人工计算系统相比，这些部分的数量严重有限。例如，目前的数字微处理器拥有近10亿个电子部件和相对充足的能源供应。这种电池的能量和部分计数效率都比未来最好的数字计算机预计的要高出几个数量级。为了推动计算机科学的基础超越其边界，为了生物技术和医学的未来，理解和人工设计活细胞中的模拟-数字混合计算是重要的。该方案的重点是如何在微生物细胞中设计一种混合的模拟-数字计算自动机，使其能够感知、放大和处理模拟输入的分子信号，并将其处理为脉动的数字输出分子信号。智慧的优点：这项工作结合了几个学科的创新和知识，潜在地在合成生物学、系统生物学、分子编程、生物技术、计算机科学和医学领域创造了改变范式的能力：1)混合模拟-数字自动机可以用很少的部件和很少的能量执行复杂的计算，这里的研究有助于推进这一领域的计算机科学的基础工作；2)在微生物中只有4个基因的尖峰神经元自动机的高效实例化创建了一个基本的新的计算基序，该基序可以移植到广泛的分子实现，包括体外分子系统、体内微生物、酵母和哺乳动物细胞；3)微生物燃料电池自动机使灵敏和连续的分子传感能够在广泛的宿主中建立，而不需要庞大、昂贵、非连续和有毒的光漂白光学系统；4)通过创建分子细胞自动机来实现复杂的分子传感、模式识别和集体计算，该提议可以使超大规模的分子计算系统成为现实。广泛的影响：模拟-数字混合自动机是一种可以广泛应用于医学合成细胞治疗的计算主题。能够对输入分子的微小浓度进行传感、放大、数字化和分类的微生物传感和计算系统在食品、生物技术、制药、环境和安全行业具有广泛的应用。PI参加了麻省理工学院的女性工程师协会、麻省理工学院暑期研究计划、周六工程丰富发现计划以及麻省理工学院的计算和系统生物学招聘计划，这些计划积极针对女性和代表性不足的少数族裔。