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Computational Design of Nonlinear Functions using Nucleic Acids - Microsoft Research Voucher 16000070 - Engineering - Synthetic Biology

使用核酸进行非线性函数的计算设计 - Microsoft Research Voucher 16000070 - 工程 - 合成生物学

基本信息

批准号：
1912307
负责人：
金额：
--
依托单位：
University of Warwick
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1912307
关键词：
Computational Design Nonlinear Functions using

项目摘要

This project aims to significantly advance the field of synthetic biology by introducing new paradigms and techniques for programming biological systems and for understanding the computations performed by living cells. Synthetic biology is truly a great revolution in the offing but has failed to scale well on programmable complexity. One reason for this failure has been the overemphasis on digital paradigms. In this project, we demonstrate how to get rid of this limitation by advancing the state-of-the-art in the DNA strand displacement (DSD) theory to synthesize programmable hybrid dynamical circuits using DNA, RNA, and enzymes. Our approach lays the foundation for a unifying framework for the design of computational nucleic acid devices and helps answer previously unexplored important questions such as "How long will a given biomolecular circuit perform reliably in the wet-lab settings?" and "How robust is a given biomolecular circuit to the interference created by the extraneous cellular reactions in the wet-lab settings?" The computational nucleic acid devices synthesized using our approach show great potential for enabling a broad range of biotechnology applications, including smart probes for molecular biology research, in vitro assembly of complex compounds, high-precision in vitro disease diagnosis and, ultimately, programmable sense-and-respond systems inside living cells. This diversity of applications is supported by a range of implementation strategies, including nucleic acid strand displacement, localization to substrates, and the use of enzymes with polymerase, nickase, and exonuclease functionality. However, existing computational design tools are unable to account for these strategies in a unified manner. Hence, we also code our theoretical approach a logic programming language that allows a broad range of computational nucleic acid systems to be designed and analyzed. The language extends standard logic programming with a novel equational theory to express nucleic acid molecular motifs. It automatically identifies matching motifs present in the full system, in order to apply a specified transformation expressed as a logical rule or as a dynamical system output. The language is sufficiently expressive to encode the semantics of nucleic strand displacement systems with complex topologies, together with computation performed by a broad range of enzymes, and is readily extensible to new implementation strategies. The language development is in collaboration with Microsoft Research (Cambridge, UK) and has resulted in the software "Visual DSD" that facilitates a user-friendly in silico design of such biomolecular circuits - the software "Visual DSD" runs on both Windows and MacOS platforms, and can be coupled to other computational platforms such as MATLAB and Python. One of the core problems in the synthesis of such biomolecular circuits is the choice of kinetic rates. Recently, Nielsen et al at the Massachusetts Institute of Technology (Cambridge, MA) have developed the platform "Cello" for an automated designed of such circuits. All the same, the design procedure of Cello is limited to only Boolean circuits and does not make use of artificial intelligence and public domain metadata to increase the accuracy and the range of operating conditions over which the circuits function as desired. We demonstrate how the novel biochemical insights developed in this project can help synthesize non-Boolean circuits (such as a low-pass filter or ratio computation or logarithm) and hybrid systems using DNA/RNA/enzymes and to dramatically increase the yield of cell-free protein synthesis (CFPS) systems in the wet-lab. Such a translational impact of the project will be achieved through collaborations with Microsoft Research (Cambridge, UK) and Arbor Bioscience (Ann Arbor, MI).

该项目旨在通过引入新的范式和技术来编程生物系统和理解活细胞执行的计算，从而显着推进合成生物学领域。合成生物学确实是一场即将到来的伟大革命，但未能在可编程复杂性上很好地扩展。这种失败的原因之一是对数字范式的过度关注。在这个项目中，我们展示了如何摆脱这种限制，通过推进最先进的DNA链置换（DSD）理论，使用DNA，RNA和酶合成可编程混合动力电路。我们的方法为计算核酸设备的设计奠定了统一框架的基础，并有助于回答以前未探索的重要问题，如“给定的生物分子电路在湿实验室环境中可靠地运行多久？以及“在湿实验室环境中，给定的生物分子回路对外来细胞反应产生的干扰的鲁棒性如何？”“使用我们的方法合成的计算核酸设备显示出巨大的潜力，可以实现广泛的生物技术应用，包括用于分子生物学研究的智能探针，复杂化合物的体外组装，高精度的体外疾病诊断，以及最终在活细胞内的可编程传感和响应系统。这种应用的多样性得到了一系列实施策略的支持，包括核酸链置换、定位于底物以及使用具有聚合酶、切口酶和核酸外切酶功能的酶。然而，现有的计算设计工具无法以统一的方式解释这些策略。因此，我们也编码我们的理论方法的逻辑编程语言，允许广泛的计算核酸系统的设计和分析。该语言扩展了标准的逻辑编程与一个新的方程理论来表达核酸分子基序。它自动识别整个系统中存在的匹配基序，以便应用表示为逻辑规则或动态系统输出的指定变换。该语言是足够的表达编码的语义与复杂的拓扑结构的核酸链置换系统，连同计算进行了广泛的酶，并很容易扩展到新的实施策略。该语言的开发是与微软研究院（英国剑桥）合作进行的，并产生了软件“Visual DSD”，该软件促进了此类生物分子电路的用户友好的计算机设计-软件“Visual DSD”在Windows和MacOS平台上运行，并且可以耦合到其他计算平台，如MATLAB和Python。合成这种生物分子电路的核心问题之一是动力学速率的选择。最近，马萨诸塞州理工学院（剑桥，MA）的Nielsen等人开发了用于自动设计这种电路的平台“Cello”。尽管如此，Cello的设计过程仅限于布尔电路，并且没有利用人工智能和公共领域元数据来增加电路按需工作的准确性和工作条件范围。我们展示了在这个项目中开发的新的生物化学见解如何帮助合成非布尔电路（如低通滤波器或比率计算或对数）和使用DNA/RNA/酶的混合系统，并显着提高无细胞蛋白质合成（CFPS）系统的产量。该项目的这种转化影响将通过与微软研究院（英国剑桥）和Arbor Bioscience（密歇根州安阿伯）的合作来实现。