ePACE: an automated system for high-throughput, closed-loop control of continuous molecular evolution to enable novel therapeutics

ePACE：一种自动化系统，用于高通量、闭环控制连续分子进化，以实现新型疗法

• 批准号: 10113365
• 负责人: Ahmad Samir Khalil
• 金额: $ 60.8万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-03 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10113365
• 关键词: Address; Algorithms; Amino Acyl-tRNA Synthetases; Apoptosis; Bacteriophage M13; Bacteriophages; Biological; Bontoxilysin; Botulinum Toxin Type A; CASP1 gene; CRISPR/Cas technology; Case Study; Caspase; Cleaved cell; Clustered Regularly Interspaced Short Palindromic Repeats; Complex; Computer software; Couples; DNA Binding; DNA-Directed RNA Polymerase; Data; Devices; Directed Molecular Evolution; Evolution; Family; Genetic Diseases; Genome; Goals; Individual; Laboratories; Life Cycle Stages; Liquid substance; Manuals; Medical; Methods; Molecular; Molecular Evolution; Mutagenesis; Nucleic Acids; Online Systems; Outcome; Peptide Hydrolases; Population; Positioning Attribute; Property; Proteins; Route; Site; Specificity; Standardization; System; Technology; Testing; Therapeutic; Time; Variant; Vial device; Viral; Work; cancer therapy; cell growth; cost; design; experience; experimental study; genome editing; human disease; method development; next generation; novel; novel therapeutics; open source; prevent; programs; promoter; rapid technique; real time monitoring; success; synthetic biology; therapeutic protein; therapeutic target

PROJECT SUMMARY/ABSTRACT The recent development of methods that allow continuous laboratory evolution of biomolecules has made it increasingly possible to generate proteins with new, tailored activities for next-generation therapeutics. In particular, phage-assisted continuous evolution (PACE), a method that allows proteins to undergo directed evolution at a rate of ~100-fold faster than conventional methods, has recently been used to evolve new activities in a number of proteins, including RNA polymerases, Cas9 proteins, and viral proteases. While these early applications illustrate the potential of the PACE system, there remain intrinsic technical barriers that limit the success rate, efficiency, and wider application of PACE for creating highly selective, designer molecular therapeutics. The first barrier is the exceedingly low throughput with which PACE experiments can be conducted in parallel, which greatly limits the number of evolutionary trajectories that can be assessed and prohibits large-scale evolution of variants with diverse specificities/activities. The second is an inability to precisely and dynamically control PACE selection conditions (positive and negative), which is critical for fine- tuning properties such as the selectivity of evolved proteins and for achieving successful PACE outcomes. We propose to overcome these barriers by developing an automated, high-throughput system for PACE with individual, real-time monitoring and control over selection conditions (ePACE). To accomplish this goal, we will adapt eVOLVER, a scalable do-it-yourself (DIY) framework we recently invented that uniquely enables scaling both throughput (>100 vials) and individual programmable control of culture conditions during continuous cell growth. Leveraging the highly modular and open source wetware, hardware, and web-based software of eVOLVER will allow us to develop ePACE with a projected throughput ~50-100-fold greater than current PACE technology, with setup costs of >10-fold lower, and the capability of programming real-time, algorithmically- driven modulation of selection conditions to comprehensively explore directed evolution landscapes. We will then demonstrate the ePACE system in two directed evolution case studies that specifically highlight and test the benefits of our enhanced functionalities. The first study will apply the high-throughput capabilities of ePACE to perform multiplex evolution of Cas9 (CRISPR) variants with compatibility for every possible PAM sequence, a large scale evolution that is impractical for traditional PACE. In the second study, we will apply adaptive (closed-loop) selection stringency modulation to the traditionally challenging problem of reprogramming proteases toward new, intracellular therapeutic targets. This effort will seek to acquire a Botulinum neurotoxin protease variant capable of selectively cleaving caspase-1, toward an ultimate goal of a deliverable, caspase- activing protease for potential cancer therapies. This work will provide a standardized, democratic, and powerful platform to streamline and expand the scope of directed evolution methods for rapidly creating new molecular entities and therapeutics.

项目摘要/摘要 最近发展的方法，允许连续的实验室进化的生物分子，使它 越来越有可能产生具有新的、定制的活性的蛋白质，用于下一代治疗。在 特别是，噬菌体辅助连续进化（PACE），一种允许蛋白质进行定向进化的方法， 进化的速度比传统方法快100倍，最近已被用于进化新的 在许多蛋白质中具有活性，包括RNA聚合酶、Cas9蛋白和病毒蛋白酶。虽然这些 早期的应用表明了PACE系统的潜力，但是仍然存在一些内在的技术障碍，限制了 PACE在创造高选择性、设计分子方面的成功率、效率和广泛应用 治疗学第一个障碍是PACE实验的吞吐量非常低， 并行进行，这极大地限制了可以评估的进化轨迹的数量， 禁止具有不同特异性/活性的变体的大规模进化。第二个是不能 精确和动态地控制PACE选择条件（积极和消极），这对于精细的 调整特性，如进化蛋白质的选择性，并实现成功的PACE结果。我们 我建议通过开发一个自动化、高通量的PACE系统来克服这些障碍， 个人实时监测和控制选择条件（ePACE）。为了实现这一目标，我们将 adapt eVOLVER，我们最近发明的一个可扩展的DIY框架， 在连续细胞培养过程中的生产量（>100瓶）和培养条件的单独可编程控制 增长利用高度模块化和开源的湿件、硬件和基于Web的软件， eVOLVER将使我们能够开发ePACE，预计吞吐量比当前PACE高约50-100倍 技术，设置成本降低>10倍，并且能够实时编程，算法- 选择条件的驱动调节，以全面探索定向进化景观。我们将 然后通过两个定向进化案例研究来演示ePACE系统，这些案例研究专门强调并测试了 我们增强功能的好处。第一项研究将应用ePACE的高通量功能 为了对Cas9（CRISPR）变体进行多重进化，并与每种可能的PAM序列兼容， 这是一个对传统PACE来说不切实际的大规模进化。在第二项研究中，我们将应用自适应 （闭环）选择严格性调制到传统上具有挑战性的重编程问题 新的细胞内治疗靶点。这项努力将寻求获得肉毒杆菌神经毒素 能够选择性切割半胱天冬酶-1的蛋白酶变体，朝向可递送的半胱天冬酶- 用于潜在癌症治疗的活化蛋白酶。这项工作将提供一个规范的，民主的， 一个强大的平台，简化和扩大定向进化方法的范围，以快速创建新的 分子实体和治疗学。