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: 9925776
• 负责人: Ahmad Samir Khalil
• 金额: $ 62.86万
• 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/9925776
• 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 允许持续实验室生物分子进化的方法的最新发展使它成为现实 越来越有可能通过新的，量身定制的活动生成蛋白质，用于下一代治疗疗法。在 特别，噬菌体辅助连续进化（pace），一种允许蛋白质进行定向的方法 进化的速度比常规方法快100倍，最近已被用来进化 许多蛋白质的活性，包括RNA聚合酶，Cas9蛋白和病毒蛋白酶。而这些 早期申请说明了速度系统的潜力，仍然存在限制的内在技术障碍 速度的成功率，效率和更广泛的应用在创建高度选择性的设计师分子中 疗法。第一个障碍是PACE实验可以是极低的吞吐量 并行进行，这极大地限制了可以评估和 禁止具有不同特异性/活动的变体的大规模演变。第二个是无法 精确，动态地控制节奏选择条件（正和负），这对于细细至关重要 调整特性，例如进化蛋白的选择性和成功的节奏结果。我们 建议通过开发自动化的高通量系统来克服这些障碍 个人，实时监控和控制选择条件（EPACE）。为了实现这一目标，我们将 适应Evolver，这是我们最近发明的可扩展自己动手（DIY）框架 连续细胞期间的吞吐量（> 100个小瓶）和对培养条件的单个可编程控制 生长。利用高度模块化和开源的湿软件，硬件和基于Web的软件 Evolver将使我们能够以预计的吞吐量比目前的速度大约50-100倍 技术，设置成本降低> 10倍，并且在实时编程的功能上，算法 - 驱动选择条件的驱动调制，以全面探索定向的进化景观。我们将 然后在两个定向的进化案例研究中演示EPACE系统，这些案例研究特别突出和测试 我们增强功能的好处。第一项研究将应用EPACE的高通量功能 要执行CAS9（CRISPR）变体的多重演化，并对每个可能的PAM序列兼容， 对于传统速度来说是不切实际的大规模演变。在第二项研究中，我们将采用自适应 （闭环）选择严格的调制到传统上具有挑战性的重新编程问题 针对新的，细胞内治疗靶标的蛋白酶。这种努力将寻求获得肉毒杆菌神经毒素 蛋白酶变体能够选择性切割caspase-1，达到可交付的caspase-的最终目标 活性蛋白酶用于潜在的癌症疗法。这项工作将提供标准化，民主和 功能强大的平台，用于简化和扩展有导进化方法的范围，以快速创建新的 分子实体和治疗学。