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

项目摘要/摘要 最近，允许生物分子在实验室中持续进化的方法的发展使它 越来越有可能为下一代治疗产生具有新的、量身定做的活动的蛋白质。在……里面 特别是，噬菌体辅助持续进化(PACE)，这是一种允许蛋白质经历定向 进化的速度比传统方法快约100倍，最近已被用于进化新的 多种蛋白质中的活性，包括RNA聚合酶、Cas9蛋白和病毒蛋白。而这些 早期的应用说明了PACE系统的潜力，但仍然存在固有的技术障碍，限制了 PACE创造高选择性、设计型分子的成功率、效率和更广泛的应用 治疗学。第一个障碍是PACE实验的吞吐量极低 并行进行，这极大地限制了可以评估的进化轨迹的数量 禁止具有不同特性/活动的变体的大规模进化。第二个问题是无法 精确、动态地控制步速选择条件(正负)，这对精细化- 调整属性，如进化蛋白质的选择性和实现成功的PACE结果。我们 建议通过开发自动化、高吞吐量的系统来克服这些障碍 对选择条件进行单独、实时的监控(EPACE)。为了实现这一目标，我们将 Adapt Evolver，这是我们最近发明的一个可扩展的DIY(DIY)框架，它以独特的方式支持扩展 连续细胞过程中的产量(&gt；100瓶)和培养条件的个人可编程控制 成长。利用高度模块化和开源的湿件、硬件和基于Web的软件 Evolver将允许我们开发ePACE，预计吞吐量将是当前速度的50-100倍 技术，安装成本降低10倍，并具有实时、算法编程的能力- 驱动调制选择条件，全面探索定向进化景观。我们会 然后在两个定向进化案例研究中演示ePACE系统，这两个案例专门强调和测试 我们增强的功能的好处。第一项研究将应用ePACE的高通量能力 为了对每个可能的PAM序列进行具有兼容性的Cas9(CRISPR)变体的多重进化， 对于传统的速度来说，这是一种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)选择严格调制以解决传统上具有挑战性的重新编程问题 蛋白水解酶向新的细胞内治疗靶点。这一努力将寻求获得一种肉毒杆菌神经毒素 能够选择性地裂解caspase-1的蛋白酶变异体，最终目标是可交付的caspase-1。 激活蛋白水解酶，用于潜在的癌症治疗。这项工作将提供一个标准化、民主和 强大的平台，简化和扩展定向进化方法的范围，以快速创造新的 分子实体和治疗学。

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.