Fluorescent biosensors for metabolite imaging in live cells

描述(由申请人提供)：所有细胞都需要能量和化学成分来生长、增殖和对环境信号做出反应。因此，包括糖尿病、癌症、发育障碍和传染病在内的病理疾病在病因学上与中枢代谢有关。解释这些病理和开发新的治疗干预措施需要了解生物体生理学的系统水平调节，其基础是酶活性和代谢产物的稳定水平。不幸的是，在活细胞中测量这些特性通常超出了当前技术的能力。代谢组学的进展使得能够测量数百种代谢物的浓度和通量，而光谱技术允许对同位素标记的化合物进行低分辨率成像。然而，所有这些技术都固有地受到侵入性、通用性、成像分辨率和吞吐量的限制。为此，这项提议的目标是使基因编码的荧光生物传感器能够快速发展，具有大的动态范围，能够测量活细胞的代谢状态。最近的工作表明，绿色荧光蛋白的高度工程化变体可以作为细胞内代谢物浓度的报告。建造这些传感器在历史上是 在理性蛋白质工程中，这是一个缓慢的、容易出错的练习，因此只有少数已知的有用的生物传感器。我们工作的目标是将这一进程加快几个数量级。我的实验室正在开发一种多重定向进化方法，用于快速分析大型生物传感器文库，使我们能够同时优化优越的光谱特性，同时还可以并行构建许多不同的传感器。作为原则的证明，我们正在将这一策略应用于构建生物传感器来测量与细胞增殖相关的代谢物，包括葡萄糖、谷氨酰胺和乳酸。在相关工作中，我们建议使用这些传感器作为基因筛选工具，在体外研究途径调控，并作为体内成像探针在线虫癌症模型中。如果成功，这些研究将使活细胞代谢功能的高通量测量和显微成像成为可能，并为细胞、组织和整个动物水平的生理学研究开辟新的途径。

DESCRIPTION (provided by applicant): All cells require energy and chemical building blocks to grow, proliferate, and respond to environmental cues. As a consequence, pathologies including diabetes, cancer, developmental disorders and infectious diseases are etiologically linked to central metabolism. Interpreting these pathologies and developing novel therapeutic interventions requires understanding the systems-level regulation of organismal physiology that has its basis in enzymatic activities and steady-state levels of metabolites. Unfortunately, measuring these properties in living cells is generally beyond the capability of current technology. Advances in metabolomics have enabled measuring the concentration and fluxes for hundreds of metabolites while spectroscopic techniques allow for the low resolution imaging of isotopically labeled compounds. However, all such techniques are inherently limited by a combination of invasiveness, generality, imaging resolution, and throughput. To this end, the goal of this proposal is to enable the rapid development of genetically-encoded fluorescent biosensors with a large dynamic range capable of measuring the metabolic state of living cells. Recent work has shown that highly engineered variants of the green fluorescent protein can act as reporters of intracellular metabolite concentration. Constructing these sensors has historically been a slow, error-prone exercise in rational protein engineering, and thus there are only a handful of known useful biosensors. The goal of our work is to accelerate this process by several orders of magnitude. My laboratory is developing a multiplex directed evolution approach for the rapid assay of large biosensor libraries, enabling us to simultaneously optimize for superior spectral properties while also constructing many different sensors in parallel. As a proof of principle, we are applying this strategy for the construction of biosensors to measure metabolites associated with cellular proliferation, including glucose, glutamine, and lactate. In related work, we propose to use these sensors as genetic screening tools for the in vitro study of pathway regulation and as in vivo imaging probes in a C. elegans cancer model. If successful, these studies will enable the high-throughput measurement and microscopic imaging of metabolic function in living cells and open up new avenues of physiologic research at the cellular, tissue, and whole-animal level.