Phenotypic assay for drug discovery and personalized medicine based on real-time vibrational spectroscopy enhanced by plasmonic metasurfaces

摘要 本研究的目的是发展一种新的光谱技术--含时红外反射 光谱分析（TIRSA）-这将使我们能够测量细胞的实时光谱响应， 各种药理学化合物。TIRSA的独特之处在于它利用了红外反射等离子体激元 （金）超颖表面检测，作为时间的函数，生物化学变化在细胞的紧密接近， 膜，以及细胞骨架重组发生。在整个过程中获得的光谱 给药后数小时，将用于确定其对信号通路的影响， 标签，因为生物分子的振动指纹是天然标签。不像耗时的细胞毒性 在检测中，TIRSA可能短至几个小时，从而解决最严重的问题之一。 表型测定的缺陷：它们的低通量。强大的机器学习（ML）技术将成为 用于处理TIRSA获得的大量生化信息，并进行 监督和无监督的数据分析，将基于光谱细胞反应的大型库 单靶化合物如激酶抑制剂等。新的基于激光的硬件， TIRSA将实现高灵敏度、时间和空间分辨率。

Abstract The goal of this research is to develop a new spectroscopic technique – Time-dependent Infrared Reflection Spectroscopy Assay (TIRSA) – that will enable us to measure the real-time spectral response of a cell to various pharmacological compounds. The uniqueness of TIRSA is that it exploits infrared-reflective plasmonic (gold) metasurfaces to detect, as a function of time, biochemical changes in close proximity of cellular membranes, as well as cytoskeleton reorganization occurring. The optical spectra obtained over the course of several hours after administering the drug will be used to identify its effects on signaling pathways without any labels because vibrational fingerprints of biomolecules are the natural labels. Unlike time-consuming cytotoxic assays, the TIRSA can be potentially as short as several hours, thereby addressing one of the most serious deficiencies of phenotypic assays: their low throughput. Powerful techniques of machine learning (ML) will be used to process the enormous amount of biochemical information obtained by TIRSA, and to conduct supervised and unsupervised data analysis that will be based on large libraries of spectral cellular responses to single-target chemical compounds such as kinase inhibitors and others. New laser-based hardware for TIRSA will enable high sensitivity, time and space resolution.