GCR: Understanding Virus Evolution Through Deep Raman Spectroscopy

这个日益趋同的研究项目旨在彻底改变如何监测和描述流行的流行病和大流行性流感病毒株。该项目汇集了对病毒进行控制突变的病毒学家，为病毒富集创建平台的纳米科学工程师，开发有效的二维材料拉曼信号增强平台的材料科学家和光谱学家，以及使用机器学习方法分析数据以实现病毒识别和预测新抗原变体潜在出现的数据科学家。研究小组的目标是开发一种能够快速捕获、感知和识别病毒的聚合设备平台，并预测人类对有限或没有免疫力的新抗原菌株。该项目通过解决用于病毒检测和进化预测的增强拉曼光谱中的深层科学问题，寻求解决监测和表征流行流行病和大流行性流感病毒株方面的重大挑战。该平台基于控制病毒学实验，通过培养和突变病毒进行特定研究任务，一种新的病毒富集平台，可有效捕获无标记的病毒，通过新型2D/金属增强拉曼光谱技术增强信号的病毒表面蛋白生物传感，以及通过增强拉曼数据的机器学习分析快速敏感的病毒鉴定和进化预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Growing Convergence Research project aims at revolutionizing how circulating epidemic and pandemic influenza virus strains are surveilled and characterized. The project brings together virologists who perform controlled mutations of the virus, nanoscience engineers who create platforms for virus enrichment, materials scientists and optical spectroscopists who develop effective 2D material Raman signal enhancement platforms, and data scientists who analyze data with machine learning methods to achieve virus identification and prediction of potential emergence of new antigenic variants. The goal of the research team is to develop a convergent device platform that can rapidly capture, sense, and identify viruses and predict new antigenic strains against which the human population has limited or no immunity.The project pursues a solution to a grand challenge in the surveillance and characterization of circulating epidemic and pandemic influenza virus strains by addressing deep scientific questions in enhanced Raman spectroscopy for virus detection and evolution prediction. The proposed platform is based on controlled virology experiments that propagate by culture and mutate viruses for specific research tasks, a novel virus enrichment platform for effectively capturing viruses without labels, biosensing of virus surface proteins with enhanced signal through a novel 2D/metal enhanced Raman spectroscopy technique, and rapid and sensitive virus identification and evolution prediction through machine learning analysis of enhanced Raman data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.