Excellence in Research: Aptamer integrated graphene-gold conjugates for machine learning aided pesticide residue screening

卓越研究：适体集成石墨烯-金缀合物，用于机器学习辅助农药残留筛查

• 批准号: 2100930
• 负责人: Renny Fernandez
• 金额: $ 50万
• 依托单位: Norfolk State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2100930&HistoricalAwards=false
• 关键词: Excellence; Research; Aptamer; integrated; graphene

The main objective of this proposal is to design graphene-gold-aptamer bioconjugates for building colorimetric pesticide sensors. The bioconjugates designed will be tailored for inkjet printing on flexible substrates. The colorimetric output will be captured by a camera integrated handheld device or a smartphone camera. Dependency on capture device and illumination conditions will be corrected using a machine learning algorithm to extract the precise chromatic information that correlate to pesticide levels. In order to prove the versatility of the proposed platform, a case study on detection of four pesticides namely Glyphosate, Malathion, Acetamiprid, and Chlorpyrifos will be performed. By being part of this project, graduate and undergraduate students of the Department of Engineering, Norfolk State University, will gain valuable multidisciplinary experience in designing sensing systems by applying concepts of engineering, nanotechnology, image processing and machine learning. This project will also be enhanced by offering curricular opportunities such as independent study, summer internships, and senior capstone projects. Project displays and demonstrations will be included in Engineering Department outreach to Norfolk area high school students and teachers. The proposed bioconjugate is based on the peroxidase like nanozyme activity of the Graphene-gold conjugate, selectivity of the aptamer and reliability of machine learning. The proposed architecture can serve as a universal colorimetric sensing platform by changing the aptamer sequence for different targets, providing a powerful and versatile engineered system which is scalable, allowing testing of a wide range of pesticides. Products of the research tasks will not only result in a rapid analysis tool for pesticide analysis but will also yield unprecedented new knowledge on aptamer-small molecule target binding. In order to accurately correlate chrominance changes to pesticide levels, the illuminance element will be separated from the chrominance factor using a machine learning approach. The effect of varying illumination conditions on the colorimetric output of the sensor using RGB, LAB and HSV color spaces will be investigated. The machine learning approach will also provide the methodological framework needed to understand the influence of experimental parameters such as sample pH and conductivity, aptamer length, and %GC on aptamer-target affinity. The platform developed will be capable of measuring binding kinetics, monitoring equilibrium affinities of aptamers and adjusting for the presence of nonspecific interactions. Moreover, this technology has high commercial potential as the sensor fabrication is based on low-cost techniques like inkjet printing and thermal embossing.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.

该提案的主要目的是设计石墨烯 - 高功能生物轭物来构建比色农药传感器。设计的Bioconjugates将针对柔性基材上的喷墨打印量身定制。比色输出将通过相机集成的手持设备或智能手机相机捕获。对捕获装置和照明条件的依赖性将使用机器学习算法进行纠正，以提取与农药水平相关的精确色彩信息。为了证明所提出的平台的多功能性，将进行四种农药，即草甘膦，马拉硫酮，乙酰氨基甲基和毒死rif虫的案例研究。通过成为该项目的一部分，诺福克州立大学工程系的毕业生和本科生将通过应用工程，纳米技术，图像处理和机器学习的概念来在设计传感系统方面获得宝贵的多学科经验。该项目还将通过提供课程机会，例如独立研究，暑期实习和高级顶峰项目。项目展示和示威活动将包括在诺福克地区高中生和老师的工程部门范围内。所提出的生物缀合物基于过氧化物酶，例如石墨烯 - 金偶联物的纳米活性，适体的选择性和机器学习的可靠性。所提出的架构可以通过更改不同目标的适体序列来充当通用的比色传感平台，从而提供了一种功能强大且具有广泛的工程系统，该系统可扩展，从而可以测试各种农药。研究任务的产物不仅会导致一种快速分析工具进行农药分析，而且还将产生关于适体分子目标结合的前所未有的新知识。为了准确地将镀铬变化与农药水平相关联，使用机器学习方法将与镀铬因子分开。使用RGB，LAB和HSV颜色空间的不同照明条件对传感器比色输出的影响。机器学习方法还将提供理解实验参数（例如样品pH和电导率，适体长度和％gc）对适体目标亲和力的影响的方法学框架。开发的平台将能够测量结合动力学，监测适体的平衡亲和力并调整是否存在非特异性相互作用。此外，这项技术具有很高的商业潜力，因为传感器制造基于诸如喷墨印刷和热压浮雕之类的低成本技术。该奖项反映了NSF的法定任务，并且通过基金会的智力优点和更广泛的影响来评估NSF的法定任务。