EFRI ELiS: Desiccatable living cell-based sensors to monitor pollutants and pathogens in built environments

嗅觉是惊人的多才多艺。鸟类和昆虫可以感知并寻找特定的花朵。猎犬可以追踪数小时甚至数天前的气味踪迹。即使是人类也能察觉到大约1万种不同的气味。相比之下，目前的传感技术在检测和区分不同气味方面做得很差。环境监测将从显著改进的气味传感技术中受益匪浅。该项目的目标是创造一种基于工程生物细胞的人造“电子鼻”技术。当检测到化合物时，这些细胞将发出荧光信号。除了监测人类环境的安全外，通用电子鼻还将有一系列应用，包括食品安全、非侵入性医疗诊断和健康监测；检测爆炸物和非法药物；绘制农业害虫地图。伦理问题将在与焦点小组的公共参与练习中进行评估。这项研究将利用表达气味受体的昆虫细胞系和钙离子的GCaMP报告器，在气味结合时发出荧光信号。该细胞系将能够在保持功能性的同时进行脱水和再水化。干燥解决了设备存储不切实际的问题，该问题阻碍了基于单元的传感器的广泛部署。从表达果蝇受体Or47a的现有细胞系开始，将描述对气味的反应，无论是单一的还是混合的，以了解在给定生物变异性的情况下可靠识别的要求。气味的引入在很大程度上仅限于液体，因此将研究引入空气中气味的方法。通过优化表达系统，将为原型阵列开发至少三个表达不同气味受体的新的稳定细胞系；最终通用电子鼻所需的大量阵列元件需要可靠地创建新的细胞系。细胞阵列对各种气味产生的时空模式将是复杂的，这给即使使用机器学习(ML)的气味识别带来了挑战，因为没有处理组合相互作用和非线性动力学现象的ML模型。新的ML算法的集成将导致在电子鼻中实现组合编码的可能性。将开发一种小型化的光学探测系统，产生关于便携式设备要求的重要知识。该项目将从生物学、硬件和数据解释等多个角度扩展关于如何实际实现人工嗅觉的知识；它还将阐明围绕工程生命系统的伦理问题和社区参与。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The sense of smell is amazingly versatile. Birds and insects can sense and seek out specific flowers. Hounds can follow scent trails that are hours and days old. Even humans can detect about 10,000 different odors. Current sensing technology, in comparison, is poor at detecting and discriminating between different odorants. Environmental monitoring would benefit greatly from a dramatically improved odor sensing technology. The objective of this project is to create an artificial “e-nose” technology based on engineered biological cells. These cells will emit fluorescent signals when compounds are detected. In addition to monitoring the safety of human environments, a general-purpose e-nose would have a range of applications including food safety, non-invasive medical diagnostics, and health monitoring; detecting explosives and illicit drugs; and mapping agricultural pests. Ethical issues will be assessed in public engagement exercises with focus groups.The research will utilize an insect cell line expressing an odorant receptor and a GCaMP reporter for Ca2+, giving a fluorescence signal upon odorant binding. The cell line will be able to be desiccated and rehydrated, while retaining functionality. Desiccation addresses the problem of the impracticality of device storage that has prevented wide-spread deployment of cell-based sensors. Beginning with an existing cell line expressing the Drosophila receptor Or47a, responses to odorants, singly and in mixtures, will be characterized to understand the requirements for reliable recognition, given biological variability. Odorant introduction has largely been confined to liquids, so methods for introducing airborne odorants will be investigated. At least three new stable cell lines expressing different odorant receptors will be developed for a prototype array by optimizing the expression system; reliable creation of new cell lines is required for the large number of array elements needed for an eventual general-purpose e-nose. The spatio-temporal patterns generated by the cell arrays to various odors will be complex, posing a challenge for odor recognition even using machine learning (ML), since there are no ML models that handle combinatorial interactions and nonlinear dynamical phenomena. The integration of new ML algorithms will lead to the possibility of implementing combinatorial coding in an e-nose. A miniaturized optical detection system will be developed, generating significant knowledge concerning requirements for a portable device. The project will expand knowledge about how to practically achieve artificial olfaction from multiple angles: biology, hardware, and data interpretation; it will also shed light on ethical concerns and community involvement around engineered living systems.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.