CDS&E: Enhancing Analyses of Live Biosamples through Chemometric Modeling of Chemical Interactions with their Environment

该项目由化学部的化学测量和成像计划资助。田纳西大学的Frank沃格特教授正在开发分析和建模方法，用于研究微藻将环境污染物转化为微藻生物量。微藻从环境中吸收营养。无机营养物被微藻转化为有机生物质。污染物或污染物释放到生态系统中会改变生态系统。这项工作的假设是，微藻的化学特征及其生物量生产可以反映生态系统的状况。对微藻进行化学分析并辅以新的数据建模的基本原理是研究微藻在暴露于化学变化的生态系统时关于化合物吸收和转化的能力。科学上更广泛的影响表现在微藻积累了环境事件和条件的历史。破译这些事件变得可行，并允许检测过去和可能挥之不去的生态系统威胁。更广泛的教育影响包括仪器分析课程的教学改进。化学计量学是一种数学和统计方法，用于提高对化学信息的理解和使用，与化学工作人员高度相关，但由于所需的数学和计算机技能水平，通常被认为对学生来说非常困难。这项工作为学生开发自己的计算机控制仪器提供了工具。通过红外光谱和流式细胞仪研究了微藻生物量在化学组成和数量方面对环境的适应性。此外，新的化学计量学建模策略的开发，以设计预测模型，链接的状态，或化学签名，微藻和生态系统。这种实验和计算方法的结合导致了关于生态系统内（人为）化合物的源和汇的知识。深入了解环境污染物与微藻之间的相互作用，对于了解生态系统的现状，并可能预测未来的状态具有重要意义。然后，微藻可以转化为环境原位探针或传感器。在这个项目中的学生培训桥梁分析化学和数据建模之间的所有太常见的差距。这一地理区域的学生也有机会接触当地的工业研究和化学生产设施。

This project is funded by the Chemical Measurement and Imaging program of the Chemistry Division. Professor Frank Vogt of The University of Tennessee is developing analytical and modeling methodologies for investigations of microalgae-based transformation of environmental pollutants into microalgal biomass. Microalgae uptake nutrients out of their environment. Inorganic nutrients are converted by the microalgae into organic biomass. The release of pollutants or contaminants into an ecosystem can alter ecosystems. The hypothesis of this work is that a microalgae's chemical signature, and their biomass production, can reflect the status of an ecosystem. The rationale for performing chemical analyses on microalgae complemented by novel data modeling, is to investigate the microalgae's capabilities regarding compound uptake and transformation when exposed to chemically changing ecosystems. The scientific broader impacts are manifested in that microalgae accumulate a history of environmental events and conditions. Deciphering these events becomes feasible and allows for the detection of past and possibly lingering, ecosystem threats. Educational broader impacts include instructional improvements in instrumental analysis courses. Chemometrics, the mathematical and statistical methods used to improve the understanding and use of chemical information, is highly relevant for the chemical workforce, but is often perceived to be very difficult for students due to the required level of math and computer skills. This work provides tools for students to develop their own computer controlled instruments. Adaptions of microalgal biomass regarding their chemical composition and quantities in response to their environment are studied by means of infrared spectroscopy and flow cytometry. Moreover, novel chemometric modeling strategies are developed to design predictive models that link the status, or chemical signature, of microalgae and an ecosystem. This combination of experimental and computational methodologies leads to knowledge about sources and sinks of (anthropogenic) compounds within an ecosystem. Gaining an in-depth understanding of interactions between environmental pollutants and microalgae living in a polluted environment is of importance for understanding the current status, and possibly predicting the future status, of an ecosystem. Microalgae can then be converted into environmental in-situ probes or sensors. Student training in this project bridges the all-too-common gap between analytical chemistry and data modeling. Underserved students in this geographic area also have exposure to local industrial research and chemical production facilities.