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

该项目由化学部门的化学测量和成像项目资助。田纳西大学的Frank Vogt教授正在开发分析和建模方法，用于研究以微藻为基础的将环境污染物转化为微藻生物量的过程。微藻从环境中吸收养分。无机营养物质被微藻转化为有机生物量。向生态系统释放污染物或污染物可以改变生态系统。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态。对微藻进行化学分析的基本原理是通过新的数据建模来补充，研究微藻在暴露于化学变化的生态系统中时对化合物的吸收和转化的能力。微藻在科学上的广泛影响表现在它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。化学计量学是一种用于提高对化学信息的理解和使用的数学和统计方法，与化学工作者密切相关，但由于对数学和计算机技能的要求，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。利用红外光谱和流式细胞术研究了微藻生物量在化学成分和数量上对环境的适应。此外，还开发了新的化学计量学建模策略来设计预测模型，将微藻的状态或化学特征与生态系统联系起来。这种实验和计算方法的结合使我们了解了生态系统内（人为）化合物的来源和汇。深入了解环境污染物与被污染环境中微藻之间的相互作用，对于了解生态系统的现状，甚至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。学生在这个项目中的训练弥合了分析化学和数据建模之间普遍存在的差距。在这个地理区域，缺乏服务的学生也有机会接触到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.