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

University Of Tennessee Knoxville, Knoxville TN

Investigators

Abstract

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.