Automated Electrophoresis Platform to Streamline Validations of Biomedical Samples - ABSTRACT Development of a universal micro total analysis system (TAS) represents the pinnacle of measurement science. Integrating all aspects of sample preparation, analysis, and detection into an inexpensive, automated platform would streamline analyses and enable rapid validation of biomedical samples. The ideal TAS would not only validate the chemical composition of a biological sample, but also characterize higher order biomolecule structure (e.g. disulfide bonds, chirality, sulfation) to evaluate bioactivity. To date, though, these dreams have not been realized. Consequently, researchers must manually prepare samples for analyses that characterize sample purity, but assessments of biological activity often remain neglected. This time-consuming, incomplete sample validation risks biasing results of subsequent research studies. To help improve the rigor and reproducibility of NIH-sponsored projects, we propose to develop a universal TAS to provide researchers with a tool to rapidly validate biomedical samples, including evaluations of higher order biological structures that dictate activity. Thermal gel electrophoresis (TGE) will serve as the heart of the TAS. Our group developed TGE to enrich, separate, and detect biomolecules within a temperature-responsive gel, thus integrating multiple steps of an analytical method into an inexpensive microfluidic device. Building on our prior work, we propose to further expand our capabilities towards the ideal comprehensive TAS. Additional characterizations will be developed to screen the higher order structure of proteins, peptides, RNAs, and sugars with high selectivity and sensitivity that are inaccessible to other techniques (e.g. LC-MS). To streamline analyses, sample preparation capabilities will be integrated into devices to filter cells, desalt samples, and label analytes for detection. This approach will enable direct analysis of biological samples on-chip, obviating the need for external sample pretreatment by the user. Additionally, label-free detection schemes will be developed to further expedite analyses and simplify operational constraints. Collectively, the innovative analytical strategies developed here will provide a convenient, inexpensive means of characterizing biomedical samples that cannot be achieved by other techniques. Ultimately, we envision our TGE-based TAS platform will make robust sample validation accessible to researchers, which will increase reproducibility of biological studies in academic, government, and industry laboratories.
