Abdallah M. Zeid, Ph.D. Analytical Chemistry 2017, Mansoura University. Neuropeptides and peptide hormones have a great role in communication between cells, acting as neurotransmitters and neuromodulators. Therefore, in vivo analysis of neuropeptides in the brain could efficiently participate in understanding many neurological disorders such as epilepsy, schizophrenia, Parkinson’s disease, and neuropathic pain. My project focuses on understanding the mechanism of certain neurological disorders via ultrasensitive LC-MS in vivo determination of neuropeptides and their metabolites in the brain using a novel microfluidic-based microdialysis probe. Sensitivity enhancement and recovery improvement of the target analytes in the microdialysate samples are among the main aims of the current project.

Caitlin Cain, PhD in Chemistry 2024, University of Washington. Developing novel non-targeted data analysis tools for chromatographic data can provide analysts with a comprehensive chemical profile. These methods can be applied to a variety of data sets to improve the discovery of potential marker analytes and uncover hidden sample-to-sample relationships. My work focuses on the application of state-of-the-art LC technology and chemometrics to examine the dynamics of brain chemistry and correlate metabolomic mechanisms to behavior.

Gillian Robbins, B.S., M.S., Microbiology and Cell Science, Chemistry, Oceanography 2010.  Mass Spectrometry is a necessary tool for label-free biological detection and quantification. My project improves sample detection by mass spectrometry through segmented flow, from engineered droplet microfluidic devices that remove complex matrices. The utilization of these droplet extraction systems will ultimately improve detection in high throughput screening and clinical assays, as well as other types of applications that require sample matrix removal.

Yue Xin, B.A. Chemistry, Jilin University, 2021. High throughput experimentation (HTE) in organic synthesis may allow testing thousands of reactions in a day with a reduced scale which saves our time, labor, and substrates in a limited supply, especially in the early stage of drug discovery. The implementation of HTE using droplet microfluidics will theoretically achieve unlimited tests of tens of thousands of reactant combinations with little material consumption and human labor. The droplet microfluidics method can also be used to improve the sample injection efficiency of UHPLC by replacing the traditional autosampler which has an issue of long cycle time. Therefore, the overall LC performance will depend on the chromatographic run instead of sample injection.

Ian Bain, B.S. Chemistry and Mathematics, University of South Carolina, 2021. Measuring neurochemical dynamics is essential to furthering our understanding of the brain. Ideal neurochemical measurements must be sensitive, and fast enough to capture the speed of neurochemical changes. My work focuses on utilizing mass spectrometry coupled with microfluidics to create a sensitive, multiplexed, and high temporal resolution screening method for compounds in the brain.

Brianna Ramos, B.S. Biology, California State University Channel Islands, 2021. Neurotransmitters are metabolites known to be able to communicate between neurons in the brain. Neurochemical characterization is a fundamental part of being able to monitor neurotransmitter changes in the brain that elicit various behavioral phenotypes. Therefore, metabolomic studies provide a broad picture of the chemistry composition that underlies the brain and its neural circuitry. I plan to use both microdialysis methods in vivo and a novel method developed from this lab based on LC-MS/MS that utilizes benzoyl chloride labeling. This labeling approach will improve retention on reversed-phase LC, sensitivity by 10-1500 fold, depending on the compound, and quantify using 13C-BzCl to make internal standards. We do this because neurotransmitters have various identities as well as different psychochemical properties. My goal is to unveil the baseline neurochemical profiles for multiple brain regions associated with decision-based behavioral responses and improve sensitivity of the neurochemical output signals detected.

Tate Hancock, B.A. Chemistry and Biochemistry, Augustana College, 2022. Liquid chromatography coupled with mass spectrometry (LC-MS) is an essential technique for separation and analysis of complex mixtures. Current efforts for performing more efficient separations have been to use long capillary columns packed with sub 2 micron particles, which require separation pressures in excess of 15,000 psi to operate. My project involves modifying our custom ultra-high pressure liquid chromatography (UHPLC) system to achieve unrivaled separation performance with capillary columns for omics based applications.

Laura Penabad, B.S. Chemistry 2022 University of Puerto Rico. Droplet microfluidics coupled to mass spectrometry (droplet MS) allows us to obtain data rich high-throughput screening of synthetic reactions. My thesis focuses on developing coupling platforms between microfluidics and ion mobility mass spectrometry to carry out high throughput screening. The main application of this coupling is to screen for structural isomers of products from bioengineered syntheses-refining, resulting in the obtention of both a CCS and m/z value per the product of interest. In combination with this, my project involves developing methods of droplet generation and manipulation to further expand the applicability of droplet microfluidics in earlier stages of the screening process, such as sample isolation, identification, and incubation. 

Kaley Simcox, B.S. Chemistry 2022, Appalachian State University. RNA modifications have the ability to alter every stage of the RNA life cycle including translation, stability, and splicing; thus, knowing what modifications exist and where they are located within an RNA is crucial to understand their role within the cell. These chemical modifications are still being discovered today, but these methods are low-throughput and lack structural information. I plan to use LC-MS/MS to identify unknown tRNA modifications and sequence them within complex tRNA mixtures. This will enable downstream analyses to elucidate the molecular level consequences of the RNA modification landscape.

Riley Stegmaier, B.S. Chemistry 2023, University of Kansas. Liquid Chromatography is a powerful technique for probing various molecular properties. This ability is especially useful in the field of polymer chemistry, where new materials are being designed to fit specific needs, such as biodegradability. These materials are often complex mixtures that contain a distribution of molecular weights and chemical compositions. These distributions can be understood through the analysis of retention behavior on various LC stationary phases. A greater understanding of a material’s property distributions can be uncovered using multiple separation mechanisms in two-dimensional liquid chromatography. Through the development of these challenging separations, a greater understanding of material degradation will be gained so that properties can be tuned to ensure suitable biodegradation.

G. Thomas Knecht, B.S. Chemistry 2023, University of Central Florida. Liquid chromatography (LC) is the most significant separation method for bioanalysis and drug development, providing crucial specificity and efficiency. Droplet microfluidics is an emerging field focused on high-throughput analysis of samples encapsulated in small volumes (nL – pL). By coupling the two analytical techniques, a system is achieved with the separatory performance of LC and the throughput of droplet microfluidics. My research focuses on developing and improving the efficiency, speed, and scalability of this fast-LC platform from an instrumental perspective.

Tyler Somerville, B.S. Chemistry 2023, Lake Superior State University. Liquid chromatography is an extremely useful tool for separating and characterizing complex mixtures. This is especially true for polymer analysis. Polymers are complex molecules that vary in molecular weight and chemical composition leading to applications across many industries. High resolution separation of oligomers will help to elucidate biodegradation pathways/mechanisms making it possible to assess environmental fate. My work involves developing 1D and 2D LC separations to gain a fundamental understanding of the complexity of these molecules and how polymer structure ultimately affects bioavailability. 

Max Unger, B.S. Chemistry 2023, University of Wisconsin – Madison. Directed evolution of proteins has been popularized in the last two decades as a method for expediting natural evolutionary processes for a desired function. Present methods for analyzing the outputs of mutant enzymes require either designing a system with a fluorescence readout for HTS or low-throughput plate-based screening which is both time- and cost-intensive. This causes a bottleneck in the engineering of proteins for improved or novel functions. Microfluidics coupled to mass spectrometry is a promising alternative that circumvents the need for fluorescence labels and plate based assays. My thesis work looks to evolve biocatalytic enzymes using microfluidics coupled to mass spectrometry to rapidly discover beneficial mutations that can unlock green synthetic routes to assembling both complex natural product scaffolds and ligands for asymmetric catalysis.

Tien Phan, B.S. Chemistry and Neuroscience 2023, University of North Carolina at Chapel Hill. Plastic products can contain a multitude of chemical contaminants such as impurities and reaction or degradation byproducts, many whose structures and toxicological effects are unknown. Often called non-intentionally added substances (NIAS), these contaminants are not bound to the polymer matrices of the plastic products, resulting in migration into consumer products such as everyday food stored in plastic packaging. My work is interested in developing a more rigorous liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) workflow for the screening and structural identification of NIAS in plastic food contact articles by utilizing high resolution and multidimensional separations, high resolution mass spectrometry, and more rigorous data processing tools to increase the confidence of “hits” while limiting false identifications. 

Ryan Snyder, B.S. Chemistry 2023, Wayne State University. Droplet microfluidics coupled to mass spectrometry represents a cutting-edge approach for high-throughput experimentation. This technique holds immense potential to accelerate reaction screening in chemical synthesis, which has historically been a time- and resource-intensive process. Specifically, photoredox reactions are of interest because they have found widespread application in the synthesis of pharmaceutically relevant molecules. Integrating droplet microfluidics with mass spectrometry enables the in-flow discovery and optimization of photochemical reactions on picomolar scale. My thesis ties reaction miniaturization and high-throughput mass spectrometry to existing technologies for continuous-flow photocatalysis through collaborative efforts with an industrial partner.

Lauren Barnes, B.S. Chemistry 2022, Ohio Wesleyan University. RNA modifications play important roles in a number of cellular processes ranging from protein synthesis to immune responses. These modifications are also associated with numerous diseases including diabetes and several forms of cancer. Despite their importance, the technologies for sequencing RNA modifications are highly limited. My work focuses on developing LC-MS/MS based methods for RNA sequencing and quantification.

Baker Angstman, B.S. Chemistry, Middlebury College, 2024. Quantifying neurochemical dynamics is essential for understanding how brain chemistry relates to behavior, emotion, and neurological disorders. Droplet microfluidics paired with nano-electrospray ionization (nESI) mass spectrometry is a powerful method for measuring in vivo neurotransmitter concentrations over time. However, many neurotransmitters exist at very low concentrations, making their quantification analytically challenging. My work aims to improve the sensitivity of nESI mass spectrometry for measuring neurotransmitter concentrations, enabling simultaneous quantification of more neurotransmitters with high temporal resolution.

Juan C. Vázquez López, B. S. Chemistry, University of Puerto Rico Río Piedras, 2020.  Modified polysaccharides present desirable features in comparison to their unmodified counterparts, such as improved biocompatibility, increased biological activity, and better stability. However, a better understanding is necessary for both their biodegradation pathways and products. Liquid chromatography coupled to mass spectrometry (LC/MS) presents itself as an essential technique for accurately identifying and quantifying these modified species. My work focuses on developing strategies for the dissociation of these polysaccharides into their constituting oligosaccharides, while also developing LC/MS methodologies for their identification and quantification.

Sydney Neibert, B.S. Chemistry 2024, Harvey Mudd College. Synthetic biology employing directed evolution (DE) has been demonstrated as a powerful method for developing organisms that produce desired chemical products. DE is achieved by iterative rounds of genetic mutation, screening for activity of interests, and selection of desired phenotypes. In DE of proteins, droplet microfluidics coupled to mass spectrometry has shown to be a fast, label-free method to screen and sort variant libraries for potential activity. My work aims to employ mass spectrometry techniques coupled with ion mobility—such as collision induced unfolding—as another metric to evaluate the evolvability of enzymes after each round of engineering.

Trevor Kempen, B.A. Chemistry, Gustavus Adolphus College, 2024. Microfluidic droplet-based reactions are a promising platform that dramatically increase the speed and efficiency of high-throughput reaction screening procedures. My work focuses on the development of closed-loop, self-driving systems that integrate real-time analysis, intelligent decision-making algorithms, and automated control to accelerate chemical reaction discovery and optimization. These systems significantly reduce the time and resources required to explore large experimental spaces, enabling the rapid development of datasets that are suitable for data-driven approaches to reaction development.