Research
Overview
Measuring chemical exposure is extremely challenging due to the range and number of anthropogenic molecules encountered in our daily lives as well as their complex transformations throughout the body. To broadly characterize how chemical exposures influence human health, a combination of genomic, transcriptomic, proteomic, endogenous metabolomic, and xenobiotic measurements must be performed to understand the different molecular changes occurring. However, while genomic, transcriptomic, and proteomic analyses have rapidly progressed over the last two decades, neither xenobiotic nor endogenous metabolite small molecule measurements have advanced to as great of a degree, even though they are essential for the direct analysis of chemical exposure.
Therefore, the Baker Group is working to develop and optimize new analytical and computational approaches for these measurements. Specifically, they are using various combinations of separation methods including automated solid phase extractions, liquid chromatography, supercritical fluid chromatography, ion mobility spectrometry and mass spectrometry to enable the analysis of thousands of longitudinal samples over the lifetime of exposure.
These analyses allow the assessment of both xenobiotic and endogenous molecular changes to probe the perturbations occurring. Additionally, the Baker Group is creating computational software programs and approaches using R, Python, Java and machine learning for the evaluation and visualization of the molecules they have detected and samples they have analyzed. These new computational capabilities are enabling improved mining of the data and more associations to be formed in the populations studied.
Finally, the Baker Group is extremely passionate about promoting their research and STEM careers to the general public through community engagement and outreach. Thus, they present at various international and local conferences and are excited to get into K-12 schools once the pandemic has lessened.
Individual Research Areas
Jessie’s work is focused on determining the best statistical approaches to use on high dimensional mass spectrometry datasets. This has included developing a scoring scheme for analyzing human tissue sections using MS imaging, streamlining feature identification in ion mobility spectrometry data, and analyzing lipids that are impacted by PFAS exposure.
Jack’s research is focused on developing and using LC-IMS-MS methods to study a variety of biologically relevant molecules, with a particular focus on leveraging IMS to elucidate structural differences present in the gas phase. Currently, he is working on using gas phase separation to optimize oligonucleotide sequencing, as well as to explore the lipidome of membrane protein complexes. Additionally, he is interested in using alternative ion mobility platforms, such as SLIM based travelling wave for improved gas phase separations.
Anna’s research centers around the theme of applying non-targeted analytical techniques to evaluate PFAS in environmental samples. Broadly, she hopes to better understand how people get exposed to PFAS, and to increase awareness of PFAS presence in ecosystems. She has assessed PFAS in locally caught fish to better understand what contaminants recreational fishers might be exposed to. She is currently evaluating PFAS in alligator samples to see how PFAS levels are changing over time in these animals and to search for novel PFAS.
James’s research focuses primarily on using LC-IMS-MS to characterize and evaluate environmental contaminants, most recently utilizing passive samplers for PFAS characterization in the Cape Fear River. James is also heavily focused on assessing instrument performance, and in 2024 will be evaluating the new lab’s new MOBILion system and its capabilities for future research. In addition to his own studies, James attempts to provide mentorship for the graduate students and fills in for Erin’s teaching when she’s away at conferences.
Amie’s research interests lie in studying lipids and ion mobility mass spec. Her first project involved studying California sea lions with a neurological condition called domoic acid toxicosis to look for lipid biomarkers for better diagnostics. Currently, she is working on developing an untargeted LC-IMS-MS method for detecting lipid mediators, which are responsible for inflammation and immune response in the body, but are challenging to analyze due to their low concentrations and numerous isomeric structures.
Greg is looking into how to quantify and detect PFAS in microliter-scale blood samples with new sampling devices. Following on from that, he is trying to determine if there’s correlation between PFAS found and autoimmune diseases diagnosed in twins. His primary interests in researching are – optimizing methods (he love being in the lab!), using Python to make my life easier (cause who wants to write out each line of a worklist?), and using R to make pretty figures that can help tell a story with all the data he’s collected.
Ashlee’s research bridges the group’s interests in PFAS and lipidomics by applying LC-IMS-MS techniques to biological and environmental samples for the analysis of PFAS exposure and correlating lipidomic disruptions. She is currently evaluating associations between PFAS accumulation and lipidomic changes in people having drinking water exposure and occupational exposure as firefighters. Future interests of Ashlee’s include analyzing tree samples from controlled wildfire simulation experiments for PFAS to better understand PFAS release during naturally occurring wildfires.
Kara’s research centers around PFAS in mammalian milk, including human breastmilk. She is currently working to optimize both PFAS and lipid extraction protocols specific to milk. In this future, these analyses will provide important information for exposed populations and may inform a strategy for removal of PFAS from milk.
Emily’s current research focuses on the detection of antidepressants (ADs) and their metabolites in environmental and biological samples. Current wastewater treatment plants lack effective methods to remove ADs and their by-products from wastewater, allowing them to contaminate many environmental matrices (including our tap water). Emily is developing a method to quantify the amount of ADs in environmental samples in order to assess the risk of excess human exposure
Allison’s research bridges using analytical experiments for data collection in tandem with computational approaches for data analysis. Currently, Allison is investigating the impact of PFOA exposure on immune response to the SARS-CoV-2 virus in ferrets. In addition to collecting LC-IMS-MS data in-lab, Allison enjoys finding new ways to incorporate biostatistics, programming, and molecular modeling into her research.
Haley’s work revolves around evaluating lipidomic dysregulation within mice that have been exposed to various biomass burn conditions using an LC-IMS-CID-MS method. She is currently working on analyzing data from plasma and lung tissue samples. Ultimately, this research seeks to inform how wildfires impact public health.
Sarah’s research focuses on the brain-bone connection and how Alzheimer’s Disease (AD) impacts lipids in bone marrow. She is currently optimizing a method using LC-IMS-CID-MS to evaluate the lipidome of bone marrow extracts in mice with varying isoforms of the apolipoprotein E (APOE) gene, which is a leading genetic cause of AD. Through this project, Sarah hopes to discover lipid biomarkers for AD diagnosis.