Research Overview
The Garrett Laboratory develops and applies cutting-edge mass spectrometry methods for metabolomics and lipidomics research in clinical applications. Our work spans cancer research, rare diseases, autoimmune disorders, and the microbiome. We focus on both technological innovation—creating new analytical tools and bioinformatic platforms—and collaborative translational research that can impact patient care.
A little bit about the metabolome. It describes all the small molecules present at a given time in a given system. Metabolomics and lipidomics are the analytical study of small molecules that are the result of enzymatic pathways, chemical reactions or external stimuli. Metabolites represent the closest phenotype for human disease because they are rapidly changed because of cellular activity.
The Omics Cascade begins with the Genome (DNA), then moves to the transcriptome (mRNA), which interacts with the Proteome and finally ends with the Metabolome. This represents enzymatically derived metabolites, but the metabolome also includes metabolites from the environment and those from chemical reactions. It is important because it is the closest the the phenotype of an individual.
Recent Research Highlights (2022-2024)
1. Insulin Thermostability Studies
Impact: This work is changing global policy on insulin storage, particularly for people living in hot climates and humanitarian crisis situations.
Key Findings: Our research demonstrated that commercial insulin formulations maintain stability well beyond manufacturer recommendations when exposed to higher temperatures. In our 2024 study published in Diabetes Care, we found that both Humulin-R and insulin glargine remained stable at room temperature for at least 6 months, and maintained activity for extended periods even at elevated temperatures.
Figure Description: Time-course stability data showing insulin concentrations over 365 days under different storage conditions (4°C, room temperature cycling, and 42°C). The data demonstrates that insulin maintains USP-specified potency (100 ± 5 U/mL) for much longer than previously thought at non-refrigerated temperatures.
Clinical Significance: These findings are particularly important for individuals with diabetes in resource-limited settings, hot climates, or during emergencies where refrigeration is unavailable. Our work provides evidence that short-term exposure to higher temperatures may not necessitate immediate disposal of insulin.
Publications:
- Christopher MW, et al. Diabetes Care 2024;47(12):e104-e105
- Pendsey S, James S, Garrett TJ, et al. Lancet Diabetes Endocrinol 2023;11:310-312
2. The Tautomeric Metabolome: Discovery of Novel Metabolites
Breakthrough: We’ve pioneered the study of what we call the “Tautomeric Metabolome”—metabolites that exist in multiple structural forms that can have different biological activities.
Key Innovation: Using advanced mass spectrometry techniques including hydrogen-deuterium exchange coupled with high-resolution MS/MS (HDX-HRMS/MS), we can now distinguish and characterize tautomeric forms of metabolites. Our 2024 publication in Analytical Chemistry describes the divergent metabolic fates of indole-3-pyruvate (IPyA), a tryptophan-derived metabolite.
Figure Description: Workflow diagram showing: (1) Ex vivo metabolism of enol and keto tautomers of indole-3-pyruvate in whole blood, (2) Discovery of two new metabolic products via UHPLC-HRMS, including glutathionyl-indole pyruvate (GSHIPyA), (3) HDX-HRMS/MS approach proving GSHIPyA exists as both enol and keto tautomers with distinct chemical properties.
Biological Significance: We discovered that the enol form of IPyA specifically forms GSHIPyA through conjugation with glutathione, suggesting tautomer-specific metabolism. One identified marker has been implicated as an oncometabolite, potentially leading to new therapeutic targets in cancer.
Technical Achievement: This research develops new analytical methods to investigate enzyme activity and identify tautomers that were previously indistinguishable by standard metabolomics approaches.
Publication:
- Christopher MW, Ericson AC, Klug AC, Dinglasan RR, Prentice BM, Garrett TJ. Analytical Chemistry 2024;96(42):16917-16925
3. LipidMatch: Open-Source Lipidomics Software Platform
Innovation: We developed LipidMatch, a comprehensive open-source software suite for lipid identification and quantification that has become widely adopted in the metabolomics community.
Key Features:
- Contains over 250,000 lipid species spanning 56 lipid classes in in silico fragmentation libraries
- Uses rule-based identification from high-resolution tandem mass spectrometry data
- Covers unique lipid classes including oxidized lipids, bile acids, sphingosines, and specialized adducts
- Vendor-neutral and integrates with multiple data processing platforms
Figure Description: Workflow diagram showing the LipidMatch pipeline: (1) Data acquisition via LC-HRMS/MS, (2) Feature detection and alignment, (3) Tandem MS fragmentation using data-dependent or data-independent methods, (4) Rule-based lipid identification using comprehensive fragmentation libraries, (5) Scoring and ranking of identifications, (6) Integration with statistical analysis tools.
Impact: LipidMatch has improved lipid annotation by over 50% compared to previous methods and enables researchers worldwide to conduct comprehensive lipidomics studies. The software is freely available and has been cited extensively in the scientific literature.
Companion Tools:
- LipidMatch Flow: User-friendly interface covering the entire data-processing workflow
- LipidMatch Normalizer: Automated relative quantification using internal standards
- Iterative Exclusion (IE Omics): Deep characterization method for comprehensive metabolite coverage
Publications:
- Koelmel JP, Kroeger NM, Ulmer CZ, et al. BMC Bioinformatics 2017;18:331
- Koelmel JP, Cochran JA, et al. BMC Bioinformatics 2019 (LipidMatch Normalizer)
4. Clinical Metabolomics Applications
Our laboratory applies metabolomics and lipidomics across diverse clinical areas:
Newborn Screening: We were awarded $4 million from the CDC to establish a National Center of Excellence in Newborn Screening at the Florida Department of Health. We developed internal quantitative dried blood spots (iqDBS), which was filed as a US Patent in 2024.
Cancer Metabolism:
- Glioblastoma treatment response prediction using serum metabolomics
- Prostate cancer detection using paper spray ionization mass spectrometry
- Metabolic profiling in various cancer types
Microbiome-Host Interactions:
- Studies linking infant gut microbes and metabolites to neurodevelopmental disorders (Cell 2024)
- Tryptophan/kynurenine metabolism in wound healing and immune function
- Microbiota-associated metabolites in Type 1 diabetes
Rare Diseases: Identification of novel genetic defects and metabolic pathways, including work on lipid pathway abnormalities associated with Fabry disease variants.
Research Approach
Technology Development
- High-resolution mass spectrometry (LC-HRMS/MS)
- Imaging mass spectrometry (MALDI, DESI)
- Paper spray ionization for rapid analysis
- Novel data acquisition strategies (Iterative Exclusion MS/MS)
Bioinformatics Innovation
- Open-source software development (LipidMatch suite)
- Quality control metrics for metabolomics
- Automated data processing workflows
- Integration with statistical analysis platforms
Collaborative Science
With over $39M in funding as PI or Co-PI, we emphasize collaborative research partnerships across academia, industry, and clinical settings to translate discoveries into real-world applications.
Laboratory Impact
- 120+ peer-reviewed publications (h-index: 46, over 7,000 citations)
- 18 graduate students and 3 postdoctoral fellows supervised
- Co-Director of SECIM, an NIH regional comprehensive metabolomics resource center
- Co-Editor-in-Chief, Journal of Mass Spectrometry and Advances in the Clinical Lab (JMSACL)
- Educational leadership: Developed metabolomics training programs including Winter and Summer schools, workshops on statistical analysis and new technologies
Future Directions
Looking ahead, we envision metabolomics incorporating:
- Artificial intelligence for data processing, metabolite identification, and experimental design
- Advanced separation technologies combining chromatography with ion mobility
- Enhanced methods for novel metabolite discovery
- Translation of research findings to clinical diagnostics
Our goal is to continue developing tools and approaches that enable the research community to make better discoveries and ultimately improve human health through metabolomics and lipidomics.
For more information:
- SECIM: https://secim.ufl.edu
- Software Tools: https://secim.ufl.edu/secim-tools/