Gary Patti, Ph.D.

Michael and Tana Powell Associate Professor

Computational and Systems Biology Program
Biochemistry, Biophysics, and Structural Biology Program
Neurosciences Program

  • 314-935-3512

  • 1134



  • metabolomics, mass spectrometry, metabolic pathway, bioinformatic tools, metabolites, therapeutic metabolomics

  • Elucidating metabolic pathways involved in neuropathic pain and aging that may serve as novel therapeutic targets

Research Abstract:

Exciting advances in mass spectrometry have enabled systems-level analysis of metabolites and revealed a large number of endogenous molecules that do not fit into the canonical metabolic pathways typically represented in classical biochemistry textbooks. In this context, our laboratory is focused on extending our understanding of comprehensive metabolism and defining its association with physiology. By using state-ofthe-art mass spectrometry, we are interested in globally quantifying metabolite alterations in biological systems under perturbation (e.g., during disease). This approach, called metabolomics, is the newest of the "omic" profiling sciences. A major effort of our program is developing new technologies and methods to drive the field forward and to integrate other “omic” information, namely from genomics. Our program emphasizes the translation of our biochemical findings into a clinical context. Specifically, we are interested in elucidating metabolic pathways involved in neuropathic pain and aging that may serve as novel therapeutic targets. Other interests include developing bioinformatic tools to deconvolve large datasets, characterizing unknown metabolites with respect to structure, function, and pathway by using modeling, and examining metabolites in situ with complementary solid-state NMR approaches. Major technological directions can be categorized into three areas.

Optimization of Global Profiling. The goal of metabolomics is to simultaneously profile as many cellular metabolites as possible without bias. The physiochemical landscape of metabolites, however, is highly diverse ranging from large hydrophobic compounds like very-long chain fatty acids to small water-soluble metabolites such as choline. The methods used for isolation of metabolites from cells and for chromatographic separation greatly influence the chemical nature of the compounds detected. We are developing multiplexed approaches that exploit new chromatographic technologies to maximize global coverage and throughput efficiency.

Modeling by Isotopic Labeling. Model organisms offer exciting opportunities to track metabolism and define pathway connectivities by the introduction of specific stable isotopes. As a simple example, the conversion of 13C-labeled pyruvate to lactate can be quantitatively tracked as a function of time by considering the mass spectrometry determined ratios of labeled to unlabeled substrate and product. For multicellular organisms such as C. elegans worms and rodents in which a comprehensive metabolomic analysis is performed, however, the introduction of 13C labels creates significant bioinformatic challenges. We are focused on developing models to exploit these 13C mass shifts to study global pathway flux and to identify biochemically connected compounds, particularly metabolic pathways related to unknowns.

Mass Spectrometry-Based Metabolite Imaging. Liquid chromatography/mass spectrometry enables the detection of thousands of metabolites, but sample preparation requires cellular homogenization and thereby prevents mapping metabolite levels spatially within the sample. We have developed a novel mass spectrometry-based approach called nanostructure-initiator mass spectrometry (NIMS) in which biological specimens are placed onto a surface and imaged by laser desorption. Unlike MALDI which relies on a matrix, NIMS uses initiator molecules trapped in nanostructured surfaces to ionize intact compounds adsorbed on the surface. We are using NIMS to globally image metabolites in biological tissues and also designing new NIMS surfaces to spatially monitor chemical reactions for compound-specific applications. By applying these technologies, we have discovered a novel endogenous metabolite in the spinal cord of rats known as dimethylsphingosine (DMS). With metabolic profiling, we have shown that DMS increases in the dorsal horn of rats suffering from neuropathic pain and that inhibition of DMS production results in a significant mitigation of neuropathic pain symptoms. Future work is focused on discovering the mechanism by which DMS mediates pain, exploring the relevance of DMS in the human central nervous system tissue, and identifying related therapeutic targets with improved specificity.

Selected Publications:

Patti GJ, Yanes O, Siuzdak G. Metabolomics: The Apogee of the Omic Triology. Nature Reviews 2012 13: 263-269.

Patti GJ, Yanes O, Shriver L, Courade JP, Tautenhahn R, Manchester M, Siuzdak G. Metabolomics Implicates Altered Sphingolipids in Chronic Pain of Neuropathic Origin. Nature Chemical Biology 2012 8: 232-234.

Patti GJ, Tautenhahn R, Siuzdak G. Meta-Analysis of Untargeted Metabolomic Data from Multiple Profiling Experiments. Nature Protocols 2012 7(3): 508-516.

Patti GJ. Separation Strategies for Untargeted Metabolomics. Journal of Separation Science 2011 34(24): 3460-3469.

Patti GJ, Shriver L, Wassif CA, Woo HK, Uritboonthai W, Apon J, Manchester M, Porter FD, Siuzdak G. Nanostructure-Initiator Mass Spectrometry (NIMS) Imaging of Brain Cholesterol Metabolites in Smith-Lemli Opitz Syndrome. Neuroscience 2010 170(3): 858-864.
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