Research Interests:

Introduction: Why all the Phytochemicals?

Plants, as sessile organisms, must be able to cope with a broad array of stressful environmental conditions that motile organisms can overcome by simply changing location.   As a result, plants exhibit numerous chemical strategies to moderate environmental stress.  Plants cannot run away from herbivores, but many synthesize toxic or unpalatable chemicals as feeding deterrents.  Plants cannot relocate when nutrients are depleted, yet many can synthesize and excrete compounds into the soil that help liberate nutrients such as phosphate or iron as needed.  Other chemicals are synthesized that help provide protection from fungal or bacterial infection, excess UV light exposure, and freezing or drought conditions.  In addition, plants synthesize a wide array of chemicals to influence the behavior of other organisms.  The more obvious of these being pigment, odor and flavor compounds in fruits and flowers that promote pollination and seed dispersal.  Less apparent are the chemicals involved in interactions with other plants, fungi or bacteria.  Phytochemicals (chemicals produced by plants) that influence the behavior of other organisms are profoundly important to people, not just because of pharmaceutical or commercially useful compounds, but because of those that make up the colors, flavors and odors that effect the quality of our food and surroundings. 

Metabolomics to Study the Regulation of Secondary Metabolite Production.

My laboratory uses high throughput chemical analysis to measure hundreds to thousands of compounds simultaneously in plant extracts.  Conceptually, we attempt to make as many simultaneous unbiased measurements as is possible to allow analysis of metabolism in an entire biological system.  This methodology, called metabolomics is related to other systems biology approaches such as genomics and proteomics, which also attempt to provide comprehensive descriptions of the molecular status of a biological system as an initial step prior to formulation of hypotheses and more traditional lines of scientific inquiry.  The approach essentially looks at a biological system with new eyes provided by state of the art analytical technologies to create an image of a life processes that were not previously observable. We are interested in utilizing metabolomics to understand the means and regulation of production of secondary metabolites as a critical first step in finding out how an organism responds to its environment.  We have started our analysis of secondary metabolism in Arabidopsis thaliana because, from a molecular perspective, it is the best characterized plant systems.  As of 2005 there were over 170 secondary metabolites identified in Arabidopsis; this number was only 36 a decade earlier (D’Auria, J. C. and Gershenzon, J. (2005) Current Opinion in Plant Biology, 8: 308-316.).  There is reason to believe that the complete set of secondary metabolites has not yet been documented even in this well characterized system.  Our initial studies focus on a specific cell type called the trichome.  These cells form hair-like or branching structures that are present on the surfaces of many plants.  Often these cells are specialized for synthesizing secondary metabolites that are either stored at the leaf surface or excreted as an herbivore deterrent.  Trichomes are one of the few plant cell types (including pollen) that can be collected free from other contaminating cell types. 

Using Stable Isotopic Metabolic Labeling for Systems Biology.

Metabolomics is a fairly young discipline, which was conceived within the past decade in a post-genomics context.  Metabolomics depends heavily on rapidly changing analytical methodologies.  As a result, many of the resources for the field are still in development.  A major interest of mine for the past year has concerned the creation of isotope-assisted metabolomics tools and resources that can take advantage of our capacity to metabolically label plant materials with stable isotopes.  With our collaborators at the University of Wisconsin Madison Metabolomics Consortium (http://mmcd.nmrfam.wisc.edu/main.html ) we have described two strategies for increasing both the usable mass range, and the confidence of mass spectral feature formula assignments using isotopically labeled metabolites from plants.  These resources are publicly accessible at the Biological Magnetic Resonance Data Bank web site (http://www.bmrb.wisc.edu/metabolomics/ ).

Subtle changes protein or metabolite abundance can be measured in a high-throughput manner using stable isotopic labeling in combination with mass spectrometry.  Fundamentally, existing quantitative approaches rely on the incorporation of a stable isotopic label into peptides so that one can observe differences in a control versus test samples by comparing the intensities of matched pairs of mass spectral peaks.  These peaks correspond to chemically identical species that co-elute in all chromatographic steps (in the case of ¹⁵N and ¹³C labeled samples where the isotope effects are minimal), and share physico-chemical properties pertaining to ionization and detection in the spectrometer, yet are distinguishable by mass.  This allows one to compare relative quantities for all labeled species in a sample with distinguishable masses.  Metabolic labeling provides additional advantages with regard to sample preparation over other labeling strategies.  Heavy and light labeled tissues are mixed immediately following collection, and so the samples have the perfect internal control for protein extraction and fractionation that can be major sources of error for in vitro labeling approaches.

Selected Publications:

Hegeman, A. D., Schulte, C. F., Cui, Q., Lewis, I. A., Huttlin, E. L., Eghbalnia, H., Harms, A. C., Ulrich, E. L., Markley, J. L., and Sussman, M. R. (2007) Stable Isotope Assisted Assignment of Elemental Compositions for Metabolomics, Anal. Chem., 79(18), 6912-21.

Nelson, C. J., Huttlin, E. L., Hegeman, A. D., Harms, A. C., and Sussman, M. R. (2007) Implications of ¹⁵N-Metabolic Labeling for Automated Peptide Identification in Arabidopsis thaliana, Proteomics, 7(8), 1279-92.

Huttlin, E. L., Hegeman, A. D., Harms, A. C., and Sussman, M. R. (2007) Comparison of full versus partial metabolic labeling for quantitative proteomic analysis in Arabidopsis thaliana, Mol. Cell Proteomics, 6(5), 860-81.

Hegeman, A. D., Rodriguez, M., Han B. W., Uno, Y., Phillips G. N. Jr., Hrabak, E. M., John C. Cushman, Harper, J. F., Harmon, A. C., and Sussman, M. R. (2006) A phyloproteomic characterization of in vitro autophosphorylation in calcium-dependent protein kinases. Proteomics, 6(12), 3649-3664.

Nelson, C. J., Hegeman, A. D., Harms, A. C., and Sussman, M. R. (2006) A quantitative analysis of Arabidopsis plasma membrane using trypsin-catalyzed ¹⁸O labeling.  Mol. Cell Proteomics, 5(8), 1382-1395.

Pischke, M. S., Huttlin, E. L., Hegeman, A. D., and Sussman, M. R. (2006) A transcriptome-based characterization of habituation in plant tissue culture. Plant Physiol. 140(4), 1255-78.

Frey, P. A., Hegeman, A. D., and Reed, G. H. (2006) Free radical mechanisms in enzymology, Chem. Rev. 106(8), 3302-16.

Hegeman, A. D., Harms, A. C., Bunner, A. E., Harper, J. F., and Sussman, M. R. (2004) An isotope labeling strategy for quantifying the degree of phosphorylation at multiple sites in proteins, J. Am. Soc. Mass Spec. 15(5), 647-653.

Textbook:

Frey, P. A., and Hegeman, A. D., Enzymatic Reaction Mechanisms, January 27, 2007, Oxford University Press, New York, NY.