Metabolomics Core

Core Director: Wai-Nang Paul Lee, MD
Co-Director: Kym Faull, PhD
Co-Principle Investigator: Laszlo G. Boros, MD

Contact information: WN Paul Lee wlee@labiomed.org

1. Introduction: Metabolic Profiling and Tracer-based Metabolomics
2. Purpose and Aims of Metabolomics Core
3. Methodologies
4. Equipments
5. Center of Excellence Projects
6. Progress Report (Please also see Center Publications and Abstracts)
7. Utilization of the Core
8. Research Proposals and Pending Projects

1) Introduction

Metabolite Profiling

- System with linear pathways is typical object of molecular biology and biochemistry studies.
- Such a system is amenable to Metabolic Control Analysis (MCA). which predicts the distribution of metabolites is a systems property. The distribution can be linked to phenotypic characteristics by association. However, there are insufficient measurements to construct a predictive model.

• Metabolic Profiling

- The traditional analysis of pathways assumes all other components of the biochemical system are held constant. When pathways share common cofactors and/or intermediates, the pathways are considered to be constrained. In a constrained system, the flux through any single pathway depends on the fluxes through all other connected pathways.

- Distribution of metabolites is a poor reflection of the enzyme functional capacity or the system’s behavior. For example, the distribution of metabolites may be the same in a cell over a wide range of substrate fluxes. In order to assess the functional properties of a metabolic network, it is important to determine the utilization and production relationship between metabolites in a cellular network of metabolic reactions.

• Profiling of Constrained Pathways (Tracer-based Metabolomics)

- In a living cell, such pathways form a closed system. The system behavior can be described by its input and output (precursor/product) relationship.
- When substrate input is labeled with ¹³C, the distribution of ¹³C in the intermediates reflects the relative importance of the pathways. The accumulation of labeled substrates for a given input is a systems property. The use of stable isotope tracers and mass isotopomer analysis are the basic tools of tracer-based Metabolomics. (www.ncbi.nlm.nih.gov/pubmed/20713038)

- There are three important considerations given such a system of pathways. These are: system optimality, system constraints and the context within which the system is defined.
- The system can be defined at many levels such as subcellular (e.g. mitochondrial), cellular, multicellular, organ, and whole animal. The system optimality and constraints are context dependent parameters.

- In order for a cell to replicate itself, precise amounts of DNA/RNA, membrane lipids and proteins are produced from varying amounts of amino acids, sugars and fatty acids. This process of taking different amounts of precursors to produce the required composition of products is known as optimization. (www.intechopen.com/books/metabolomics/metabolic-pathways-as-targets-for-drug-screening)

• Tracer-based Approach to Metabolomics of Metabolic Network

- There are three important considerations given such a system of pathways, These are: system optimality, system constraints and the context within which the system is defined.
- The system can be defined at many levels such as subcellular (e.g. mitochondrial), cellular, multicellular, organ, and whole animal. The system optimality and constraints are context dependent parameters.

• Phenotypic Phase Plane Analysis (Optimization)

- In order for a cell to replicate itself, precise amounts of DNA/RNA, membrane lipids and proteins are produced from varying amounts of amino acids, sugars and fatty acids.
- This process of taking different amounts of precursors to produce the required composition of products is known as optimization

• Tracer-based Approach to Metabolomics of Metabolic Network

-The use of specific ¹³C labeled precursors to trace the distribution of ¹³C in various metabolites is the basis of tracer-based metabolomics. Since the distribution of ¹³C in metabolic intermediates is dependent on the pathways that it has traveled, the resultant isotopomers are themselves unique metabolites, and the distribution of isotopomers is the direct result of the multiple interactions among connected pathways.

Currently, the Metabolomics Core has extensive experience with modeling the glycolytic/ gluconeogenic and pentose pathways. We have been able to determine mass isotopomers in ribose, deoxyribose, glycogen, lactate, fructose and glycerol using GC/MS. The mass isotopomer distributions among these metabolites provide detail information of the metabolic network which would otherwise be impossible based on metabolite concentrations alone.

Similarly, we have developed GC/MS methods to tracer mitochondrial metabolism and lipid metabolic pathways. Mitochondrial functions are reflected by isotopomers generated from pyruvate carboxylase/pyruvate dehydrogenase, anaplerotic flux, malate and citrate cycling. These parameters are accurately reflected by ¹³C labeling in the various amino acids such as aspartate and glutamate. Furthermore, methyl-donor metabolism is reflected by isotopomers of glycine and serine as well as those of purines and pyrimidines.

Fatty acids metabolic pathways such as those of beta-oxidation, chain elongation and chain shortening, desaturation can be modeled using mass isotopomer distribution analysis using specific labeled ¹³C fatty acids or glucose (ref). Lipid turnover can be studied using deuterated water method.

2) Purpose and Aims of Metabolomics Core

Purpose of the core
The purpose of the Metabolomics Core is to provide metabolic profiling for the NCCAM Center of Excellence investigators

To understand the role of metabolism in the genesis of cellular phenotypes, and
To understand the effects of phytonutrients on the selection of cellular phenotypes.

Specific Objectives and Aims
The following specific objectives will be the aims of the Core:

To study metabolic pathways and flux with stable isotope 13C and 2H labeled compounds using GC/MS and LC/MS/MS analysis;
To measure with stable isotope tracers whole body or organ balance of carbohydrate, protein, amino acid, or lipid uptake or production.
To measure changes in metabolic flux and substrate balance in response to exogenous hormones or diets in collaboration with the Animal Physiology Core, and
To develop new mass spectrometric methods for metabolic profiling and substrate kinetic analyses.

3) Methodologies

Non-targeted global GCMS and LCMS metabolite screening protocols have been developed in addition to several targeted LC/MS-MRM protocols. The existing protocols are listed below.

Global metabolite screening by GC/MS and LC/MS. Methyloxime-TMS derivatives are used for GCMS, positive and negative ion screening is used for LCMS. Tissue homogenates, cell cultures and their extra-cellular fluid, CSF and plasma are screened for amino acids, organic acids including fatty acids, polyamines and neutral compounds such as sugars and sugar alcohols.

Redox cycle components – Including cysteine, cysteine, cystathionine, reduced and oxidized glutathione, homocysteine, a-glutamylcysteine, and lactoylglutathionine, and their precursors glycine and glutamic acid. This is an LC/MS/MS-MRM protocol. Free thiol blocking is accomplished with 4-vinylpyridine, methyl esters are prepared with methanolic HCl and an ion-paring reagent in the LC effluent greatly helps with chromatography.

Nucleotides, nucleosides and related compounds. We have developed a comprehensive quantitative LC-ESI-MS/MS-MRM screen for 14 different nucleosoides and nucleotides including adenosine, guanosine, 5-methyluridine, uridine, cytidine, deoxyadenosine, deoxyguanosine, deoxythymidine, deoxycytidine, 5-methyl-deoxycytidine, 5-hydroxymethyl-deoxycytidine, inosine, xanthine, and hypoxanthine using N6-methyldeoxyadenosine as an internal standard.

Fatty acids and related compounds. GCMS analysis of fatty acid methyl esters and related compounds is widely used and is up-and running in the laboratory.

Cholesteryl esters and Sulfated lipids. ESI in the presence of ammonium acetate gives strong signals for the (M+NH4)+ ions from cholesteryl esters, all of which upon CAD give a single signal corresponding to loss of the labile ester function at m/z 369 (C27H45). Consequently, the parent scan mode on a triple quadrupole instrument (reverse phase LC-ESI-MS/MS) is used to profile these compounds in lipid extracts via reverse phase LC. The sulfated lipids sulfatide and sulfogalactosylglycerolipid upon CAD both give a strong fragment ion for the sulfate anion at m/z 97 (HSO4-). Consequently we use parent ion scans on the triple quadrupole instrument to profile these compounds in urine and tissue extracts.

Mass isotopomer profiling. Mass isotopomer profiling is the basic technology for tracer-based metablomics. The general profiling and mass isotopomer methods differ in the scanning methods employed. The method for profiling of glucose metabolic pathways, TCA cycle and pentose cycle has been published. Glucose labeled with ¹³C ([U¹³C₆]-glucose or [1, 2 ¹³C₂]-glucose has been used to introduce ¹³C into glucose metabolic intermediates. Cell or tissue extracts, and culture media are processed as in targeted metabolomics. In general with metabolite profiling, GC peaks are first identified by the respective retention times and spectral characteristics using spectral data libraries. Once that has been determined, the total ion chromatogram or more usually reconstructed individual selected ion traces, are used for comparing the relative concentration of metabolites in a sample. In mass isotopomer profiling, we first determine the retention time for the particular compound, then we carefully monitor the molecular ion and its accompanying isotope peaks to profile the mass isotopomer distribution. This process is repeated for all compounds of interest with their associated isotope peaks. If intense fragment ions are available, the isotopomer distribution of the fragment can be used to provide additional information regarding label position. Different isotope precursors such as uniformly labeled fatty acids can be used to generate isotopomers for profiling of other metabolic systems.

4) Equipments

Currently, the complete array of available instruments to support the work of the core includes three Agilent 5973 GC/MS’s, a Waters GC-TOF, and six LC/MS and hybrid LC/MS (2 Agilent 6460 triple quad, 1 Agilent 6540 hybrid Q-TOF, 1 Applied Biosystem Q-TOF (Q-Star XL), and 2 Applied Biosystems triple quads (ABI 5000)) instruments. This suite of equipment and the complementary expertise of Dr. Faull in global metabolite profiling and Dr. Lee in tracer-based metabolomics will be jointly applied to provide a wide range of metabolomics expertise and services of the Technology Core.

5) Center of Excellence Projects

• Project 1 – Phytochemicals and Metabolism in Pancreatic Diseases (Stephen J. Pandol, PI)

- Phytochemicals: rottlerin, ellagic acid, emblin

- Pathways: pentose synthesis (oxidative and non-oxidative pathways), tricarboxylic acid cycle (anaplerotic and cataplerotic pathways), fatty acid synthesis (de novo lipogeneisis, desaturation, chain elongation, b-oxidation).

- Tracers: [1, 2 ¹³C₂]-glucose, U¹³C-stearate

- Metabolites (isotopomers): ribose, deoxyribose, amino acids, palmitate, stearate, oleate and arachidate

• Project 2 – Polyphenols Regulate Lipid Inflammatory Processes in Pancreatic Cancer (Diane M. Harris, PI)

- Phytochemicals: green tea polyphenols

- Pathways: pentose synthesis (oxidative and non-oxidative pathways), essential fatty acid metabolism ( desaturation, chain elongation, b-oxidation).

- Tracers: deuterated water (D₂O) and U¹³C-linoleic

- Metabolites (isotopomers): ribose, deoxyribose, palmitate, arachidonic acid, and eicosanoids

• Project 3 – Flavonoids in Pancreatic Carcinogenesis and Angiogenesis (Oscar Joe Hines, PI)

- Phytochemicals: flavonoids – genistein

- Pathways: pentose synthesis (oxidative and non-oxidative pathways), TCA cycle (anaplerotic and cataplerotic pathways), lipid synthesis and mitochondrial _-oxidation.

- Tracers: U¹³C-glucose

- Metabolites (isotopomers): ribose, deoxyribose, amino acids, palmitate, stearate, oleate and arachidate

6) Progress and Achievements of the Core (Please also see Center Publications and Abstracts)

1) Continuing development in Tracer-based metabolomics: In the past four years, much effort has been devoted to understand the relationship between tracer-based metabolomics and systems biology. Tracer-based metabolomics has its theoretical underpinning in constraint based modeling which is a bioengineering model of metabolic network in bacteria. The concept of metabolic pathways in a network being “constrained” by shared enzymes, substrates or co-factors is the basic difference between metabolomics and traditional biochemistry or molecular biology. Living organisms (cells) are metabolic systems (networks) continuously exchanging energy and matter with their environments to maintain the biological systems in a homeostatic state. Tracer-based metabolomics measures the dynamic changes in “extreme pathways” as mechanisms in maintaining cellular homeostasis. Combining measurements of “extreme pathways” and phenotypic phase plane analysis, we have developed a Tracer-based metabolomics database for the investigation of mechanisms of action of phytochemicals and signaling pathways. (www.ncbi.nlm.nih.gov/pubmed/20713038)

2) The application of phenotypic phase plane analysis in phytonutrient research - The application of phenotypic phase plane (PPP) analysis of balance of flux data from tracer-based metabolomics has allowed us to have a better understanding of the homeostatic mechanism of a cell and its adaption to maintain homeostasis when the system is perturbed. The application of phenotypic phase plane analysis to investigate metabolic mechanisms is illustrated in the attached figure below. Panel (i) of the figure shows the metabolic response of a cell to two phytochemicals (or drugs) A and B. These treatments result in changes in phenotypes (decrease in production of Z) accompanied by different metabolic compensations in substrate utilization. Treatment B results in a decreased utilization of substrate X (or its metabolic pathways) which is compensated by an increase in the utilization of substrate Y. Whereas treatment A results in the increase utilization of both X and Y or their pathways. If the mechanism of action of treatment B is known (such as a specific kinase inhibitor), one can conclude that treatment A must act on a different set of metabolic and/or signaling pathways. Such an approach will allow discovery of new treatment or new pathways. Panel (ii) shows result of treatment A which is orthogonal to the phenotypic phase plane of X and Y. This means that treatment A affects a different part of the metabolic system which is not linked to the utilization of substrates X and Y. This is important because there are potentially hundreds of these orthogonal phenotypic phase planes which can be discovered using tracer-based metabolomics. The finding of orthogonal planes is one of the unique capability of the metabolomics approach in generating mechanistic hypothesis. Panel (iii) shows the proportional response to inhibitor of substrate X where all of the isoclines are parallel to each other. Panel (iv) shows response to two inhibitors of substrate X with non-linear compensation of substrate Y. In summary, we have achieved a better understanding of metabolic adaptation in cellular homeostasis through tracer-based metabolomics. Using PPP and isocline analysis, we can directly exploit the large dataset accumulated from previous tracer-based metabolomics studies. (www.intechopen.com/books/metabolomics/metabolic-pathways-as-targets-for-drug-screening)

The application of pheno-typic phase plane analysis was applied to compare the antihyperglycemic effect of loquat leaf extract and purified sesquiterpene to those of metformin and rosiglitazone, two known anti-diabetes drugs. We found that the effect of alcohol extract of loquat leaves is similar to that of the purified sequiterpene which is different from that of metformin and rosi-glitazone. Therefore, the anti-hyperglycemic effect of loquat leaf extract is probably due to sequiterpene; and such effect may act through a mechanism which is different from those of known insulin sensitizers.

Another application of tracer-based metabolomics is in the classification of mechanisms of polyphenolic compounds in MIA pancreatic cancer cell. The growth inhibiting effects of luteolin, resveratrol, and quercetin in MIA PaCa-2 cells were studied by comparing changes in glucose metabolic pathways. These effects were compared with those of a fatty acid synthase inhibitor C75. It is interesting that despite the structural similarities of these compounds, diverse metabolic effects (mechanisms) were observed for their growth inhibiting effect. The study confirms the power of tracer-based metabolomics in revealing underlying metabolic mechanisms of polyphenolic compounds. These metabolic mechanisms can be used as a classification tool to systematically investigate the mechanism of actions of phytonutrients. The study is published online in Metabolomics (3/25/2011) (Metabolomics DOI 10.1007/s11306-011-0300-9).

3) The interaction of metabolic and signaling pathways – In collaboration of Dr. Gary Xiao of Creighton University, we have examined the interaction between metabolic and signaling pathways using metabolic inhibitors. Signaling path-ways are by nature post-translational modification of proteins using high energy phosphate compounds or acyl-CoA as precursor substrates. Thus, signaling pathways are part of the extended metabolic network and are subject to metabolic regulation based on the concept of constraint-based modeling. We previously have examined the signaling response (phosphorylation of proteins) to oxythiamine (a transketolase inhibitor) (publication #1). Recently, we investigated the changes in signaling pathways in response to a glycogen phosphorylase inhibitor (CP-320626). We found the expression profile patterns of cellular phosphorylated proteins of MIA PaCa-2 were significantly suppressed affecting cell cycle progression and apoptosis. Moreover, many proteins were involved in the pathway associated with chronic diseases, including cancer, inflammatory response, gastrointestinal disease, cardiovascular disease and neurological disease (Pancreas. 2012 Apr;41(3):397-408.).

4) Development of tracer method to examine phospholipid turnover. The work on method development for phospholipid analyses continues. Phospholipids are structural elements of cell membrane and are precursors for lipid signaling molecules such as platelet activating factor (PAF) and endocannabinoids. In collaboration with Dr. Christina Wang, we have examined the turnover of non-essential fatty acids in cardiolipin from the rat heart under two different dietary conditions. By measuring the turnover of these individual fatty acids, we found that in addition to linoleic acid (C18:2), oleate (C18:1 n-9) and vaccenate (C18:1 n-7) turnovered rapidly while palmitate (C16:0) and stearate (C18:0) did not during a period of 14 days. The results support our hypothesis that the turnover of fatty acids in phospholipids may generate signaling molecules or alter the dynamics of cell membrane affecting the metabolism in cells (J Lipid Res. 2011 Dec;52(12):2226-33

7) Utilization of the Core

Assay Procedure	Principal Investigator	Sample Description
	Grant Support
Tissue Processing	Hine, Joe (Project 3 P01 AT003960-01A)	Cell culture
	Pandol, Stephen (Project P01 AT003960-01A)	Cell culture
	Yee, Jennifer (K12 HD034610, K23 DK083241-01)	Animal tissue/cell culture
	Rehan, Virender (RO1-HD051857)	Cell culture
Amino acid profiling	Hine, Joe (Project 3 P01 AT003960-01A)	Cell lysate, culture medium
	Pandol, Stephen (Project P01 AT003960-01A)	Cell lysate, culture medium
	Rehan, Virender (RO1-HD051857)	Cell lysate, culture medium
Fructose/glucose	Patterson, Mary Beth (institutional support)	Culture medium
	Patterson, Mary Beth (institutional support)	Clinical samples
Glycogen	Hine, Joe (Project 3 P01 AT003960-01A)	Cell lysate
	Patterson, Mary Beth (institutional support)	Cell lysate
	Rehan, Virender (RO1-HD051857)	Cell lysate
Fatty acid profiling	Yee, Jennifer (K12 HD034610, K23 DK083241-01)	Cell/tissue extract/rat plasma
	Hine, Joe (Project 3 P01 AT003960-01A)	Cell extract
	Garg, Meena (Institutional funds)	Rat plasma
Ribose/deoxyribose	Hine, Joe (Project 3 P01 AT003960-01A)	Cell extract
	Patterson, Mary Beth (institutional support)	Cell extract
	Rehan, Virender (RO1-HD051857)	Cell extract
Protein extraction	Hirshberg Foundation project	Cell extract
Phospholipids	Xu, Jun NIH KO1 career development award	Animal tissue/cell extract
	Wang, Christina (institutional support)	Animal tissues

8 ) Research Proposals and Pending Projects

Funded Projects:

1RO1-HD051857 Rehan (PI), Lee (Co-I) 07/01/2008 – 06/30/2013 0.36 cal months

Project title: Fibroblast Cell Signaling in Utero Nicotine-Induced Lung Injury The Metabolomics Core will support metabolic phenotype studies in lung injury and remodeling.

2 T32 DK007571-21A1 Ronald Swerdloff (PI), Lee (Co-PI) 07/01/2009-6/30/2014

NIH Fellowship in Endocrinology and Metabolism

This is a NIH fellowship training grant providing three fellowship positions per year.

1 R01 AA019954-01A1 Lugea, Aurelia, PhD (PI), Lee (Co-PI) 07/01/2011-06/30/2016

Project Title: Alcohol abuse and Endoplasmic Reticulum dysfunction in exocrine pancreas

The Metabolomics Core will provide measurement of protein turnover in alcohol induced pancreatitis.

Pending applications:

R21 application - Gary Xiao (P.I.), WN Paul Lee (Co-PI) 7/01/2012-6/30/2014

Project title: Metabolic Regulation of the Cell Cycle – A Metabolomics – Proteomics Study

This is a R21 application to examine the coordinated changes in metabolic phenotype and proteomic phenotype in different phases of the cell cycle. The main hypothesis is that cell cycle initiation and progression are regulated by signaling pathways, gene expression and metabolic changes in response to nutrient environment with different sensitivities at different phases of the cell cycle.

U24 application – Go, Vay Liang (PI) 9/01/2012-8/31/2017

Project title: UCLA Comprehensive Metabolomic Core Resources

This proposal plan to expand and improve the core instrumentation capacity and capability to conduct comprehensive metabolomic studies thus providing the opportunity to expand faculty expertise and develop new training programs to improve our knowledge of metabolism in health and diseases to fulfill the goals and mission of the NIH Common Fund Program in Metabolomics.

Completed Projects

Hirshberg Foundation Research Grant Lee (PI) (10% effort) 11/1/08-10/30/09

Proteomics of Pancreatic Ductal Cancer Cells: Measuring Protein Turnover in vivo

This is a feasibility project to examine whether isotope infusion in whole animal provides accurate metabolic labeling of proteins in pancreatic cancer in vivo for proteomic analysis.

1S10RR025606-01 Christina Wang, MD (PI), Lee (Co-PI) 04/01/2009-3/31/2010

Proposal Title: Liquid Chromatography Tandem Mass Spectrometry

This is a shared instrumentation application for an ABI5000 LC/MS/MS. The instrument will be used in support of clinical projects from the General Clinical Research Center as well as small molecule analysis from the UCLA Center of Excellence in Pancreatic Diseases.