Day 2

Tuesday, December 5

8:00am Morning Coffee

8:30 Comments by Session Chairperson
Rakesh Dixit, Ph.D., DABT., Senior Director and Head, Toxicology Department, MedImmune Incorporated

8:35 Report-Back of Problem-Solving Roundtable Groups
Representatives from each of the Problem-Solving Roundtable groups will present a 10-minute summary of their group’s discussion/findings.

Improving Technology Performance

9:25 Non-Destructive Ex Vivo and In Vivo Metabolic Profiling Using High Resolution 1H-NMR 
Jian Zhi Hu, Ph.D., Pacific Northwest National Laboratory
Several new high resolution 1H-NMR metabolic profiling techniques have recently been developed at Pacific Northwest National Laboratory. These techniques include: (i); Metabolic profiling of intact body fluids such as urine, plasma/serum and cerebral fluids, with limited mass supply of potentially as small as less than 1.0µl by slow magic angle spinning (MAS) of a capillary sample tube. (ii); Non-destructive metabolic profiling of excised intact tissues and organs such as brain, liver, lung, and any other excised tissues using slow-MAS NMR at a sample spinning rate of 40-80Hz. (iii); High sensitivity metabolic profiling of lavaged fluids, where the metabolite concentration is much lower than the intact body fluids due to the added water, using a recently developed liquid tight sample cell and fast MAS at a sample spinning rate of 2kHz. Metabolite concentrations as low as 50µM can be studied by using this method. The amount of lavage fluid required is from 80 to 120µl. (iv); In vivo metabolic profiling of a live object such as a mouse using ultra-slow-MAS NMR using a sample spinning rate of 1-4Hz. Preliminary results will be shown of mice exposed to silica dust by intrachacheal instillation. 

9:55 GC-MS as a Tool for Metabonomics 
Klaus Rumpel, Ph.D., Scientist, PGRD, Pfizer Global R & D 
The use of NMR and LC-MS as technologies for the metabonomic analysis of biological fluids is well established. We have explored the use of GC-MS as a metabonomics platform; it will be shown that GC-MS can be used as a powerful and complementary tool to NMR in metabonomic studies.

10:25 Coffee Break, Poster and Exhibit Viewing

10:55 Integrating High-Throughput Data into Genome-Scale Network Models
Jason Papin, Ph.D., Assistant Professor, Biomedical Engineering, University of Virginia
The reconstruction and mathematical analysis of genome-scale biochemical networks is a pressing challenge for making the connection between genotype and phenotype of biological systems. Current efforts to integrate network reconstructions of signaling, metabolic, and regulatory processes will be discussed, as well as emerging analytical frameworks that incorporate high-throughput data, such as metabolomics, to quantitatively characterize systems properties.

11:25 Nonlinear Chromatogram Alignment, UPLC and Multiple Ionization Mass Spectrometry for Enhanced Metabolomics
Anders Nordstrom, Ph.D., Research Associate, Scripps Center for Mass Spectrometry, Scripps Research Institute
The multitude of metabolites present in human fluids or tissue represents a great challenge for comprehensive and non-targeted analysis. Ultrahigh pressure chromatography and multiple ionization strategies prior to mass spectrometry detection, enhances the metabolite coverage. This paired with an in-house developed nonlinear chromatogram alignment algorithm can provide a comprehensive analysis result in a format ready for further data mining

Data Mining and -omics Data Integration

11:55 The Last C’omic Standing – Challenges and Opportunities for Gene Expression and Metabolite Integration in Systems Toxicology
Craig E. Thomas, Ph.D., Senior Research Advisor, Investigative Toxicology, Lilly Research Laboratories
Measurement of genes, proteins and metabolites has gained increasing acceptance as a means by which to study an organism’s response to stimuli, be it environmental, genetic, pharmacologic, toxicologic, etc. As independent entities, the measurement approaches referred to as genomics, proteomics, and metabonomics or metabolomics, have undoubtedly provided new biological insight that was not possible a decade ago. However, integration of these ‘omic data sets may better link the individual biological elements together to provide a more complete understanding of dynamic biological processes. Challenges for data integration range from the practical, such as the invasive nature of tissue sampling for genomics, to the technological, such as limited metabolite annotation in global profiling. In this presentation, case studies with agents inducing tissue injury will be presented that will illustrate how linkages between changes in gene expression and urinary or serum metabolites can enhance biological inference.

12:25pm Lunch (on your own)

1:30 A Study of Spectral Integration and Normalization in NMR-Based Metabonomic Analyses
Bobbie-Jo Webb-Robertson, Ph.D., Senior Research Scientist, Computational Biology/Bioinformatics, Pacific Northwest National Laboratory
Metabonomics involves the quantitation of the multivariate metabolic response of an organism to a pathological event or genetic modification. Data analysis requires the use of exploratory data analysis approaches such as principal component analysis (PCA). PCA has been documented as a valuable pattern recognition technique for 1H-NMR spectral data, however prior to PCA the data is typically processed through four steps: (1) baseline correction, (2) endogenous peak removal, (3) variable reduction via spectral region integration and (4) normalization. This study evaluates the effects of the size of the spectral integration region and normalization procedure.

2:00 Non-Negative Matrix Factorization for Metabolic Markers
S. Stanley Young, Ph.D., Assistant Director for Bioinformatics, National Institute of Statistical Sciences
Metabolic compounds are correlated. Matrix factorization takes advantage of these correlations and can be used to cluster samples and metabolic compounds. The resulting sets of compounds can be linked to biological outcomes. The method is presented using a real example.

2:30 Human Metabolome MS/MS Database: Development and Applications
Liang Li, Ph.D., Professor of Chemistry and Canada Research Chair in Analytical Chemistry, Department of Chemistry, University of Alberta, Edmonton, 
Human metabolome identification is a very challenging task. The goal of our research is to create a MS/MS database of endogenous human metabolites to facilitate their identification in body fluids. The database will consist of positively identified metabolites, their structures, MS and MS/MS data, experimental conditions and other relevant information. This presentation will highlight our efforts of constructing this database by using metabolites standards commercially available or readily synthesized or the ones newly identified from a biological source such as human urine or blood. In addition, an in vitro metabolite identification approach using cells, microsomes, and animal models for expanding the database will be presented. Selected applications of this database for urine and blood metabolome profiling will be discussed.

3:00 Refreshment Break, Poster and Exhibit Viewing

Metabolomics and Biomarkers

3:30 Evaluation of NMR-Based Metabolic Profiling in Models of Patient Outcome in the Phase II and Phase III Studies of Sorafenib in Advanced Renal Cell Carcinoma
Sarah L. Heald, Ph.D., Research Fellow, Department of Chemistry Research, Bayer HealthCare, Pharmaceuticals
The Phase II and Phase III studies of sorafenib in patients with advanced renal cell cancer (RCC) investigated the effects on overall survival. An exploratory objective of this study was to assess treatment effects on specific biomarkers, and to evaluate the association between these biomarkers and patient outcome. A brief introduction of our Biomarker strategies, as well as highlights of the preliminary results from the various initiatives, will be provided. The presentation will cover the challenge of applying metabolic profiling to urine samples collected during oncology clinical studies, the approaches used to model the data, the influence of demographics and the potential of NMR-based models to associate urinary metabolic profiles with patient outcome. These studies provide preliminary information on candidate biomarkers in renal cell carcinoma and early insight into means for improving the success of metabolic profiling initiatives in a clinic study paradigm.

4:00 Application of Capillary LC-MS in Metabolic Fingerprinting Studies of Type 1 Diabetes Mellitus
Thomas O. Metz, Ph.D., Senior Research Scientist, Environmental and Molecular Sciences Laboratory, Pacific Northwest National Laboratory
High-efficiency capillary LC was coupled with high-mass accuracy FTMS and applied in metabolic fingerprinting studies of well-characterized samples from the Diabetes Autoantibody Standardization Program. Perturbations were revealed in the serum phospholipid profiles of patients with type 1 diabetes mellitus versus control individuals. Candidate biomarkers were tentatively identified based on accurate mass measurements, comparison of theoretical and observed isotopic distribution, targeted MS/MS experiments, and/or comparison to authentic standards.

4:30 Closing Remarks by Session Chairperson

4:45 Conclusion of Conference