Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Metabolic Modeling of Biology Stephen Fong Bioinformatics and Bioengineering Summer Institute Monday, June 16, 2008

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Overview Monday Applications of Modeling in Biology Tuesday How do we use Genome-scale Models? Running simulations

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Seminar Questions?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Scenario Human genome sequenced at the end of billion bases –Only 0.1% difference between individuals (3.2 million discrete bases) What causes one person to be more susceptible to disease (cancer) than another person?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Central Biological Problem Cause and effect relationships are central to most biological problems. Why is it hard to elucidate these relationships?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Cellular components A + B C DNARNA Protein Metabolite Genomics Transcriptomics Proteomics Metabolomics Fluxomics

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Biological cause-effect DNA is the basic biological cause Problem is that biology is similar to the telephone game How can we track down where the changes are introduced?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Setting up Experiments Define your question (What are you specifically studying?) Know your system (What are the important parameters?) Know the accuracy of your testing (What do I need to make conclusions?)

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory What does this look like? # of genes # of conditions

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory An Engineer’s View Living cells are chemical factories We are concerned with 2 things: 1. The condition of the factory (cell) 2. The factory products (chemicals)

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Medical/Health Applications

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Perspective We want to keep the cell functioning properly, so how do we monitor it to keep things running smoothly?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Biomarkers Identify some characteristic of a cell that uniquely specifies its functional state Know the outcome, need to determine the real cause

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory In the News

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Cancer biomarkers Cancer antigen 125 (CA125) – associated with ovarian cancer Also found in people with pancreatic, kidney or liver disease Carcinoembryonic antigen (CEA) – associated with colorectal cancer Also found in people who smoke

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Options for Research 1.Tabulate data -Collect as much data as possible -Record the corresponding phenotype -Correlate results 2.Model it! -Use principles to predict effects -Verify with select data

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Phenomics in Humans National Center for Biotechnology Information (NCBI) is a government-run resource Online Mendelian Inheritance in Man (OMIM) compiles data on specific genes

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Chemical Industry Applications

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Perspective We’re interested in what the cell is producing, how can we make it more efficient?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Metabolism

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Cells as Chemical Factories Eukaryotes have specialized sub-cellular functions Prokaryotes are a mixed-bag

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Modeled Metabolism

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Constraint-based Model chemical reaction: aA + cC vivivivi eE + hH A-a B0 C-c D0 E+e F0 G0 H+h compounds vivi Representation as a column in a matrix: reactions

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Simulating a Gene Deletion chemical reaction: aA + cC vivivivi eE + hH A-a B0 C-c D0 E+e F0 G0 H+h compounds vivi Representation as a column in a matrix: reactions

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory OptKnock Algorithm Uncoupled Secretion at Max GR (wild-type) Coupled secretion at Max GR (designed strain) Fong et al., Biotech & Bioeng 2005 By-Product Secretion (mmol/g-DW hr)

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Systems-level metabolic engineering ComputationalExperimental Computational Model Genome-scale model Algorithmic Design OptKnock algorithm Strain Construction Gene deletion Adaptive evolution Strain Characterization By-product secretion

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Chemical targets Polymers and plastics Antibiotics Enzymes Fuels

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Constraints Example: The bouncing ball

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Genome-scale Extreme Pathways

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Scenario C 298 Metabolites 339 Reactions

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Introduction to Genome-scale Modeling

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Brainstorming: Modeling

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Why Develop Models? An accurate model: – Confirms our understanding of biology –Allows predictions to be made –Indicates areas where knowledge is incomplete

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Model: Biological Approach Plasmid partitioning

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Traditional Biological Model Process-specific Descriptive in nature Built for hypothesis-testing

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Model: Engineering/Math Approach Tegner, PNAS 100(10):

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Traditional Math Modeling Process-specific Quantitatively detailed Fit to observed behavior

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Modeling Comparison BiologicalMathematical Pro Applicable to wide variety of processes Quantitatively predictive ConLimited predictive capability Difficult to develop for all processes

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Genome-scale Constraint-based Models A hybrid of biological and mathematical modeling

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Genome-scale modeling Conceptually the same as traditional biological approaches Differences: –Scale of model –Model is of organism instead of a process –Model is mathematical instead of illustrative

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Constraint-based modeling Line of Optimality (LO) Substrate uptake rate Oxygen uptake rate Constrained Solution space Unconstrained Solution space Growth rate By-production secretion Flux distributions Phenotype Phase Plane

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Constraint-based modeling Annotation argE ppc Phosphoenolpyruvate + H 2 O + CO 2 Oxaloacetate + Phosphate 1 Phosphoenolpyruvate H 2 O CO 2 Oxaloacetate Phosphate

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Linear Programming Results Cellular Growth rate Predicted flux through each reaction Transport in and out of chemicals Sensitivity of each flux

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Generations of constraints-based models: use of ‘omics’ data 1st generation –Hard constraints –Determine capabilities (what) 2nd generation –Regulation of expression –Determine choices (why) 3rd generation –Regulation of activity –Determine trajectories (how) Genomics –annotated sequence –legacy data Expression profiling –transcriptomics –proteomic Concentration data –metabolomics –proteomic

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Genome-scale Modeling Recap Built on genomic and biochemical data Scales easily for large systems, but assumes steady state Starting point for biological prediction and understanding system-wide cause and effect

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory The Delphic Boat

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Application to biology If every molecule in a cell is replaced over time, is it still the same cell? If every cell in an organism is replaced over time, is it still the same organism?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory Reaction?

Virginia Commonwealth University Department of Chemical and Life Science Engineering Evolutionary Engineering Laboratory What does this mean? The connections/blue print that make up the boat and biological systems are important