Modeling the Cell Cycle with JigCell and DARPA’s BioSPICE Software

Departments of Computer Science* and Biology+,Virginia Tech

Blacksburg, VA 24061

Faculty:Kathy Chen+

Cliff Shaffer*

John Tyson+

Layne Watson*

Students:Nick Allen*

Emery Conrad+

Ranjit Randhawa*

Marc Vass*

Jason Zwolak*

The Fundamental Goal of Molecular Cell Biology

Application:Cell Cycle Modeling

How do cells convert genes into behavior? Create proteins from genes Protein interactions Protein effects on the cell

Our study organism is the cell cycle of the budding yeast Saccharomyces cerevisiae.

mitosis(M phase)

DNA replication(S phase)

cell division

G1

G2

Modeling Techniques

We use ODEs that describe the rate at which each protein concentration changes Protein A degrades protein B:

… with initial condition [A](0) = A0.

Parameter c determines the rate of degradation.

]A[]B[

cdt

d

Modeling Lifecycle

Data NotebookData Notebook

Wiring DiagramWiring Diagram

Differential EquationsDifferential Equations Parameter ValuesParameter Values

AnalysiAnalysiss

SimulationSimulation

ComparatorComparator

Data NotebookData Notebook

ExperimentalExperimentalDatabasesDatabases

Tyson’s Budding Yeast Model

Tyson’s model contains over 30 ODEs, some nonlinear.

Events can cause concentrations to be reset.

About 140 rate constant parameters Most are unavailable from experiment and must set by

the modeler “Parameter twiddling” Far better is automated parameter estimation

JigCell

Current Primary Software Components:JigCell Model Builder

JigCell Run Manager

JigCell Comparator

Automated Parameter Estimation (PET)

Bifurcation Analysis (Oscill8)

http://jigcell.biol.vt.edu

JigCell Model Builder

(Frogegg model)

Mutations

Wild type cell

Mutations Typically caused by gene knockout Consider a mutant with no B to degrade A.

Set c = 0 We have about 130 mutations

each requires a separate simulation run

JigCell Run Manager

Phenotypes

Each mutant has some observed outcome (“experimental” data). Generally qualitative. Cell lived Cell died in G1 phase

Model should match the experimental data. Model should not be overly sensitive to the rate

constants. Overly sensitive biological systems tend not to

survive

Comparator

BioSPICE

DARPA projectApproximately 15 groupsMany (not all) active systems biology modelers and software developers representedAn explicit integration teamGoal: Define mechanisms for interoperability of software tools, build an expandable problem solving environment for systems biologyResult: software tools contributed by the community to the community

Tools

Specifications for defining models (SBML)Standards for data representation, APIsSimulators (equation solvers; stochastic)Automated parameter estimationAnalysis tools (plotters, bifurcation analysis, flux balance, etc.)Database support for simulations (data mining)