Title
Optimal Experimental Design For Parameter Estimation Of A Cell Signaling Model
Abstract
Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP3) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP3 lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.
Year
DOI
Venue
2009
10.1371/journal.pcbi.1000558
PLOS COMPUTATIONAL BIOLOGY
Keywords
Field
DocType
experimental design,kinetics,rate constant,numerical method,differential equation,differential equations,pleckstrin homology,ellipsoids,cell signaling,optimization,fluorescence microscopy,signal processing,iterative design,parameter estimation,covariance,systems biology,algorithms,second messengers,cell communication
Pleckstrin homology domain,Differential equation,Ellipsoid,Biology,Systems biology,Cell signaling,Estimation theory,Bioinformatics,Numerical analysis,Covariance
Journal
Volume
Issue
ISSN
5
11
1553-734X
Citations 
PageRank 
References 
25
1.52
7
Authors
5
Name
Order
Citations
PageRank
Samuel Bandara1251.52
Johannes P. Schlöder229733.65
Roland Eils364470.09
Hans Georg Bock461067.24
Tobias Meyer5251.52