The overarching objective of the proposed theoretical and experimental studies is to elucidate the complex relationship between genetic architecture and the ability of a cell population to adapt to environmental challenges. Adaptation is tightly coupled with the dynamics of regulatory networks, which, in turn, determine the phenotype of each individual cell. However, cell populations are heterogeneous systems in the sense that phenotypic responses vary between genetically identical cells. To study cell population heterogeneity and its relationship to regulation of gene expression, we developed a general cell population balance modeling framework and the numerical algorithms necessary for its efficient simulation. We also employed flow cytometry and microscopy to study the distribution characteristics of E.coli cell populations. The E.coli cells contained an artificial genetic network, known as the genetic toggle, consisting of two promoter-repressor pairs and the green fluorescent protein (GFP) as a reporter. Both the experimental and simulation results indicated that neglecting population heterogeneity leads to significant qualitative and quantitative errors in predicting system behavior. In addition, we applied our modeling and computational framework to the well-characterized lac operon system and studied the effects that a) systemic parameters such as binding affinities and promoter strengths, b) operating conditions, and c) specific modifications of network topology have on the distribution of cellular phenotypes. Moreover, the modeling/computational framework was used to study the dependence of adaptation dynamics on the initial cell distribution characteristics. Our preliminary studies led to the formulation of the following hypotheses: A) The structure of regulatory networks as well as their systemic characteristics, will vastly influence the distribution characteristics of heterogeneous cell populations and B) The initial distribution characteristics of heterogeneous cell populations will have a profound, predictable impact on the dynamics of adaptation to sudden changes in environmental conditions. To test these hypotheses, we propose to develop an integrated modeling and experimental framework. We will use the lac operon genetic network as well as its combination with two specific artificial genetic networks as our model systems. The comparison between modeling and experimental results will be used for model validation and refinement.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM071888-03
Application #
7104249
Study Section
Special Emphasis Panel (ZRG1-MABS (01))
Program Officer
Anderson, James J
Project Start
2004-08-01
Project End
2009-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
3
Fiscal Year
2006
Total Cost
$291,748
Indirect Cost
Name
Rice University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005
Spetsieris, Konstantinos; Zygourakis, Kyriacos (2012) Single-cell behavior and population heterogeneity: solving an inverse problem to compute the intrinsic physiological state functions. J Biotechnol 158:80-90
Stamatakis, Michail; Zygourakis, Kyriacos (2011) Deterministic and stochastic population-level simulations of an artificial lac operon genetic network. BMC Bioinformatics 12:301
Stamatakis, Michail; Zygourakis, Kyriacos (2010) A mathematical and computational approach for integrating the major sources of cell population heterogeneity. J Theor Biol 266:41-61
Stamatakis, Michail; Mantzaris, Nikos V (2010) Intrinsic noise and division cycle effects on an abstract biological oscillator. Chaos 20:033118
Stamatakis, Michail; Mantzaris, Nikos V (2009) Comparison of deterministic and stochastic models of the lac operon genetic network. Biophys J 96:887-906
Spetsieris, Konstantinos; Zygourakis, Kyriacos; Mantzaris, Nikos V (2009) A novel assay based on fluorescence microscopy and image processing for determining phenotypic distributions of rod-shaped bacteria. Biotechnol Bioeng 102:598-615
Portle, Stephanie; Iadevaia, Sergio; San, Ka-Yiu et al. (2009) Environmentally-modulated changes in fluorescence distribution in cells with oscillatory genetic network dynamics. J Biotechnol 140:203-17
Mantzaris, Nikos V (2007) From single-cell genetic architecture to cell population dynamics: quantitatively decomposing the effects of different population heterogeneity sources for a genetic network with positive feedback architecture. Biophys J 92:4271-88
Portle, Stephanie; Causey, Thomas B; Wolf, Kim et al. (2007) Cell population heterogeneity in expression of a gene-switching network with fluorescent markers of different half-lives. J Biotechnol 128:362-75
Mantzaris, Nikos V (2006) Stochastic and deterministic simulations of heterogeneous cell population dynamics. J Theor Biol 241:690-706