A cell's behavior is governed by a complex dynamical system of genetic interactions. A central role in the understanding of the nature of living systems, their stability in a changing environment, and how such systems fail in disease, such as cancer, is played by the process of differentiation. The goal of this project is to understand this process, along with cellular homeostatic stability from a systems perspective.

The 'state-space' of such complex nonlinear dynamical systems, representing genetic regulatory networks, consists of all possible combinations of gene activities. The regulatory interactions result in a dynamical 'flow' in this state-space. That flow or trajectory typically reaches a recurrent pattern of activities, which constitutes an attractor or the steady-state behavior of the system. Many different trajectories typically flow to the same attractor and constitute its basin of attraction. One objective of this study is to test the hypothesis that the attractors of such networks constitute the cell types of an organism, while differentiation is precisely a route (gene expression program) from one attractor into the basin of attraction of another attractor and subsequent flow to that new attractor.

Another objective is to test the hypothesis that there are several distinct paths in the state-space along which cells proceed towards differentiation. A related goal is to characterize a particular differentiation process at the gene expression level. To achieve these objectives, we are mapping the molecular paths by gene expression profiling for differentiation pathways. Finally, another objective is to study the process of cellular homeostasis on the gene expression level. The particular questions related to this objective are: do the cells exhibit homeostasis on the expression level by returning to their original states in the state-space and, if so, do they retrace the same trajectory on their way back?

The methods designed to achieve these goals include treating HL60 promyelocytic leukemia cells, a well-established differentiation model, with different doses and durations of all-trans retinoic acid (ATRA) to differentiate the cells into granulocytes. Using early differentiation cell surface markers (CD11b) and flow cytometry, we have constructed loci on the dose-duration plane such that a given locus corresponds to a fixed percentage of differentiated cells, as shown in Figure 1.

Figure 1: Loci in the dose-duration plane as determined by flow cytometry using CD11b cell surface marker. There are a total of 88 different dose-duration combinations, each in triplicate.

In order to study homeostatic stability, cells will be treated such that they are on the 50 percent locus (i.e., half of the cells committed to differentiation) and microarray profiling will be performed at different time points during treatment. After live sorting of the cells using CD11b, the CD11b positive and negative cells will be cultured in the absence of differentiation inducing agents. Microarrays will be used to profile each of these cell populations using time-point measurements, thus making possible the characterization of homeostatic behavior on the gene expression level.

Primary methodologies/approaches/strategies used to accomplish the goals

Our approach is rooted in genomic technologies with system-level modeling. By treating the genetic regulatory network of a cell as a nonlinear dynamical system, we are studying the process of differentiation and homeostasis via the state-space approach. Our data are gathered by means of microarray technology and flow cytometry.

Group members involved with Project

Ilya Shmulevich (PI)
Albert Huang (Ph.D. student)

External collaborators

Wei Zhang - Cancer Genomics Laboratory, University of Texas M. D. Anderson Cancer Center, Houston, TX
Stuart A. Kauffman- Institute for Biocomplexity and Informatics, University of Calgary, Calgary, Canada