Dynamics of cellular level function and regulation derived from murine expression array data

doi:10.1073/pnas.0406707102

Dynamics of cellular level function and regulation derived from murine expression array data

^*Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138; ^‡Vascular Biology Program, Departments of Pathology and Surgery, Children's Hospital and Harvard Medical School, Boston, MA 02115; and ^§New England Complex Systems Institute, Cambridge, MA 02138

Edited by Charles R. Cantor, Sequenom, Inc., San Diego, CA, and approved November 4, 2004 (received for review September 10, 2004)

Abstract

A major open question of systems biology is how genetic and molecular components interact to create phenotypes at the cellular level. Although much recent effort has been dedicated to inferring effective regulatory influences within small networks of genes, the power of microarray bioinformatics has yet to be used to determine functional influences at the cellular level. In all cases of data-driven parameter estimation, the number of model parameters estimable from a set of data is strictly limited by the size of that set. Rather than infer parameters describing the detailed interactions of just a few genes, we chose a larger-scale investigation so that the cumulative effects of all gene interactions could be analyzed to identify the dynamics of cellular-level function. By aggregating genes into large groups with related behaviors (megamodules), we were able to determine the effective aggregate regulatory influences among 12 major gene groups in murine B lymphocytes over a variety of time steps. Intriguing observations about the behavior of cells at this high level of abstraction include: (i) a medium-term critical global transcriptional dependence on ATP-generating genes in the mitochondria, (ii) a longer-term dependence on glycolytic genes, (iii) the dual role of chromatin-reorganizing genes in transcriptional activation and repression, (iv) homeostasis-favoring influences, (v) the indication that, as a group, G protein-mediated signals are not concentration-dependent in their influence on target gene expression, and (vi) short-term-activating/long-term-repressing behavior of the cell-cycle system that reflects its oscillatory behavior.

Footnotes

↵ † To whom correspondence should be addressed. E-mail: bivort{at}fas.harvard.edu.
Author contributions: B.d.B., S.H., and Y.B.-Y. designed research, performed research, analyzed data, and wrote the paper.
This paper was submitted directly (Track II) to the PNAS office.
Abbreviations: AfCS, Alliance for Cellular Signaling; SOM, self-organizing map.