Office 3312 GBSF
Ph.D. in Systems Engineering and Cell Physiology, Stanford University 1967
Biomedical Engineering Graduate Group
Function, Design, and Evolution of Cellular and Molecular Networks
The physical basis for complex phenotypes is the context-dependent expression of the organism’s genome. The context is provided by the life cycle of the organism; the molecular mechanisms of gene regulation interpret that context and orchestrate appropriate responses. The importance of this governing role has made the experimental study of gene regulation central to nearly all areas of modern molecular biology. The regulation of many gene systems has been studied in detail, and the results have revealed an enormous diversity of molecular elements and circuits. We are just beginning to understand the functional implications of such variations in design and to grasp the factors that have influenced their evolution. The relationship of these variations in design to the phenotype of the organism is even less clear. A quantitative systems approach is required to elucidate these relationships, for without it our understanding will remain descriptive and lack predictive value. The genome projects and resulting expression-array technologies are providing (at an ever-accelerating rate) global data on gene expression. Thus, there is both an opportunity and a challenge to integrate the detailed knowledge of individual molecular mechanisms with the abundance of global expression data to produce a deeper understanding of organizationally complex biological systems. Indeed, there are many who consider this type of quantitative systems biology and the elucidation of biological design principles to be the outstanding problems in the post-genomic era.
The focus of research in Professor Savageau’s laboratory is on quantitative systems biology aimed at further elucidation of biological design. Specific goals include elucidating the design features in elementary gene circuits, enlarging the scope of the search for predictable patterns of gene circuitry to include different mechanisms of signal transduction and control by global regulators, and continuing the development of new methodologies for the quantitative analysis of large genomic-scale systems. The following are six current projects in the lab: (1) develop and apply a theory of gene control by multiple regulators, (2) elucidate the design of circuits with two types of genetic switches, (3) design and construct a genetic clock with a circadian period in E. coli, (4) analyze and compare alternative signal transduction mechanisms, (5) determine the implications of connectivity in regulatory gene networks, and (6) develop and test methods for the analysis of genomic-scale models. The lessons learned from these projects provide a deeper understanding of intact biological systems in their natural environments. They also provide guidance as we attempt to re-engineer systems with the intent of correcting pathologies through rational treatment or of producing useful products through biotechnology.
Igoshin, O.A., M.S. Brody, C.W. Price, and M.A. Savageau, Distinctive topologies of partner-switching signaling networks correlate with their physiological roles, J. Mol. Biol. 369, 1333-1352 (2007).
Igoshin, O.A., R. Alves, and M.A. Savageau, Hysteretic and graded responses in bacterial two-component signal transduction, Mol. Microbiol. 68, 1196-1215 (2008).
Coelho, P.M.B.M., A. Salvador, and M.A. Savageau, Global Tolerance of Biochemical Systems and the Design of Moiety-Transfer Cycles, PLoS Comput. Biol. 5, e1000319 (2009).
Savageau, M.A., P.M.B.M. Coelho, R.A. Fasani, D.A. Tolla, and A. Salvador, Phenotypes and tolerances in the design space of biochemical systems, Proc. Natl. Acad. Sci. USA 106, 6435-6440 (2009).
Savageau, M.A., and R.A. Fasani, Qualitatively distinct phenotypes in the design space of biochemical systems, FEBS Lett. 583, 3914-3922 (2009).
Integrated behavior of organizationally complex systems, quantitative relationship of such behavior to its underlying molecular determinants, generic methods for mathematical and computer analysis of such systems, application of such methods to specific classes of cellular and molecular networks, biological design principles governing the organization of metabolic pathways and gene circuits, system robustness.