Our primary long-term objective is development and application of methods for relating function, design, and significance of integrated biological systems to their underlying molecular determinants. As a result of the molecular advances in the past few decades, we are now in a position to examine the integrated behavior from an informed molecular perspective. This proposal is concerned with five specific aims; namely, (1) analysis of a new class of linked gene circuits for the regulation of inducible systems, (2) analysis of analogous linked gene circuits for the regulation of repressible systems, (3) analysis of accessory elements in the control of transcription termination and their influence on the dynamics of regulation, (4) analysis of symmetrical regulatory mechanisms governing amphibolic processes, and (5) development of canonical nonlinear methods for efficient simulation of biological processes. The methodology emphasized in our approach is mathematical and computer- assisted analysis because of their unique ability to systematically relate integrated function and design of organizationally complex biological systems to their molecular elements. The general outline for the analysis in each case is as follows: Specific models based on known or suspected molecular elements and interactions are formulated; the integrated behavior of these models is analyzed and compared according to several different criteria for functional effectiveness; the results of the analysis are interpreted in terms of optimal designs for specific functions; and, finally, the biological significance of the results is addressed and predictions are made for experimental testing. The projects of this proposal are likely to contribute to our understanding of normal processes such as homeostasis, growth and development, and of pathological manifestations such as metabolic diseases, developmental abnormalities and cancer.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM030054-06
Application #
3277695
Study Section
Mammalian Genetics Study Section (MGN)
Project Start
1982-04-01
Project End
1992-06-30
Budget Start
1988-07-01
Budget End
1989-06-30
Support Year
6
Fiscal Year
1988
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
Schools of Medicine
DUNS #
791277940
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Lomnitz, Jason G; Savageau, Michael A (2016) Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems. Front Genet 7:118
Lomnitz, Jason G; Savageau, Michael A (2016) Rapid Discrimination Among Putative Mechanistic Models of Biochemical Systems. Sci Rep 6:32375
Fasani, Rick A; Savageau, Michael A (2015) Unrelated toxin-antitoxin systems cooperate to induce persistence. J R Soc Interface 12:20150130
Tolla, Dean A; Kiley, Patricia J; Lomnitz, Jason G et al. (2015) Design principles of a conditional futile cycle exploited for regulation. Mol Biosyst 11:1841-9
Lomnitz, Jason G; Savageau, Michael A (2015) Elucidating the genotype-phenotype map by automatic enumeration and analysis of the phenotypic repertoire. NPJ Syst Biol Appl 1:
Fasani, Rick A; Savageau, Michael A (2014) Evolution of a genome-encoded bias in amino acid biosynthetic pathways is a potential indicator of amino acid dynamics in the environment. Mol Biol Evol 31:2865-78
Lomnitz, Jason G; Savageau, Michael A (2014) Strategy revealing phenotypic differences among synthetic oscillator designs. ACS Synth Biol 3:686-701
Fasani, Rick A; Savageau, Michael A (2013) Molecular mechanisms of multiple toxin-antitoxin systems are coordinated to govern the persister phenotype. Proc Natl Acad Sci U S A 110:E2528-37
Williams, Kristen; Savageau, Michael A; Blumenthal, Robert M (2013) A bistable hysteretic switch in an activator-repressor regulated restriction-modification system. Nucleic Acids Res 41:6045-57
Lomnitz, Jason G; Savageau, Michael A (2013) Phenotypic deconstruction of gene circuitry. Chaos 23:025108

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