Although gene circuits and biochemical networks are receiving increased attention in the post-genomic era because of their role in linking genotype to phenotype, little is known about the forces that lead to the selection or maintenance of a specific mechanism for the regulation of a given set of genes in a particular organism. This knowledge is important for understanding the evolution of gene regulation. It also is important for redirecting normal expression for biotechnological purposes or correcting pathological expression for therapeutic purposes. The long-term objective of this project is to relate functional, design, and evolution of integrated biological systems to their underlying molecular determinants - to relate genotype to phenotype. This will be difficult to achieve with purely experimental means. It will require analysis of the systemic function of particular gene circuits and biochemical mechanisms, classification of these into specific categories of design, and examination of their natural selection and maintenance.
The specific aims of this proposal are to (10 develop and apply a theory of gene control by multiple regulators, (2) elucidate the design of circuits with two types of genetic switches, (3) analyze and compare alternative signal transduction mechanisms, (4) determine implications of connectivity in regulatory gene networks, and (5) develop and test methods for analysis of genomic-scale models. The methodology emphasizes mathematical and computer-assisted analysis because of their unique ability to systematically relate integrated function and design of complex 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; their integrated behavior is analyzed and compared according to several criteria for functional effectiveness; the results 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. This approach is helping to crate a more rational basis for predicting the integrated behavior of complex biological systems. Accurate predictions of this nature will be necessary if we are to understand more fully the normal systemic processes of homeostasis, growth and development, or their pathological manifestations such as metabolic diseases, developmental abnormalities and cancer. A focus on prokaryotic organisms is important not only because they serve as model systems for understanding higher organisms, but also because of their role in the pathogenesis of infectious diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM030054-22
Application #
6917804
Study Section
Special Emphasis Panel (ZRG1-GEN (02))
Program Officer
Anderson, James J
Project Start
1982-04-01
Project End
2007-06-30
Budget Start
2006-07-01
Budget End
2007-06-30
Support Year
22
Fiscal Year
2006
Total Cost
$224,766
Indirect Cost
Name
University of California Davis
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
047120084
City
Davis
State
CA
Country
United States
Zip Code
95618
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:
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 (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
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
Balderas-Martínez, Yalbi Itzel; Savageau, Michael; Salgado, Heladia et al. (2013) Transcription factors in Escherichia coli prefer the holo conformation. PLoS One 8:e65723

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