In recent years, there has been a growing appreciation for the complex roles that small regulatory RNA (sRNA) can play in coordinating gene activities in both prokaryotes and eukaryotes. There exists by now a basic understanding of the molecular components and mechanisms involved in sRNA-mediated gene regulation in bacteria. Theoretical analysis by our lab suggest a number of unique functional features for sRNA-mediated gene regulation, including a threshold-linear response and a resistance to noisy fluctuation, with interesting implications on properties of genetic circuits involving sRNA. Here we propose a joint experimental/computational research program to characterize the functions of sRNA in E. coli at multiple scales. At the molecular scale, we will elucidate the sequence determinant of sRNA-target interaction for the most common RyhB-class sRNA by characterizing the gene expression of selected mutants, and constructing biopysical/bioinformatic models of the interaction. At the """"""""device"""""""" scale, we will characterize various novel properties predicted for sRNA-mediated regulation, including hierarchical cross talk between different targets of the same sRNA. At the circuit scale, we will construct synthetic circuits and study the properties of common circuit motifs such as the cascade and switches, and investigate their temporal characteristics. In addition we will develop models to design antisense sRNAthat target and silence specific host genes. We expect that the knowledge of the molecular interaction to lead to predictive tools to identify the potentially large number of sRNA targets and construct additional layers of the gene regulatory network involving sRNA in E. coli, while knowledge of the devices and common circuit motifs will shed light towards understanding the special roles that sRNA regulators may play in coordinating larger scale networks. Additionally, the silencing of endogenous target may lead to an effective tool to generate multiple gene knockdown strains which may be used for drug discover studies as well as gene- gene interaction studies at the genome-wide scale. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM077298-02
Application #
7414037
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Bender, Michael T
Project Start
2007-05-01
Project End
2011-04-30
Budget Start
2008-05-01
Budget End
2009-04-30
Support Year
2
Fiscal Year
2008
Total Cost
$281,246
Indirect Cost
Name
University of California San Diego
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Klumpp, Stefan; Hwa, Terence (2014) Bacterial growth: global effects on gene expression, growth feedback and proteome partition. Curr Opin Biotechnol 28:96-102
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Hao, Yue; Zhang, Zhongge J; Erickson, David W et al. (2011) Quantifying the sequence-function relation in gene silencing by bacterial small RNAs. Proc Natl Acad Sci U S A 108:12473-8
Klumpp, Stefan (2011) Growth-rate dependence reveals design principles of plasmid copy number control. PLoS One 6:e20403
Hermsen, Rutger; Erickson, David W; Hwa, Terence (2011) Speed, sensitivity, and bistability in auto-activating signaling circuits. PLoS Comput Biol 7:e1002265
Scott, Matthew; Hwa, Terence (2011) Bacterial growth laws and their applications. Curr Opin Biotechnol 22:559-65
Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M et al. (2010) Interdependence of cell growth and gene expression: origins and consequences. Science 330:1099-102
Schug, Alexander; Weigt, Martin; Hoch, James A et al. (2010) Computational modeling of phosphotransfer complexes in two-component signaling. Methods Enzymol 471:43-58
Lunt, Bryan; Szurmant, Hendrik; Procaccini, Andrea et al. (2010) Inference of direct residue contacts in two-component signaling. Methods Enzymol 471:17-41
Klumpp, Stefan; Zhang, Zhongge; Hwa, Terence (2009) Growth rate-dependent global effects on gene expression in bacteria. Cell 139:1366-75

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