Gene regulatory networks are decision-making and control systems of cells whose dynamical properties underlie their proper function. Large scale in silico models can aid in understanding how changes in network components lead to qualitatively different dynamics, aberrant function, and disease states. These models often use a bottom-up engineering approach;therefore, the accuracy of models is contingent on appropriate descriptions for component interactions, with just enough detail to capture the essential dynamics. Promoters dictate how gene expression (output) depends on inputs (gene-specific regulators). This relationship has traditionally been described using semi-empirical models based on the thermodynamics of protein-DNA interactions. However, even a single eukaryotic promoter likely exhibits complex dynamics because of many non-equilibrium interactions. Two dynamical properties of single genes that can qualitatively change the dynamics of the regulatory networks in which they are embedded are variability (stochastic noise) in expression of single cells and delays and memory in gene activation or repression. The project goal is to describe these dynamics using simple lumped kinetic models and connect model parameters to promoter architecture. This would be invaluable to improving larger scale efforts aimed at understanding network malfunction in disease or identifying therapeutic targets. Using fluorescence in situ hybridizaition (FISH) to detect single mRNA's in single budding yeast cells, we can extract mRNA distributions to infer steady-state dynamics and noise in gene expression. We have also developed a novel tool, the 'gene oscilloscope', to probe the kinetics of gene activation and the presence of delays and memory in yeast. The Pho4p activator, whose activity is controlled at the level of nuclear localization, is the observable, dynamically controllable input, and a fluorescent reporter is the observable output. Input/output behavior is extracted from movies of single cells grown in microfluidic devices. The current oscilloscope is limited to studies of phosphate-responsive (PHO) genes regulated by Pho4p.
In Aim 1, we will identify a minimal shuttling domain in Pho4p to which we can fuse an arbitrary activation and DNA binding domain, creating a modular tool capable of probing an arbitrary promoter.
In Aim 2, we will measure mRNA statistics in a panel of synthetic TET promoter variants to assess the suitability of a simple kinetic model in describing those statistics across a range of perturbations and establish how promoter and activator properties influence mRNA statistics.
In Aim 3, we will use the gene oscilloscope to study how PHO promoter chromatin architecture confers delays in gene activation and measure accurate delay distributions. We will also study the frequency response of these promoters, to establish whether delayed activation filters high frequency signals. Together, these aims will help establish simple ways of incorporating crucial dynamical properties in models and yield mechanistic insights by comparing how different features of promoters and activators affect kinetics.

Public Health Relevance

The dynamical nature of gene regulation can lead to single cell variability, or noise, in expression and delays in activation, which qualitatively change the predictions of larger scale in silico models of gene regulatory networks. By examining how promoter architecture and activator choice influences these dynamics in budding yeast using novel experimental tools, we will likely establish simple models to incorporate this behavior. These basic results should influence and constrain modeling efforts and assumptions in diseased and normal regulatory networks in eukaryotic organisms, making this project is relevant to the mission of NIH and of broad interest to researchers studying gene regulation.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Molecular Genetics A Study Section (MGA)
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Sledjeski, Darren D
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Massachusetts Institute of Technology
Engineering (All Types)
Schools of Engineering
United States
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Zopf, C J; Quinn, Katie; Zeidman, Joshua et al. (2013) Cell-cycle dependence of transcription dominates noise in gene expression. PLoS Comput Biol 9:e1003161
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Niesner, Bradley; Maheshri, Narendra (2013) Using the Cre-lox system to randomize target gene expression states and generate diverse phenotypes. Biotechnol Bioeng 110:2677-86
Lee, Tek-Hyung; Maheshri, Narendra (2012) A regulatory role for repeated decoy transcription factor binding sites in target gene expression. Mol Syst Biol 8:576