Ruprecht-Karls-Universität Heidelberg
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BioQuant_Hoefer0116 - Scientist (f/m) / PhD position
Project no:
BioQuant_Hoefer0116

Project leader:

Project supervisor:
Höfer, Thomas
Application deadline:
30. Sep 2017
Start of PhD project:
1. Oct 2017

Project description:

Title:
Regulation of gene expression: a non-equilibrium process
Summary:
Background and scientific question:
Switching on (and off) the transcription of genes is a fundamental process of life. The traditional model for gene regulation considers the regulator proteins – so-called transcription factors –to serve as structural scaffolds for the recruitment of the multi-component transcription machinery to specific genes. This model can be phrased mathematically in terms of a well-understood theory from physics, equilibrium statistical mechanics. In this model, genes are transcribed continuously with a rate that ‘averages’ over the different configurations of bound transcription factors. However, recent experimental progress in probing gene regulation in living cells has yielded two key findings that cannot be reconciled with the equilibrium model. First, genes are not transcribed continuously but in brief bursts of messenger RNA (mRNA) production interspersed by long silent intervals. Second, many transcription factors in eukaryotic cells do not serve as (stably binding) structural scaffolds but as (transiently interacting) facilitators of enzymatic changes to the chromatin (the structure into which DNA is packaged in the cell nucleus), thus giving the transcription machinery access to a specific gene. These findings pose anew the question of how transcription factors regulate the rate of gene transcription.

Project goal and planned work:
In this project, we will develop non-equilibrium models of gene regulation driven by experimental data. We will do this in cooperation with the group of Michael Brunner, using a natural ‘optogenetic system’ in the fungus Neurospora crassa that allows us to synchronize gene transcription in a large population of cell nuclei by light (Cesbron et al., 2014).
We will combine deterministic and stochastic mathematical models, parameter estimation from data, model selection, and optimal control theory to address the following questions: (1) How do transcription factors act on the intrinsic stochastic bursting cycles of genes (potentially controlling burst frequency, amplitude or/and duration)? (2) Does the non-equilibrium regime overcome limits of sensitivity and speed of transcriptional regulation inherent in the equilibrium model? (3) How does stochastic transcriptional bursting allow the robust functioning of physiological control circuits, using the Neurospora circadian clock as a case study (Gin et al., 2013)?
References:
1. Cesbron F, Oehler M, Ha N, Sancar G, Brunner M (2015) Nature Commun. 6: 6753.

2. Coulon A, Chow CC, Singer RH, Larson DR (2013). Rev. Genet. 14(8): 572-84.

3. Gin E, Diernfellner ACR, Brunner M, and Höfer T (2013) Mol. Syst. Biol. 9: 667.
Methods that will be used:
Cooperation partners:
This project is part of a research training group “Mathematical Modeling for the Quantitative Biosciences” at the Bioquant Center for the Quantitative Analysis of Cellular and Molecular Biosystems. The program is targeted at students from the quantitative sciences (physics, math, physical chemistry, computer science, systems or computational biology). The key goal of the program is to train versatile data analyzers and modelers for modern biology. Through the broad and complementary expertise of its principal investigators it will acquaint the PhD students with a comprehensive array of techniques for computationally analyzing experimental data from the biosciences and modeling biological processes mathematically. A unique part of the education will be internships in experimental laboratories of the PIs to gain first-hand experience of how quantitative data are measured in biological systems and participate in the planning of experiments.

Experimental partner: Prof. Dr. Michael Brunner (Biochemistry Center)
Personal qualifications:
Keywords: