StoNets - Controlling and exploiting stochasticity in gene regulatory networks

Research Project
|
01.03.2013
- 28.02.2017

The precision with which cells undergo differentiation programs or respond to external stimuli is remarkable, especially when considering the inherently "noisy" molecular interactions underlying these processes. StoNets aims to understand how stochasticity is controlled - and even exploited - to allow the development of robust behaviors of genetic networks, cells and cellular systems. Although all cells within an organism carry the same genetic information, regulatory mechanisms that operate at essentially all steps of gene expression lead to a large variety of cell types and behaviors. Progress in measurement technologies has enabled the precise and high-throughput probing of molecules and cells. This in turn has revealed that stochasticity is pervasive in all gene expression regulatory systems. The central question we will address in this StoNets project is how robust and reproducible cellular behaviors can emerge in spite of these noisy molecular interactions. A "slice" across the levels of gene expression organization We will undertake a systematic investigation into the mechanisms that have emerged to control noise at different organizational scales of gene expression regulation, from transcription of individual genes to cell fate switching. Each of the example systems that we selected is interesting in its own right and exhibits important stochastic aspects. Questions motivated by modeling With the continuous progress in understanding the basic mechanisms of gene regulation, many key molecular players have been identified and numerous direct regulatory interactions have been mapped. Theoreticians have started to model the way in which specific behaviors emerge from the underlying interactions. These efforts have led to a large number of new, inherently quantitative questions regarding the biological systems. Through a very tight integration of experimental and computational approaches StoNets aims to answer such questions ultimately contributing to an improved, quantitative understanding and thereby controllability of cellular behaviors.

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Collaborations & Cooperations

2099 - Participation or Organization of Collaborations within own University

Zavolan, Mihaela, Biozentrum, University of Basel, Research cooperation

2025 - Participation or Organization of Collaborations on an international level

Myers, Eugene, Max Planck Institute of Molecular Cell Biology and Genetics, Research cooperation

2020 - Participation or Organization of Collaborations within own University

Pfohl, Thomas, Dep. Chemistry, University of Basel, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Gatfield, David, Université de Lausanne, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Lutolf, Matthias, EPFL, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Naef, Felix, EPFL, Research cooperation

Publications

Urchueguía, Arantxa et al. (2021) ‘Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network’, PLoS Biology, 19(12), p. e3001491. Available at: https://doi.org/10.1371/journal.pbio.3001491.

URLs

Kaiser, Matthias et al. (2018) ‘Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software’, Nature Communications, 9(1), p. 212. Available at: https://doi.org/10.1038/s41467-017-02505-0.

URLs

Rzepiela, Andrzej J. et al. (2018) ‘Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction’, Molecular systems biology, 14(8), p. e8266. Available at: https://doi.org/10.15252/msb.20188266.

URLs

Breda, Jeremie et al. (2015) ‘Quantifying the strength of miRNA-target interactions’, Methods, 85, pp. 90–9. Available at: https://doi.org/10.1016/j.ymeth.2015.04.012.

URLs

Baresic, Mario et al. (2014) ‘Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program’, Molecular and cellular biology, 34(16), pp. 2996–3012. Available at: https://doi.org/10.1128/mcb.01710-13.

URLs

Members (30)

Mihaela Zavolan

Principal Investigator

Attila Becskei

Co-Investigator

Erik van Nimwegen

Co-Investigator

Jeremie Breda

Project Member

Thomas Julou

Project Member

Maria Katsantoni

Project Member

StoNets - Controlling and exploiting stochasticity in gene regulatory networks

Research Project
|
01.03.2013
- 28.02.2017

Collaborations & Cooperations

2099 - Participation or Organization of Collaborations within own University

Zavolan, Mihaela, Biozentrum, University of Basel, Research cooperation

2025 - Participation or Organization of Collaborations on an international level

Myers, Eugene, Max Planck Institute of Molecular Cell Biology and Genetics, Research cooperation

2020 - Participation or Organization of Collaborations within own University

Pfohl, Thomas, Dep. Chemistry, University of Basel, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Gatfield, David, Université de Lausanne, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Lutolf, Matthias, EPFL, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Naef, Felix, EPFL, Research cooperation

Publications

Urchueguía, Arantxa et al. (2021) ‘Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network’, PLoS Biology, 19(12), p. e3001491. Available at: https://doi.org/10.1371/journal.pbio.3001491.

Kaiser, Matthias et al. (2018) ‘Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software’, Nature Communications, 9(1), p. 212. Available at: https://doi.org/10.1038/s41467-017-02505-0.

Rzepiela, Andrzej J. et al. (2018) ‘Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction’, Molecular systems biology, 14(8), p. e8266. Available at: https://doi.org/10.15252/msb.20188266.

Breda, Jeremie et al. (2015) ‘Quantifying the strength of miRNA-target interactions’, Methods, 85, pp. 90–9. Available at: https://doi.org/10.1016/j.ymeth.2015.04.012.

Baresic, Mario et al. (2014) ‘Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program’, Molecular and cellular biology, 34(16), pp. 2996–3012. Available at: https://doi.org/10.1128/mcb.01710-13.

Members (30)

Mihaela Zavolan

Principal Investigator

Attila Becskei

Co-Investigator

Erik van Nimwegen

Co-Investigator

Jeremie Breda

Project Member

Thomas Julou

Project Member

Maria Katsantoni

Project Member

Research Groups

Function and evolution of genome-wide regulatory networks

Key regulators of gene expression and cell identity

Mechanisms controlling gene regulatory networks

StoNets - Controlling and exploiting stochasticity in gene regulatory networks

Research Project | 01.03.2013 - 28.02.2017

Collaborations & Cooperations

2099 - Participation or Organization of Collaborations within own University

Zavolan, Mihaela, Biozentrum, University of Basel, Research cooperation

2025 - Participation or Organization of Collaborations on an international level

Myers, Eugene, Max Planck Institute of Molecular Cell Biology and Genetics, Research cooperation

2020 - Participation or Organization of Collaborations within own University

Pfohl, Thomas, Dep. Chemistry, University of Basel, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Gatfield, David, Université de Lausanne, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Lutolf, Matthias, EPFL, Research cooperation

2017 - Participation or Organization of Collaborations on a national level

Naef, Felix, EPFL, Research cooperation

Publications

Urchueguía, Arantxa et al. (2021) ‘Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network’, PLoS Biology, 19(12), p. e3001491. Available at: https://doi.org/10.1371/journal.pbio.3001491.

Kaiser, Matthias et al. (2018) ‘Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software’, Nature Communications, 9(1), p. 212. Available at: https://doi.org/10.1038/s41467-017-02505-0.

Rzepiela, Andrzej J. et al. (2018) ‘Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction’, Molecular systems biology, 14(8), p. e8266. Available at: https://doi.org/10.15252/msb.20188266.

Breda, Jeremie et al. (2015) ‘Quantifying the strength of miRNA-target interactions’, Methods, 85, pp. 90–9. Available at: https://doi.org/10.1016/j.ymeth.2015.04.012.

Baresic, Mario et al. (2014) ‘Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program’, Molecular and cellular biology, 34(16), pp. 2996–3012. Available at: https://doi.org/10.1128/mcb.01710-13.

Members (30)

Mihaela Zavolan

Principal Investigator

Attila Becskei

Co-Investigator

Erik van Nimwegen

Co-Investigator

Jeremie Breda

Project Member

Thomas Julou

Project Member

Maria Katsantoni

Project Member

Research Groups

Function and evolution of genome-wide regulatory networks

Key regulators of gene expression and cell identity

Mechanisms controlling gene regulatory networks

Research Project
|
01.03.2013
- 28.02.2017