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RetroNets SIGNED

Reverse Engineering Gene Regulatory Networks

Total Cost €

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EC-Contrib. €

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Partnership

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 RetroNets project word cloud

Explore the words cloud of the RetroNets project. It provides you a very rough idea of what is the project "RetroNets" about.

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Project "RetroNets" data sheet

The following table provides information about the project.

Coordinator
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE 

Organization address
address: BATIMENT CE 3316 STATION 1
city: LAUSANNE
postcode: 1015
website: www.epfl.ch

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 1˙993˙858 €
 EC max contribution 1˙993˙858 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-COG
 Funding Scheme ERC-COG
 Starting year 2017
 Duration (year-month-day) from 2017-04-01   to  2022-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE CH (LAUSANNE) coordinator 1˙993˙858.00

Map

 Project objective

Gene regulatory networks (GRNs) are an important cellular signal processing mechanism for translating input signals into appropriate phenotypes by modulating expression of the genome. The quantitative details of how cells process information through GRNs are still poorly understood, but of central importance in a large number of biological processes. Considerable progress has been made in mapping the topology of GRNs and more recently in deciphering the relationship between promoter sequence and function. Nonetheless, it is not yet possible to computationally predict the output of most native promoters, nor is it trivial to build promoters that integrate signals in a novel and predictive manner. Developing a quantitative understanding of transcriptional regulation, ultimately leading to the ability to predict entire GRNs will be a significant achievement and a prerequisite for our ability to engineer biological systems. I propose a multi-disciplinary approach incorporating biology, engineering, and computational modelling to improve our quantitative understanding by reverse engineering GRNs in S. cerevisiae. My research group has developed a powerful set of unique, high-throughput microfluidic technologies that enable the quantitative analysis of GRNs in vitro and in vivo. Specifically I propose to quantitatively investigate the yeast phosphate regulatory network and to develop a master model capable of predicting output of the network under various inorganic phosphate concentrations, to develop novel approaches for modulating GRNs using engineered Zn-finger transcription factors (TF) and CRISPR/Cas, to link GRN output to fitness in order to develop an understanding of how networks are optimized and evolve, and to reverse engineer an exact functional copy of the native phosphate regulatory network with orthogonal components.

 Publications

year authors and title journal last update
List of publications.
2019 Zoe Swank, Nadanai Laohakunakorn, Sebastian J. Maerkl
Cell-free gene-regulatory network engineering with synthetic transcription factors
published pages: 5892-5901, ISSN: 0027-8424, DOI: 10.1073/pnas.1816591116
Proceedings of the National Academy of Sciences 116/13 2020-04-24
2017 Kristina Woodruff, Sebastian J. Maerkl
Microfluidic Module for Real-Time Generation of Complex Multimolecule Temporal Concentration Profiles
published pages: 696-701, ISSN: 0003-2700, DOI: 10.1021/acs.analchem.7b04099
Analytical Chemistry 90/1 2020-04-24
2018 Jui-Chia Chang, Zoe Swank, Oliver Keiser, Sebastian J. Maerkl, Esther Amstad
Microfluidic device for real-time formulation of reagents and their subsequent encapsulation into double emulsions
published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-018-26542-x
Scientific Reports 8/1 2020-04-24

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