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Quantitative in vivo characterization of RNA interference using Synthetic and Systems Biology

Applicant Benenson Yaakov
Number 149802
Funding scheme Project funding (Div. I-III)
Research institution Computational Systems Biology Department of Biosystems, D-BSSE ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Molecular Biology
Start/End 01.08.2014 - 31.07.2018
Approved amount 610'000.00
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Keywords (5)

Single-cell measurements; RNA interference; Synthetic Biology; Systems Biology; Biosensors

Lay Summary (German)

Lead
RNA Interferenz (RNAi) wird seit einiger Zeit wegen ihrer enormen Bedeutung in der Biologie und ihrer potentiellen Anwendungen in der Medizin intensiv erforscht. Trotzdem sind die heutigen Erkenntnisse zur RNA Interferenz unzureichend um intrazelluläre microRNA Mengen mittels genetischen Sensoren exakt bestimmen zu können. Dieses Projekt soll dazu dienen die grundlegenden Parameter des RNAi Prozesses zu identifizieren, um zuverlässige, universelle und unmittelbar anwendbare microRNA Sensoren generieren zu können.
Lay summary

Inhalt und Ziele des Forschungsprojekts

            RNA Interferenz wurde vor zwei Jahrzehnten entdeckt und entpuppte sich als ein fundamental wichtiger Prozess der Biologie; einerseits wegen ihrer Bedeutung für die Genexpressionsregulation in vielen mehrzelligen Lebewesen, andererseits wegen ihrer potentiellen Bedeutsamkeit in der Diagnostik und Behandlung von Krankheiten. Ausserdem bildete RNA Interferenz den Ausgangspunkt von sogenannten genetischen Schaltkreisen, welche zahlreiche Anwendungen in der Grundlagenforschung bis hin zur Biomedizin finden.

            Obwohl enorme Fortschritte im Verständnis und in der Anwendung der RNA Interferenz erzielt wurden, weiss man erstaunlich wenig über die quantitativen Parameter des Prozesses. Beispielsweise kann die Frage; „Wie stark ist die Repression eines Gens, das eine vorgegebene microRNA-Bindungstellensequenz im 3’UTR besitzt, wenn es einer microRNA mit bekannter Konzentration ausgesetzt ist?“, mit heutigem Wissen nicht beantwortet werden. Wir sind überzeugt, dass das Charakterisieren dieser Parameter der Schlüssel zum Erfolg von künftigen Untersuchungen der RNA Interferenz ist und sowohl der Grundlagenforschung als auch der Entwickelung diverser Anwendungen dienen wird.

Dieser Antrag beschreibt eine Serie von Experimenten, deren gemeinsames Ziel die quantitative Beschreibung von RNA Interferenz in Säugerzellen ist. Die darunterliegenden Eigenschaften werden auf Zellpopulationsebene sowie in Einzelzellen aufgeklärt. Dabei ist unser Hauptziel, die Menge von intrazellulären microRNA Molekülen in absoluten Einheiten zu messen und mit der beobachteten Stärke der Repression des Zielgens zu verknüpfen. Die experimentellen Variablen die dazu beachtet werden beinhalten die Sequenz der microRNA, die Sequenz der microRNA Bindungstelle (von partiell bis zu komplett komplementär und mit einer variierenden Anzahl von Bindungsstellen), und der Zelltyp.

Direct link to Lay Summary Last update: 18.07.2014

Responsible applicant and co-applicants

Employees

Publications

Publication
Synthetic control systems for high performance gene expression in mammalian cells
LillacciGabriele, BenensonYaakov, KhammashMustafa (2018), Synthetic control systems for high performance gene expression in mammalian cells, in Nucleic Acids Research, 46(18), 9855-9863.
A Workflow for In Vivo Evaluation of Candidate Inputs and Outputs for Cell Classifier Gene Circuits
Dastor Margaux, Schreiber Joerg, Prochazka Laura, Angelici Bartolomeo, Kleinert Jonathan, Klebba Ina, Doshi Jiten, Shen Linling, Benenson Yaakov (2018), A Workflow for In Vivo Evaluation of Candidate Inputs and Outputs for Cell Classifier Gene Circuits, in ACS Synthetic Biology, 7(2), 474-489.
Synthetic gene circuits and cellular decision-making in human pluripotent stem cells
Prochazka Laura, Benenson Yaakov, Zandstra Peter W. (2017), Synthetic gene circuits and cellular decision-making in human pluripotent stem cells, in Current Opinion in Systems Biology, 5, 93-103.
Automated Design of Synthetic Cell Classifier Circuits Using a Two-Step Optimization Strategy
Mohammadi Pejman, Beerenwinkel Niko, Benenson Yaakov (2017), Automated Design of Synthetic Cell Classifier Circuits Using a Two-Step Optimization Strategy, in Cell Systems, 4(2), 207-218.e14.
Model‐guided combinatorial optimization of complex synthetic gene networks
Schreiber Joerg, Arter Meret, Lapique Nicolas, Haefliger Benjamin, Benenson Yaakov (2016), Model‐guided combinatorial optimization of complex synthetic gene networks, in Molecular Systems Biology, 12(12), 899-899.

Collaboration

Group / person Country
Types of collaboration
Ron Weiss Lab/Massachusetts Institute of Technology United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
Eduardo Sontag/Rutgers University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
Savas Tay/ETH Zurich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Bose Institute Centennial Celebration Talk given at a conference Mammalian Synthetic Biology: Past, Present and Future 29.11.2018 Calcutta, India Benenson Yaakov;
AI for Synthetic Biology 2, Federated artificial intelligence meeting (FAIM18) Talk given at a conference Whither synthetic biology and artificial intelligence? 13.07.2018 Stockholm, Sweden Benenson Yaakov;
PhD student conference, Institute of Molecular Genetics Talk given at a conference Mammalian gene circuits: from fundamentals to applications 29.06.2018 Prague, Czech Republic Benenson Yaakov;
CompuGene Symposium, UT Darmstadt Talk given at a conference Synthetic mammalian gene circuits - from fundamentals to applications 19.06.2018 Darmstadt, Germany Benenson Yaakov;
69. Mosbacher Kolloquium - "Synthetic Biology - from Understanding to Application" Talk given at a conference Mammalian gene circuits: from fundamentals to applications 22.03.2018 Mosbach, Germany Benenson Yaakov;
Synthetic biology seminars, Imperial college Individual talk Synthetic mammalian gene circuits - from fundamentals to applications 02.03.2018 London, Great Britain and Northern Ireland Benenson Yaakov;
Bioengineering Department Seminar, UT Dallas Individual talk Synthetic mammalian gene circuits - from fundamentals to applications 12.01.2018 Dallas, TX, United States of America Benenson Yaakov;
Synthetic Biology Seminar, Boston University Individual talk Synthetic mammalian gene circuits - from fundamentals to applications 10.01.2018 Boston, MA, United States of America Benenson Yaakov;
Farewell Bauer Fellows Program Symposium Talk given at a conference Talking to cells with gene circuits 09.01.2018 Boston, United States of America Benenson Yaakov;
Computational Biology Seminar, University of Basel Individual talk Synthetic mammalian gene circuits - from fundamentals to applications 21.11.2017 Basel, Switzerland Benenson Yaakov;
SynBio Conference Talk given at a conference Genetic Circuits in Mammalian Cells 19.09.2017 Venice, Italy Benenson Yaakov;
The FEBS Congress 2017 Talk given at a conference Synthetic Biology for Cancer cell targeting: The signal and the noise 10.09.2017 Jerusalem, Israel Benenson Yaakov;
2017 Synthetic Biology: Engineering, Evolution & Design (SEED) Poster Extracting Input/Output Relationship of Mammalian Gene Circuits using Transient Transfections 20.06.2017 Vancouver, Canada Stelzer Christoph;
Ascona Wrokshop: Statistical Challenges in Single-Cell Biology Talk given at a conference Synthetic gene circuits for in situ cell classification 30.04.2017 Ascona, Switzerland Benenson Yaakov;
NSF/Rice Workshop: Systems and Synthetic Biology for Designing Rational Cancer Immunotherapies Talk given at a conference Cell classifiers for precise cell targeting 06.10.2016 Washington DC, United States of America Benenson Yaakov;
Basel Life Science Week Talk given at a conference Biomolecular computing systems for diagnostics and treatment 22.09.2016 Basel, Switzerland Benenson Yaakov;
International Synthetic and Systems Biology Summer School - SSBSS 2016 Talk given at a conference The Practice of Mammalian Synthetic Biology and Mammalian Cell Classifiers 08.07.2016 Volterra, Italy Benenson Yaakov;
Latsis Symposium Talk given at a conference Synthetic Biology for Precision Medicine 29.06.2016 Zurich, Switzerland Benenson Yaakov;
Synthetic Biology Seminar, UT Darmstadt Individual talk Biological computing - from concepts to applications 16.06.2016 Darmstadt, Germany Benenson Yaakov;
The first Pearl Seiden International meeting in Life Sciences, Technion Talk given at a conference Biomolecular Computing Systems: From concepts to applications 09.12.2015 Haifa, Israel Benenson Yaakov;
Second International Mammalian Synthetic Biology Workshop Talk given at a conference Biomolecular Computing meets Synthetic Biology 02.05.2015 Boston, United States of America Benenson Yaakov;
Symposium "Sage perspectives on science, technology and industry". Weizmann Institute Talk given at a conference Biomolecular Computing Systems 02.03.2015 Rehovot, Israel Benenson Yaakov;


Self-organised

Title Date Place
Dagstuhl Seminar 18082 Formal Methods for the Synthesis of Biomolecular Circuits 18.02.2018 Dagstuhl, Germany

Communication with the public

Communication Title Media Place Year
Talks/events/exhibitions Closing the cellular circuit, Boston MA International 2015

Use-inspired outputs


Start-ups

Name Year
Pattern BioSciences 2018

Abstract

RNA interference (RNAi) was discovered about two decades ago and since then has become a focus of intense investigation, both due its basic biological importance in controlling gene expression across multiple kingdoms of life and because of its potential importance in disease diagnostics and treatment. RNAi has also formed the basis of an increasing number of synthetic gene circuits, whose applications range from basic biological research to biomedicine. Yet despite enormous progress in our understanding and utilization of RNAi pathway, surprisingly little is known about fine-grained quantitative parameters of this process. For example, a question such as "What is the expected gene knockdown by a specific concentration of a certain microRNA molecule, given the sequence of a microRNA target in this gene's 3'-UTR?" cannot be answered using current knowledge. We contend that measuring and understanding these parameters is key to future advances of basic and applied exploration of RNA interference. This proposal described a series of experiments whose collective aim is to elucidate quantitative features of RNAi in mammalian cells on a population and single-cell level. The key experimental goal is to link the amount of intracellular microRNA molecules, measured in absolute units, to the observed degree of target gene knockdown under different conditions. The experimental variables include the sequence of a microRNA itself, sequence of the microRNA target (ranging from partial to full complementarity and varying the number of target repeats), and the cell type in which the knockdown takes place. Quantitative data will form the basis of a computational model that will recapitulate RNAi pathway with unprecedented degree of precision, capturing both average features and cell-to-cell heterogeneity ("noise"). Ultimately, the data in combination with the model will allow the construction of "universal" genetic microRNA sensors capable of reporting absolute intracellular microRNA levels based on fluorescent readouts. Such easy-to-use, high-throughput sensors will be of immediate importance in both basic biological studies and as a diagnostic tool in the clinic.
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