How the Team Met
Part of the team learned about iGEM during the [http://www.vvz.ethz.ch/Vorlesungsverzeichnis/lerneinheitPre.do?lerneinheitId=48939&semkez=2008S&lang=en Synthetic Biology Lecture] given by our instructors at ETH. Another part of the team applied after receiving the following ETH wide e-mail promoting iGEM:
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What is the most exciting thing natural scientists and engineers can do together? - The iGEM summer competition!
iGEM is an international student competition in the field of synthetic biology, organized by MIT. Each participating university sets up an interdisciplinary student team consisting of 8 to 10 biologists,chemists and engineers.
Half of the team has to be undergraduate students, but also MSc and PhD students can participate.
The team's goal is to collect ideas on a novel biological system, analyze the biological and engineering design alternatives, including mathematical modeling of the system, and choose the 'best' design.
This system is then translated into DNA code, put into a cell and tested experimentally.
In November, all teams present their projects at the MIT in Boston. In 2007, there were 57 teams from all over the world, including teams from MIT, UCSF, Caltech, Duke, Stanford, TIT, Princeton, Cambridge, Imperial, Harvard, UC Berkeley, and more teams from the US, Australia, India, China, Japan, and Europe (http://parts.mit.edu/igem07/index.php/Main_Page ).
After major successes in 2005 (best engineering), 2006 (best device) and 2007 (best presentation), ETH is participating again this year, and professors Sven Panke and Jörg Stelling are assembling a mixed team of engineers and natural scientists from the Bachelor, Master and PhD level. If you want to be part of the iGEM experience, apply until April 11th on
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For this year's team nine students got selected, and on Wednesday, April 16th, the first meeting was scheduled.
As you can see on our Team Members Page, students from very diverse fields were offered the possibility to participate in the ETH iGEM team.
Boot Camp
The following weeks were what last year's team had refered to as "Boot Camp".
Our advisors organized two weeks of an intense crash course into the field of synthetic biology, during which we learned about the diverse aspects of the field:
The "Boot Camp" Schedule
| Date | Topic1 | Topic2
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| Mo, 21.4
| Synthetic Biology:
[http://www.nature.com/nature/journal/v438/n7067/full/nature04342.html Foundations for engineering biology]
[http://www.nature.com/msb/journal/v1/n1/full/msb4100025.html Refactoring bacteriophage T7]
| DNA de nova design:
[www.nature.com/nature/journal/v432/n7020/full/nature03151.html Accurate multiplex gene synthesis from programmable DNA microchips]
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| Th, 24.4
| Distance:
[http://www.pnas.org/content/101/17/6355.abstract?ct Spatiotemporal control of gene expression with pulse-generating networks]
| DNA circuits:
[http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2223271 Implications of Rewiring Bacterial Quorum Sensing]
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| Mo, 28.4
| Modeling biological systems:
[http://www.nature.com/nature/journal/v443/n7111/abs/nature05127.html From in vivo to in silico biology and back]
[http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B7CV1-4R0B1NJ-W&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_version=1&_urlVersion=0&_userid=10&md5=986df2ce56132cac5c30392f7970e2a4 Methods for Simulating the Dynamics of Complex Biological Processes]
| Network dynamics:
[http://www.iop.org/EJ/article/1478-3975/1/3/006/ph4_3_006.html The statistical mechanics of complex signaling networks: nerve growth factor signaling]
[http://bib.oxfordjournals.org/cgi/content/full/bbm029v1 Petri net modelling of biological networks]
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| Wed, 30.4
| Identification & Robustness:
[http://bib.oxfordjournals.org/cgi/content/full/bbm007v1 Bayesian methods in bioinformatics and computational systems biology]
[http://www.galenicom.com/es/medline/article/17003073 Strategies for dealing with incomplete information in the modeling of molecular interaction networks]
| Synthetic circuit design:
[http://www.biophysj.org/cgi/content/full/87/4/2195 Optimizing Genetic Circuits by Global Sensitivity Analysis]
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| Fr, 2.5
| Oscillators:
[http://www.nature.com/nature/journal/v403/n6767/abs/403335a0.html A synthetic oscillatory network of transcriptional regulators]
[http://www.cell.com/retrieve/pii/S0092867403003465 Development of Genetic Circuitry Exhibiting Toggle Switch or Oscillatory Behavior in Escherichia coli]
| Hysteresis:
[http://www.pnas.org/content/102/27/9517.abstract?ck=nck Hysteresis in a synthetic mammalian gene network]
[http://www.nature.com/nature/journal/v427/n6976/abs/nature02298.html Multistability in the lactose utilization network of Escherichia coli]
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| Tu, 6.5
| Noise/single cells:
[http://www.nature.com/nature/journal/v405/n6786/abs/405590a0.html Engineering stability in gene networks by autoregulation]
| mRNA tools, protein tools:
[http://www.nature.com/nbt/journal/v24/n8/full/nbt1226.html Combinatorial engineering of intergenic regions in operons tunes expression of multiple genes]
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| Fr, 9.5
| Meeting - reduce Topics from Brainstorming
| Restriction enzymes
Cloning strategies
Biobrick standard
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| Th, 15.5
| Meeting
| The MIT registry
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| Wed, 21.5
| Meeting
| Protein half-life, specific proteases,
epPCR to adapt systems
Parameter manipulations
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| Th, 29.5
| Meeting
End of Planning Phase - Submission DNA Sequence
| GFP - protein and measurements.
Chemical/physical basis of XFP. Flourescence, excitation and emission spectra of various proteins, measurement techniques
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| 2.-5.6
| LABCOURSE at CNB
| Basic hands-on modelling
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Lab Course
Additionally, one week of lab crash course was integrated into the "Boot Camp" in the beginning of June. The aim of this course was to introduce non-biologists to basic techniques of micro- and molecular biology. That way they were able to assist the biologists so that the latters could concentrate more on experimental planning and interpretation of results. The idea was to grasp this chance of an interdisciplinary project in order to offer the students the possibility to get an insight into a field that is totally different from their university background. Therefore, the modellers got comfortable in the lab, and the biologists learned about modelling.
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