Synthetic Biology

Follow-up to Group meeting: Boston and Jerusalem from Schreibfaul in Warwick

…and it comes back to haunt you. Need to make an overview of the Heidelber conference. Let's look at the Collins talk first :

Title: "Integrating synthetic biology and systems biology"
Collins, J. J., 20 Oct 2005

1. Building synthetic gene networks: Gene toggle and RNA swithces
2. Applications in microbiology: (anti)toxins and cell death pathways
3. Inferring genetic networks: using the network model to infer the mode of action of drugs

To one. Synthetic gene networks:

• Forward Engineering. Design switch, simple modeling,produce plasmids and see if it works. Gardner in Nature 2000. (Toggle switch in E.coli).
• moving from e. coli up to yeast and mammalian systems. coupling to natural systems.
• RNA based synthetic biology: Enginieered ribo–regulators. Issacs Nature Biotechnology 2004

To two. Applications in microbiology:

• biosensors and programmable cells
• wirkung von toxins. Afif 2001 CcdB
• gradielles anschalten von toxins, antibiotics. following along the cell death pathway. iron comes in at later stage. unpublished at the time.

To Three. Infering genetic networks:

• Reverse engineering gene networks
• overexpress genes of interest, obtain expression profiles, feed into NIR algorithm, reverse engineer regulatory network
• Yeung PNAS 2002 and Tegner PNAS 2003
• Example with E Coli SOS pathway: Gardner Science 2003
• 9 gene subnetwork. perturb gene expression. output by real time pcr. algorithm gives graphs, sign and strength of interaction.
• next step: use result to find key players with most influence over the other genes. recA, lexA which confirms previous biological results.


• Most exciting application: Infer the mode of action of compounds.
• drugs: know drug hits some target. but: what else does that drug hit? difficult
• now if you know the network and you know the output, you can infer what the input was.
• test approach with the sos pathway by upregulating recA, lexA, measure output, run NIR and infer that recA, lexA was upregulated. horay.


• up to higher organism. very costly to turn genes up or down. So you are only left with the output. hope is that by a lot of perturbations like drugs, mutations etc. might still infer network. Bernardo Nature Biotechnology 2005

*Future applications:"

• Mammalian Systems
• Network based drug development
• Multi–scale approaches

: 26 Jun 2006 12:03 |  Comments (0) |  Report a problem