IGEM:IMPERIAL/2009/Feedback & Debriefs/Feedback 4 9

Feedback – 090904 – Debrief with Profs, Supervisors, Advisors

• Good reception to the casein pill exemplar.
• Show this at the Jamboree as a demonstration of what the end result would be.

• Just test enzyme activity in M1 as opposed to concentrations. No quantitative method without purifying the protein. Can get someone in the dept to purify some protein for us?
• Have a backup in case the RcsB constructs don’t work. Constituitively express RcsB.

• Need critical path. Drop things that aren’t as important e.g. trehalose is additional to optimise the system. This is not as essential as RcsB.
• Need to get something going that actually works. Can get into complex details and make it more sophisticated once it is working. Need data that shows the system works.
• Autoinduction/switch between M1 and M2 is high priority and needs to be well characterised.

• Can we add an RFP degradation tag to C2?
• Characterise secondary carbon source.

• Test M3: Digest genomic prep in vitro vs. overexpressed digest in vivo and compare.
• Test another inducible GFP at different temperatures (e.g. IPTG) – do temp shift and induce, see if it is being degraded or expression is increased.
• Dam +ve and –ve strains – ASK GEOFF!!!

• Always keep in mind the critical steps and what is minimally needed to obtain data.

• YouTube videos are good.
• Do Flash animation for presentation. Start now because it will take time.

• Don’t spend too much time on ethics. Must agree to the video before it’s posted and everyone must be happy about it. Must agree to it being posted on YouTube. If you’re not happy about anything then speak up.

• Wiki – like the new template and logo.
• Make the wiki more visual, there is too much text at the moment.
• Standardise all diagrams.
• Make important links more prominent.

• Including equations for models is important. And don’t forget to connect all modelling back to the biological representation of the system.
• Synergise wet lab and dry lab.
• Use the modelling to optimise or troubleshoot, if possible.
• Is there any parameter sensing/sensitivity testing to show?
• Sensitivity analysis doesn’t make sense unless parameters are known. Bit of a vicious circle.
• Know what to expect in the wet lab. Is there any sensitivity analysis that we can do?
• Influence wet lab with what is done in the dry lab – has this been done so far? Can modelling bring advantages to the wet lab?
• Ensure wet lab give data to dry lab.
• In the presentation need to ensure we can show how the modelling helped our project.
• Make sure modelling has a role, not that it is just used as an add-on.

• Ethos of SB is to drive engineering-type concepts and approaches to biology. Demonstrate this in our project – is it possible?