Last week I joined the International Synthetic and Systems Biology Summer School in Taormina, Italy and as the title describes it was all about Synthetic and Systems biology with some pretty cool speakers. Weiss talked about the general principles of genetic circuits and the current limitations (record is currently 12 different synthetic promoters in 1 designed network). Sarpeshkar focused on the stochastic nature and the associated noise of cells, he showed how they can be simulated or mirrored using analog circuits. Paul Freemont took Ron Weiss’ design principles and showed how to apply them on different examples, he also elaborated on an efficient way of characterizing new circuits and parts. Tanja Kortemme, a former postdoc from the Baker lab, gave an introduction to the capabilities of computational protein design and using some neat examples showed the power (and limitations) of computational design. Below some highlights and the relevant links of the literature that was discussed.
Ron Weiss, MIT
About the noise propagation and general rules for building genetic circuits:
A software tool to program genetic networks called BioCompiler:
Rahul Sarpeshkar, MIT
About analog vs. digital
On the deep connections and entanglement between electronics and biochemistry
An almost 1000 page book Sarpeshkar wrote on “bioelectronics” couple of chapters are freely downloadable:
Ultra Low Power Bioelectronics: Fundamentals, Biomedical Applications, and Bio-inspired Systems
Farren Isaacs, Yale
Review on the current genome editing tools:
Paul Freemont, Imperial College London
On the standardisation of DNA elements (RBS, promotor, etc):
Very nice “How to build a biosensor review/guide/tutorial”:
Goers, L. et al. Engineering Microbial Biosensors. Microb. Synth. Biol. 40, 119–156 [$]
Tanja Kortemme, UCSF
Loop closure in protein design based on robot algorithms:
Rewiring cellular signal pathways using computational protein design:
The seminal article of the Bakerlab on the basic design rules of proteins:
Koga, N. et al. Principles for designing ideal protein structures. Nature 491, 222–7 (2012). [“OA”]