Researchers studying simple, synthetic gene networks created mathematical models that enabled them to predict more complex network behaviors, providing a proof-of-principle of one of the central tenets of synthetic and systems biology, according to a report in this week?s Nature.?This broad kind of approach that we call a bottom-up approach is in fact feasible,? senior author J. J. Collins of Boston University told The Scientist. He added that other studies have shown that mathematical models can describe simple synthetic network behavior, but no one had yet shown that these models could then be used to predict more complex behaviors.Led by Collins and first author Nicholas Guido, the researchers engineered four different types of simple gene networks in Escherichia coli cultures. Due to differences in transcriptional promoters, adding certain chemicals to the cultures activated transcription of the green fluorescent protein (GFP) gene in one system, but repressed transcription of...

Interested in reading more?

Become a Member of

Receive full access to more than 35 years of archives, as well as TS Digest, digital editions of The Scientist, feature stories, and much more!
Already a member?