Mathematics in everyday life

New paper on temperature compensation in synthetic gene circuits

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Will Ott, Chinmaya Gupta and I  have been collaborating with Matt Bennett’s group at Rice on modeling different synthetic gene circuits.  A new paper in PNAS describes some of our recent work (link to paper at bottom).  Matt is interested in engineering  synthetic gene circuits that are robust and predictable.  This is difficult, since most current technology produces circuits that are often fragile – perturbations will alter their behavior.  The mathematical tools that will allow us to design circuits with desired properties are also in their infancy.  

In our work we showed that environmental sensitivity can be reduced by simultaneously engineering circuits at the protein and gene network levels. Faiza Hussain and others in Matt’s lab constructed a synthetic genetic clock whose period does not depend on temperature.  Why is this surprising?  Well, as temperature changes, biochemical reactions speed up.  Unless the genetic oscillator has special properties, its frequency will thus increase with temperature (BTW, this is also a problem with mechanical clocks which was solved by John Harrison).

To solve the problem , Matt’s group engineered thermal-inducibility into the clock’s regulatory structure.  What this means, is that they used a mutant gene as part of the gene circuit.  We hypothesized that this mutation changed the rates of a particular reaction in the genetic circuit. Chinmaya Gupta used a computational model to check whether this idea explains the observed temperature compensation.  Indeed, the results of including the rate changes in the computational model resulted in a clock with a stable period across a large range of temperatures. This matched precisely the behavior of the mutant synthetic clock.

I find this satisfying for two reasons:  First I think that it shows that we can set out to design genetic circuits that behave robustly. Second, and more important to me, we can use mathematical modeling to understand what about these circuits makes them tick and how. I hope that we will be able to understand native gene circuits, and design new ones using such tools.  

Here is some coverage with a video.

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