Karen M. Ong, John A. Blackford, Jr., Benjamin L. Kagan, S. Stoney Simons, Jr., and Carson C. Chow. A theoretical framework for gene induction and experimental comparisons PNAS 200911095; published ahead of print March 29, 2010, doi:10.1073/pnas.0911095107
This is an open access article so it can be downloaded directly from the PNAS website here.
This is a paper where group theory appears unexpectedly. The project grew out of a chance conversation between Stoney Simons and myself in 2004. I had arrived recently at the NIH and was invited to give a presentation at the NIDDK retreat. I spoke about how mathematics could be applied to obesity research and I’ll talk about the culmination of that effort in my invited plenary talk at the joint SIAM Life Sciences and Annual meeting this summer. Stoney gave a summary of his research on steroid-mediated gene induction. He showed some amazing data of the dose response curve of the amount of gene product induced for a given amount of steroid. In these experiments, different concentrations of steroid are added to cells in a dish and then after waiting awhile, the total amount of gene product in the form of luciferase is measured. Between steroid and gene product is a lot of messy and complicated biology starting with steroid binding to a steroid receptor, which translocates to the nucleus while interacting with many molecules on the way. The steroid-receptor complex then binds to DNA, which triggers a transcription cascade involving many other factors binding to DNA, which gives rise to mRNA, which is then translated into luciferase and then measured as photons. Amazingly, the dose response curve after all of this was fit almost perfectly ( > 95%) by a Michaelis-Menton or first order Hill function
where P is the amount of gene product, [S] is the concentration of steroid, Amax is the maximum possible amount of product and EC50 is the concentration of steroid giving half the maximum of product. Stoney also showed that Amax and EC50 could be moved in various directions by the addition of various cofactors. I remember thinking to myself during his talk that there must be a nice mathematical explanation for this. After my talk, Stoney came up to me and asked me if I thought I could model his data. We’ve been in sync like this ever since.