In a field that is new and rapidly expanding, everyday we see different scientists performing amazing feats centered on furthering our understanding on how to control molecular biological systems. One scientist at Pennsylvania State University is taking a unique approach by focusing his team on the development of predictive biophysical models of gene expression, and developing algorithms to help rationally design genetic circuits and pathways.
Dr. Howard Salis has been running his own wet lab for roughly three and a half years with a team of six grad students and a post doctorate fellow. Howard, himself, earned his Ph.D in Chemical Engineering from The University of Minnesota, and now focuses primarily on synthetic biology, genetic compilers, and metabolic engineering. By truly understanding the biophysical models of genetic regulation his goal is to “eliminate the trial-and-error from the engineering of biology”.
In his lab each of his students learn how to clone and characterize their genetic system and then take the data and both formulate and validate their biophysical models based on statistical mechanics, kinetics, and thermodynamic measurements. When designing the experiments to validate the models Dr. Salis and his team do it with systematic perturbation of very specific interactions in mind within industrially useful or medically relevant bacteria and eukaryotes.
Part of the beauty of his work is that the product of it is readily accessible online. What he has is a ribosome binding site calculator and a small RNA calculator. As a user, you can either select to forward or reverse engineer a sequence. In reverse engineering mode, the user inputs any mRNA sequence and for each start codon the calculator will calculate the translation initiation rate for those start codons. The user also has the ability, in forward engineering mode, to input in a protein coding sequence and a target translation initiation rate, which is on a scale from 1-100,000+ depending on how much protein is desired. What the calculator ultimately does is it helps control gene expression at the translation initiation step, which is rate limiting. The user is also able to apply constraints to their model because often times when designing a strain the RBS is next to a restriction site or a primer binding site.
Scientists, whether they are a part of academia or industry, are really interested in tuning protein levels. It affects the amount of protein they can purify at the end of the day and its solubility. This is very popular in the biopharmaceutical industry because those companies generally want to express a high valued protein. So far his algorithm is accurate to within two-fold, meaning that if your target is ten you can get anywhere from 5-20.
Another magnificent piece of work is his algorithm helps you narrow down to the optimal translation initiation rate in order to produce a system that makes the most protein (or money). With his RBS Library Calculator, you can design a single degenerate RBS sequence and carry out a small number of experiments (8 to 32) where the protein levels have all been varied across a wide range; for example (5, 10, 50, 100… 100,000). In a recently accepted paper, he demonstrated how algorithm could be used to systematically increasing the biosynthesis of renewable chemical by systematically varying the expression levels of a three-enzyme pathway, constructing the pathway variants using the Gibson method of combinatorial cloning, and characterizing a relatively small number of variants (73). With the biophysical model predictions and these experimental measurements, they were able to create a map of the pathway that shows where the pathway’s optimal enzyme expression levels are located. These optimal expression levels are then achieved by another round of mutagenesis, using their biophysical models to rationally design DNA mutations.
We are excited to see this tool continue to evolve and are looking forward to the effect this will have on the industry of synthetic biology.
Read his recently published paper Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria .
Check out more on his lab’s website.
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