Gluten intolerance disorders such as Celiac sprue elicit a painful immunological response in the intestines of patients who consume gluten. Gluten is a polypeptide found in wheat, barley, and rye, and contains repeating Pro-Gln-Leu-Pro (PQLP) motifs. Currently the only treatment for gluten intolerance is elimination of gluten from the diet. Our goal is to design an enzyme therapeutic that can be taken as a drug therapeutic in pill form. The engineered enzyme will break down the immunogenic PQLP motifs before gluten reaches the small intestine and can elicit an inflammatory response. Kumamolisin-As, a protein isolated from Alicyclobacillus sendaiensis, demonstrates promising proteolysis on PQ residues, and works in the low pH of the stomach. Using the protein-engineering program “FoldIt,” we designed novel mutations to Kumamolisin to improve its activity on PQLP. Our best version of the enzyme, dubbed KumaMax, degrades gluten over 700 times faster at pH 4 than SC-PEP, an enzyme currently in clinical trials. After further protein characterization, we hope to start clinical trials on KumaMax with the future goal of creating an effective treatment for gluten intolerance.

Recent advances in genome sequencing have allowed for the study of metagenomes, genetic material recovered directly from environmental samples. This has produced an enormous number of enzyme sequences without efficient methods for characterization. Since it is unknown whether a characterized enzyme is the best catalyst for a specific reaction, uncharacterized, natural enzymes in the metagenome may be better candidates for catalyzing the specific reaction. Thus, I am developing methods to search for and computationally characterize metagenomic enzymes with the same function as enzymes of therapeutic and commercial interest. By utilizing the Rosetta Software Suite to produce highly accurate models of enzyme structures, this method will evaluate an enzyme sequence’s potential for catalysis directly from a gene sequence. In order to validate my computational techniques, I will experimentally determine catalytic rates of enzyme candidates. As the method for an efficient metagenome search is still unknown, I am working to determine proper parameters for a homology search by using visual and statistical analysis of enzyme structure models in order to produce a diverse set of genes for experimental characterization.

Synthetic biology holds great promise regarding the production of important compounds, and the degradation of harmful ones. Last summer, we harnessed the power of synthetic biology to meet the world’s needs for fuel and medicine. We constructed a strain of Escherichia coli that produces a variety of alkanes, the main constituents of diesel fuel, by introducing a pair of genes recently shown convert fatty acid synthesis intermediates into alkanes. Using this method, we were able to produce on average 160 mg of alkanes per liter. Also, we identified a protease with gluten-degradation potential, and then reengineered it to have 100 times increased gluten-degrading activity, allowing for the breakdown of gluten in the digestive track when taken in pill form. Finally, to enable next-generation cloning of standard biological parts, BioBrick vectors optimized for Gibson assembly, an emerging DNA cloning technique, were constructed and used to construct the Magnetosome Toolkit: genes for biofabrication of magnetic particles.

Conversation analysis has shown that certain linguistic factors (avoidance of pronouns, increased negative words, e.g.) are affected by the act of deception. Studies have proven that the act of deception increases cognitive load and results in behavioral and linguistic indicators. Little research has been done on the potential cognitive strain that could result from speaking in a second language and none has been done to explore the effect that deception and second language production would have when done simultaneously. Second language discourse has also been proven to increase cognitive load. Therefore we expect that the added cognitive strain resulting from the use of a second language while participating in an act of deception will further exaggerate the well known linguistic indicators of deception. We believe our findings will show that the increased cognitive effort caused by a speaker using a second language while participating in deception will exaggerate the linguistic factors affected by deception, making it easier to identify in discourse analysis.