Education & Certifications
Bachelors, University of Kansas, Math (2012)
Master's, University of Kansas, Physics (2013)
I study computationally and analytically the Type Three Secretion System.
The Type Three Secretion System (TTSS) is a nanomachine in pathogenic bacteria that is used to transport effector proteins from bacteria into the eukaryotic host cells during infection. The "needle complex," also known as the injectisome, is a main component in the system, composed of a multi-ring base and a needle. In Salmonella, the needle is composed of a single protein, PrgI. It is connected to another structure in the TTSS, the inner rod, which extends along the lengh of the base and is composed of a single protein PrgJ. The assemble of the needle is a regulated in order to prevent needle lengths that are shorter than the Bacteria's Glycen layer and longer than the host cell's range of antibodies. Several mechanisms have been proposed to explain the control of needle assemble. One of these is the substrate switching hypothesis. It states that the inner rod and the needle assemble simulatenously and that termination of inner rod assembly triggers changes in the TTSS which terminate assembly of the needle. The length of an assembled inner rod is not known.
I developed a mathemtical model which assumes the substrate switching hypothesis as the mode of regulation. The mathemtical model shows relationships at steady-state between needle length, inner rod length, protein concentrations, and production rates which can be tested experimentally. In addition, the model predicts a nontrivial relationship between average needle length and variance which is confirmed by available experimental data. Moreover, based on available needle length histograms for experiments that vary production rates of PrgI and PrgJ, the model predicts the assembled inner rod length using the average and variance in the histograms which is consistent across the various histograms. Finally, the model shows the possible regimes in needle assembly under extreme conditions (for example, overabundance of empty injectisome bases) and the expeted changes in the steady-state relationships.
To further test the mathemtical model, I developed rule-based stochastic simulations of the needle asssembly process. The simulation results at steady state confirm all the analytic predictions in the mathematical model. Furthermore, a best fit estimator of the experimental needle length histograms from the simulations predicts the same inner rod length that the mathemtical model predicts based on the average and variance in the histograms.