Stochastic Modeling of the Quorum Sensing Network in Agrobacterium tumefaciens Brendan Davis*, Leigh Nicholl, David Brown, and Phoebe Lostroh, Departments of Mathematics and Biology. For years, prokaryotes were thought to be simple, single cell organisms without communicate or interact. We now know bacteria, such as Agrobacterium tumefaciens, use small, autoinducing molecules to sense population densities. This "quorum sensing" (QS) model works on a positive feedback loop and signals the bacteria to insert a tumor inducing (Ti) plasmid into the nucleus of a plant cell by horizontal gene transfer. Here, we used a stochastic model to mathematically evaluate the quorum sensing system. We found under certain conditions the model acted as a "bistable switch", turning the system “on” and "off" at random. When a second cell was introduced to the model it increased the probability of the system turning "on". We also found that by manipulating various variables we could alter the frequency of the QS network turning "on". With this research, we are able to better understand the coordination involved in the infection of host plants by Agrobacterium tumefaciens. Thus, we can predict possible treatments for the progression of tumors in plants that are infected by crown gall disease. This type of model has implications to many other mathematical models in which this “bistable” phenomenon may be observed, as well as applications to other quorum sensing networks.