(230f) Stochastic Modeling of Biological and Gates

The objective of this project is to build and stochastically model components of a novel biological AND gate, using principles of engineering and synthetic biology. Stochastic modeling gives us the ability to quantitatively analyze the behavior of biological systems using networks of reactions. We can use these models to test if our understanding of the system is correct. If not, we can easily make changes to describe the system without doing any potentially costly or time-consuming experiments. This motivates using models in all contexts, but is of particular value as a predictive tool with previously unstudied synthetic systems. These synthetic biological systems have great potential and have the potential to help solve many of the pressing problems in our world today, such as the growing cost of drugs and the growing energy demand. These new constructs are engineered by modifying and combining natural biological components. For drug production, cells have already been made to produce anti-malarial drugs much cheaper than through industrial synthesis methods. Addressing our energy demand, synthetically engineered ethanol-producing bacteria have allowed us to utilize previously unusable biomass in order to produce energy. Our synthetic system, a novel biological AND gate, has great potential as well. It can be used in a variety of systems, from a biological comparator to ethanol-producing bacteria. In order to build up to these more complex systems, we are first working on understanding and modeling to understand the base components of the AND gate using stochastic modeling. Once we accomplish this, we can build a more robust AND gate by analyzing how each component contributes to the system. Our logic gate shows a fluorescent response if and only if two inducer molecules, anhydrotetracycline (aTc) and isopropyl β-D-1-thiogalactopyranoside (IPTG) are present in the system. Otherwise, the system will show very low response. This type of construct has been built and tested previously by Ramalingam and coworkers.We have built on this work by experimentally creating and stochastically modeling the individual operator sites which make up this AND gate. Our system consists of combinations of two different operator sites, tetO and lac, which bind two different repressor proteins, TetR and LacI, respectively. By shifting these operator sites in the synthetic DNA sequence, multiple alternative designs of the AND gate are possible. Several of these combinations led to an effective AND gate, but it was unclear what the role of each individual operator was in the logic gate. To understand more completely what is occurring in the AND gate, stochastic models were created that describe the biological phenomena occurring in the cell. We modeled all the steps of the molecular biology dogma, such as transcription and translation, along with the specific repression present in our systems. This type of modeling allows us to make very specific changes to analyze the experimental systems. This work shows that this type of modeling can accurately describe experimental results, and can broaden our knowledge of the mechanisms occurring in the system. We can use a similar approach to study other aspects of the AND gate, and expand this approach to other, more complex logical structures.