Engineering Advanced Logical Operations for Gene Control

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

Living systems respond to stimuli in the environment. Personalized medicine and bio-industrial applications are made possible by this trait. An obstacle to developing these applications is a lack of regulators (i.e., switches that can turn genes on or off) that can facilitate complex operations. This project will attempt to create a new class of gene regulators that can perform fundamental logical operations (i.e., AND, OR, NOT). These regulators can be combined in sequences that mimic a computer program. These biological programs will direct the cell to fulfill specific functions. One example might be the following: if compounds E (AND) F are detected, then turn on gene G; if E (OR) F are present individually, then NOT G. This project will be complemented by outreach activities aimed at educating students from underrepresented groups in state-of-the-art biological engineering. This initiative will contribute to the development of a diverse engaged science and engineering workforce, building a firm foundation for a lifetime of contributions to research, education and their integration. The goal of this project is to develop combinational logic gates (programs) in cells to implement multiple input signal control over gene transcription. The biological programming envisioned will require the creation of a new class of DNA-binding transcription factors. Successful completion of the project will result in a new class of orthogonal and modular DNA-binding transcription factors that work as logical systems. The resulting system will allow programmable microbial decision making, where different combinations of signal inputs result in distinctive combinations of genetic outputs. These transcription factors can be directly introduced into existing genetic circuits at any position where transcription is regulated by a DNA binding protein (or system of transcription factors). Successful completion of this project will result in a significant enhancement in biological computing capacity, which will enable the construction of synthetic regulatory networks at the scale of natural networks in bacteria. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.