Jeffrey J. Tabor
Assistant Professor of Bioengineering
Assistant Professor, Biochemistry and Cell Biology
Postdoctoral Fellow, Department of Pharmaceutical Chemistry,
University of California, San Francisco (2006-2010)
Ph.D., Molecular Biology, University of Texas (2006)
B.A., Biology, University of Texas (2001)
Jeff Tabor builds synthetic signaling circuits to engineer biological behaviors such as multicellular pattern formation and social interactions. Tabor takes an engineering approach by using cellular sensors and synthetic gene circuits to control genes of interest in tractable model organisms. Because these control systems are constructed in a step-wise fashion, they are amenable to rigorous characterization and optimization. This allows the development of well-parameterized mathematical models that increase the predictability of the design process in synthetic biology. Reprogramming how cells respond to their environment and interact with one another is of interest to basic science and has broad biomedical and industrial applications.
Projects in Tabor's laboratory at Rice include using light and other forms of electromagnetic radiation to control the activities in proteins inside of cells in real time, constructing synthetic transcriptional and post-translational signaling circuits, programming cells to communicate using unnatural signals, and combining all of these technologies to program synthetic multicellular behaviors.
Tabor is the principal investigator on a new $2 million, NSF-funded collaboration between Rice and the University of Washington that aims to program the model bacterium E. coli to autonomously grow into a wide range of shapes and structures. The goal is to combine experimental and computational approaches from computer science, physics and synthetic biology to understand and control how cells interact and make decisions in space and time.
Tabor is also the recipient of the Rice University Institute of Biosciences and Bioengineering’s Hamill Innovation Award (2011). The funding supports collaborative efforts to engineer synthetic microbial ecosystems.
In previous research, Tabor worked as a postdoctoral fellow in Christopher Voigt’s laboratory at University of California, San Francisco where he programmed bacterial communities to function as a light-responsive photographic film and work as a parallel computer to perform the image-processing task of edge detection. The research, which was supported by a Ruth L. Kirschstein National Research Service Award (NRSA) from the National Institutes of Health, demonstrated that complex multicellular behaviors can be engineered by the stepwise assembly of well-characterized genetic modules.
During his Ph.D. research with Andrew Ellington at the University of Texas, Tabor studied how synthetic genetic circuits affect stochasticity, or noise, in gene expression. Using the model bacterium E.coli his work demonstrated that synthetic genetic circuits can result in a competition for the protein translation machinery and this competition can reduce the level of precision with which the cell can express genes. He went on to demonstrate that the operon architecture, where multiple genes are transcribed on a single mRNA, serves to buffer away much of the natural noise in gene expression and can even protect against extra noise introduced by synthetic gene circuits.
The tools of modern molecular biology allow the DNA of living organisms to be rapidly rewritten, and this in turn allows unnatural biological behaviors to be engineered. We take a synthetic biological approach to studying how population-level phenomena, such as multicellular pattern formation and cooperation, are coordinated by the underlying gene regulatory networks. By constructing synthetic gene regulatory networks and linking cells together with artificial communication systems we aim to understand the rules by which a sequence of DNA can encode a population-level process. Also, by evolving our engineered gene circuits in the laboratory we can ask not only how biology works but why certain biological control systems are preferred over others. The study of biological ‘design principles’ has broad applications in science, medicine and biotechnology.