Combinatorial Engineering of Essentiality

Mutations in genes affect their function in many different ways. There are thousands of genes in the genome of any organism, so it is a major challenge to decipher the role of each gene. The focus of this project is to build a new and more efficient technology platform that will enable researchers to efficiently understand how mutations in a gene affect the function encoded by that gene. This platform which uses the tools of synthetic biology will allow researchers to develop such understanding much more rapidly. Such efforts are central to a broad range of applications in both applied and basic science. It may help with the development of new strains for the production of pharmaceutical proteins, enzymes, chemicals, or fuels. It will also help to develop forward engineering paradigms central to the future of bioengineering. In the development of this platform, the investigators will also train multiple graduate and undergraduate students in cutting edge science, technology, engineering and mathematical (STEM) approaches and technologies. These students will develop expertise in experimental and computational methods, the design, execution, and reporting of scientific research, and the generation of intellectual property.

A fundamental goal of synthetic biology is to develop new paradigms for the forward engineering of biological systems. The prototypical forward engineering process involves design, build, test, and learn (DBTL) stages, which ideally are performed in a cyclical and highly parallel fashion leading to the build up of knowledge bases, codified design rules, and optimized designs. In biological endeavors, the 'DBTL' strategy has historically been realized through 'sequence to activity relationship (SAR)' mutational mapping, which has traditionally been limited in throughput to addressing only the smallest of biological systems. Advances in DNA synthesis and sequencing technologies however, have paved the way for new massively parallel approaches to SAR that extend to the genome scale. Several technologies that have been developed will be optimized in a generally accessible framework for use by the larger synthetic biology community. Such a framework will enable new forward DBTL-type engineering strategies at scales that are orders of magnitude more advanced than methods currently available. The investigators in this project have chosen to focus their efforts on the comprehensive mapping of gene essentiality in the model bacterium Escherichia coli because this model system is not only ideal for demonstrating their platform but also will allow them to address foundational questions concerning essentiality, evolvability, epistasis and fitness. This will have broad implications across genetics, synthetic biology and biotechnology.