Engineering Biology
Biomolecular Engineering Goal:

Holistic, integrated design of multi-part genetic systems (i.e., circuits and pathways).

Current State-of-the-Art

A long-standing goal of molecular engineering is to create components that can control genetic processes. There are commonly used predictive models that can design short genetic parts to control gene expression processes both within cells and in cell-free in vitro systems. These parts are then combined into larger genetic systems (operons, regulons) to create desired cellular functions, including sensors, genetic circuits, transporters, multi-enzyme metabolic pathways, organelle compartments, and orthogonal expression systems. These multi-part genetic systems are particularly useful, as they are used by natural organisms as a central information processing component to sense and respond to changing internal and external conditions. Thus, being able to de novo design or engineer these systems offers many points of control of fundamental cellular processes. However, there are several challenges that have been encountered in trying to develop multi-part genetic systems. For example, there are many coupled interactions, between adjacent parts or between distant genetic modules, that alter system function in unpredictable and undesired ways. Therefore, new approaches are needed to correctly design large genetic systems, taking into account these poorly understood mechanisms, within an even larger genomic background.

Breakthrough Capabilities & Milestones

Design of highly-stable, large genetic systems (genomes) with targeted expression levels in a host organism or cell type, incorporating system-wide effects.

Ability to rationally engineer sensor suites, genetic circuits, metabolic pathways, signaling cascades, and cell differentiation pathways.


  1. Caspi, R., Billington, R., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., … Karp, P. D. (2018). The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Research, 46(D1), D633–D639. View publication. MetaCyc is available at
  2. Jeske, L., Placzek, S., Schomburg, I., Chang, A., & Schomburg, D. (2019). BRENDA in 2019: a European ELIXIR core data resource. Nucleic Acids Research, 47(D1), D542–D549. View publication. BRENDA is available at

You, M., & Jaffrey, S. R. (2015). Designing optogenetically controlled RNA for regulating biological systems. Annals of the New York Academy of Sciences, 1352, 13–19. View publication.

Last updated: June 19, 2019 Back