Inspired by Nature


Catalysis – Metabolic Engineering

Cells are capable of exquisite catalysis.  Taking a wide variety of raw materials, cells are capable of synthesizing alkanes, sophisticated small molecules, and high information content polymers (DNA, RNA, protein) that exist in complex three-dimensional structures.

We use these capabilities to produce small molecule drugs, protein therapeutics, and fuels from very cheap, renewable raw materials.  This involves

  • Introducing new enzymes to perform the chemical reactions we desire
  • Developing control strategies to balance native metabolic pathways with foreign enzymes to maximize product yield

These novel metabolic pathways can be utilized to synthesize precursors and final drugs for HIV and Tuberculosis, where complex steriochemisty and low yields have rendered traditionally produced therapies too expensive for broad use in resource-poor areas.

Sensing – Signaling Engineering

Microbes must accurately sense the environment around it to protect itself from harm and capitalize on nutrient opportunities. Microbial sensing is highly effective because it is specific and sensitive and produce a desired cellular response in a timely manner.

We use these capabilities to engineer cells that can detect new environmental cues.  We focus on the detection of biomarkers that currently do not have effective low-cost diagnostics.  By engineering cells that can detect these biomarkers, cell-based diagnostic devices could perform critical functions in resource-poor settings such as  detect the presence of harmful agents in drinking water. Active dry yeast is a particularly well suited to this task because it is easy to transport and store, cheap to manufacture and genetically programmable.

Uniting computational predictions with experimental applications

To accomplish these aims we bring together expertise ranging from in silico modeling to genetic engineering and experimental validation. Computational resources, designed by and developed in conjunction with the Broadbelt lab, are currently being used to direct the design of novel biosynthetic pathways.  In silico simulations such as Flux Balance Analysis and Ensemble Modeling can also tell us more about how perturbations of the metabolome will affect a cell and the efficiency of proposed synthetic routes.

Biochemical assays  are used confirm enzymatic  activity and these pathways are transformed into E. coli and yeast for experimental validation. By harnessing protein degradation machinery and synthetic switching we develop strains that are both robust and produce desired chemical products with high efficency. Statistical tools enable directed evolution and enrichment to produce biosensors which are both sensitive and accurate.