Sustainable ecosystems using synthetic biology tools to simplify, miniaturize and automate engineering of photosynthetic organisms

Our research aims to provide a sustainable ecosystem for future generations, by working openly and collaboratively with synthetic biology tools to simplify, miniaturize and automate engineering of photosynthetic organisms.

Currently, we are focused on developing a mechanistic understanding of (1) adaption of photosynthesis to environmental stress and fluctuations (2) how protein structure influences the activity of genes involved in photosynthesis.

This will allow us to take engineering approaches to introduce improvements in crop performance, as photosynthesis is one of the few remaining traits that breeders have not optimized. To do this we take an interdisciplinary approach, collaborating with researchers on campus to leverage advances in synthetic biology, machine learning, protein engineering, gene editing, genomics and automation to assess the performance of enzyme variants and gene function on photosynthetic performance before translating these findings into crops for field experiments on campus.

The major focus of our lab at the moment is to (1) Develop the smallest know photosynthetic eukaryote, Ostreoccocus tauri, as a model to studying phototrophs, and as a chassis for testing computational predictions of metabolic models and alternate carbon fixation pathways. (2) Developing platforms for directed evolution of photosynthesis enzymes.