Related Experiment Video
Updated: Nov 1, 2025

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
Published on: October 17, 2025
The LASER database: Formalizing design rules for metabolic engineering
James D Winkler1, Andrea L Halweg-Edwards1, Ryan T Gill1
1Department of Chemical and Biological Engineering, University of Colorado-Boulder, Jennie Smoly Caruthers Biotechnology Building, Research Park, Boulder, CO 80303, USA.
Abstract:
The ability of metabolic engineers to conceptualize, implement, and evaluate strain designs has dramatically increased in the last decade. Unlike other engineering fields, no centralized, open-access, and easily searched repository exists for cataloging these designs and the lessons learned from their construction and evaluation. To address this issue, we have developed a repository for metabolic engineering strain designs, known as LASER (Learning Assisted Strain EngineeRing, laser.colorado.edu) and a formal standard for disseminating designs to metabolic engineers. Curation of every available genetically-defined E. coli and S. cerevisiae strain from 310 metabolic engineering papers published over the last 21 years yields a total of 417 designs containing a total of 2661 genetic modifications. This collection has been deposited in LASER and represents the known bibliome of genetically defined and tested metabolic engineering designs in the academic literature. Properties of LASER designs and the analysis pipeline are examined to provide insight into LASER capabilities. Several future research directions utilizing LASER capabilities are discussed to highlight the potential of the LASER database for metabolic engineering.

