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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

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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.

Metabolic Engineering Communications

|June 21, 2021

Summary

This summary is machine-generated.

Metabolic engineering strain designs are now cataloged in LASER, a new open-access repository. This database standardizes and shares genetic modifications for improved strain development and evaluation.

Keywords:

Design tools Metabolic engineering Standardization Synthetic biology

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Area of Science:

Metabolic Engineering
Synthetic Biology
Bioinformatics

Background:

The field of metabolic engineering has advanced significantly, yet lacks a centralized repository for strain designs and associated data.
Existing literature contains numerous genetically defined strains and modifications crucial for metabolic engineering research.
A standardized method for sharing and accessing this valuable information is needed to accelerate innovation.

Purpose of the Study:

To develop a centralized, open-access repository for metabolic engineering strain designs.
To establish a formal standard for disseminating metabolic engineering designs.
To create a searchable database of genetically defined strains and modifications.

Main Methods:

Developed the Learning Assisted Strain EngineeRing (LASER) repository.
Curated genetically defined strains from 310 metabolic engineering papers published over 21 years.
Established a formal standard for data dissemination and cataloging genetic modifications.

Main Results:

LASER now contains 417 metabolic engineering designs, encompassing 2661 genetic modifications.
The repository includes all available genetically defined *E. coli* and *S. cerevisiae* strains from the curated literature.
Analysis of LASER designs provides insights into repository capabilities and trends in metabolic engineering.

Conclusions:

LASER serves as a comprehensive bibliome of genetically defined and tested metabolic engineering designs.
The repository and its associated standard facilitate easier access to and utilization of strain design data.
LASER has the potential to significantly advance metabolic engineering research through data sharing and analysis.