Rapid in silico screening of algae productivity under diel light conditions
Developing a dynamic diurnal metabolic model to improve algae strain design for enhanced bioproduct yield under real-world light cycles. This approach integrates gene expression and biomass data to streamline productivity screening and enhance genetic engineering.
Overview
The proposed solution focuses on developing a dynamic diurnal metabolic model for algae, specifically the DOE benchmark strain, Picochlorum renovo. This model aims to address the challenges of designing algae production strains that perform well under real-world light conditions, as opposed to constant laboratory light. By integrating data on gene expression and biomass composition, the model allows for in silico screening of potential genetic modifications, ultimately streamlining the design/build/test cycle for algae strains optimized for bioproduct yield.
Technical specifications
- Dynamic diurnal metabolic model: Capable of simulating gene expression and metabolic changes in algae under day/night cycles.
- Model organism: Picochlorum renovo, known for its rapid growth and tolerance to saline and high-temperature environments.
- Data integration: Incorporates biomass composition and flux data over a 24-hour cycle, along with transcriptomic data collected at 2-hour intervals.
- Simulation capabilities: Enables prediction of genetic modifications and metabolic pathway adjustments to enhance production of compounds like naptha under diel light conditions.
Technology readiness level
This technology is currently at TRL 4, indicating that it has been validated in a laboratory environment. The next steps involve extending the model to industrially relevant algae strains to further improve strain design and production performance in outdoor conditions.
About Colorado School of Mines
Mines is a specialized public research university focused on engineering and applied science, known for a hands-on, industry-facing culture. Companies collaborate with faculty in co-located labs and at field-scale test sites across the Rocky Mountain region, enabling validation in real-world conditions. Its Golden location places partners near a U.S. Department of Energy national laboratory and within the Front Range innovation corridor, providing access to suppliers, startups, and major corporate R&D. Research is supported by competitive federal funding, notably from the National Science Foundation and the U.S. Department of Energy. A dedicated technology transfer office streamlines IP, licensing, sponsored research, and startup formation.
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