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Charting the state of GEMs in microalgae: progress, challenges, and innovations
Jacob Tamburro1, Nanette R Boyle1,2
1Quantitative Biosciences & Engineering, Colorado School of Mines, Golden, CO, United States.
Frontiers in Plant Science
|June 30, 2025
Summary
This review details the progress of genome-scale metabolic models (GEMs) for microalgae, focusing on advancements and future directions for sustainable biotechnology applications.
Area of Science:
- Systems biology
- Metabolic engineering
- Microalgal biotechnology
Background:
- Genome-scale metabolic models (GEMs) are crucial for understanding microalgal metabolism.
- The development of GEMs has evolved significantly, with key advances in specific areas.
Purpose of the Study:
- To review the evolution of microalgal GEMs.
- To highlight advancements in light modeling, automation, and multi-omics integration.
- To discuss limitations and future directions, including dynamic modeling and machine learning.
Main Methods:
- Literature review of microalgal GEMs.
- Focus on *Chlamydomonas reinhardtii* as a model organism.
- Analysis of current limitations and emerging technologies.
Main Results:
- GEMs have advanced significantly, particularly with multi-omics integration and improved light modeling.
- Automation and machine learning are emerging as key areas for development.
- *Chlamydomonas reinhardtii* serves as a critical model for these advancements.
Conclusions:
- Current microalgal GEMs have limitations but are rapidly improving.
- Dynamic modeling and machine learning promise more predictive and adaptable models.
- Enhanced GEMs will accelerate microalgal applications in sustainable production.
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