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Sustainable bioenergy manufacturing in plants
Xiaolei Yu1, Pengliang Wei1, Chengyi Qu2
1College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 311215, China.
Plant Communications
|January 10, 2026
Summary
This review explores how synthetic biology, AI, and chemistry advance sustainable bioenergy by engineering optimized biomass. Autoluminescent plants, using the fungal bioluminescence pathway, exemplify this synergy for biological illumination and plant-based energy.
Area of Science:
- Biotechnology
- Synthetic Biology
- Bioenergy Engineering
Background:
- Conventional bioenergy production faces efficiency, cost, and versatility limitations.
- Transitioning to a circular bioeconomy requires sustainable alternatives to fossil fuels.
- Interdisciplinary advances are crucial for overcoming current bioenergy challenges.
Purpose of the Study:
- To review how synthetic biology, genomics, AI, and chemistry are revolutionizing bioenergy production.
- To highlight strategies for engineering optimized biomass and developing smart biorefineries.
- To present autoluminescent plants as a case study for sustainable biological illumination.
Main Methods:
- Genomic editing of energy crops for improved nutrient efficiency and lignin content.
- Development of AI-informed algorithms for smart biorefinery operations.
- Case study analysis of the fungal bioluminescence pathway (FBP) in autoluminescent plants.
Main Results:
- Synergistic integration of omics, engineering, and agronomy enables complex bioengineering solutions.
- Autoluminescent plants harness the FBP, utilizing caffeic acid for autonomous biological illumination.
- Engineered plants demonstrate potential for high-brightness, sustainable light production.
Conclusions:
- An integrated, multidisciplinary approach is essential for advancing sustainable bioenergy.
- Autoluminescent plants represent a frontier application with transformative potential for biological illumination.
- Generative AI is poised to drive the next paradigm shift towards holistic, convergent bioengineering research.
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