About 150 words.
My project addresses plastic pollution by utilizing synthetic biology to identify and optimize microbial enzymes capable of degrading plastic waste efficiently. Advanced biochemical engineering, directed enzyme evolution, artificial intelligence (AI), and machine learning techniques will accelerate enzyme discovery and enhancement. AI-driven structural bioinformatics and predictive modeling will be employed to improve enzyme thermostability, intermediate tolerance, and performance against high-crystallinity plastics. Additionally, lifecycle and techno-economic analyses, supported by machine learning, will assess the practical sustainability and industrial viability of these optimized enzymes. This integration of synthetic biology and AI technologies aims to develop innovative enzyme-based solutions, fostering environmental sustainability and paving the way for significant biotechnological advancements.
a. Explain your motivation for pursuing your project
Plastic pollution is a global crisis, with millions of tons accumulating annually in oceans, rivers, and urban environments. This environmental burden, coupled with the inefficiencies of traditional mechanical recycling, motivated me to pursue a synthetic biology approach that leverages microbial biodiversity to discover and engineer enzymes capable of breaking down plastic waste. Biological degradation offers a cleaner and more energy-efficient pathway for recycling, and I aim to contribute to a circular economy by transforming plastic waste into valuable chemical building blocks.
b. Describing the current state of knowledge related to your project. Try to cite at least 2 peer-reviewed research papers.
Recent research has demonstrated the promise of enzyme-based plastic degradation. Knott et al. (2020) engineered a two-enzyme system from Ideonella sakaiensis capable of depolymerizing PET into its monomers, offering a model for enzymatic recycling pathways [1]. Xu et al. (2023) reviewed current bottlenecks and future priorities for enzymatic plastic degradation, particularly highlighting the need to discover enzymes from diverse microbial sources and to optimize enzyme performance through protein and process engineering [2]. These studies reveal both the opportunities and challenges associated with biocatalytic plastic waste management.
Structural Characterization of MHETase Reveals a Core Domain Similar to That of PETase. (Knott et al, 2020)
Bottlenecks and Priorities in Enzymatic Plastic Degradation (Xu et al., 2023)
| Bottlenecks | Future Priorities |
|---|---|
| Over-reliance on known enzymes (e.g., IsPETase, LCC) | Discover new classes of plastic-degrading enzymes from diverse microbial ecosystems |
| Limited enzymatic activity on high-crystallinity plastics | Engineer enzymes for higher thermostability and better substrate interaction |
| Low tolerance to degradation intermediates (e.g., terephthalic acid, TPA) | Improve enzyme robustness and intermediate resistance through protein engineering |
| Insufficient depolymerization efficiency under industrial conditions | Apply AI and machine learning for structure prediction and smart directed evolution strategies |
| Lack of efficient enzymes for biodegradable plastics (e.g., PLA, PBS, PBAT) | Develop and characterize hydrolases for emerging biodegradable polymer types |
| High cost and scale-up limitations | Optimize enzyme production and process engineering for economic feasibility |
[1] Knott, B. C., Erickson, E., Allen, M. D., Gado, J. E., Graham, R., Kearns, F. L., ... & Beckham, G. T. (2020). Characterization and engineering of a two-enzyme system for plastics depolymerization. Proceedings of the National Academy of Sciences, 117(41), 25476–25485.
https://doi.org/10.1073/pnas.2006753117
[2] Xu, A., Zhou, J., Blank, L. M., & Jiang, M. (2023). Future focuses of enzymatic plastic degradation. Trends in Microbiology.