Project Contribution: Converting Waste Cooking Oil to High-Value Squalene

This project aims to efficiently convert waste oil into high-value squalene through synthetic biology technology.

Through systematic metabolic engineering, we introduced high-efficiency lipases for waste oil degradation, improved the squalene synthesis pathway in Yarrowia lipolytica, and innovatively adopted a peroxisomal compartmentalization strategy using the optimal peroxisomal targeting peptide identified by model-based algorithms to enhance yield. Additionally, we developed a low-cost, automated fermentation processing system, providing a complete solution for the scalable production of squalene.

Part 1: Parts

These parts are crucial for constructing the squalene synthesis pathway. Our project has registered several basic parts, achieving efficient conversion from waste oil to squalene through the combination of the following modules.

Figure 1 All plasmid maps
Figure 1 All plasmid maps
Figure 1 All plasmid maps

1.1 Metabolic Pathway Optimization Module

1.2 β-Oxidation Enhancement Module

1.3 Peroxisomal Compartmentalization Module

1.4 Peroxisome Regulation Module

1.5 Lipase Secretion Module

1.6 Biosafety Module

Part 2: Wet Lab

2.1 Genetic Engineering

When constructing large metabolic pathways containing multiple genes, we initially attempted traditional restriction enzyme digestion and ligation methods. However, due to the complex plasmid structures and large number of fragments, the efficiency was low. Subsequently, we switched to Gibson Assembly technology. By precisely designing homologous arms, we successfully constructed all complex multi-gene expression plasmids. This experience demonstrates that for complex metabolic engineering projects, selecting the appropriate DNA assembly method is crucial.

2.2 Growth Curve Measurement

During the first measurement of strain concentration in oily medium, we were surprised to find that the resulting growth curves were not the standard “S-shaped” curve. All growth curves showed an initial decrease followed by an increase, then entering a plateau phase. Investigation revealed that oil droplets also absorb light at OD600. In the early stage, as the strain degrades oil droplets for growth, the increase in yeast cell count is slower than the rate of oil droplet degradation, so the OD600 shows a downward trend. Subsequently, the yeast strain enters the logarithmic phase, and the cell count increases rapidly, causing OD600 to show an upward trend. Later, we utilized centrifugation operations, measuring the OD600 before and after centrifugation of samples multiple times to objectively determine the current growth status of the strain. This experience indicates that for OD measurements in media containing oil droplets, centrifugation operations are necessary.

Part 3: Hardware

Figure 2 iFPS Schematic Diagram
Figure 2 iFPS Schematic Diagram
Figure 2 iFPS Schematic Diagram

During the project advancement, we identified a significant technological gap between traditional laboratory shake flask cultivation and industrial fermentation. To address this, we independently designed and developed an Integrated Fermentation & Processing System (iFPS). This system innovatively integrates microbial fermentation, cell centrifugation and collection, and mechanical disruption/lysis functions into a compact desktop device. Through automated control, it achieves the entire process operation from inoculation to obtaining crude lysate. Our device is available for all teams to replicate and use, hoping to provide a viable solution for the iGEM community and the field of synthetic biology regarding micro-fermentation issues, thereby promoting the development of synthetic biology.

Part 4: Modeling

Figure 3 Molecular_docking
Figure 3 Molecular_docking
Figure 3 Molecular_docking

The functions and value our model can provide to other researchers or teams: The Model digital twin modeling system we built not only serves the metabolic reprogramming research of this project but also provides a universal framework and reusable tools for other teams engaged in microbial metabolic engineering and systems modeling.

Through this three-tier architecture, users can comprehensively evaluate biological system performance from structure, function, to phenotype, achieving interpretable, transferable, and reusable modeling design. In the future, we hope to expand this model into an open, callable computational platform to support more iGEM teams and researchers.