Our work adheres to the DBTL principles, undergoing three complete engineering iterations, ultimately achieving a remarkable yield of sulforaphane.

Cycle1 :Preliminary pathway construction

Discovery and Optimization of Pathways

Design Goal:

To identify and optimize an efficient pathway for the synthesis of sulforaphane.

Challenges in Construction:

• We attempted to find the optimal pathway through computer-aided metabolic simulation, facing several challenges:
  1. The synthesis pathway from methionine to sulforaphane (SFN) is excessively long, making mathematical modeling impractical.
  2. Calculating Gibbs free energy and enzyme kinetic coefficients is complex.
• The natural pathway for sulforaphane is intricate and relatively inefficient, lacking detection methods for intermediate products and effective optimization strategies.

Testing, Learning, and Solutions:

In addressing the calculation of Gibbs free energy, we shifted from quantitative calculations to qualitative assessments, concluding that ΔG < 0 is sufficient. By simplifying the calculations, we developed a qualitative approach that narrows the data range, making it easier to identify feasible pathways through experiential judgment.

Based on the natural pathway, we conducted extensive research on existing studies to screen, optimize, and replace enzymes in the pathway. Combining these findings with the analysis results from metabolic simulation, we identified a final feasible pathway.

Preliminary Construction of the Pathway

Design Goal:

To initially construct the genes involved in the pathway onto a suitable vector.

Challenges Encountered:

• The large number of genes makes conventional plasmid construction methods complex and time-consuming.
• Eukaryotic-derived genes require more sophisticated regulatory systems.

Testing, Learning, and Solutions:

• A simplified construction strategy was adopted, utilizing a faster in-fusion homologous recombination method to build the plasmids, alongside refined team collaboration.
• Extensive literature review was conducted to design a more rational combination of expression regulatory elements.

Conclusion:

The team conducted a thorough research investigation and successfully developed a metabolic simulation framework, optimizing existing pathways and creating a universal metabolic simulation protocol for future iGEM teams. We also constructed a preliminary pathway for sulforaphane synthesis.

However, we discovered that the current number of constructed plasmids is too large and complex to transform all of them for subsequent experiments or fermentation. Therefore, we decided to continue learning and improving the project, leading to a second engineering iteration.

Cycle2: Co-expression Plasmid Construction, P450 Enzymes Modification, and Genome Integration

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(1) Co-expression Plasmid Construction

Design Goal:

To further combine the initially constructed single-frame plasmids for easier transformation and fermentation processes.

Challenges in Construction:

• The construction scheme is complex and requires consideration of interactions between genes.
• Literature review indicates that directly transforming plasmids into yeast for fermentation results in unstable yields.

Testing, Learning, and Solutions:

• A refined design was implemented using overlap PCR to integrate numerous fragments, reducing the number of segments introduced during homologous recombination and increasing success rates.
• A genome integration strategy was employed for the final fermentation experiments.

(2) P450 Enzymes Modification

Design Goal:

To modify the P450 enzymes in the pathway using computer-aided design, while adjusting subcellular localization and cofactor supply to enhance P450 enzymes efficiency.

Challenges in Construction:

• The computer optimization of P450 enzymes is complex and often yields low efficiency.
• The effects of modified enzymes lack direct characterization methods, with conclusions drawn only from final fermentation data.

Testing, Learning, and Solutions:

• Discussions with multiple experts in the field of proteins were conducted to optimize the hydrophilicity and hydrophobicity of the enzyme's substrate channel, thereby enhancing enzyme efficiency.

(3) Genome Integration

Design Goal:

To address the instability of plasmid fermentation in Saccharomyces cerevisiae, we aim to integrate the pathway into its genome.

Challenges in Construction:

• Large Gene Fragment Lengths: Integration of longer gene fragments is challenging.
• Long Yeast Cultivation Cycles: Verification processes are complex and time-consuming.

Testing, Learning, and Solutions:

• Stepwise Integration: Integrate all fragments in stages, gradually constructing strains for intermediate product synthesis and final sulforaphane production.

• Rational Design of Verification Plan

Conclusion:

We successfully constructed genome-integrated strains for the synthesis of intermediates and the pathway for producing sulforaphane. However, detailed fermentation validation is necessary to confirm the final yield and the effectiveness of the optimization, prompting the initiation of the third engineering iteration.

Cycle3: Fermentation and Yield Verification

Design Goal:

Conduct detailed fermentation experiments to validate the production capacity of engineered strains using HPLC, LCMS, and other methods.

Challenges in Construction:

• Difficulty in obtaining or the high cost of standard intermediates.
• Instability and low concentration of intermediates complicate detection, with sulforaphane requiring GS for analysis.

Testing, Learning, and Solutions:

• Some key intermediates were analyzed using LC-MS.
• Lyophilization was employed to concentrate the fermentation broth and enhance intermediate detection.
• Research indicated that modifications to myrosinase yielded positive results; therefore, we assessed whether GRA, a precursor to SFN, could achieve similar outcomes to validate the pathway. GRA can be quantitatively analyzed via HPLC with a UV detector.
• After confirming GRA yield, we proceeded to test sulforaphane, significantly reducing experimental costs and time consumption.

Conclusion:

Through fermentation experiments, we accurately measured the yield of GRA in the fermentation broth (including samples tested after P450 optimization) and determined the yield of sulforaphane.