Week 3 HW: CFPS Reaction Design

HW3: Cell-Free Protein Synthesis Reaction Design

Introduction

Cell-free protein synthesis (CFPS) lets us make proteins outside of living cells by using cell lysate, DNA templates, energy sources, amino acids, nucleotides, salts, and other ingredients.

For this assignment, I designed reaction mixes for three proteins, each with different requirements for expression and folding:

• sfGFP, a fluorescent reporter with no disulfide bonds.
• PETase, an enzyme containing one disulfide bond.
• Reteplase, a more difficult protein containing nine disulfide bonds.

The main goal is to find reaction conditions that produce functional protein while keeping the cost per gram as low as possible.

Part A — Compare Cell-Free Reaction Compositions

A1. Potassium Glutamate and Magnesium Glutamate

Potassium glutamate and magnesium glutamate are important because they help control the ionic environment of the CFPS reaction.

Potassium glutamate mainly affects ionic strength and helps create suitable conditions for transcription and translation.

Magnesium glutamate supplies Mg²⁺, which is required by many enzymes and is especially important for ribosome function, nucleotide interactions, and ATP-dependent reactions.

The optimal concentrations of potassium and magnesium are different because they have different roles in the reaction.

Magnesium is generally more sensitive. Too little Mg²⁺ can reduce translation efficiency, while too much can also interfere with the reaction. Therefore, relatively small changes in magnesium concentration can have a strong effect on protein production.

A2. PEP + NTP versus Ribose + NMP

A PEP + NTP formulation uses phosphoenolpyruvate (PEP) as an energy substrate and ATP, CTP, GTP, and UTP as nucleotide triphosphates.

PEP supports ATP regeneration, while the NTPs provide the substrates needed for RNA synthesis.

A Ribose + NMP formulation uses ribose as an alternative metabolic substrate and nucleotide monophosphates such as AMP, CMP, GMP, and UMP instead of nucleotide triphosphates.

The main difference is therefore the way energy and nucleotide substrates are supplied.

The Ribose + NMP approach is interesting for cost optimization because NMPs can be less expensive than NTPs. However, the CFPS system still needs to convert these substrates into the appropriate forms for transcription and energy metabolism.

A3. Comparison of CFPS Formulations

I compared the sfGFP PEP and sfGFP Ribose reference formulations available in the Coopetition reaction designer.

The main difference is the energy and nucleotide system:

The reference formulations also differ in their salt, amino acid, buffer, and other reagent concentrations.

This comparison shows that CFPS does not require one fixed recipe. Different combinations of energy sources, nucleotides, salts, and cofactors can be used to obtain functional protein.

For my designs, I used the reference compositions as starting points and adjusted the formulation according to the requirements of each target protein.

Part B — Design of CFPS Reaction Compositions

Each reaction has a final volume of 20 µL (20,000 nL).

The following components are fixed in all three reactions:

• Base buffer: 2000 nL
• Lysate: 5000 nL
• DNA template: 2000 nL

The remaining volume was used for the variable components.

B1. sfGFP

sfGFP is the simplest of the three proteins to work with. It has no disulfide bonds, although it contains two free cysteines.

Therefore, I chose a standard reducing CFPS setup rather than an oxidizing one.

My main considerations were:

• Maintain an appropriate potassium and magnesium concentration.
• Provide amino acids for protein synthesis.
• Provide NTPs for transcription.
• Use PEP as an energy source.
• Include spermidine to support the reaction environment.
• Avoid DsbC and glutathione because sfGFP does not require disulfide-bond formation.

sfGFP reaction composition

The design uses a PEP-based energy system and standard NTPs for transcription. Since sfGFP does not require disulfide bonds, I did not add DsbC, GSSG, or GSH.

sfGFP JSON

{
  "sample_id": "",
  "sample_type": "experimental",
  "reagent_list": {
    "base_buffer": 2000,
    "lysate": 5000,
    "template_sfgfp": 2000,
    "potassium_glutamate": 3500,
    "magnesium_glutamate": 300,
    "hepes_koh": 1000,
    "amino_acid_mix_17": 1500,
    "pep_mono": 4000,
    "atp": 250,
    "ctp": 125,
    "gtp": 125,
    "utp": 125,
    "spermidine": 75,
    "nuclease_free_water": 0
  },
  "metadata": {
    "ai_model": "",
    "protein_target": "sfGFP",
    "acknowledgements": "",
    "comments": ""
  }
}

sfGFP activity is measured directly through fluorescence. Correctly folded sfGFP produces the fluorescent signal, so this assay provides a direct measurement of functional folded protein.

B2. PETase

PETase is more challenging than sfGFP because it contains one disulfide bond.

However, the assignment indicates that PETase can be produced under standard CFPS conditions. Therefore, I kept a mainly reducing formulation instead of using the fully oxidizing formulation required for Reteplase.

I also included DsbC as a folding support.

My main considerations were:

• Maintain appropriate potassium and magnesium concentrations.
• Use PEP as the energy source.
• Provide NTPs for transcription.
• Provide amino acids for protein synthesis.
• Add DsbC to support correct disulfide-bond formation and rearrangement.

PETase reaction composition

Compared with my sfGFP formulation, the PETase formulation uses slightly less PEP and adds DsbC.

The idea is that DsbC could help PETase achieve its correct folded state while avoiding the more complex oxidizing environment required by Reteplase.

PETase JSON

{
  "sample_id": "",
  "sample_type": "experimental",
  "reagent_list": {
    "base_buffer": 2000,
    "lysate": 5000,
    "template_petase": 2000,
    "potassium_glutamate": 3500,
    "magnesium_glutamate": 300,
    "hepes_koh": 1000,
    "amino_acid_mix_17": 1500,
    "pep_mono": 3500,
    "atp": 250,
    "ctp": 125,
    "gtp": 125,
    "utp": 125,
    "spermidine": 75,
    "dsbc": 1000,
    "nuclease_free_water": 0
  },
  "metadata": {
    "ai_model": "",
    "protein_target": "PETase",
    "acknowledgements": "",
    "comments": ""
  }
}

PETase activity is measured by tracking the release of p-nitrophenol at 405 nm. Therefore, the assay measures enzymatic activity rather than simply the total amount of protein produced.

B3. Reteplase

Reteplase is the most difficult of the three proteins because it contains nine disulfide bonds.

Unlike sfGFP and PETase, Reteplase requires an oxidizing environment so that its disulfide bonds can form correctly.

Therefore, my design includes:

• GSSG as an oxidizing component.
• GSH to establish a controlled redox environment.
• DsbC as a disulfide-bond isomerase.
• No DTT, because DTT would maintain cysteines in the reduced state.
• Appropriate salts, amino acids, and energy substrates for protein synthesis.

The goal is not just to produce the Reteplase polypeptide, but to produce correctly folded and enzymatically active protein.

Reteplase reaction composition

The GSSG/GSH pair establishes an oxidizing redox environment, while DsbC can help rearrange incorrectly paired disulfide bonds.

Reteplase JSON

{
  "sample_id": "",
  "sample_type": "experimental",
  "reagent_list": {
    "base_buffer": 2000,
    "lysate": 5000,
    "template_reteplase": 2000,
    "potassium_glutamate": 3000,
    "magnesium_glutamate": 300,
    "hepes_koh": 1000,
    "amino_acid_mix_17": 1500,
    "pep_mono": 2825,
    "atp": 250,
    "ctp": 125,
    "gtp": 125,
    "utp": 125,
    "spermidine": 75,
    "gssg": 475,
    "gsh": 200,
    "dsbc": 1000,
    "nuclease_free_water": 0
  },
  "metadata": {
    "ai_model": "",
    "protein_target": "Reteplase",
    "acknowledgements": "",
    "comments": ""
  }
}

Reteplase activity is measured using the fluorogenic substrate IPR-AMC. When active Reteplase cleaves the substrate, fluorescent AMC is released.

Therefore, this assay checks for functional activity, not just total protein production.

B4. Community Reagent

FkpA

For the Community Reagents section, I selected FkpA, an E. coli chaperone with peptidyl-prolyl isomerase activity.

I chose FkpA because one of the biggest challenges in producing Reteplase is correct protein folding. Reteplase contains nine disulfide bonds, so producing the polypeptide chain alone is not enough.

FkpA could provide additional folding assistance and potentially reduce aggregation of difficult proteins.

This is particularly interesting because the Reteplase formulation already uses DsbC. DsbC mainly helps rearrange incorrectly formed disulfide bonds, while FkpA could provide additional folding support.

My hypothesis is that combining different folding-support mechanisms could increase the amount of functional Reteplase.

I would test this by comparing Reteplase activity with and without FkpA and by considering the additional cost of the reagent.

The FkpA suggestion in the Community Reagents section was supported by previous work showing that FkpA can reduce aggregation and support folding in cell-free systems, including in combination with DsbC.

B5. CFPS Coopetition Forum

I also checked the CFPS Coopetition forum to follow discussions about CFPS optimization.

One optimization idea that I found interesting is the use of alternative energy sources such as maltodextrin.

Maltodextrin is relatively inexpensive and could provide a slower and more controlled energy supply compared with PEP.

This could potentially improve protein production while reducing the cost of the reaction.

AI Use

I used ChatGPT (GPT-5.6 Luna) as an AI tool during the design process.

I used AI to:

• Understand the differences between CFPS reaction formulations.
• Compare PEP + NTP and Ribose + NMP strategies.
• Check the volume calculations for the 20 µL reaction designs.

Examples of prompts used included:

• “Explain the differences between PEP + NTP and Ribose + NMP strategies in cell-free protein synthesis.”
• “Using the available reagents and the 20 µL reaction constraints, help design CFPS compositions for sfGFP, PETase, and reteplase.”
• “Check that these reaction compositions satisfy the required reagent volumes and total 20 µL reaction volume.”

I selected the final reaction designs based on the assignment information, the reference formulations available in the Coopetition website, and the biological requirements of each protein.

The AI was used as a design and reasoning aid, while the final choices were made based on the experimental constraints and biological requirements described in the assignment.

References

Jewett, M. C., & Swartz, J. R. (2004). Mimicking the Escherichia coli cytoplasmic environment activates long-lived and efficient cell-free protein synthesis. Biotechnology and Bioengineering, 86(1), 19–26. DOI: 10.1002/bit.20026.

Silverman, A. D., Karim, A. S., & Jewett, M. C. (2020). Cell-free gene expression: an expanded repertoire of applications. Nature Reviews Genetics, 21, 151–170. DOI: 10.1038/s41576-019-0186-3.

Rasor, B. J., Vögeli, B., Landwehr, G. M., Bogart, J. W., Karim, A. S., & Jewett, M. C. (2021). Toward sustainable, cell-free biomanufacturing. Current Opinion in Biotechnology, 69, 136–144. DOI: 10.1016/j.copbio.2020.12.012.

Smith, A. A., et al. (2026). Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis. bioRxiv. DOI: 10.64898/2026.02.05.703998.

Olsen, M. L., Copeland, C. E., Sundberg, C. A., Aw, R., Shaver, Z. M., Rao, G., Swartz, J. R., Karim, A. S., & Jewett, M. C. (2026). Design-driven optimization of low-cost reagent formulations for reproducible and high-yielding cell-free gene expression. Nature Communications. DOI: 10.1038/s41467-026-69605-8.