Week 3 HW: Cell-Free Protocols

CFPS REACTION DESIGN FOR SFGFP, PETASE, RETEPLASE

Goal: using the collective intelligence of the HTBAA community and accessible AI systems, design novel CFPS reaction compositions for each of the three target proteins: sfGFP, PETase, and Reteplase to reduce the cost per gram of functional protein. Each design should be compatible with the experimental framework described above and should reflect the distinct expression and folding requirements of that protein. You can learn more about the details of the coopetition here.

A. COMPARE CELL-FREE REACTION COMPOSITIONS (20 minutes)

As I don’t have any backgrund in this field, I asked Claude AI (Opus 5) for help. For this I used the following prompt: Based on the literature provided, answer the following questions: Why does the concentration of potassium glutamate and magnesium glutamate differ between compositions? Which is more sensitive? Explain how a PEP+NTP reaction formulation is different from a Ribose+NMP reaction formulation. Choose two cell-free reaction compositions from the literature, compare and contrast the choice of reagents and the concentration of reagents. Note: A recommended starting point would be to review a least one published formulation, such as PANOx-SP (Jewett & Swartz 2004), a cost-optimized formulation from Olsen et al. (2026), and/or an AI-designed formulation from Smith et al. (2026). How would you explain the answers to a 14 year old kid?

1. Why does the concentration of potassium glutamate and magnesium glutamate differ between compositions? Which is more sensitive?

Two salts show up in the recipes: potassium glutamate and magnesium glutamate. They do completely different jobs.

Potassium is like the water in a swimming pool. Potassium makes the general environment feel right to the molecules, not too salty, not too dilute. Magnesium is like the screws holding a machine together. Ribosomes literally need magnesium ions to clamp their two halves onto each other. Too few and the machine falls apart; too many and it seizes up. The numbers back this up. In Jewett and Swartz’s tests, being 4 mM off on magnesium cost them 10–35% of their protein. Being 8 mM off cost them half. Meanwhile potassium could swing by 100 mM — a huge range — with barely any effect.

There’s a wrinkle that explains why magnesium keeps changing between recipes: some ingredients grab magnesium and hold onto it. PEP (one of the fuels) grabs it tightly; pyruvate doesn’t. So when the Stanford team switched fuels, they had to drop magnesium from 20 mM to 8 mM — not because the ribosomes wanted less, but because less was being stolen.

2. Explain how a PEP+NTP reaction formulation is different from a Ribose+NMP reaction formulation.

Building a protein takes energy, the same way your body needs energy to move. Cells carry energy in a molecule called ATP — think of it as a tiny rechargeable battery. Use it, it goes flat, something recharges it.

The old way: buy expensive batteries

Pour in ready-made ATP plus a chemical called PEP that recharges it fast.

It works — for about two hours. Then three things go wrong at once:

Every time PEP recharges a battery, it leaves behind phosphate, which is garbage. Above about 30 mM, phosphate jams the machinery. The reaction poisons itself with its own waste. The soup turns acidic, down below pH 6.5, which the machines don’t like. It costs about $4,000 for a gram of protein. PEP alone is most of that.

The new way: buy the parts and let the soup build its own batteries

Don’t add ATP at all. Add cheap raw materials — ribose (a sugar), nucleoside monophosphates (half-built battery pieces), a controlled amount of phosphate — and let the enzymes already floating in the soup assemble batteries themselves, continuously.

It sounds like it shouldn’t work. It does. Within 30 minutes the soup has made just as much ATP as the expensive version, starting from zero. And instead of spiking and crashing, the ATP level stays steady for the whole 20 hours.

The clever bit: phosphate is now an ingredient you add on purpose instead of garbage that builds up. Same chemical, opposite role.

Results: more than double the protein, for $60 a gram instead of $4,000. About 98% cheaper.

The catch. This version runs on the soup’s own breathing machinery, so it needs oxygen. In a deep narrow tube, the liquid at the bottom suffocates. The researchers found that reaction yields depended on the shape of the container — and when they piped pure oxygen in, yields jumped by 45%. That’s a weirdly physical result for a chemistry problem: the shape of your tube matters as much as your recipe.

3. Choose two cell-free reaction compositions from the literature, compare and contrast the choice of reagents and the concentration of reagents.

A team at Ginkgo Bioworks hooked GPT-5 up to a robot laboratory. The AI designed the experiments, robots physically ran them, the data went back to the AI, and it designed the next round. Six months, about 36,000 different recipes, 150,000 measurements. Humans mostly just loaded supplies into the machines.

Compare the AI’s best recipe to the best human one:

Two things stand out.

The AI cut the expensive stuff. The humans had already made the chemicals so cheap that the soup itself and the DNA became over 90% of the cost. So the AI used less soup and less DNA — attacking whatever was most expensive, which is exactly what a good engineer does.

The AI put something back. Spermidine is a cheap molecule that helps stabilise DNA and RNA. The human optimisation had nearly removed it. The AI added it back at nearly ten times the amount — landing almost exactly where the original 2004 paper had put it, twenty-two years earlier.

Note: A recommended starting point would be to review a least one published formulation, such as PANOx-SP (Jewett & Swartz 2004), a cost-optimized formulation from Olsen et al. (2026), and/or an AI-designed formulation from Smith et al. (2026).

B. DESIGN ONE REACTION COMPOSITION FOR EACH OF THE THREE PROTEINS (40 minutes)

1. Sign in to coopetition.htgaa.org and publish your first unique 20 µL CFPS reaction composition for each of the following (don’t worry, you can resubmit later): sfGFP PETase Reteplase

For each composition, specify the reagents you would adjust from the relevant categories, including salts, energy sources, building blocks, cofactors, and redox components.

2. As a HTBAA research team, we will have the opportunity to suggest new reagents to add to the cell-free reagent inventory. Contribute (or upvote) at least one reagent to the “Community Reagents” section of the website and provide a short rationale. Include in your homework documentation how you decided on that specific reagent and provide links to any relevant research.

3. Visit the cfps-coopetition forum page to ensure you will be able to take part in the discussion. Bonus: send a note in the channel about a CFPS optimization idea that you have! If you would like clarification on aspects of the project, please message in this dedicated channel.