Week 09 HW: Cell Free Systems

Part A: General and Lecturer-Specific Questions

1. Explain the main advantages of cell-free protein synthesis over traditional in vivo methods, specifically in terms of flexibility and control over experimental variables. Name at least two cases where cell-free expression is more beneficial than cell production.

According to Biocompare “Advantages of Cell-Free Protein Expression,” Cell-free protein expression uses cellular lysates, instead of living cells as a source of components required for protein synthesis. The advantages include ease of use, speed in protein production, and minimal lab equipment and expertise requirements compared to traditional methods.

The first case is the rapid prototyping and high-throughput screening. I think COVID screening was used as an example in the lecture. The second case was also mentioned in the lecture, which used cellular lysates (ribosomes and enzymes) rather than living cells to ensure that the toxic protein couldn’t kill the machine that produces it.

2. Describe the main components of a cell-free expression system and explain the role of each component.

According to New England Biolabs, Cell-free protein synthesis (CFPS) is a protein expression approach that enables production of a target protein without the use of living cells. In CFPS, a solution containing all the cellular machinery needed to direct protein synthesis (e.g., ribosomes, tRNAs, enzymes, cofactors, amino acids, etc.) is used to transcribe and translate a supplied nucleic acid template (e.g., plasmid DNA, linear DNA or mRNA).

3. Why is energy provision regeneration critical in cell-free systems? Describe a method you could use to ensure continuous ATP supply in your cell-free experiment.

This is because the CFPS system always requires a high ATP input, which outperforms traditional ATP-regeneration systems. An article titled “Cell-free Systems to Mimic and Expand Metabolism” indicates that machine learning, design of experiments, and model-based predictions will accelerate the improvement of cell-free metabolism, particularly because in vitro experiments can rapidly generate large sets of training data required for useful algorithms.

4. Compare prokaryotic versus eukaryotic cell-free expression systems. Choose a protein to produce in each system and explain why.

Prokaryotic cell-free systems offer high yields and low costs, making them ideal for simple proteins, such as the E. coli system for producing Green Fluorescent Protein. Eukaryotic systems offer complex folding and post-translational modification. For Human Erythropoietin, Eukaryotic lysates provide the machinery that prokaryotic systems can’t perform and ensure the protein is properly folded.

5. How would you design a cell-free experiment to optimize the expression of a membrane protein? Discuss the challenges and how you would address them in your setup.

According to Google AI overview, designing a cell-free experiment to optimize the expression of a membrane protein focuses on maximizing yield by adjusting detergent concentration, optimizing magnesium/potassium ratios, and increasing template concentration. Key challenges include protein aggregation and incorrect folding. To address them, using detergents for solubilization without interfering with translation and adding DnaK, etc., to assist with folding can be considered.

6. Imagine you observe a low yield of your target protein in a cell-free system. Describe three possible reasons for this and suggest a troubleshooting strategy for each.

A common reason is the rapid depletion of energy resources, such as ATP. Using a continuous-exchange cell-free (CECF) system allows for the continuous replenishment of substrates and removal of inhibitory byproducts. Another reason is the improper protein folding. Lowering the incubation temperature can slow down translation and allow more time for proper folding. Inefficient transcription/translation coupling can also be a reason, which can be tackled by optimizing the DNA template concentration and quality.

Part B: Homework question from Kate Adamala Design an example of a useful synthetic minimal cell as follows:

The answers heavily relied on GenAI.

1. Pick a function and describe it.

a. What would your synthetic cell do? What is the input and what is the output?

My cell is a synthetic minimal cell designed to detect lactate levels. The input would be normal things like sweat or tissues, and the output would be a fluorescent signal when lactate is high.

b. Could this function be realized by cell-free Tx/Tl alone, without encapsulation?

Maybe, but encapsulation improves stability.

c. Could this function be realized by genetically modified natural cell?

Yes, engineered Escherichia.

d. Describe the desired outcome of your synthetic cell operation.

A visible fluorescent signal proportional to lactate concentration, enabling real-time metabolic monitoring.

2. Design all components that would need to be part of your synthetic cell.

a. What would be the membrane made of?

Phospholipid bilayer.

b. What would you encapsulate inside? Enzymes, small molecules.

Cell-free transcription/translation (Tx/Tl) system, DNA encoding sensor + reporter RNA polymerase, ribosomes, Amino acids, ATP, cofactors, and Lactate-responsive transcription factor

c. Which organism your Tx/Tl system will come from? Is bacterial OK, or do you need a mammalian system for some reason? (hint: for example, if you want to use small molecule modulated promotors, like Tet-ON, you need mammalian)

It will come from a bacterial system such as Escherichia coli, simple, fast, and sufficient for small-molecule sensing.

d. How will your synthetic cell communicate with the environment? (hint: are substrates permeable? or do you need to express the membrane channel?)

Lactate can passively diffuse across the membrane.

3. Experimental details

a. List all lipids and genes. (bonus: find the specific genes; for example, instead of just saying “small molecule membrane channel” pick the actual gene.)

Lipids: POPC (phosphatidylcholine); Cholesterol (optional)

Genes: LldR (lactate-responsive transcription factor); Promoter regulated by LldR GFP (reporter protein); Optional: LldP (lactate transporter)

b. How will you measure the function of your system?

Measure fluorescence intensity and compare the signal across different lactate concentrations.

Parc C: Homework question from Peter Nguyen: Freeze-dried cell-free systems can be incorporated into all kinds of materials as biological sensors or as inducible enzymes to modify the material itself or the surrounding environment. Choose one application field — Architecture, Textiles/Fashion, or Robotics — and propose an application using cell-free systems that are functionally integrated into the material. Answer each of these key questions for your proposal pitch:

The answers heavily relied on GenAI.

a. Write a one-sentence summary pitch sentence describing your concept.

A smart textile embedded with freeze-dried cell-free systems that detects sweat biomarkers (e.g., stress or fatigue) and produces a visible colour change in real time.

b. How will the idea work, in more detail? Write 3-4 sentences or more.

A Freeze-dried cell-free transcription/translation system is embedded into fabric fibres or patches. When activated by sweat (moisture), the system rehydrates and detects specific biomarkers such as lactate or cortisol. A biosensor circuit triggers the production of a fluorescent protein, causing the fabric to visibly change color. This enables continuous, non-invasive monitoring during daily activities or exercise.

c. What societal challenge or market need will this address?

This addresses the growing demand for real-time, non-invasive health monitoring, particularly in fitness, mental health, and occupational safety. It enables early detection of fatigue, stress, or overexertion, reducing risks in high-performance or high-risk environments (e.g., athletes, healthcare workers).

d. How do you envision addressing the limitation of cell-free reactions (e.g., activation with water, stability, one-time use)?

Use sweat as a natural trigger for rehydration. Stability in protective polymers or hydroge is to extend shelf life

Part D: Homework question from Ally Huang

Freeze-dried cell-free reactions have great potential in space, where resources are constrained. As described in my talk, the Genes in Space competition challenges students to consider how biotechnology, including cell-free reactions, can be used to solve biological problems encountered in space. While the competition is limited to only high school students, your assignment will be to develop your own mock Genes in Space proposal to practice thinking about biotech applications in space!

For this particular assignment, your proposal is required to incorporate the BioBits® cell-free protein expression system, but you may also use the other tools in the Genes in Space toolkit (the miniPCR® thermal cycler and the P51 Molecular Fluorescence Viewer). For more inspiration, check out https://www.genesinspace.org/ .

The answers heavily relied on GenAI.

a. Provide background information that describes the space biology question or challenge you propose to address. Explain why this topic is significant for humanity, relevant for space exploration, and scientifically interesting. (Maximum 100 words)

Long-duration spaceflight exposes astronauts to microgravity, which alters metabolism and can lead to muscle fatigue and impaired recovery. Monitoring metabolic stress in space is challenging due to limited lab infrastructure. Cell-free systems, such as BioBits Cell-Free Protein Expression System, offer a lightweight and stable platform for biosensing in resource-constrained environments. Developing a portable system to detect metabolic biomarkers like lactate could enable real-time health monitoring in space. This is significant for maintaining astronaut performance, reducing health risks, and advancing autonomous biomedical diagnostics for deep-space missions.

b. Name the molecular or genetic target that you propose to study. Examples of molecular targets include individual genes and proteins, DNA and RNA sequences, or broader -omics approaches. (Maximum 30 words)

Lactate and the lactate-responsive regulator LldR, coupled to a GFP reporter system.

c. Describe how your molecular or genetic target relates to the space biology question or challenge your proposal addresses. (Maximum 100 words)

Lactate is a key biomarker of metabolic stress and muscle fatigue, both of which are affected by microgravity. The transcription factor LldR responds to lactate levels and can regulate gene expression accordingly. By coupling LldR to a reporter gene, such as GFP, the system can translate metabolic changes into a measurable fluorescent signal. This enables indirect monitoring of astronaut physiological status using a simple biochemical assay, making it highly suitable for space environments where traditional diagnostic tools are limited.

d. Clearly state your hypothesis or research goal and explain the reasoning behind it. (Maximum 150 words)

We hypothesize that a freeze-dried cell-free system incorporating an LldR-regulated genetic circuit can reliably detect lactate levels and produce a quantifiable fluorescent signal under space-relevant conditions. The goal is to demonstrate that cell-free biosensors remain functional after storage and activation in microgravity-like environments. This approach leverages the stability and portability of cell-free systems while avoiding the complexity of maintaining living cells. If successful, this system could provide a scalable platform for monitoring astronaut health biomarkers in real time. The reasoning is based on prior success of cell-free systems in detecting small molecules on Earth, combined with their demonstrated robustness to freeze-drying and rehydration.

e. Outline your experimental plan - identify the sample(s) you will test in your experiment, including any necessary controls, the type of data or measurements that will be collected, etc. (Maximum 100 words)

Freeze-dried reactions using the BioBits Cell-Free Protein Expression System will be rehydrated with samples containing varying lactate concentrations. A genetic circuit with LldR controlling GFP expression will be tested. Controls include reactions without lactate and without DNA. Fluorescence output will be measured using the P51 Molecular Fluorescence Viewer. If needed, DNA amplification can be performed using the miniPCR thermal cycler. Data will be collected as fluorescence intensity relative to lactate concentration.