Week 1 HW: Principles and Practices

Class Assignment: Biosensors for Anxiety

1. Describe a biological engineering application or tool you want to develop and why.

Currently as I am working with microbiome sequencing, I have developed an interest in the relationship between the microbiome and mental health, hence my interest in using genetically modified bacteria to create biosensors for anxiety. Consider bacteria like Lactobacillus reuteri, which are specifically engineered to identify high quantities of cortisol, the hormone that human bodies release during stressful situations. GABA (gamma-aminobutyric acid), a naturally occurring substance that aids in nervous system relaxation, would be produced by the modified bacteria in response to an increase in these cortisol levels. Not everyone reacts to traditional anxiety medications equally, and they frequently have negative side effects. So my proposed strategy presents a viable substitute—a probiotic supplement that supports mental health in real time and functions organically with the body. The simplicity of this concept—using something as ubiquitous as gut microbes to create a significant impact—is what makes it beautiful and potentially innocuous.

2. Describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals.

This technology needs to be developed ethically if it is to be genuinely helpful. The following are the main objectives that ought to direct its governance: Promoting safety, preventing harm, and upholding ethical behaviors are the main objectives.

• Sub-Goal 1: Biosafety - Reduce the possibility of accidentally releasing genetically modified bacteria into the environment. Make sure the modified strains don’t upset the human gut microbiome’s natural equilibrium.
• Sub-Goal 2: Informed Consent and Public Awareness - Provide simple, understandable information to users regarding the biosensor’s operation. Encourage openness by making sure individuals are aware of the advantages as well as any possible risks.
• Sub-Goal 3: Access Equity - Make sure that not only a select few have access to this technology. Ensuring extensive and cheap access is essential in Ecuador due to its various communities and healthcare inequities. In Ecuador, genetically modified (GM) crops and seeds are banned, except in rare cases where the President and the National Assembly approve them for national interest. Although GM crops are not grown locally, some food products containing GM ingredients (like maize and soy) are imported. Additionally, research with GMOs is allowed under strict biosafety conditions. Food products with over 0.9% GM content must be labeled clearly. This regulatory context will guide how Sbiosensors are developed and used responsibly in Ecuador.

3. Describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”).

Governance Actions

4. Score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals.

5. Drawing upon this scoring, describe which governance option, or combination of options, you would prioritize, and why. Outline any trade-offs you considered as well as assumptions and uncertainties.

Biosafety Certification is the most important factor when it comes to scoring because it guarantees that the product is safe for human use and reduces environmental hazards. Prior to any public deployment, this fundamental step is essential. International collaboration is also key, as it offers access to global biosafety standards, proven governance frameworks, and technical support. Ecuador already works with organizations such as the FAO and WHO, and expanding these collaborations can strengthen the effectiveness of national efforts across biosafety, education, and equity. The significance of public education campaigns, which promote understanding and trust among the general public and are essential for acceptance and appropriate use, comes next. Finally, the Equity Monitoring Program is also important since it will help guarantee that the technology is accessible to everyone who needs it, not just those in places with ample resources, especially in Ecuador where access to healthcare can differ greatly between urban and rural areas. By defining a balance between these criteria, biosensors for anxiety will develop into a useful, moral, and safe instrument that will benefit not only Ecuador but the entire world.

References

• Bravo, J. A., Forsythe, P., Chew, M. V., Escaravage, E., Savignac, H. M., Dinan, T. G., … & Cryan, J. F. (2011). Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proceedings of the National Academy of Sciences, 108(38), 16050-16055.
• Cryan, J. F., & Dinan, T. G. (2012). Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nature Reviews. Neuroscience, 13(10), 701–712. https://doi.org/10.1038/nrn3346
• https://www.ambiente.gob.ec/wp-content/uploads/downloads/2015/08/BIOSEGURIDAD.pdf
• https://www.fao.org/fileadmin/user_upload/gmfp/docs/Biosafety%20Brochure.pdf
• Santos, E., Sánchez, E., Hidalgo, L., Chávez, T., Villao, L., Pacheco, R., & Navarrete, O. (2014, August). Status and challenges of genetically modified crops and food in Ecuador. In XXIX International Horticultural Congress on Horticulture: Sustaining Lives, Livelihoods and Landscapes (IHC2014): 1110 (pp. 229-235).

The assistance of OpenAI’s ChatGPT was employed to help clarify ideas, revise language and grammar.

Week 2 HW: DNA read, write and edit

Week 2 Lecture Prep

Jacobson’s Questions

1. Nature’s machinery for copying DNA is called polymerase. What is the error rate of polymerase? How does this compare to the length of the human genome. How does biology deal with that discrepancy?

Error rate of polymerase: Natural DNA polymerase has an error rate of 1 in 10^6 bases.

Human genome length: The human genome is around 3.2 billion base pairs.

At an error rate of 1 in 10⁶, polymerase would introduce roughly:

3.2 x 10^{9 / 1 x 10}6 = 3200 errors per genome

How biology deals with it: Despite this potential for errors, the cell uses multiple mechanisms to maintain genome stability:

• Proofreading by DNA polymerase during replication.

• Mismatch repair systems that fix errors after DNA synthesis.

• Excision repair pathways for damaged or mismatched bases.

These systems reduce the final mutation rate to approximately 1 in 10⁹ bases, making DNA replication remarkably accurate.

2. How many different ways are there to code (DNA nucleotide code) for an average human protein? In practice what are some of the reasons that all of these different codes don’t work to code for the protein of interest?

Because the genetic code is degenerate —meaning 61 different codons specify only 20 amino acids— a single protein sequence can be represented by countless, often billions or more, combinations of DNA sequences. For an average human protein of 400 amino acids, there are approximately 10^200 different DNA sequences that can encode the same protein.

Why not all work:

• Codon bias (organisms prefer certain codons over others).

• mRNA stability and folding may affect translation.

• Regulatory sequences (e.g., hairpins, internal ribosome entry sites) may be unintentionally formed.

• Toxic sequences might be formed (e.g., repeats, CpG motifs).

Week 3 HW: Lab Automation

Assignment: Python Script for Opentrons Artwork

1. Generate an artistic design using the GUI at opentrons-art.rcdonovan.com.

I used the GUI for converting my rising phoenix image into the dot design, I loved the tool, very helpful, easy to use and to edit and perfectionate my design. The tool supplied the coordinates to add to my code, and the result looks perfect!

I selected the rising phoenix as it represents transformation, resilience, and renewal. It reminds me that growth often comes from challenges, and I have the capacity to transform and emerge stronger.

2. Using the coordinates from the GUI, follow the instructions in the HTGAA26 Opentrons Colab to write your own Python script which draws your design using the Opentrons.

Ready in Google Colab

I used ChatGPT to polish written explanations, to clarify concepts and clean and debug Opentrons Python code. All final decisions and interpretations were reviewed and confirmed by me.

Post-Lab Questions

One of the great parts about having an automated robot is being able to precisely mix, deposit, and run reactions without much intervention, and design and deploy experiments remotely.

For this week, we’d like for you to do the following:

1. Find and describe a published paper that utilizes the Opentrons or an automation tool to achieve novel biological applications.

“Cell-free biosensor with automated acoustic liquid handling for rapid and scalable characterization of cellobiohydrolases on microcrystalline cellulose”

This study presents a cell-free biosensor designed to rapidly detect the activity of enzymes that break down crystalline cellulose. Instead of relying on traditional, slow assays or cell-based systems, the authors built a transcription factor-based biosensor that produces a fluorescent signal when cellobiose is generated. By integrating this system with the Echo 525 acoustic liquid handler, they demonstrated highly precise, optimized the reactions for small-volumes, and automated reactions that match manual performance while increasing a lot the throughput. Overall, the work shows how combining cell-free systems with automation can significantly accelerate enzyme screening and improve the efficiency of the complete experiment cycle in synthetic biology.

3. Write a description about what you intend to do with automation tools for your final project. You may include example pseudocode, Python scripts, 3D printed holders, a plan for how to use Ginkgo Nebula, and more. You may reference this week’s recitation slide deck for lab automation details.

For my project on biosensors for anxiety, I plan to use automation tools like Opentrons to support the genetic engineering of bacteria. My goal is to modify Lactobacillus reuteri so that it can sense elevated cortisol levels and respond by producing GABA, a calming neurotransmitter. By automating key molecular cloning steps, I hope to make the strain engineering process more consistent, efficient, and scalable while reducing human error during repetitive lab work.

Molecular cloning is a central step in building this biosensor system. Automating these procedures will help ensure precision and reproducibility, allowing the design-build-test cycle to move faster and more reliably.

2.1.DNA Fragment Preparation

• Use Opentrons liquid handling to accurately pipette reagents for plasmid extraction and PCR amplification of gene fragments.
• Automate purification steps (e.g., magnetic bead-based purification or column-based cleanup) to standardize DNA yields.

2.2.Restriction Digestion & Ligation

• Automate enzymatic digestion using restriction enzymes to cut plasmids and insert fragments under precise conditions.
• Program ligase reactions for efficient DNA assembly, ensuring consistent reaction times and temperatures.

2.3.Transformation of Engineered Constructs

• Use Opentrons to pipette competent cells, mix them with recombinant DNA, and automate the heat shock or electroporation process.
• Plate transformed cells onto selective agar using a robotic liquid handler to ensure even distribution.

2.4.Screening and Colony Picking

• Automate pipetting of selection media for colony growth.
• Use robotic colony pickers (if available) or automate PCR setup for rapid screening of positive clones.

2.5.PCR & Validation

• Automate PCR setup for screening transformed colonies, ensuring each reaction is prepared with high accuracy.
• If sequencing is needed, automate DNA preparation for submission to sequencing facilities.

REFERENCES

• Taeok Kim, Eun Jung Jeon, Kil Koang Kwon, Minji Ko, Ha-Neul Kim, Seong Keun Kim, Eugene Rha, Jonghyeok Shin, Haseong Kim, Dae-Hee Lee, Bong Hyun Sung, Soo-Jung Kim, Hyewon Lee, Seung-Goo Lee, Cell-free biosensor with automated acoustic liquid handling for rapid and scalable characterization of cellobiohydrolases on microcrystalline cellulose, Synthetic Biology, Volume 10, Issue 1, 2025, ysaf005, https://doi.org/10.1093/synbio/ysaf005