Week 1 HW: Principles and Practices

Class Assignment

1. First, describe a biological engineering application or tool you want to develop and why.

I want to develop a membraneless organelle within plant cells that is able to detect breakage of the cell membrane by a foreign organism. This organelle, which is comprised of intrinsically disordered proteins (IDPs), would trigger immune system responses upon detection. The purpose of this organelle is to detect and shut down fungal plant pathogens that infect through breaching cell membranes. This novel application would lower yield loss in rice plants (primarily Oriza Sativa) from fungal diseases like Rice Blast (Magnaporthe grisea) which is responsible for 10%-30% yield losses every year for rice, preventing the possibility of feeding about 60 million people.

2. Next, 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.

To ensure an ethical future, it is imperative to use preventative measures against ecological harm or unintended spread of this tool. One sub-goal to support this goal is to pursue the genetic containment of any engineered constructs within the plant cells. This could be done through designing constructs that can only function within plant cells. Another sub-goal is ensuring reversibility of the tool and monitoring altered organsism over time. Molecular constructs that are able to disable the tool along with monitoring programs can secure reversibility in case of adverse effects to the environment. Another policy goal to pursue is promoting equitable and responsible agricultural use. Promoting equitable use can be done through confirming affordable implementation for small farmers. Practicing transparency on the mechanics of the engineered system with farmers and consumers along with informed consent are vital for responsible agricultural uses.

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

Option 1. Currently, engineered crops are evaluated for environmental risk without any requirement for active containment mechanisms beyond general biosafety assessment. Federal regulators like the USDA-APHIS should create a requirement where engineered disease-responsive crops must have genetic containment features within its design to reduce unintended spread. This requirement should be a condition for any field trials/commercialization of genetically modified plants. The developers of the engineered crops will document containment logic and submit documentation to regulators within the federal agency for approval. This design assumes that genetic containment strategies will effectively reduce ecological risk and that regulators can consistently evaluate various containment designs across differing technologies. This option carries the risk of mutations or environmental variability bypassing containment procedures in practice. In addition, this option could slow innovation and burden smaller developers.

Option 2. Novel pathogen resistance strategies often only evaluated for efficacy and not for how they can shape pathogen evolution. Research institutions and academic funders (e.g., NSF, USDA-NIFA) can create new incentives for researchers to create new design strategies for pathogen resistance that take evolution and ecological pressure into consideration. Academic funders can reward researchers for designing damage-based or multi-signal immune systems over single effector type targets. This can be enforced through giving priority funding or recognition to projects that demonstrate reduced selective pressure. This option assumes that researchers can accurately anticipate evolutionary dynamics upon design. There is still a risk of pathogens adapting in an unforeseen way. It is also important to note that pathogen resistance strategies can lead to overly sensitive immune responses in crops which could hinder crop yield.

Option 3. Many engineered crops today are owned and controlled by companies which makes it more difficult for farmers to use these technologies. By using regulatory or financial incentives, we can encourage developers to commit to equitable licensing and deployment models to ensure more accessibility for small farmers. Government agencies can offer incentives such as faster regulatory review or public grant eligibility so that developers will agree to low-cost licensing and clear communication to farmers on benefits and limitations. This policy assumes that broader access to engineered crops will improve food security and the incentives are enough to influence company behavior. A possible issue with this policy is that smaller crop developers may struggle to meet equity requirements, unintentionally favoring bigger companies.

4. Last, 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.

The scoring demonstrates that the best course of action would be to combine Option 2 (incentives for evolution-resilient design) and Option 3 (accessible deployment and licensing). Option 2 would be prioritized as it performs the strongest in prevention-focused categories (biosecurity and environmental protection) while also minimizing burdens on researchers and scientific discovery. This option is vital in preventing detrimental harm to the environment.

Option 3 complements Option 2 by strengthening its gaps found outside of prevention-based categories. Option 3 allows for accessibility while also minimizing costs to stakeholders. By combining these two options, my bioengineering tool maximizes accessibility and impact while minimizing risks to the environment.

While Option 1 is strong in response to risks, it scored poorly on cost, accessibility, and research freedom. Prioritizing this option would ultimately slow innovation and burden smaller research teams. With our chosen options, we assume that developers would prioritize equitable deployment incentives and that early design decisions are effective at preventing ecological/evolutionary risk. However, we are uncertain as to whether incentives may be enough to convince profit-driven companies and if preventative design measures are able to prevent pathogens from evolving in unforeseen ways.

Week 2 Lecture Preparation

Homework Questions from Professor Jacobson

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?

The error rate of polymerase is 1:10⁶. Since the human genome is 3.2 billion base pairs long, this error rate would create about 32,000 errors per replication cycle. This would be catastrophic for genetic stability. Biology deals with this discrepancy by using error correcting polymerase, which actively corrects mistakes before they become permanent mutations in the DNA.

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?

The average human protein has about 1036 base pairs. With about 345 codons, there can easily be 10¹⁰⁰ or more ways to code the average human protein. A possible reason for why all these different codes do not work to code for the protein of interest is that mRNA could have an altered structure which could affect translation initiation, elongation, or stability. Another possible reason is that some sequences can create splice sites, promoter elements, or miRNA binding sites.

Homework Questions from Dr. LeProust

1. What’s the most commonly used method for oligo synthesis currently?

The most commonly used method for oligo synthesis currently is phosphoramidite-based solid-phase synthesis.

2. Why is it difficult to make oligos longer than 200nt via direct synthesis?

The main reasons for why it is so difficult to make oligos longer than 200 nt via direct synthesis is because of various reasons. To start, each cycle has a small failure rate which dramatically drops yield after 200 cycles. Long synthesis also increases the risk of base damage and full-length product is difficult to separate from failure sequences of a similar length.

3. Why can’t you make a 2000bp gene via direct oligo synthesis?

You can’t make a 2000bp gene via direct oligo synthesis as the small failure rate for each cycle would make the yield essentially zero. Too many errors would accumulate for a 2000-mer sequence.

Homework Questions from George Church

1. What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

The 10 essential amino acid in all animals are histidine, isoleucine, lysine, methionine, phenylalanine, threonine, typtophan, valine, and arginine. This makes me feel as if the Lysine Contingency is a very flawed method. While the dinosaurs did require lysine to survive, they could have eaten lysine from any animal in their diet. A more robust contingency would’ve involved multiple essential nutrients or synthetic auxotrophy.

2. What code would you suggest for AA:AA interactions?

For AA:AA interactions, I would suggest a “Lock-and-Key” chemical match based on the charge, hydrophobicity, size, shape, and special pairs (like Cysteine forming strong bonds).

3. Given the one paragraph abstracts for these real 2026 grant programs sketch a response to one of them or devise one of your own:

If our most advanced biological medicines were as easy to store and ship as aspirin, this would mean that more people could receieve life-saving gene and cell therapies. We would not have to worry about ultra-cold freezers which saves hundreds of thousands of dollars. We would be able to reach people in remote areas who would not have the resources to have frigid freezers to store medicines. This would revolutionize medicine and allow for cheap distribution to every corner of the world.

Week 2 HW: DNA Read, Write, & Edit

Part 1: Benchling & In-silico Gel Art

Part 3: DNA Design Challenge

3.1. Choose your protein.

The protein that I chose is the human testis-determining factor. I chose this protein because I find it interesting how one gene plays such a big role in sex differentiation and is the largest factor in deciding how a human embryo will grow. It is interesting to think about how one type of protein encoded by one gene in the human genome can spark significant change in the entire development process of humans. This sequence was taken from the NCBI:

>NP_003131.1 sex-determining region Y protein [Homo sapiens] MQSYASAMLSVFNSDDYSPAVQENIPALRRSSSFLCTESCNSKYQCETGENSKGNVQDRVKRPMNAFIVWSRDQRRKMALENPRMRNSEISKQLGYQWKMLTEAEKWPFFQEAQKLQAMHREKYPNYKYRPRRKAKMLPKNCSLLPADPASVLCSEVQLDNRLYRDDCTKATHSRMEHQLGHLPPINAASSPQQRDRYSHWTKL

3.2. Reverse Translate: Protein (amino acid) sequence to DNA (nucleotide) sequence.

.> reverse translation of NP_003131.1 sex-determining region Y protein [Homo sapiens] to a 612 base sequence of most likely codons. ATGCAGAGCTATGCGAGCGCGATGCTGAGCGTGTTTAACAGCGATGATTATAGCCCGGCGGTGCAGGAAAACATTCCGGCGCTGCGCCGCAGCAGCAGCTTTCTGTGCACCGAAAGCTGCAACAGCAAATATCAGTGCGAAACCGGCGAAAACAGCAAAGGCAACGTGCAGGATCGCGTGAAACGCCCGATGAACGCGTTTATTGTGTGGAGCCGCGATCAGCGCCGCAAAATGGCGCTGGAAAACCCGCGCATGCGCAACAGCGAAATTAGCAAACAGCTGGGCTATCAGTGGAAAATGCTGACCGAAGCGGAAAAATGGCCGTTTTTTCAGGAAGCGCAGAAACTGCAGGCGATGCATCGCGAAAAATATCCGAACTATAAATATCGCCCGCGCCGCAAAGCGAAAATGCTGCCGAAAAACTGCAGCCTGCTGCCGGCGGATCCGGCGAGCGTGCTGTGCAGCGAAGTGCAGCTGGATAACCGCCTGTATCGCGATGATTGCACCAAAGCGACCCATAGCCGCATGGAACATCAGCTGGGCCATCTGCCGCCGATTAACGCGGCGAGCAGCCCGCAGCAGCGCGATCGCTATAGCCATTGGACCAAACTG

3.3. Codon optimization.

Optimizing a codon sequence can have various impacts. Codon optimization replaces less-favored codons in a specific organism with more common codons. An optimized codon sequences has a higher efficiency in translation which then leads to higher levels of protein expression. In addition, an optimized codon improves the stability of the mRNA since they are more likely to be recognized by tRNAs. Overall, an optimized codon is more likely to have increased protein expression.

.> Optimized codon sequence of NP_003131.1 sex-determining region Y protein to Humans (Homo sapiens). ATGCAGTCCTATGCCTCCGCCATGCTGAGCGTGTTTAACAGTGATGACTACTCCCCAGCCGTGCAGGAGAACATCCCAGCCCTGAGACGCAGCAGCTCATTCCTGTGTACCGAGTCTTGCAACTCCAAGTACCAGTGCGAGACCGGCGAGAACAGTAAGGGAAACGTGCAGGATCGCGTGAAAAGGCCCATGAACGCTTTCATCGTGTGGAGCCGCGATCAGAGGAGGAAGATGGCCCTGGAGAATCCCAGGATGCGGAACAGCGAAATCTCCAAGCAGCTGGGCTACCAGTGGAAGATGCTGACCGAGGCCGAGAAGTGGCCATTTTTCCAGGAGGCACAGAAGCTGCAGGCCATGCACAGAGAGAAGTACCCCAATTACAAGTACAGACCCAGAAGAAAGGCCAAAATGCTGCCTAAGAACTGTTCCCTGCTGCCCGCCGACCCAGCCTCCGTGCTGTGCTCTGAAGTCCAGCTGGACAACCGCCTGTACAGAGACGACTGTACCAAGGCCACCCACTCCCGCATGGAACACCAGCTGGGGCACCTGCCCCCCATTAATGCCGCATCCTCCCCCCAGCAGCGCGACCGGTACAGCCACTGGACAAAGCTG

3.4. You have a sequence! Now what?

To produce this protein from my DNA, we can use a multitude of both cell-dependent and cell-free methods.

We can living cells as “factories” for our proteins. We can design a plasmid containing our TDF-encoding gene that also has a promoter, ribosome binding site, and antibiotic resistance marker. Through transforming a host cell (like Escherichia coli) with this DNA, we can then induce expression of the TDF protein within the cells. Upon harvesting and purifying the protein, we can then have a batch of TDF proteins.

If a cell-free system was preferable, we could combine ribosomes, tRNAs, polymerases, amino acids + nucleotides, and an energy system with our DNA to create our protein in a test tube. This method would be much faster.

Part 4: Prepare a Twist DNA Synthesis Order

Part 5: DNA Read/Write/Edit

5.1 DNA Read

(i) What DNA would you want to sequence (e.g., read) and why?

I would want to sequence the genome of a lactose intolerant person. I want to sequence this genome to better understand what genes are implicated in the reduced expression of lactase in lactose-intolerant patients.

(ii) In lecture, a variety of sequencing technologies were mentioned. What technology or technologies would you use to perform sequencing on your DNA and why?

To sequence my DNA, I would use Illumina Whole-Genome Sequencing. I would use this method as it can give a complete, highly accurate view of someone’s entire DNA sequence. This is a second-generation sequencing method that can sequence millions of short fragments in parallel and uses PCR amplification. For our input, we must extract blood/saliva and purify the genomic DNA of these cells. Then, we shear the DNA into ~200-500 bp fragments using enzymes. Once we ligate synthetic adapters to both ends of the fragments, we can then PCR amplify the adapter-ligated fragments. The prepared DNA can be combined with complementary oligos from a flow cell to generate clusters. This method uses a sequencing-by-synthesis method. By adding fluorescently labled nucleotides, we can use a camera to record which color/nucleotide attached to the sequence. After removing the nucleotide chemically and repeating the process with each type of nucleotide, we can then generate a raw FASTQ file.

DNA Write

(i) What DNA would you want to synthesize (e.g., write) and why?

I would like use synthesize a sequence of DNA that can work in a cell-free system and detect certain molecules present in a disease. This circuit will detect specific molecules from a pathogen like malaria. I want to create this biosensor to give impoverished areas a way to detect disease with cheap methods.

(ii) What technology or technologies would you use to perform this DNA synthesis and why?

I will perform this DNA synthesis using Gibson Assembly and molecular cloning. I can order the parts of the genetic circuit and assemble them accordingly using Gibson Assembly. After assembling the plasmid, the plasmid can be amplified through transformation, cloning in a bacterial cell, and purification. The limitations of this method is that it can be slower due to colony screening and sequencing verification and could include failed ligations, wrong inserts, etc. It also requires that I have already synthesized DNA.

DNA Edit

(i) What DNA would you want to edit and why?

One application for editing human DNA is to cure lactose intolerance. By editing the genome of a lactose intolerant human to be able to produce lactase, we can cure his lactose intolerance and allow him to consume foods with lactose. This application of gene editing is just one example of how synthetic biology can be leveraged to solve common human disorders.

(ii) What technology or technologies would you use to perform these DNA edits and why?

Lactose intolerance is commonly caused due to reduced expression of the lactase enzyme. To fix this, one could modify regulatory variants near the LCT gene in the human genome. The best way of doing this uses base editing systems (a CRIPSR-derived technology) to convert one base into another at a targetted location. This process works by a guide RNA first directing a Cas protein to a specific DNA sequence. Upon finding this DNA sequence, the Cas protein binds to the target site and a fused enzyme will then chemically convert the base into another base. After the cell’s repair mechanisms fix the strand, there will be a single-letter DNA change.

To prepare to preform this DNA edit, you must first identify which regulatory variant is implicated in adult lactase expression. Then, you have to prepare a sequence-specific guide RNA, base editor protein, and delivery system (maybe viral?). As a note, this system will target human intestinal stem cells in vivo. This method, however, carries various limitations. Since it is in vivo, delivery will be extremely difficult and all cells will not be edited (mosaic editing). In addition, this editing method may cause unintended edits in other areas of the genome.

Week 3 HW: Lab Automation

Assignment: Python Script for Opentrons Artwork

This is a link to the code for my Opentrons Artwork.

AI Contributions: I used AI to generate large portions of my code as I am largely unfamiliar with python programming. I used Gemini AI and asked it to integrate my coordinates for my artwork into the code in Colab.

Post-Lab Questions

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

The published paper that I found is titled “Semiautomated Production of Cell-Free Biosensors” (Brown, 2025). In this publication, the researchers develop and demonstrate an automated pipeline using the Opentrons OT-2 liquid handling robot to (mostly) automate and scale the manufacturing of cell-free biosensors. In their pipeline, they used the Opentrons to produce a full 384-well plate of fluoride-sensing biosensors. The researchers had the objective of using the Opentrons OT-2 robot to develop a method capable of high-throughput manufacturing, reduced variability in sensor performance, and accessibility across global labs.

When compared to manually assembled biosensors, the biosensors created by the robot proved to have greater consistency among detection thresholds. This research suggested that facilities or field clinics could use Opentrons robots to assemble diagnostic tests on-demand rather than importing them from outside sources. In addition, the success of this study shows how the cheaper OT-2 robot can be used in replacement of industrial-grade liquid handlers so that the production of synthetic biology-based diagnostics can be done in resource-limited settings.

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.

In my final project, I want to use automation tools to reliably produce biosensors and test them. I want to use the Opentrons robot to create multiple samples of protoplast cells altered by CRIPSR/Cas9 to produce a certain biosensor within the cell. These cells would be incubated and grown. Then, in an experiment, the automation tools would expose these cells to pathogens to see if the biosensor is able to reliably detect the presence of the pathogen. The fluoresence created by the biosensor can be measured by PHERAstar.

References

Brown, D. M., Phillips, D. A., Garcia, D. C., Arce, A., Lucci, T., Davies Jr., J. P., Mangini, J. T., Rhea, K. A., Bernhards, C. B., Biondo, J. R., Blurn, S. M., Cole, S. D., Lee, J. A., Lee, M. S., McDonald, N. D., Wang, B., Perdue, D. L., Bower, X. S., Thavarajah, W., … Lucks, J. S. (2025). Semiautomated Production of Cell-Free Biosensors. ACS Synthetic Biology, 14(3), 979-986. https://doi.org/10.1021/acssynbio.4c00703.s001