Week 1 HW: Principles and Practices

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

I want to develop a soft material actuator powered directly by living cells rather than electronics or mechanical pumps. The system would use microbial metabolism, specifically gas produced during fermentation, to generate pressure inside a flexible chamber, allowing the material to inflate and perform mechanical work. Instead of using batteries, compressors, or microcontrollers, the material would respond to environmental conditions such as temperature or moisture because those conditions naturally regulate cellular activity. In this way, the environment becomes the control signal and biology becomes both the energy source and the actuator. If metabolic activity can reliably produce mechanical motion, it opens pathways toward deployable biohybrid interfaces, such as agricultural materials that respond to weather, environmental monitors that operate without batteries, or wearable materials that adapt to the human body. The goal is not to replace traditional machines but to investigate whether biological processes can serve as power, sensing, and control within soft matter systems.

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)

Design the system to fail safely (loss of function, not uncontrolled release) with proper precautions

Ensure transparency about the potential risks involved in the prototype, especially with the use of gas produced

Understand the material lifecycle

Describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”). Try to outline a mix of actions (e.g. a new requirement/rule, incentive, or technical strategy) pursued by different “actors” (e.g. academic researchers, companies, federal regulators, law enforcement, etc). Draw upon your existing knowledge and a little additional digging, and feel free to use analogies to other domains (e.g. 3D printing, drones, financial systems, etc.)

1. Biosafety Regulation

• Purpose: Ensuring there’s no uncontrolled release and exposure of cells

• Design, Actors: Biosafety staff, public health agencies, trained researchers

• Assumptions: There will likely be minimal risks in my proposal, but just in case

• Risks: Improper handling, out of control containment of yeast or other actives

2. Education and Trust

• Purpose: Have clear documentation of the work and be transparent about its effects.

• Design, Actors: Conference participation, community outreach/engagement programs

• Assumptions: Educating the public and sharing knowledge would allow for acceptance of living materials

• Risks: Informal attempts to replicate without proper lab set up, misinformation, not enough market adopting the product

3. Sustainability in Design and Environment

• Purpose: Figure out the material lifecycle of the product, whether the biohybrid material actually help to reduce environmental impact or is it creating a new waste stream. How to properly dispose of this? How can we make this material more resilient?

• Design, Actors: Recycling centers, waste systems, manufacturers

• Assumptions: Bio materials are not automatically environmentally friendly

• Risks: May risk creating new class of waste or contaminating the waste stream, materials may degrade faster than ideal in certain environmental conditions

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

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

This was a close scoring, but I would prioritize option 2 (Education & Trust) since communities must be open minded to living materials and we can assume that early engagement can improve long-term adoption and safer use. This is important not only for obtaining data for continuous research and evaluation but also understand the true impact of the system. Prioritizing Education & Trust means relying more on public understanding and voluntary compliance rather than strict control. This can make research participation, feedback, and acceptance easier, but it may reduce enforceability compared to formal regulation. Extensive communication takes time and resources that could otherwise be spent on technical development.

Assignment (Week 2 Lecture Prep)

1. Homework Questions from Professor Jacobson:

• 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 is 1:10^6, length of human genome is 3.2 billion base pairs, biology deals with this discrepancy through a repair system (to be cont.)

• 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?

2. Homework Questions from Dr. LeProust:

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

Phosphoramidite

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

Depurnification, more prone to error

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

It would be difficult to achieve with error rates

3. Homework Question from George Church • 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 acids in animals are Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, Valine, Arginine. The takeaway for Lysine Contingency is that animals didn’t reinvent it and that it evolved only after plants and microbes.

https://chatgpt.com/share/698b047d-1078-800e-b269-af9a7e193d73

Week 2 HW: DNA Read, Write, Edit

3.1. Choose your protein

I chose miniSOG (mini Singlet Oxygen Generator) using the protein table from FPbase. It is described as a cyan fluorescent protein that can be controlled with blue light. When illuminated, the molecule absorbs energy and transfers it to nearby oxygen, briefly converting it into a reactive form called singlet oxygen. This state lasts only a few microseconds inside cells and travels about 10–20 nanometers, making it useful for nanoscale targeting. Because it can repeatedly trigger localized reactions without being consumed, it behaves more like a catalyst than a reagent.

miniSOG is an engineered 106-amino-acid protein derived from a plant protein in Arabidopsis thaliana (mouse-ear cress). Plants need to sense light to grow toward the sun and regulate circadian rhythms, so they evolved blue-light-detecting proteins called phototropins. These proteins contain a LOV domain (Light, Oxygen, Voltage sensing domain) that holds a vitamin B2-derived molecule called FMN (flavin mononucleotide). FMN acts as a photosensitizer by absorbing blue light and transferring energy to oxygen.

By modifying this domain, researchers repurposed the natural light sensor into miniSOG, which generates localized oxidative reactions when activated. This allows scientists to mark proteins, damage specific organelles such as mitochondria, selectively kill cells, and stain cellular structures for imaging.

The protein sequence is as follows:

MEKSFVITDP RLPDNPIIFA SDGFLELTEY SREEILGRNG RFLQGPETDQ ATVQKIRDAI RDQREITVQL INYTKSGKKF WNLLHLQPMR DQKGELQYFI GVQLDG

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

I used the Bioinformatics reverse translation tool to obtain 318 base sequence of most likely codons:

atggaaaaaagctttgtgattaccgatccgcgcctgccggataacccgattatttttgcg agcgatggctttctggaactgaccgaatatagccgcgaagaaattctgggccgcaacggc cgctttctgcagggcccggaaaccgatcaggcgaccgtgcagaaaattcgcgatgcgatt cgcgatcagcgcgaaattaccgtgcagctgattaactataccaaaagcggcaaaaaattt tggaacctgctgcatctgcagccgatgcgcgatcagaaaggcgaactgcagtattttatt ggcgtgcagctggatggc

3.3. Codon optimization

E. coli is the easiest organism to work with in the lab so for this exercise the below is the codon optimization using GenSmart:

ATGGAAAAATCATTTGTAATAACAGATCCCCGCCTGCCAGATAACCCGATTATTTTCGCTAGCGACGGCTTTTTGGAGTTGACTGAGTACAGCCGTGAGGAAATTCTGGGTCGCAACGGCCGTTTTCTGCAAGGTCCGGAAACCGATCAGGCAACGGTGCAAAAGATCCGTGACGCGATTCGCGACCAACGTGAGATCACCGTCCAGCTTATCAACTATACCAAATCCGGTAAAAAGTTCTGGAATCTGCTGCACCTGCAGCCGATGCGTGACCAGAAGGGTGAATTACAGTACTTCATCGGCGTTCAACTGGATGGC

3.4. What technologies could be used to produce this protein from your DNA?

To produce the miniSOG protein, the DNA sequence encoding miniSOG is inserted into a plasmid expression vector containing a promoter, ribosome binding site, and terminator. The plasmid is introduced into E. coli through transformation. Inside the bacteria, RNA polymerase binds to the promoter and transcribes the miniSOG gene into messenger RNA (mRNA). Ribosomes then translate the mRNA codons into amino acids with the help of tRNAs, forming the 106-amino-acid miniSOG polypeptide. The protein folds into its functional structure and binds FMN, allowing it to function as a light-activated singlet oxygen generator.

4. Twist and Benchling

I imported the GenBank file from Twist Bioscience into Benchling and below is the resulted visualization:

5.1. DNA Read I would use nanopore sequencing (for example Oxford Nanopore sequencing) to sequence the DNA encoding miniSOG. This method can read very long DNA molecules, so it can sequence the entire plasmid containing the gene in a single read instead of reconstructing it from short fragments.

Nanopore sequencing is a third-generation sequencing technology because it reads single DNA molecules directly in real time without PCR amplification or synthesis reactions. Unlike second-generation methods, it does not rely on fluorescence or imaging.

Input and sample preparation: purified plasmid DNA isolated from E. coli.

Preparation steps: Extract plasmid DNA from the bacteria > Linearize or lightly fragment the plasmid > Ligate sequencing adapters and a motor protein to the DNA ends > Load the DNA library onto the nanopore flow cell

Essential sequencing steps and base calling. The flow cell contains a membrane with tiny protein nanopores. An electrical voltage is applied across the membrane, causing ions to flow through each pore and creating a measurable current.

A motor protein feeds a single DNA strand through the nanopore > As bases pass through the pore, they partially block ion flow > Each base (A, T, C, G) produces a characteristic change in electrical current > The instrument records this current trace > Software analyzes the signal and converts the current pattern into nucleotide identities.

The output is long sequencing reads that contains the nucleotide sequence and a Q score for each base

Week 3 HW: Lab Automation