Week 1 HW: Principles and Practices

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

My plan for the final project is a synthetic membrane that has Mesenchymal Stem Cells Microvesicules (which have scientifically proven regenerative and other positive properties) intercalating inbetween the membrane’s layers. Which could be used for burn wounds and/or donation organs preservation while in transportation.

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.

I can’t seem to see much possibility for malfeasance after proper testing. But the two biggest questions that arise are: Reproductibility and Universal (or almost) access to the treatment. A. Reproductibility: This step is essential to make sure that the design is simple enough to be able to be reproduced by as many labs as possible even in the harshest conditions. Sub goals: Testing and optimizing the design so it uses the simplest technology possible. Trialing in several conditions and labs across the world.

B. Ensuring universal access: This step is to make sure that, after proper testing, the therapy is accessible by the general population and not just a select few. Sub goals: Collaboration with public health systems globally. Ensuring no malicious patenting of the design can be made.

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

Action 1: Creation of a bioethics and biosafety commitee; Purpose: Making sure that every material is non-harmful and is in fact composed of what it is expected to. Example: Making sure that the MV’s are indeed microvesicules and that their content is beneficial to health. Design: Proper lab testing protocols such as Flow Cytometry, Electron Microscopy and such; And parameters for consistency in the design. Risk of failure and “success”: Failure: the output is not as expected and the consistency of the therapy can’t be guaranteed. Success: the design is properly tested and may be applied to patients willing to test.

Action 2: Implementation of proper trials and validation; Purpose: Testing the therapeutic with willing and acknowledging subjects to ensure that the effects are real, beneficial and consistent. Design: Double blind studies. Risk of failure and “success”: Failure: the therapeutics has no effect or is harmful to whoever is subjected. Success: the effects are, in fact, benign and consistend independent of characteristics of the patient.

Action 3: Preemptive adoption of a framework for dealings with regulatory organs; Purpose: Making sure that, after the testing is done, the therapy can be introduced to as many patients as possible while being in concordance with local regulations. Design: Keeping proper documentation of all design steps, dialoguing with regulatory organs to plan proper introduction to new patients. Risk of failure and “success”: Failure: the design is proper and has effects but it can’t be introduced due to not fitting regulations. Success: the design is introduced properly to more populations.

4. Next, score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals. The following is one framework but feel free to make your own:

5. 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

I would prioritize making sure that international and national regulations do not become an obstacle for the application of the therapy. While it may seem idealist to aim for it, I believe in universal healthcare and the feasability of more accessible therapies.

6. Reflecting on what you learned and did in class this week, outline any ethical concerns that arose, especially any that were new to you. Then propose any governance actions you think might be appropriate to address those issues. This should be included on your class page for this week.

Mainly the use of creatures (animals and others) that may not consent to their usage in research. For governance actions, regulations and societies and maybe even the general public should make sure that the subjects of the research are treated in the most humane way possible.

Week 2 lecture preparation

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?

1:10⁶. The human genome consists of about 3.2 billion base pairs. The discrepancy is dealt with using proofreading mechanisms and other corrective measures.

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?

According to uniprot the average human protein consists of about 400 aminoacids. Most AA’s have multiple codons which encode them (being redundant). That makes it so that there are more possibilities of DNA coding than humanly possible to consider. In practice, some of the reasons why they wouldn’t work are: codon usage bias (some codons are preferred due to optimal functioning), formation of CPG islands promoting methylation and thus leaving the DNA useless. Other reasons include structural integrity and such…

Dr. LeProust:

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

Phosphoramidite chemistry on solid-phase synthesizers

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

Could not find this in the slides, had to make use of the emergencial AI resource through the use of Deepseek AI (Where I just made the same question as the homework). Apparently, it is because the efficiency of coupling is not 100%, accumulating various errors and unwanted reactions after said length.

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

Reffering to the answer above… The actual yield would be too low. Deepseek said that that’s the reason why “synthetic biology relies on assembly methods rather than direct synthesis for genes and long constructs.”

Mr. George Church:

6. [(Advanced students)] Given the one paragraph abstracts for these real 2026 grant programs sketch a response to one of them or devise one of your own:

I chose the BoSS – BioStabilization Systems program from Arpa-H. My response towards this problem would be to employ AI to find more stable molecular structures of existing or even of new proposed drugs. Simulating responses towards a multitude of different conditions, and trying to predict different environmental parameter threshholds that are supported by the molecules.

Week 2 HW: DNA Read Write and Edit

Part 1: Benchling & In-silico Gel Art:

• Simulate Restriction Enzyme Digestion with the following Enzymes:

• Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks.

I tried to make a pattern that looked like a staircase going down by using logic but couldn’t quite seem to get it right…

Part 3: DNA Design Challenge:

Protein Choice: AFP III (Antifreeze Protein Type III) I chose AFP III because it has an incredible practical application: allowing organisms to survive in sub-zero temperatures. In biotechnology, it is used to create smoother ice cream textures (by preventing large ice crystals) and in the preservation of organs for transplant. It is a fascinating example of how nature solves extreme physical challenges through molecular engineering.

Protein Sequence (UniProt P05140): sp|P05140|ANP3_MACAM Antifreeze protein type 3 NQASVVANQLIPINTALTLVMMKAEVVTPMGIPAEEIPNLVGMQVNRAVPLGTTLMPDMV KNY

Reverse Translation aatcaagcctctgtagtagccaaccagctgatccccatcaacaccgccctcaccctggtcatgatgaaggccgaggtcgtcacccccatgggcatccccgccgaggagatccccaacctggtcggcatgcaggtcaaccgcgccgtccccctcggcaccaccctgatgcccgacatggtcaagaactac

Codon Optimization In your own words, describe why you need to optimize codon usage. Which organism have you chosen to optimize the codon sequence for and why? This answer takes back to last homework, due to codon bias, using a sequence that’s not ideal for your chosen organism, you may have some problems with codons used tipically by the species that produces said protein naturally. I picked E.Coli because it is the standart for easy cultivation. I ran VectorBuilder’s tool with some uncertainty but it seemed good because it was the only one that said ‘free’ on the google search. This is the optimized sequence: AACCAGGCGAGCGTGGTGGCGAATCAGCTGATTCCGATTAATACCGCCCTGACCCTGGTGATGATGAAAGCCGAAGTGGTGACCCCGATGGGCATTCCGGCGGAAGAAATTCCGAACCTGGTGGGCATGCAGGTGAATCGCGCGGTGCCGCTGGGCACCACCCTGATGCCGGATATGGTGAAAAATTAT

You have a sequence, now what? Cell-Dependent Expression (In Vivo): The most common method is to transform E. coli cells with the plasmid. When an inducer (like IPTG) is added to the growth media, the bacteria’s internal machinery (RNA Polymerase and Ribosomes) begins to transcribe the DNA into mRNA and translate that mRNA into the physical AFP III protein.

Cell-Free Protein Synthesis (In Vitro): Alternatively, one could use a “cell-free” extract. This involves mixing the DNA directly with a “molecular soup” containing ribosomes, enzymes, and amino acids in a test tube.

Part 4: Prepare a Twist DNA Synthesis Order:

I made an account and twist doesn’t seem to allow me to use the website, saying I need to contact a distributor… I checked with a fellow brazilian colleague and he seems to be having the same issue, maybe it’s a regional block?

Part 5: DNA R/W/E:

In graduation I learned a ton about mangroves and their importance, so, to sequence the mangrove microbiome, I’d target the DNA in the sediment and root zones of these coastal forests. Mangroves are massive “blue carbon” sinks, and by reading the genetic material of the microbes living there, we can find hidden enzymes that fix nutrients or even break down plastics in salty water. This helps us understand how these forests fight climate change and gives us new “bio-tools” for cleaning up the environment. I would use Illumina Sequencing for this because it’s the best for handling the complex mix of species found in soil. This is a second-generation technology that uses “sequencing by synthesis” to read millions of DNA fragments at once. First, I’d extract the DNA, break it into tiny pieces, and attach “adapters” so they can stick to a glass flow cell. Inside the machine, the DNA is copied into clusters, and as fluorescently labeled bases are added, they flash a specific color for each letter (A,T,C, or G). A camera captures these flashes, and the software translates them into digital FASTQ files that we can piece together like a giant puzzle.

For the “DNA Write” part, I’d synthesize a caffeine biosynthetic pathway to put into yeast. This would let us “brew” caffeine in a lab without needing huge coffee or tea plantations, saving a lot of land and water. I’d use silicon-based synthesis (like Twist Bioscience), which uses a silicon chip to build thousands of DNA strands at once using a chemical process called phosphoramidite chemistry. We’d print short pieces of the caffeine genes and then stitch them together into a full circuit. The main catch is that it’s hard to write very long or repetitive sequences, but it’s incredibly fast and scalable for these kinds of metabolic projects.

Finally, I’d use CRISPR-Cas9 to edit a banana or tomato so it grows with the caffeine pathway built right in. The idea is to create a “Caffeine Fruit” for a natural, healthy morning energy boost. CRISPR works like a molecular GPS and scissors; a guide RNA leads the Cas9 enzyme to a specific spot in the plant’s DNA to make a cut. By providing a “donor template” with our caffeine genes, the plant’s own repair system pastes the new instructions into its genome. We’d use a “shuttle” like Agrobacterium to get the CRISPR tools into the plant cells. It’s a powerful method, though it can sometimes be slow to grow a full plant from an edited cell, and we have to be careful that the enzyme doesn’t cut the DNA in the wrong place.

Week 3 HW: Lab Automation

Part 1: Python Script for Opentrons Artwork

I used Ronan’s provided GUI and a nice little pixelart of a kidney to try out the design and figure out coordinates. Python coding was new and quite… surprising. But using the toad.py provided by the USFQ node I figured out how to get the code to work. This is a kidney art that i’ll try to print. Hopefully it actually resembles something!

This is a small test of the gui and code, it reads nefrologia (nephrology in portuguese) and has a small heart.

Part 2: Post lab

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

https://www.nature.com/articles/s44172-025-00575-3 is the paper I picked because it initially uses opentrons for a small scale production of a living cell hydrogel. I found it quite alike my proposed final project product so it may serve as a nice starting point to figure out fabrication. Although the paper uses their product for drug trialing instead of what I proposed.

I reckon the best use of automation for my idea is to help with the fabrication with properly placing the scaffolds and the microvesicules in between them.

Part 3: Final project ideas

I uploaded my ideas to the slide deck. Here is a copy of my slide and ideas.

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project