Week 1 HW: Principles and Practices

1)First, describe a biological engineering application or tool you want to develop and why.( This could be inspired by an idea for your HTGAA class project and/or something for which you are already doing in your research, or something you are just curious about.)

One of the areas of greatest interest in bioengineering is gene therapy, a field where bioengineering and neuroengineering converge. The majority of these areas still lack a distribution. Therefore, gene therapies should be investigated in conjunction with supportive biological agents. For example, there is still no complete cure for schizophrenia, one of the biggest reasons being that schizophrenia is a polygenic disease. A synthetic promoter could be created to address this. This promoter, in the case of cellular neural activity, creates a biological control system that temporarily suppresses the expression of risk genes through signals from the natural signaling cell.

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.

Although this biological control system is designed for patients with schizophrenia, it opens a significant door for the improvement and treatment of other neurological diseases in the future. Furthermore, it helps integrate individuals with many neurological disorders into society.

Therefore, three different prioritary goals can be identified:

Goal 1: Preventing unwanted damage to the cell

Subgoal: Promoter specificity should be investigated before any clinical phase, and CRISPR-based gene modifications should not be performed.

Goal 2: A large patient population is needed so that genetic diversity can be assessed.

Goal 3: Abuse should be limited by providing controlled access.

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

Purpose: Currently, there is no definitive cure for schizophrenia. The process is carried out through drug development and psychological support. However, thanks to the synthetic promoter method, a treatment is offered that both suppresses the disease and minimizes the impact of biological factors.

Design: First, this system must be supported in a laboratory environment. For this, it should be tested in a university laboratory by experts in the fields of genetic engineering, synthetic biology, and neuroengineering. Furthermore, for disease modeling, funding should be sought from neuroscience and psychiatry departments, and for financing, from private and public funds such as Horizon Europe, NIH, etc. And since human or animal cells will be used in these experiments, approval from ethics committees such as IRB and IBC is required.

Assumptions: The cell type used in creating this system may be incorrect, which could reduce its suitability for the biology of schizophrenia. Additionally, biological design errors may occur, such as incorrect promoter selection, incorrect suppressor dosage, etc.

Failure: From an ethical standpoint, failure to obtain IRB approval can lead to failure. From a biological perspective, the system may be working correctly, but it may suppress the gene too much, disrupting the cell’s physiological balance. The cell, whose balance is disrupted, may experience disruptions in learning or normal signal transmission. Or, the system may not suppress the correct gene at the correct time, leading to the suppression of the cell and, consequently, the signaling system, rendering the treatment system ineffective.

4)Next, score 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.

In this case, the first option is best because neural gene editing prioritizes safety in biological design. Therefore, the process should be ethically evaluated and supported. Initially, we should examine whether there are any problems in the design, and where potential problems might arise in the design structures. Safety and ethical discussions should then be meticulously examined in the subsequent process. Because there are many uncertainties in this type of neural bioengineering, and we need to minimize them.

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? DNA polymerase makes an error roughly once every 10⁸ nucleotides, and given that the diploid human genome contains about 6 billion nucleotides, this would theoretically result in around 60 errors per cell division. However, cells possess multiple DNA repair mechanisms, including the proofreading activity of DNA polymerase and mismatch repair pathways, which significantly reduce the actual mutation rate during cell division.

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? An average human protein is about 350–400 amino acids long, and due to the degeneracy of the genetic code, an enormous number of DNA sequences (≈10¹⁹⁰) could theoretically encode the same protein. In practice, most of these sequences do not work because codon choice affects translation efficiency, mRNA structure, protein folding, and gene regulation, meaning only a small subset can be properly expressed in cells.

Homework Questions from Dr. LeProust:

What’s the most commonly used method for oligo synthesis currently? The most commonly used method is solid-phase phosphoramidite synthesis, where DNA nucleotides are added sequentially to a growing chain attached to a solid support.

Why is it difficult to make oligos longer than 200nt via direct synthesis? Because each nucleotide addition step is not perfectly efficient, errors and truncated products accumulate as the oligo gets longer, greatly reducing the yield of full-length sequences.

Why can’t you make a 2000bp gene via direct oligo synthesis? Direct synthesis of such a long sequence would result in extremely low yields and high error rates, so long genes are instead assembled from multiple shorter oligos.

Homework Question from George Church:

Project Proposal: Light-Driven Genetic Programming (Lumina-Code) The Challenge Current genetic engineering is limited by physical delivery. Whether we use viral vectors or nanoparticles, we are essentially trying to “ship” biological instructions into a cell. This process is slow, often triggers immune responses, and lacks spatial precision. My project addresses the DARPA GO challenge: How can we send genetic instructions at the speed of light, without any physical material?

The Solution I propose the development of Lumina-Code, a protein-based “intracellular printer.” Instead of delivering pre-made DNA, we will engineer a specialized Nucleic Acid Compiler (NAC) that stays dormant inside the cell. This NAC will be designed to recognize specific wavelengths of light as digital commands. For instance, a specific pulsing pattern of blue light will trigger the enzyme to assemble a precise RNA sequence from the cell’s internal building blocks.

Potential Impact This “massless” transmission of information would change everything. In a medical setting, a doctor could use a laser to “type” a therapeutic code directly into a tumor, telling it to stop growing, without affecting healthy tissue. In extreme environments, like deep-space missions, we could transmit life-saving medical codes as radio or light signals to be synthesized instantly by the astronauts’ own cells.

Next Steps Our first year will focus on engineering the NAC protein to respond to two distinct light frequencies. Our goal is to demonstrate that we can “print” a short, 20-base genetic sequence inside a living cell using only external optical triggers, achieving a new frontier in biological remote control.

Week 2: DNA Read, Write and Edit

Part 1: Benchling & In-silico Gel Art

First I start to stimulate Restriction Enzyme in Lambda DNA:

Also shown above,with Ronan’s website, I try to pattern with enzymes.

Part 3: DNA Design Challenge

3.1. Choose your protein:

I decided to choose GFP protein in water jellyfish(Also called “Aqua Victoria”). Because with GFP protein I can see that organization of cell. I can track protein and find to where to go in the cell. On the shown below, you can see GFP Protein Sequence:

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

3.3. Codon optimization:

I want to use codon optimization tool for E.coli genom.

3.4 You have a sequence! Now what?

What technologies could be used to produce this protein from your DNA? Describe in your words the DNA sequence can be transcribed and translated into your protein. You may describe either cell-dependent or cell-free methods, or both.

To make GFP protein from DNA, the DNA first needs to be transcribedinto mRNA and then translated into protein. The DNA has a promoter, the GFP coding sequence, and other regulatory parts. RNA polymerase reads the DNA to make mRNA, and ribosomes read the mRNA to assemble the amino acids into the GFP protein, which then folds and becomes fluorescent.

Ways to produce GFP:

In cells (cell-dependent):

In bacteria like E. coli, you put the GFP DNA in a plasmid and the bacteria make the protein for you—fast and cheap.

For more complex proteins, yeast or mammalian cells can be used to get proper folding and modifications.

Cell-free (in vitro):

You can use a test-tube system with the cell’s transcription and translation machinery. Add GFP DNA, and the protein is made directly. This is fast and easy to control.

Both methods let you get functional GFP for experiments or imaging.

Part 4: Prepare a Twist DNA Synthesis Order:

Here are expression cassed and its vector DNA:

Part 5: DNA Read/Write/Edit:

5.1 DNA Read:

(i) What DNA would you want to sequence (e.g., read) and why? This could be DNA related to human health (e.g. genes related to disease research), environmental monitoring (e.g., sewage waste water, biodiversity analysis), and beyond (e.g. DNA data storage, biobank). I want to sequence DNA related to Alzheimer’s disease which is neurodegenerative diseases that affects memorh, cognition and behavior. The main risk genes are APP, PSEN1 and PSEN2 and these genes are linked to early-onset familial Alzheimer’s disease. And sequencing these genes would help identify pathogenic mutations, assess genetic risk etc.

(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?

I use Whole Exome Sequencing (WES) on an Illumina platform.This method focuses on protein-coding regions (exons), where most disease-causing mutations occur, and is cost-effective compared to whole genome sequencing. Also answer the following questions:

Is your method first-, second- or third-generation or other? How so?

This is a second-generation sequencing method because it relies on massively parallel short-read sequencing and requires PCR amplification of DNA fragments.

What is your input? How do you prepare your input (e.g. fragmentation, adapter ligation, PCR)? List the essential steps.

The input is genomic DNA extracted from patient samples, such as blood or saliva.

Essential preparation steps include:

1. Fragmentation of DNA into short fragments (~150–200 bp).

2. Adapter ligation to allow binding to the sequencing flow cell.

3. PCR amplification to increase the quantity of DNA library.

4. Exome capture using hybridization probes to enrich for coding regions.

5. Library quality control to check fragment size and concentration.

What are the essential steps of your chosen sequencing technology, how does it decode the bases of your DNA sample (base calling)?

1. DNA fragments are attached to a flow cell and amplified into clusters (bridge amplification).

2. Sequencing by synthesis: fluorescently labeled nucleotides are added one at a time.

3. Each incorporated nucleotide emits a specific color that is captured by a camera.

4. The software converts these fluorescence signals into nucleotide sequences (A, T, G, C) — this process is called base calling.

What is the output of your chosen sequencing technology?

The sequencing produces FASTQ files, containing millions of short DNA reads with associated quality scores. After bioinformatic analysis, variant calling identifies single nucleotide polymorphisms (SNPs), insertions, or deletions, producing variant call files (VCFs) for interpretation of disease-associated mutations.

5.2 DNA Write

(i) What DNA would you want to synthesize (e.g., write) and why? Selected DNA to Synthesize: A Synthetic Genetic Circuit for Detecting Inflammation

I would design and synthesize a synthetic genetic circuit capable of sensing inflammatory signals and generating a controlled therapeutic response. Specifically, this construct would be compatible with human cells and engineered to detect activation of the NF-κB signaling pathway, which is a central regulator and biomarker of inflammation. Upon activation, the circuit would trigger the expression of either an anti-inflammatory cytokine, such as IL-10, or a fluorescent reporter protein for diagnostic purposes.

Rationale for Synthesizing This DNA

This synthetic DNA construct has both therapeutic and diagnostic potential. From a therapeutic perspective, engineered immune cells or stem cells containing this circuit could respond locally to inflammatory signals and produce anti-inflammatory molecules in conditions such as autoimmune diseases or inflammatory bowel disease (IBD). From a diagnostic standpoint, the system could function as a living biosensor, providing real-time detection of inflammatory activity through measurable reporter expression. Additionally, this project exemplifies key principles of synthetic biology, including modular genetic design, where distinct elements—such as promoters, sensing modules, logic components, and output genes—are assembled into a programmable biological system.

Simplified Genetic Components of the Circuit

The proposed construct would include:

An NF-κB–responsive promoter to sense inflammatory signaling

A minimal promoter combined with enhancer elements to regulate transcription

Coding sequence (e.g. IL10 or GFP) • PolyA signal • Insulator sequences

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

Chosen Technology: Array-based Chemical DNA Synthesis (Phosphoramidite Method)

This is the dominant commercial method used by companies like Twist.

Also answer the following questions:

What are the essential steps of your chosen sequencing methods?

1. In silico DNA design Everything starts on the computer. First, I would digitally design the full DNA sequence of the genetic circuit. During this step, I would optimize the codons to ensure efficient expression in human cells. I would also remove problematic elements such as repetitive sequences, unwanted restriction sites, and regions that might form strong secondary structures. The goal here is to make sure the DNA is not only correct in theory but also stable and easy to synthesize and express.

2. Chemical oligonucleotide synthesis Once the design is finalized, the DNA is synthesized in small fragments called oligonucleotides. Using phosphoramidite chemistry, nucleotides are added one at a time in a controlled, step-by-step process. In simple terms, the DNA strand is chemically built base by base.

3. Oligo amplification and error correction Because chemical synthesis is not perfectly error-free, the short DNA fragments are amplified using PCR to increase their quantity. At this stage, error-correction methods can be applied to remove sequences that contain mismatches or synthesis mistakes, improving the overall accuracy of the final product.

4. DNA assembly After obtaining the correct short fragments, they are assembled into the full-length gene or genetic circuit. Techniques such as Gibson Assembly or Golden Gate Assembly are used to seamlessly join overlapping DNA pieces. This step is where the smaller parts come together to form the complete functional construct.

5. Cloning and validation Finally, the assembled DNA is inserted into a plasmid vector and introduced into host cells for replication. To confirm that the sequence matches the original design, sequencing is performed. This verification step ensures that the synthesized DNA is accurate and ready for downstream applications.

What are the limitations of your sequencing method (if any) in terms of speed, accuracy, scalability?

Array-based chemical DNA synthesis using phosphoramidite chemistry is widely used, but it has several limitations in terms of speed, accuracy, and scalability.

In terms of speed, the process is relatively slow because nucleotides are added one at a time through sequential chemical reactions. Although many oligonucleotides can be synthesized in parallel on an array, additional steps such as amplification, assembly, and validation increase the overall time required.

Regarding accuracy, synthesis errors accumulate as the DNA strand gets longer. Since each base addition is not 100% efficient, longer sequences are more likely to contain deletions or substitutions. For this reason, DNA is usually synthesized in short fragments and later assembled, followed by sequence verification.

In terms of scalability, the method is highly efficient for producing large numbers of short oligonucleotides. However, synthesizing very long genes or complex genetic circuits becomes more expensive and technically challenging due to assembly and error-correction requirements.

Overall, while the method is reliable and scalable for short sequences, it becomes less efficient and more error-prone as sequence length increases.

5.3 DNA Edit

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

I would edit disease-causing mutations in the human genome, specifically monogenic disorders such as sickle cell disease caused by mutations in the HBB gene. Since this condition results from a single nucleotide substitution, it is an ideal candidate for precise genome editing. The goal would be therapeutic—to correct the mutation in a patient’s hematopoietic stem cells and restore normal hemoglobin production. Similar strategies could be applied to other inherited diseases. The purpose of the edit would be to treat or cure genetic disorders rather than enhance human traits.

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

I would use CRISPR-Cas9 genome editing because it allows precise, targeted modification of specific DNA sequences.

Also answer the following questions: How does your technology of choice edit DNA? What are the essential steps?

CRISPR works by using a guide RNA that directs the Cas9 enzyme to a specific location in the genome. Cas9 creates a cut in the DNA, and the cell repairs it. If a correct DNA template is provided, the mutation can be replaced through homology-directed repair.

What preparation do you need to do (e.g. design steps) and what is the input (e.g. DNA template, enzymes, plasmids, primers, guides, cells) for the editing?

The main inputs include Cas9, a guide RNA, a repair template, and patient-derived cells. After delivery into the cells (e.g., via electroporation), edited cells are screened and verified by sequencing.

What are the limitations of your editing methods (if any) in terms of efficiency or precision? Limitations include possible off-target effects, limited editing efficiency, and challenges in achieving precise repair. Despite these limitations, CRISPR remains one of the most promising tools for treating genetic diseases.

Week3: Lab Automation

Review this week’s recitation and this week’s lab for details on the Opentrons and programming it.

This week was all about moving from manual pipetting to the world of liquid handling automation. I’ve been diving deep into the Opentrons ecosystem, specifically focusing on how to bridge the gap between writing Python code and seeing the robot actually execute those movements on the deck.

The Technical Workflow The core of my work this week involved getting comfortable with the Opentrons Python API (v2.13). I’ve learned that a solid protocol isn’t just about moving liquid; it’s about defining the environment perfectly. My scripts now follow a strict structure:

Metadata & Requirements: Setting the apiLevel and identifying the project.

Labware Loading: Mapping out the 11-slot deck (e.g., placing the 96-well plate in Slot 1 and the 300µL tip racks in Slot 4).

Instrument Definition: Defining the pipettes on the Left and Right mounts to ensure the robot knows its “limbs.”

The “Opentrons Art” Lab The highlight was the “Opentrons Art” challenge. It sounds fun, but it’s actually a high-stakes lesson in precision and coordinate systems.

Calibration is Everything: I spent a significant amount of time on the Labware Position Check (LPC). Even a 1mm offset in the Z-axis can lead to a crashed tip or an air-gap dispense that ruins the “painting.”

Optimization with Loops: Instead of hard-coding every single movement, I used Python for loops to iterate through the plate’s rows and columns. This makes the code cleaner and allows for more complex patterns with fewer lines of logic.

Fluid Dynamics: I practiced using .top() and .bottom() offsets during the dispense() command to control surface tension and avoid cross-contamination when “painting” with dyes.

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

I want to make hourglass pattern and also ı want to add colors my pattern so ı used sfGFP and mRFP1 bacterias together.

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.

Post-Lab Questions:

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

Paper Title: Opentrons for automated and high-throughput viscometry (Soh et al., 2025)

https://www.sciencedirect.com/org/science/article/pii/S2635098X25000348

We always think that opentrons only transition liquid form but this article that completeley flips the script.Thay achieved that ınstead of just using the robot to prep samples, they actually turned the robot itself into the measuring tool. In bioengineering, measuring how hard to a liquid is because of the its viscosity. You need expensive rheometers, and doing it manually for hundreds of hydrogel or protein samples takes forever.These researchers had a great idea that why not use the physics of the pipette itself? They realized that the speed at which a liquid enters or leaves a pipette tip tells you exactly how viscous it is. They hacked their Opentrons OT-2 by clearing a spot on the deck for a high-precision scale. As the robot dispensed the liquid, they tracked the weight changes every 0.2 seconds. Then, they fed all that timing and weight data into a machine-learning model. So we didn’t have to do anything that much. Basically,the robot wasn’t just “moving” stuff anymore; it was “sensing” it. It could prep a brand-new biomaterial mix and immediately tell you its physical properties without a human ever touching a beaker.Therefore, ıt’s a perfect example of how automation isn’t just about saving time—it’s about doing science in a way that’s literally impossible for a human to do by hand.

2.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 final project, I’m tackling a pretty complex challenge: developing a synthetic promoter that can sense when a “hallucination state” is occurring in a cell and then automatically suppress specific schizophrenia risk genes. Since I need to test a huge library of different promoter sequences to see which one reacts most precisely, doing this by hand would be a nightmare. This is where the Opentrons comes in.

So what is the plan?I want to use the robot as the “brain” of my high-throughput screening. Instead of manually pipetting 96 different versions of a promoter, I’ll program the Opentrons to handle the Golden Gate Assembly. The robot will mix the DNA parts, run the transformation into cells, and—most importantly—handle the dynamic dosing. I want to simulate “hallucination signals” by adding specific chemical inducers at different concentrations across a plate to see exactly at what threshold my synthetic promoter “turns on” the suppression. Also ı am thinking other tools to using for my project. For example, -Custom Labware: I’m thinking about 3D printing a custom rack to hold my specific microfuge tubes on the Opentrons deck so I don’t waste any of my expensive synthetic DNA.

-Ginkgo Nebula: Since designing synthetic promoters involves a lot of trial and error, I plan to use Ginkgo Nebula to synthesize the most promising DNA sequences I find. I’ll send my digital designs to them, get the DNA back, and then use the Opentrons to run the final verification experiments locally.

By using automation, I’m not just “doing an experiment”—I’m building a system that can find the perfect genetic switch for schizophrenia much faster and more accurately than I ever could manually.

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project