Week 1 HW: Principles and Practices

I am an artist interested in growing and using the following bacterial pigments:

• Serratia marcescens (red/pink)
• Bacillus species (orange/yellow)
• Environmental isolates from soil

Firstly, in growing them myself (which I am new to), as well as mechanotransduction experiments with sounds and vibrations; having the bacteria’s pigment respond to sounds and vibrations. Connecting mechanosensitive channels to pigment gene expression.

If possible, explore the possibilities of UV-protective, antimicrobial, colored bioplastic material or packaging using bacterial pigments in a seaweed matrix, and build on what has been done to amplify natural pigment production through gene cloning. Combining bacterial pigments directly with seaweed‑based bioplastic matrices (like carrageenan or alginate) for UV‑protection and antimicrobial function.

Further experiments,looking at creating hybrid strains.

Bio-Art Ethics & Policy Framework

I looked at governance and policy from an artist’s, non-science public, point of view, as well as the fact that in my usage case, the bacterial samples may be presented to the public in a gallery setting.

Primary Goal: Ensure Safe & Responsible Use of Engineered Organisms in Artistic Practice

Secondary Goal: Maintain Public Trust in Bio-Art While Enabling Innovation

Three Governance Actions

Action 1: Tiered Institutional Approval System Highlighting the roles of Biosafety Committees, Art Institutions, and Artists.Actor 1 (Biosafety Committees),Actor 2 (Art Institutions),Actor 3 (Artists).

Action 2: Open-Source Documentation Standard & Community Vetting Outlining the purpose of shared safety standards and the involvement of Artists, Scientists, and the Community. Purpose: Currently, bio-art practitioners work in isolation without shared safety standards, Actor 1 (Artists & Scientists), Actor 2 (Community.

Action 3: Technical Safety Infrastructure & Insurance Product Addressing artist liability through the collaboration of Engineers, Certification Bodies, and Artists.Purpose: Currently, artists mostly bear full liability for bio-art installations. Actor 1 (Engineers/Companies), Actor 2 (Certification Bodies), Actor 3 (artist)

Risk Assessment Matrix

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References: Figure 1 & 2: Governance & Bio-Art Risk Assessment Matrix. Generated by Manus AI (2026) based on the author’s framework.

Week 2 HW: DNA Read, Write, and Edit

Part 1

Benchling & In-silico Gel Art

To be continued.

Part 2

No wet lab access

Part 3

DNA Design Challenge

Choose Protein

I chose the amino acid sequence of VioC - Chromobacterium violaceum for Violacein pigment.

I will reverse translate and codon optimize to amplify pigment production and thus its antimicrobial, UV-resistant properties.

sp|Q9S3U9|VIOC_CHRVO Violacein synthase OS=Chromobacterium violaceum (strain ATCC 12472 / DSM 30191 / JCM 1249 / CCUG 213 / NBRC 12614 / NCIMB 9131 / NCTC 9757 / MK) OX=243365 GN=vioC PE=1 SV=2 MKRAIIVGGGLAGGLTAIYLAKRGYEVHVVEKRGDPLRDLSSYVDVVSSRAIGVSMTVRG IKSVLAAGIPRAELDACGEPIVAMAFSVGGQYRMRELKPLEDFRPLSLNRAAFQKLLNKY ANLAGVRYYFEHKCLDVDLDGKSVLIQGKDGQPQRLQGDMIIGADGAHSAVRQAMQSGLR RFEFQQTFFRHGYKTLVLPDAQALGYRKDTLYFFGMDSGGLFAGRAATIPDGSVSIAVCL PYSGSPSLTTTDEPTMRAFFDRYFGGLPRDARDEMLRQFLAKPSNDLINVRSSTFHYKGN VLLLGDAAHATAPFLGQGMNMALEDARTFVELLDRHQGDQDKAFPEFTELRKVQADAMQD MARANYDVLSCSNPIFFMRARYTRYMHSKFPGLYPPDMAEKLYFTSEPYDRLQQIQRKQN VWYKIGRVN

Reverse translate

sp|Q9S3U9|VIOC_CHRVO Violacein synthase OS=Chromobacterium violaceum (strain ATCC 12472 / DSM 30191 / JCM 1249 / CCUG 213 / NBRC 12614 / NCIMB 9131 / NCTC 9757 / MK) OX=243365 GN=vioC PE=1 SV=2 ATGAAGCGAGCGATTATTGTCGGGGGGGGTTTAGCTGGAGGTCTAACTGCGATATACTTGGCTAAACGTGGATACGAGGT ACATGTGGTCGAGAAACGGGGCGACCCACTCAGGGACCTGTCTAGCTATGTTGATGTGGTTTCATCACGCGCAATCGGGG TCAGCATGACTGTAAGAGGCATCAAGTCAGTTTTAGCGGCCGGTATCCCCCGAGCTGAATTAGATGCCTGTGGTGAGCCA ATAGTTGCCATGGCGTTTTCCGTCGGGGGACAATATCGCATGCGGGAACTTAAACCACTCGAAGACTTCCGACCGCTTTC GCTTAACCGAGCAGCCTTCCAGAAGCTTTTGAACAAGTACGCAAACCTTGCCGGCGTACGGTACTATTTCGAACATAAAT GCCTGGATGTAGACCTGGATGGGAAATCCGTACTGATCCAAGGGAAGGACGGACAGCCGCAGCGACTTCAAGGAGATATG ATTATCGGCGCAGATGGGGCACACAGTGCAGTTCGCCAAGCGATGCAGTCAGGATTGCGGCGCTTTGAGTTTCAACAAAC GTTCTTTAGGCACGGGTATAAAACGCTGGTCCTACCCGACGCCCAAGCACTCGGGTATCGAAAGGACACGTTATATTTTT TTGGAATGGACAGCGGAGGGTTGTTCGCAGGCCGAGCCGCAACAATACCCGATGGTAGCGTGTCCATAGCTGTGTGTCTG CCCTACTCCGGCTCCCCCAGTTTGACAACCACAGATGAACCGACTATGCGTGCATTTTTCGACAGGTACTTTGGAGGTCT TCCACGGGATGCGAGGGACGAGATGCTTAGACAATTTTTAGCCAAGCCGTCTAATGATCTAATAAATGTGCGATCTTCAA CTTTTCATTACAAAGGTAACGTTCTGCTTTTAGGCGACGCCGCACATGCTACCGCGCCATTTTTAGGACAAGGCATGAAT ATGGCGTTAGAGGATGCGCGAACATTCGTAGAATTACTTGATCGCCACCAAGGCGATCAGGATAAAGCGTTTCCAGAGTT CACGGAGCTTAGAAAGGTGCAAGCGGACGCGATGCAAGATATGGCCCGGGCGAATTACGATGTTCTATCTTGCTCCAACC CGATTTTTTTTATGAGGGCGCGGTATACCCGCTACATGCACAGCAAGTTTCCGGGACTGTACCCGCCGGATATGGCCGAG AAACTGTATTTCACGTCAGAGCCGTACGATCGATTACAACAAATACAGCGCAAGCAAAACGTATGGTACAAGATAGGCAG AGTTAAT

Codon Optimize

https://en.vectorbuilder.com/tool/codon-optimization/b93b7790-7536-4d9b-a72e-02d62c3944e8.html

Next Next steps would be to embed into a seaweed matrix.

Part 4

Prepare a Twist DNA Synthesis Order

After reading more on living materials, bacterial pigments, and connecting it to my interest in light and circadian rhythms, I wanted to explore how to make a simple biological system that expresses anti-microbial or other elements only when needed, rather than all the time. So building a ’temporal’ antimicrobial system that produces a bacteria-killing peptide Magainin on a 24-hour schedule controlled by a circadian promoter RpaA. I started with just learning how to design the Magainin peptide and annotate properly.

Benchling

Twist

REF:

1. Fang et al. (2025) - “Mechanism and reconstitution of circadian transcription in cyanobacteria”
2. Salis et al. (2009) - “Automated Design of Synthetic Ribosome Binding Sites”
3. Westerhoff et al. (2008) - “Structure, Membrane Orientation, Mechanism, and Function of Pexiganan (Magainin derivative)”

Part 5

DNA Read/Write/Edit

5.1 DNA Read (Sequencing)

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

I would sequence my pLight-Circadian-Color plasmid (which contains the RpaA gene from Synechococcus elongatus, an anthocyanin color gene, and a light sensor) to check that it was made correctly before testing if bacteria with this plasmid change color on a 24-hour schedule when exposed to light.

5.1(ii) What sequencing technology would you use?

I would use Sanger sequencing because it’s most accurate.

5.2 DNA Write (Synthesis)

5.2(i) What DNA would you synthesize and why?

I would synthesize my yet-to-be-completed pLight-Circadian-Color plasmid containing three genes (RpaA from Synechococcus elongatus for timing, anthocyanin for color, light sensor for activation) to test if bacteria can change color on a 24-hour schedule in response to light.

5.3 DNA Edit

5.3(i) What DNA would you edit and why?

After I verify the plasmid works, I would edit the RpaA promoter to make it stronger so the color changes are brighter and more noticeable on a 24-hour schedule.

5.3(ii) What editing technology would you use?

I would use site-directed mutagenesis to make small changes to the RpaA promoter because it’s precise.

Week 3 HW: Project Ideas

#DRAFT FINAL PROJECT IDEAS

Week 4 HW: Protein Design Part 1

Part A: Conceptual Questions (9)

1. How many molecules of amino acids do you take with a piece of 500g of meat? (avg amino acid ~100 Daltons)
2. Why do humans eat beef but do not become a cow, eat fish but do not become fish?
3. Why are there only 20 natural amino acids?
4. Can you make other non-natural amino acids? Design some new amino acids.
5. Where did amino acids come from before enzymes that make them, and before life started?
6. If you make an α-helix using D-amino acids, what handedness (right or left) would you expect?
7. Can you discover additional helices in proteins?
8. Why are most molecular helices right-handed?
9. Why do β-sheets tend to aggregate?
10. What is the driving force for β-sheet aggregation?
11. Why do many amyloid diseases form β-sheets?
12. Can you use amyloid β-sheets as materials?
13. Design a β-sheet motif that forms a well-ordered structure.

Part B: Protein Analysis and Visualization

1. Briefly describe the protein you selected and why you selected it.
2. Identify the amino acid sequence of your protein.
3. How long is it? What is the most frequent amino acid?
4. How many protein sequence homologs are there? (Use UniProt BLAST)
5. Does your protein belong to any protein family?
6. Identify the structure page of your protein in RCSB.
7. When was the structure solved? Is it good quality? (Resolution: smaller = better, aim < 2.70 Å)
8. Are there any other molecules in the solved structure apart from protein?
9. Does your protein belong to any structure classification family?
10. Open the structure in 3D visualization software (PyMol):
    • Visualize as “cartoon”, “ribbon”, and “ball and stick”
    • Color by secondary structure — more helices or sheets?
    • Color by residue type — hydrophobic vs hydrophilic distribution?
    • Visualize the surface — any binding pockets?

Part C: Using ML-Based Protein Design Tools

C1. Protein Language Modeling

Deep Mutational Scans

• Use ESM2 to generate an unsupervised deep mutational scan based on language model likelihoods
• Can you explain any particular pattern? (choose a residue and mutation that stands out)
• (Bonus) Compare language model predictions to experimental scans

Latent Space Analysis

• Embed proteins in reduced dimensionality using the provided sequence dataset
• Analyze neighborhoods — do they approximate similar proteins?
• Place your protein in the map and explain its position and similarity to neighbors

C2. Protein Folding

• Fold your protein with ESMFold — do predicted coordinates match the original structure?
• Try mutations, then larger sequence changes — is the structure resilient?

C3. Protein Generation

• Use ProteinMPNN to inverse-fold your protein backbone and propose sequence candidates
• Analyze predicted sequence probabilities vs the original sequence
• Input the new sequence into ESMFold and compare the predicted structure to original

Part D: Group Brainstorm on Bacteriophage Engineering

Week 5 HW: Protein Design Part ii

Week 1 Lab: Pipetting

Week 2 Lab: Gel Art

Week 3 Lab: Opentrons

Python Script for Opentrons Artwork

Since I am not present to interact directly with the Opentrons output, I thought about why I would want to pipette an image and what that image should represent and decided to use Ndebele bead patterns as inspiration.

Ndebele bead patterns have a very specific geometric logic. They are built on a grid of “bead units” arranged in bold, angular, symmetric designs. The traditional South Ndebele aesthetic uses high-contrast colors in step-like diagonal and horizontal bands, often with thick outlines and mirrored symmetry.

They are also studied as Ethno mathematics, which often promotes a more humanistic and inclusive perspective on mathematics, focusing on how different groups manage, understand, and navigate their reality.

I found it interesting to bring the mathematical and social aspects of this indigenous knowledge to the biochemical level, as this layering of meaning creates interesting avenues for reflection on various levels.

Example of Ndebele paintings and beadwork:

Python Visuals & Scripts Ex.

I am not a coder, but playing around with the example scripts, I ended up using Claude to vibe-code the desired patterns and position. It required some debugging and made various output versions.

Although the co-lab script runs without error, I am not sure if this will work on Opentrons.

EARLY VERSIONS BEFORE KNOWING COLOUR AVAILABILITY

Post Lab Homework

Published Paper

A directly relevant paper is Fang et al. (2025) in Nature Communications, which demonstrates circadian-gated gene expression circuits in bacteria, using automated temporal sampling to characterize rhythmic protein output over 24-hour cycles. This paper is not a peripheral reference; it is one of the primary foundational sources for my final project concept and is already cited in my main project documentation. The automation approach used to verify rhythmic expression in that work is precisely what I intend to replicate and extend with the Opentrons platform.

What I Intend to Automate

My project proposes a bacterial AND gate where the antimicrobial peptide Magainin is only expressed when two conditions are simultaneously true: the circadian regulator RpaA is active, and a pathogen signal is present. The core experimental challenge is verifying this gate actually works as designed, which requires sampling bacterial expression levels repeatedly across a full 24-hour cycle, under multiple conditions, without human error or gaps overnight. This is the automation task.

The Opentrons OT-2 would run an unattended 24-hour sampling protocol across three experimental conditions:

• RpaA active + pathogen signal present (AND gate should trigger)
• RpaA active + no pathogen signal (gate should stay silent)
• RpaA inactive + pathogen signal present (gate should stay silent)

At each 2-hour timepoint, the robot samples each culture well, transfers to a measurement plate for fluorescence reading, and replaces the sampled volume with fresh media to keep cultures alive. This builds a full temporal expression profile across all three conditions without any overnight manual intervention.

I would use Claude for the coding and guidance in the technical parts of this.

Why This Automation Matters

The AND gate only has meaning if you can show it is silent when it should be silent and active only at the right circadian phase with the right pathogen or other signal. That requires clean data across all three conditions at every 2-hour window through the night. Manual pipetting at 2am introduces the exact inconsistency that would make the rhythmic signal unreadable. The Opentrons removes that variable entirely.

Future Extensions

If access to Ginkgo Nebula becomes available, the next step would be submitting the AND gate genetic construct for scaled fermentation and characterization; using Nebula’s high-throughput infrastructure to screen circuit variants with different RpaA promoter strengths or pathogen-sensing thresholds, generating the kind of combinatorial data that would take months on a single benchtop robot.

References

• Fang et al. (2025) — Nature Communications
• UCSD (2024) — “Researchers Rebuild Microscopic Circadian Clock”
• Bilska et al. (2021) — Experimental Dermatology
• Claude Anthropic was used to check that my understanding of the intended scientific goal is using the correct terminology

Week 4 Lab: Protein Part I

Week 5 Lab: Protein Part II

Week 6 Lab: Gibson Assembly

Week 7 Lab: Neuromorphic Circuits

Individual Final Project

Group Final Project