Week 1 HW: Principles and Practices

The halfpipe of Doom- How to grow good?

For the first weeks lecture we had an introduction to the fundamental principles of synthetic biology and the HTGAA program. The focus of the lecture was on the governance and ethics of synthetic biology. David S. Kong discussed the balance between decentralized and centralized synBio development and the importance of thrust (something we are lacking these days). As a global community we have largely agreed to certain rules (e.g. bioweapon treaty 1975) however emerging synBio technologies also allow a much broader audience to participate in the development (e.g. community labs/ biohackers) that might not necessary always align with large governmental policies. He draws the parallel to how the early governance of the internet have allowed for a decentralized scaling that have contributed to an increased “computer literacy”. This might allow us to make better (although not perfect) personal decisions for how to use this new technology. Coming from a background of community focused biolab practice this was an interesting topic and made me think of the importance for a global bio-literacy. It also got me to think about the importance to apply these principals in a simple enough way that it doesn’t stifle participation.

Questions that I tried to include in my homework:

1. Describe a biological engineering application

Programmable colors for bacterial cellulose production

The textile dyeing industry is a major source of chemical pollution and water use. Coloration of bacterial cellulose (BC) can also be technically challenging because pigments often diffuse slowly into the material’s dense nanofibrillar network, making post-growth dyeing difficult and time consuming. This project proposes a bioengineering approach to generate color in situ during BC growth, eliminating conventional dyeing steps.

TerraPods

Prior work demonstrates the feasibility of embedding pigmentation into BC production. Walker et al.(2025) ¹ engineered the cellulose-producing bacterium Komagataeibacter rhaeticus to generate melanin during BC growth, producing pigmented material. Zhou et al. (2025) ² demonstrated a “one-pot” co-culture strategy coupling BC production by Komagataeibacter xylinus with pigments synthesised in engineered E. coli, enabling a broader palette by combining violacein derivatives (green/blue/navy/purple) and carotenoids (red/orange/yellow).

Zhou et al. (2025)

Building on these studies, the core concept here is light-patterned control of pigment production during BC formation. A cellulose-forming culture generates the sheet while a pigment-producing bacteria is engineered to be light-responsive, so that pigmentation occurs in illuminated regions. Patterned illumination via projection enables spatial control of coloration. Furthermore this technique would also enable varying projected patterns across growth phases that could yield multi-layer visual effects, (e.g. moiré-like effects).

Walker et al.(2025)

Drawing from my previous experiences on working in various community biolab the project is framed as a distributed biofabrication platform for community labs, which creates governance questions around biosafety practice in a decentralized settings, concider the relative complex technique I was for this excersice imagining a centralized organization providing the framework and digital infrastructure for the community labs to safetly experiment with the protocol. Although consumer product are less ethically complicated then for example medicine or bioweapon their came up important questions concerning consumer/skin-contact safety, environmental release and waste handling, and norms for responsible dissemination of methods and bacteria strains.

2. governance/policy goals

                CENTRAL PLATFORM / ORG
     (protocol repo + training + registry + reporting)
            |           |               |
     SOP minimums   pigment safety   open hardware stack
     (Option 1)      (Option 2)          (Option 3)
            |           |               |
            +-----------+---------------+
                        |
        -----------------------------------------
        |                  |                   |
   Community Lab A     Community Lab B     Community Lab C...
 (local biosafety)   (local biosafety)   (local biosafety)
   - containment        - containment       - containment
   - waste handling     - waste handling    - waste handling
   - incident reports   - incident reports  - incident reports
   - minimal tests + labeling (skin-contact, leaching, etc.)
                        |
  Local authorities / partners / funders
  (disposal rules, validation support, incentives)

Actors: Community labs and networks, open-hardware designers, academic partners, funders, and (optionally) insurers.

A. Biosecurity

A1: Reduce risk of malicious repurposing of organisms, materials, or protocols.
A2: Improve traceability and incident reporting to support response.

B. Lab safety

B1: Standardize safe practices (training, containment, waste handling) across labs.
B2: Establish clear response procedures for spills, exposures, and contamination.

C. Environmental protection

C1: Prevent release of organisms or harmful pigments/byproducts.
C2: Enable remediation and corrective action after incidents.

D1: Ensure skin-contact safety (low leaching, low irritation risk, stability).
D2: Maintain low barrier access; avoid governance that excludes low-resource labs.
D3: Require transparency and avoid misleading sustainability claims.

E. Feasibility and innovation

E1: Keep requirements simple for community labs.
E2: Avoid unnecessary friction to legitimate research and education.

3. Governance actions (three options)

➡️ Option 1 — Network baseline: certification + SOP minimums

Purpose: Reduce variability in biosafety practice across distributed labs.

Design: A lightweight participation standard for labs using the platform including training checklist; Standard operating procedure (SOP) templates for handling, contamination response, waste logs and periodic documentation checks.

Assumptions: Labs will opt in if benefits are tangible and the extra admistrive work is not to burdensome.

Risks: Uneven enforcement; exclusion of under-resourced labs if standards become to complex.

➡️ Option 2 — Pigment/material safety standard: whitelist + minimal testing + labeling

Purpose: Address the most important downstream risk for the product: skin-contact, pigment safety and environmental implications.

Design: Shared “allowable pigment classes” (whitelist) plus minimum evidence requirements for testing (basic leach, washfastness, disposal guidance, documentation of lab status). Standard labeling for intended use and safety-relevant claims.

Assumptions: Low-cost testing tools or institutional partners are available; whitelist stays current and not to restrictive.

Risks: The process to complex and hindering community engagement, or weak tests gives unreliable results, slowed innovation if the whitelist narrows too far.

➡️ Option 3 — Open-source hardware standards for safe, distributed BC biofabrication

Purpose: Reduce reliance on expensive proprietary equipment while lowering barriers to participation without lowering safety. The goal is to make safe practice easier by default through standardized, well-documented hardware and workflows suitable for community labs.

Design: an open-source “reference stack” that includes:

Validated hardware designs for core needs (e.g., enclosed growth modules with spill containment, filtered airflow concepts, light/projection enclosures to reduce eye/UV exposure, basic sensing/logging for temperature/pH proxies where appropriate).
A documentation package: build BOMs with substitutions, maintenance/calibration checklists, cleaning/decon compatibility notes, and safety labels.
Inter-lab benchmarking: common test artifacts and reporting templates so labs can compare performance and identify failure modes early.

Assumptions:

Standardizing equipment and documentation will reduce accidents and variability more effectively than rules alone.
Community labs have enough fabrication capacity (or partner access) to build/maintain hardware.
A shared reference design can remain adaptable across different local constraints.

Risk:

Hardware reliability varies; incomplete documentation leads to unsafe modifications; lack of maintenance causes drift in performance.
Lowered barriers increase scale of adoption faster than training capacity; designs are copied without safety context; fragmentation into many forks undermines standardization.

4. Score

Does the option:	Option 1	Option 2	Option 3
Enhance Biosecurity
• By preventing incidents	1	2	2
• By helping respond	1	2	2
Foster Lab Safety
• By preventing incident	1	2	1
• By helping respond	1	2	1
Protect the environment
• By preventing incidents	2	1	2
• By helping respond	2	2	2
Other considerations
• Minimizing costs and burdens to stakeholders	2	3	1
• Feasibility in community labs?	1	2	1
• Not impede research	2	2	1
• Promote constructive applications	1	1	1

5. Prioritization and recommendation

I would prioritize Option 1 + Option 2 as the baseline governance package, with Option 3 as a longer-term technical pathway. Option 1 provides uniform safety culture and response capacity across labs; Option 2 directly governs consumer-contact risks and environmental externalities specific to pigment-enabled textiles. Option 3 is desirable for uniformed implementation of option 1 and 2 in a community lab setting.

Primary audiences: community lab networks and lab leads (implementation), funders/partners, and local safety/environment authorities (alignment on waste and disposal practices).

ChatGBT 5.2 was used for brainstorming bioengineering ideas for BC production in a community based setting

Prompt1

I have this homework for my new How to grow almost anything: To start with I need to come up with a bioengineering project that suits this class. I am thinking about different ways that I can use my current work maybe on bacterial cellulose production for material production would it be possible to use syn bio to improve material production for fabric development in fashion. and decentrialised manufacturing and design. could we start with coming up with 10 ideas that could be interesting for this homework focus on BC but could also be other materials. after that is finished we can think about the legal framework. here is the class: + the homework guidlines!

Aswell as searching for academic literature

Prompt2

do you have any good academic articles for referencing this project around the topics: engineering bacteria to produce pigment when exposed to light, insitu pigmentation of BC, community lab governance structure?!

and correct spelling error and double checking if I understood the research correctly

Prompt3

check this improved text and restructure, improve when needed also mark out if their is something in the text that I missunderstod from the research articles. Highlight any changes that you make to the text!

and to make the code for the governance chart:

Prompt4

can you draw a map of this governance structure: Drawing from my previous experiences on working in various community biolab the project is framed as a distributed biofabrication platform for community labs, which creates governance questions around biosafety practice in a decentralized settings, concider the relative complex technique I was for this excersice imagining a centralized organization providing the framework and digital infrastructure for the community labs to safetly experiment with the protocol. Although consumer product are less ethically complicated then for example medicine or bioweapon their came up important questions concerning consumer/skin-contact safety, environmental release and waste handling, and norms for responsible dissemination of methods and bacteria strains. this is the full text: https://pages.htgaa.org/2026a/alve-lagercrantz/homework/week-01-hw-principles-and-practices/index.html

It was also used for debugging some of the problems that I had with the website build, I am not including those prompts here…

Homework Questions from Professor Jacobson

Jacobson

Error rate of (proofreading) DNA polymerase: about 1 error per 10⁶ bases added (≈10⁻⁶). Human genome length (diploid not specified on slide; genome size shown): about 3.2 Gbp ≈ 3.2×10⁹ base pairs. you’d expect roughly 3.2×10⁹ / 10⁶ ≈ 3.2×10³ ≈ 3,200 misincorporations per genome copy.

Proofreading built into polymerase via a 3′→5′ exonuclease that removes misincorporated bases. Post-replication mismatch repair systems (the slides show the MutS/MutL/MutH pathway) that find mismatches and replace the wrong stretch. Beyond that (general bio context): other DNA repair pathways and cellular checkpoints reduce which errors persist as heritable mutations.

The genetic code is triplet-based (codons like AUG/GUU/GGA encode amino acids). The slide gives average human protein coding length ≈ 1036 bp. That’s about 1036/3 ≈ 345 codons (≈345 amino acids, ignoring stop/start details). Because most amino acids have multiple synonymous codons, the number of distinct DNA sequences that can encode the same protein is roughly: “Rule of thumb” average ~3 codons per amino acid ⇒ ~3^{345 ≈ 4×10}164 possible coding sequences. Using 61 sense codons / 20 amino acids ≈ 3.05 average degeneracy ⇒ ~(3.05)^{345 ≈ 1×10}167. So: on the order of 10^165–10167 different DNA sequences could encode an “average” human protein sequence. Why don’t all those synonymous options work in real cells? (practical constraints) nucleotide sequence affects behavior even when the amino-acid sequence is unchanged: mRNA secondary structure / folding changes with GC% and sequence, affecting translation and stability. RNA cleavage / degradation sensitivity depends on sequence/structure (RNase III cleavage rules shown). And in practice (common synthetic biology reasons, consistent with the above): Codon-usage bias & tRNA availability in the host: “rare” codons can slow or stall translation, reduce yield, or increase misfolding. Unwanted sequence motifs: accidental promoters/terminators, cryptic splice sites (eukaryotes), repeats/homopolymers, extreme GC or AT stretches that break synthesis/PCR or trigger regulation.

Homework Questions from Dr. LeProust:

LeProust

Solid-phase phosphoramidite chemical synthesis (automated DNA synthesizers running repeated deprotection/coupling/capping/oxidation-type cycles). 2. Because chemical synthesis is “open loop” (no proofreading), and errors + incomplete coupling accumulate every base-addition cycle. The slide gives a chemical synthesis error rate ~1:10² per base addition. That means the fraction of perfect molecules drops roughly exponentially with length (e.g., if ~1% error per step, the chance of an error-free 200-mer is about (0.99)200 ≈ 0.13 (0.99) 200 ≈0.13, so most product is wrong/truncated), and purification becomes dominated by a complex mixture. 3. A 2000 bp strand would require ~2000 sequential chemical addition cycles, so with ~1% error per base (from the slide’s 1:10² figure), the probability of getting a full-length error-free molecule is ~ (0.99) 2000 ≈2×10−9(0.99) 2000≈2×10 −9—essentially none, and you’d mostly produce a huge smear of incorrect/truncated products. So instead, genes are made by assembling shorter oligos/fragments (the slides point to assembly approaches like Gibson assembly and whole-genome assembly from synthetic oligos).

Homework Question from George Church:

George Church

the protein analog of A–T / G–C complementarity in NA:NA.

Walker, K. T., Li, I. S., Keane, J., Goosens, V. J., Song, W., Lee, K.-Y., & Ellis, T. (2025). Nature Biotechnology, 43, 345–354. https://doi.org/10.1038/s41587-024-02194-3 ↩︎
Zhou, H., Lin, P., Jeong, K. J., & Lee, S. Y. (2025). Trends in Biotechnology. https://doi.org/10.1016/j.tibtech.2025.09.019 ↩︎