Week 1 HW: Principles and Practices

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

I’m curious about cellular agriculture and lab-grown meat. in this project im proposing to develop a living, light-activated scaffold that produces and spatially distributes oxygen inside a growing tissue. this is one of the needed early steps toward making a thick, steak-like cut rather than thin sheets or ground meat. Today, animal cells grown for food struggle beyond a few millimeters because oxygen and nutrients don’t diffuse well. the interior becomes starved and dies unless you add complex and expensive hardware. My project reframes that bottleneck as a biological engineering opportunity: a biofabricated “breathing” matrix that couples geometry + metabolism so that illumination drives localized oxygen generation and makes it visible and tunable. In this course’s context it would be explored as a living installation: a translucent scaffold whose oxygen field can be visualized in real time under light/dark cycles, producing both data and an intuitive, aesthetic demonstration of how engineered living materials might reduce reliance on expensive hardware in future cultivated-meat systems.

2. 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.

Governance policy goal #1: ensuring Biosafety and non-malfeasance

Make sure the system can’t cause harm to people, ecosystems, or lab staff through accidental release, contamination, or unsafe handling.

  • Making sure every engineered organism used in the project is not viable outside of the controlled lab conditions.
  • Contamination monitoring and incident reporting standards for all project related activities in the wet lab.
  • Use ‘Low Risk’ Chassis Organisms and avoid incorporating traits that increase survivability of harmful actions.

Governance policy goal #2: maximize public benefit

directing this tool toward clear societal value—lowering barriers to safer, more resource-efficient cellular agriculture research and accelerating pathways to scalable cultivated meat.

  • Define ‘Constructive Use’ criteria and require study to explicitly show qualitative improvement over one of the following criteria : lower resource use, improving oxygen diffusion limits, reducing complexity of tissue cultivation, reducing cost of tissue cultivation.
  • Encourage standardized open-source documentation for non-sensitive aspects like negative results and measurement methods.

Governance policy goal #3: promote equity & autonomy

Ensure this tool’s benefits are broadly shared rather than concentrated, and that people retain meaningful choice and informed consent.

  • cultural and livelihood impacts: include early stakeholder perspectives (food cultures, labor/farming communities) to reduce the risk that “technical success” drives social harm or displacement.
  • if such a risk is assesed as high, co-develope a slow transition plan.

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

Action 1: Project specified containnment regime

Purpose: Replace generic lab norms with a project-specific containment regime so accidental release and unsafe handling are structurally less likely.

Design: A mandatory SOP covering labeling, storage, transport, and validated inactivation/disposal for every culture/run. chain-of-custody log for strains and materials.

Assumptions: Containment does not undermine biological performance.

Risks: Failure - checkbox compliance or incomplete logs, resulting in bad lab norms and culture. Success risk - issue of a compliance-overhead that will evemtually become a barrier for smaller teams unless tooling/templates reduce burden.

Action 2: Pre-registered public-benefit targets

Purpose: Ensure the work advances constructive uses by tying it to explicit, testable public-benefit goals rather than novelty.

Design: Before experiments, declare 1–2 primary public-benefit targets (reduced process complexity/reduced resource use) and define how they will be evaluated. after, conduct a brief impact evaluation including tradeoffs and limits.

Assumptions: Labs track real constraints; teams won’t optimize for non-beneficial metrics.

Risks: Failure - metric gaming or proxies that don’t translate. Success risk - the encourageing or incentivizing a ‘follower’ culture where the first metrics to have consenseus are repeated as defaults.

Action 3: stakeholder review & benefit-sharing

Purpose: Ensure “success” does not override cultural values, informed consent, or fairness in who benefits from the technology.

Design: A stakeholder checkpoint with at least two external perspectives (labor/farming and food culture/ethics) plus explicit benefit-sharing commitments (open standards, non-exclusive licensing norms, accessible documentation, and clear communication of uncertainties to support informed choice).

Assumptions: Early stakeholder engagement surfaces blind spots. benefit-sharing commitments foster trust between community and research/venture.

Risks: Failure risk -tokenism or performative consultation. Success risk - added friction slows iteration—but that is an intentional tradeoff to protect autonomy and prevent concentrated capture.

Action 4: responsible release of documentation

Purpose: Maximize reproducibility and shared learning while reducing misuse risk.

Design: Two publication layers: Open (concept, results, non-sensitive documentation) and Restricted (step-by-step replication details and other speceficities). an external mechanism decides classification of research documents. access to the Restricted layer will be granted by same mechanism.

Assumptions: Sensitive details can be identified; restriction won’t destroy scientific value.

Risks: Failure risk - misassuming the layer definitions as too open (misuse) or too closed (no benefit). Success risk - restricted knowledge becomes a chokepoint that concentrates power and limits equitable access.

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

Policy_Scoring Policy_Scoring

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 a combined governance package aimed at two audiences: First would be an institutional biosafety governance body (such as an IBC) and the second would focus on field-facing actors (research funders, journals, and cultivated-meat research networks). The core package is Action 1 (Containment Regime), Action 2 (Pre-registered public-benefit targets), and Action 3 (Stakeholder review & benefit sharing). I would start with Action 1 because it most directly reduces non-malfeasance risks (accidental release, unsafe handling, or unmanaged contamination). Action 2 ensures the project is oriented toward constructive use by requiring explicit evidence of benefit rather than novelty alone. Action 3 is prioritized early because success in this domain can create downstream social impacts—such as concentration of ownership or displacement pressures—so stakeholder input and benefit-sharing commitments are necessary to protect autonomy and legitimacy.

The primary trade-off is speed and ease of iteration vs. safety, accountability, and equity. These actions add overhead (documentation, evaluation, review), and if implemented too rigidly they could become barriers for smaller teams. the assumption is that this can be mitigated with lightweight templates and clear defaults. A key uncertainty is whether lab-scale proxies for oxygen distribution translate to real thick-tissue outcomes. Action 2 should make a clear and defined outline through central—pre-registering of what counts as improvement, to structured and goal-oriented claims rather than post-hoc storytelling. Overall, this prioritized set aims to make the project safe by default, oriented toward public benefit, and socially accountable if it succeeds.

References

Prof. Jacobson’s Questions:

  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?

Polymerase makes about 1 error per 106 bases. The human genome is about 3.2×109 bp, so a genome-length copy would imply roughly ~3,200 errors. Biology closes that gap by layering proofreading and post-replication mismatch repair on top of polymerase.

  1. 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?

Because many amino acids have multiple equivalent codons, the number of possible DNA sequences encoding the same protein is huge. In practice, many variants fail because the codon choice will change translation efficiency and because sequence composition changes mRNA structure.

Dr. LeProust’s Questions:

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

The most common method is solid-phase phosphoramidite chemical synthesis. It builds DNA one nucleotide at a time on a solid support through repeated cycles (coupling, capping, oxidation, deblock).

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

Because each added base requires another chemical cycle, small inefficiencies and side reactions add-up over hundreds of cycles.

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

A 2000 bp gene would require ~2000 sequential synthesis cycles, making correct full-length yield very low because errors and truncations will become significant along the process.

Prof. Church’s Question:

Using Google & Prof. Church’s slide #4 : What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

The EAAs in all animals are Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, and Valine. To my understanding ‘The Lysine Contingency’ was a strategy in the ‘Jurassic Park’ fiction implemented by Henry Wu to disable dinosaurs’ ability to create Lysine by themselves, thus forcing them to obtain it through supplements provided by the park, or die. Since I now know no known-animal has the ability to self-produce the EAA Lysine, this renders as complete nonsense - because the dinosaurs did not have the ability to create the Lysine in the first place. The concept of a kill-switch however, still stands valid as a bio-safety measure.

References: