Week 1 HW: Principles and Practices

Biological Engineering Application

1. Description:

My idea is to develop a biosensor for heavy metal detection using engineered Escherichia coli bacteria as a chassis. Lead, cadmium, and mercury are the most problematic heavy metals, accumulating in organisms and slowly killing them. The tool would involve genetically modifying E. coli to incorporate metal-responsive genetic circuits that detect the presence of heavy metals and respond by producing an easily observable response. Right now I am considering green fluorescent protein (GFP) to be the best fit. When exposed to contaminated water, the bacteria would “light up” proportionally to the metal concentration, allowing for quick detection via a simple handheld fluorometer. Heavy metal pollution from industrial runoff, mining, and urban waste is a major global issue, leading to contaminated drinking water that causes neurological damage, kidney failure, and ecosystem disruption in affected communities. Traditional detection methods, like atomic absorption spectrometry, are expensive, lab-based, and time-consuming, often delaying response to pollution events. In contrast, biosensors are low-cost, portable, and provide real-time results, enabling faster interventions in polluted areas, such as rivers or municipal water supplies in developing regions. Iit promotes sustainable monitoring and could integrate with community science initiatives to empower local environmental stewardship.

2. Governance/Policy Goals

To ensure this biosensor contributes to an ethical future, the overarching goal is to promote responsible innovation that prioritizes non-malfeasance—preventing harm to human health, ecosystems, and society—while fostering beneficial uses. This adapts the synthetic genomics framework mentioned, emphasizing safety and security alongside equity to address potential disparities in access and impact. I break this into three specific sub-goals: Biosafety Sub-Goal: Minimize environmental and health risks from the release or unintended spread of engineered organisms. This includes preventing ecological disruption, such as engineered bacteria outcompeting native microbes or transferring genes, which could alter biodiversity in water systems. Policies should require containment strategies to ensure the biosensor is used in controlled settings without persistent environmental persistence. Biosecurity Sub-Goal: Prevent misuse or dual-use applications that could enable harm, like weaponizing metal-detection circuits for bioterrorism or creating biosensors that inadvertently aid in evading pollution regulations. This promotes secure handling of genetic designs to avoid exploitation by malicious actors, drawing on broader SynBio governance to safeguard public trust. Equity Sub-Goal: Ensure fair access and distribution of the technology, particularly for underserved communities facing water pollution. This involves policies that avoid exacerbating global inequalities, such as patent barriers limiting deployment in low-income countries, and instead encourage open-source designs or subsidies to promote inclusive benefits and autonomy in environmental monitoring.

3. Potential Governance Actions

Action 1: Mandatory Biosafety Certification for Biosensor Deployment (Regulatory Rule by Federal Regulators like the EPA or FDA)

Purpose: Currently, environmental biosensors fall under general biotech regulations like the Coordinated Framework for Biotechnology, but lack specific mandates for field-use certification. The proposed change requires pre-approval testing for ecological safety before commercial or research deployment, similar to EPA pesticide registrations, to prevent accidental harm. Design: Regulators would develop a certification process involving lab and field trials assessing containment, gene stability, and non-toxicity. Actors include federal agencies (implementers), companies/academics (applicants who must fund tests), and expert panels (approvers). Funding could come from application fees, with international harmonization via bodies like the OECD. Assumptions: Assumes regulators have sufficient expertise in SynBio and that testing protocols accurately predict real-world impacts; uncertainties include long-term ecological effects in diverse water environments. Risks of Failure & “Success”: Failure could occur if bureaucracy delays innovation, stifling biosensor adoption in pollution hotspots. “Success” might unintendedly create over-reliance on certified tools, marginalizing non-certified community innovations, or lead to complacency in broader pollution prevention.

Action 2: Grant Incentives for Equity-Focused Biosensor Development

Purpose: Today, funding for SynBio often prioritizes commercial viability over equity, leading to tech concentrated in wealthy nations. The proposal introduces grants rewarding projects with open-access designs in polluted developing regions, analogous to financial incentives for green tech under the Paris Agreement. Design: Organizations would allocate funds via competitive calls, requiring proposals to include equity metrics like tech transfer to low-income areas. Actors: Funders (providers), researchers/companies (opt-in applicants), and NGOs (implementers for distribution). Approval involves peer review emphasizing ethical impact. Assumptions: Assumes grantees will genuinely prioritize equity without gaming the system; uncertainties around measuring “equitable” outcomes in diverse cultural contexts. Risks of Failure & “Success”: Failure if funds are insufficient or misallocated, perpetuating inequities. “Success” could flood markets with subsidized tools, undercutting local innovations or creating dependency on international aid, potentially ignoring region-specific pollution needs.

Action 3: Integration of Genetic Kill Switches in Biosensor Designs

Purpose: Current SynBio designs sometimes lack built-in safeguards, risking uncontrolled spread. The change mandates researchers to embed “kill switches”—genetic circuits that deactivate the organism after use or under certain conditions (e.g., absence of a lab-provided nutrient)—inspired by 3D printing’s software locks for safety. Design: Researchers would incorporate switches during engineering, sharing protocols via open repositories like Addgene. Actors: Academics (implementers who opt-in for ethical best practices), funders (requiring it for grants), and journals (enforcing via publication guidelines). No major new funding needed, but training workshops could accelerate adoption. Assumptions: Assumes kill switches are foolproof and won’t evolve away; uncertainties include efficacy in variable field conditions like polluted water pH changes. Risks of Failure & “Success”: Failure if switches malfunction, allowing escape and ecological harm. “Success” might give a false sense of security, encouraging riskier deployments, or raise biosecurity concerns if switches are hacked for malicious persistence.

4. Score

5. The most important governance option

Based on the scoring, I would prioritize a combination of Action 2 and Action 3 (Integration of Genetic Kill Switches), with Action 1 as a supportive but secondary measure. This hybrid approach balances prevention, response, and promotion of beneficial uses without excessive burdens. Action 2 excels in equity and constructive applications, addressing the critical need to make biosensors accessible in pollution-affected developing regions, while fostering innovation through incentives rather than mandates. Action 3 complements this by providing strong biosafety and biosecurity, offering technical safeguard that integrates seamlessly into development workflows. Together, they minimize risks like environmental harm. Action 1, while effective for prevention, scores poorly on burdens, feasibility for small actors, and not impeding research, making it better as an optional escalation for high-risk commercial applications rather than a blanket requirement. Trade-offs considered: This combo trades some regulatory rigor (Action 1’s strength) for flexibility and lower costs, potentially allowing minor incidents if voluntary adoption lags, but it avoids stifling research in a field like synthetic biology where rapid iteration is key. It also prioritizes equity over uniform enforcement, which might mean uneven global standards but better real-world impact in vulnerable areas.

Homework Questions from 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?
   • Polymerase error rate: 1:10^6
   • The human genome has 4.2 billion base pairs, which means that polymerase makes 3200 errors at each celll division.
   • In order to deal with this high error rate, cells have systems made of multiple proteins that correct those errors, although they are not perfect.
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?
   • Human protein: ~1036bp –> ~345 amino acids W
   • Different codons can enconde for the same AA, but not all these sequences are equally efficcinet. Depending on the organism, a codon might be better for correctly and fast/slow enough being translated into an amino acid.

Homework Questions from Dr. LeProust:

1. What’s the most commonly used method for oligo synthesis currently?
   • The solid-phase phosphoramidite chemical synthesis
2. Why is it difficult to make oligos longer than 200nt via direct synthesis?
   • error accumulation and chemical limitations
3. Why can’t you make a 2000bp gene via direct oligo synthesis?
   • mailny due to error accumulation

Homework Question from George Church:

What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

The 10 essential amino acids that animals cannot synthesize on their own and must obtain through their diet are: Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, Valine

The “Lysine Contingency” refers to the fictional failsafe mechanism in Michael Crichton’s Jurassic Park, where resurrected dinosaurs were genetically engineered to lack the ability to produce lysine, one of these essential amino acids. The idea was that without lab-supplied lysine supplements, the dinosaurs would die, preventing them from surviving if they escaped containment. Lysine is an essential amino acid for all animals which reinforces why this contingency is fundamentally flawed as a control measure. In reality, no animal can synthesize lysine endogenously—they all rely on dietary sources like plants, insects, or meat, which are abundant in natural ecosystems. If the engineered dinosaurs escaped, they could simply consume lysine-rich foods in the wild (as they do in the story), rendering the dependency moot. It highlights a clever narrative device but poor fictional science, as it overlooks basic nutritional biology and ecology. A more effective contingency might target a non-essential amino acid or something truly unique to the lab environment.