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.

I want to develop a biological engineering application that uses directed evolution to develop super-enzyme(s) capable of converting cassava peels which are a rich, low-cost source of lignocellulosic waste into prebiotic oligosaccharides. Cassava peels contain Xylan (a type of hemicellulose) that, when broken down through alkali pretreatment and enzymatic hydrolysis, yields Xylooligosaccharides (XOS), which acts as a prebiotic by promoting the growth of beneficial gut bacteria and can be used for food and nutraceutical applications.

Nigeria is the world’s largest producer of cassava. For every ton of cassava processed, about 10-15% of the total weight is lost in the form of wet peels. Over 95% of these peels are currently wasted, often discarded in open dumpsites where they rot, produce methane, or are burnt, representing a missed opportunity for value creation within local food systems. At the same time, there is a growing global demand for prebiotic oligosaccharides, due to their role in supporting gut health, metabolic health, and immune function. Despite high local demand, Nigeria imports most functional food ingredients, including prebiotics.

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. Below is one example framework (developed in the context of synthetic genomics) you can choose to use or adapt, or you can develop your own. The example was developed to consider policy goals of ensuring safety and security, alongside other goals, like promoting constructive uses, but you could propose other goals for example, those relating to equity or autonomy.

The overaching governance goal is to ensure that enzyme-based agricultural biomass conversion technologies advance sustainable development, public health, and economic inclusion without contributing to biosafety risks, environmental harm or extractive IP practices.

Goal 1 - Biosafety and Containment That is, to prevent harm while recognizing limited biosafety infrastructure.

Sub-goals

• To ensure safe handling of engineered enzymes and host organisms in laboratories and pilot facilities.
• To avoid environmental contamination from enzyme residues or production organisms.

Goal 2 - Ethical and Regulatory Accountability To strengthen trust and legitimacy through oversight.

Sub-goals

• To align research and deployment within Nigerian biosafety laws and food safety regulations
• To prevent diversion into environmentally harmful or monopolistic practices.
• To ensure that farming communities/processors generating cassava waste are not excluded from decision-making or value creation.

Goal 3 - Industry Standards To prevent unsafe or environmentally damaging scale-ups

Sub-goals

• To establish minimum quality and safety standards for enzyme-produced prebiotics
• To prevent pollution of water bodies near cassava processing zones.

Goal 4 - Equitable IP, Data Sharing and Value Distribution To avoid repeating extractive biotechnology models

Sub-goals

• To enable local researchers and stakeholders co-own innovations

3. Next, describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”). Try to outline a mix of actions (e.g. a new requirement/rule, incentive, or technical strategy) pursued by different “actors” (e.g. academic researchers, companies, federal regulators, law enforcement, etc). Draw upon your existing knowledge and a little additional digging, and feel free to use analogies to other domains (e.g. 3D printing, drones, financial systems, etc.).

Action 1 - Biosafety by Design Purpose Nigeria’s biosafety system, overseen by the National Biosafety Management Agency (NBMA) is primarily focused on genetically modified crops, not enzyme engineering or cell-free biocatalysis. I propose enzyme-specific biosafety guidance relevant to the Nigerian context and industrial conditions.

Design

• Actors : NBMA, Universities, research institutes (FIIRO, IITA)
• Key elements:
  • Preferential use of cell-free enzyme systems or GRAS microbial hosts
  • Mandatory enzyme inactivation steps before waste disposal
  • Tiered containment standards matching laboratory capacities
  • Regulators periodically audit and validate compliance.

Assumptions:

• Enzymes pose lower risk than living GMOs but still require oversight
• Clear, practical guidelines increase compliance more than imported standards

Risks of Failure & “Success”:

• Failure - Informal or unregulated adoption bypassing safety constraints
• Success - Excessively conservative safety requirements may slow adoption or raise costs for low-resource users.

Action 2 - Bioeconomy Ethics and Community Oversight Boards Purpose To embed ethical review beyond technical biosafety, particularly in cassava producing communities.

Design

• Actors : Federal Ministry of Science, Technology & Innovation (FMSTI), universities, local governments, farmer associations.
• Mechanism:
  • Establish regional Bioeconomy Ethics Boards modelled after IRBs (Institutional Review Boards)
  • Require community consultation and benefit-sharing plans for pilot processing plants.
  • Integrate social scientists and local representatives.

Assumptions:

• Community inclusion reduces resistance and improves sustainability
• Ethical review can be localized without excessive bureaucracy.

Risks of Failure & “Success”:

• Failure - Boars lack authority or funding
• Success - Political capture or elite dominance in decision-making

Action 2 - Blockchain-Enabled DAO Based Governance Purpose: To manage enzyme IP, processing data, and revenue flows in a transparent and participatory way.

Design:

• Actors: Researchers, startups, cassava cooperatives, fintech partners.
• DAO features
  • On-chain registration of enzyme variants and performance data
  • Smart contracts governing licensing to food manufacturers and exporters.
  • Revenue-sharing mechainsms allocating tokens to researchers, processing bodies, and community development funds.

Assumptions:

• Technical knowledge about DAOs
• Nigerian fintech adoption lowers barriers to blockchain governance
• That DAO-based governance can meaningfully represent diverse stakeholders.
• DAOs can complement, not replace, national IP law.

Risks of Failure & “Success”: Failure - Digital exclusion of rural actors Success - Speculation overwhelms productive governance.

4. Next, score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals.

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. For this, you can choose one or more relevant audiences for your recommendation, which could range from the very local (e.g. to MIT leadership or Cambridge Mayoral Office) to the national (e.g. to President Biden or the head of a Federal Agency) to the international (e.g. to the United Nations Office of the Secretary-General, or the leadership of a multinational firm or industry consortia). These could also be one of the “actor” groups in your matrix.

I would prioritize a layered governance approach that combines Action 1 and Action 2 as the foundational governance infrastructure, while treating Action 3 as a longer-term experimental complement.

Biosafety by design directly reduces the likelihood of environmental or laboratory incidents without relying heavily on enforcement capacity. However it scores weakly on equity and value retention and does very little to address how value flows through the system. However, ethics and community boards addresses ethical risks that biosafety frameworks often ignore. It creates social legitimacy and accountability which are essential for long term sustainability. On the other hand, DAO based governance has high transformative potential but it is also early and highly fragile. While Nigeria’s fintech adoption makes blockchain based coordination plausible, the risks of digital exclusion, speculation and legal ambiguity means DAO governance should not be the back-bone of early stage policy development.

Trade-Offs Considered

• Speed vs. legitimacy: Action 1 enables rapid, safe deployment; Action 2 slows processes but builds trust and social license.
• Technical control vs. distributive justice: Biosafety-by-design controls risk but does not redistribute value.
• Innovation vs. institutional readiness: DAO governance promises equity but currently outpaces regulatory and social readiness.

Assumptions and Uncertainties

• Assumptions include:
  • That Nigeria’s regulatory agencies can adapt existing biosafety frameworks to enzyme engineering without major reform.
  • That community governance structures can be resourced and insulated from political capture
  • That DAO-based governance can eventually interoperate with national IP law rather than conflict with it.
• Uncertainties include:
  • How quickly informal enzyme production might scale beyond regulatory reach
  • Whether community boards will have meaningful enforcement power
  • Whether blockchain governance will remain accessible or become exclusionary over time

Reflecting on what you learned and did in class this week, outline any ethical concerns that arose, especially any that were new to you. Then propose any governance actions you think might be appropriate to address those issues. This should be included on your class page for this week.

Some of the ethical concerns that arose were malicious individuals using biotechnological innovation for harm instead of good. Although it was not new to me (movies), it was interesting to understand that it could happen in real life as well. In the Nigerian context, governance must be robust enough to prevent harm, flexible enough to scale, and intentional enough to redistribute value.

Use of AI Tools Disclosure: AI tools (ChatGPT and Gemini) were used to refine wording, improve structure, and adapt the context to the Nigeria’s governance landscape. The core ideas and ethical framing were developed independently.

References

1. Kumar, R., Næss, G., & Sørensen, M. (2024). Xylooligosaccharides from lignocellulosic biomass and their applications as nutraceuticals: a review on their production, purification, and characterization. Journal of the science of food and agriculture, 104(13), 7765–7775. https://doi.org/10.1002/jsfa.13523

Assignment (Week 2 Lecture Prep)

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? Answer Polymerase has an error rate of approximately 1 in 1,000,000 (1:10⁶). This is significantly more accurate than standard chemical synthesis methods, which have an error rate of about 1 in 100. This is massive in comparison to the length of the human genome, which consists of billions of base pairs (between 10⁹ and 10¹⁰ base pairs). This leads to a significant discrepancy between the error rate and the genome length. If the polymerase simply copied at a rate of one error per million bases, every replication of the human genome would result in thousands of errors (roughly 3,000 errors per copy). Biology deals with this discrepancy through proofreading mechanisms. The DNA polymerase enzyme contains built-in “exonuclease” activity (specifically 3’-5’ proofreading exonuclease and 5’-3’ error-correcting exonuclease). which allows the enzyme to detect when an extension error has occurred, pause to remove the incorrect nucleotide, and then resume extending the DNA strand with the correct base. Additionally, biological systems utilize repair proteins (such as MutS, MutL, and MutH) to further identify and correct mismatches that escape the polymerase’s initial proofreading.

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?

Answer The number of ways to code for a single protein is astronomical due to the redundancy of the genetic code (where multiple codons can specify the same amino acid). An average human protein requires a DNA sequence of approximately 1036 base pairs. This translates to a chain of roughly 345 amino acids. Since there are synonymous codons for most amino acids (codon redundancy), a protein of this length has a massive number of potential DNA coding sequences (roughly 3³⁴⁵, a number far exceeding the number of atoms in the universe). Most codes don’t work in practice due to several physical and biological reasons;

• RNA cleavage and degradation - The specific nucleotide sequence can create targets for cellular enzymes that destroy RNA.
• Secondary structure - The DNA sequence determines the folding of the resulting mRNA molecule. Synonymous sequences (which code for the same protein) can fold into vastly different Minimum Free Energy Secondary Structures. If an mRNA folds into a tight structure that blocks the ribosome or is unstable, translation will fail.
• Biological function and context - Research into Genomically Recoded Organisms demonstrates that altering codon usage (recoding) is not neutral; it can affect biological functions such as viral resistance and cell doubling times. This indicates that the “synonymous” codes interact differently with the cell’s machinery (e.g., tRNA availability or translation speed).

Homework Questions from Dr. LeProust

What’s the most commonly used method for oligo synthesis currently? Answer Electrochemical-based microarray developed by CombiMatrix in 2005.

Why is it difficult to make oligos longer than 200nt via direct synthesis? Answer The core problem is error accumulation from imperfect stepwise yields. This leads to compounding yield loss, domination of truncated products and accumulation of chemical damages. Beyond 150-200nt, the fraction of correct, full-length, error free oligos becomes impractically low and expensive to purify.

Why can’t you make a 2000bp gene via direct oligo synthesis? Answer Basically the same reason as the question above, separating a 2000nt full-length gene from thousands of near-length failures is practically impossible.

Homework Question from George Church

[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 10 amino acids generally considered essential for animals (meaning they must be obtained through diet) are Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, and Valine. The “Lysine Contingency” (from the movie Jurassic Park) was a method of biocontainment where the dinosaurs were supposedly genetically modified to be unable to produce Lysine, which made them dependent on supplemental lysine to survive. The idea is flawed from a biological standpoint because since lysine is an essential amino acid, all animals are technically already lysine-dependent, the contingency was unnecessary or based on a deep misunderstanding of basic biology.