Week 1 HW: Principles and Practices

Project Propalsal:

A small, low-cost desktop platform that combines short DNA synthesis with cell-free expression. Users (students, community labs, small clinics) design short DNA sequences through a web interface, send them to a benchtop “DNA printer,” and immediately test them in a cell-free system. This pushes “personal fabrication” into biology and could support education and grassroots innovation, but raises serious questions about biosecurity, safety, and equity when DNA writing becomes cheap and widely accessible.

Option 1: Mandatory sequence screening and basic customer vetting for all DNA synthesis providers (including cartridge vendors), coordinated through national / international standards.

Option 2: Built-in technical safeguards in desktop devices (on-device sequence screening, hard limits on sequence length and volume, whitelist mode for education deployments).

Option 3: Community lab / school codes of conduct, safety & security training, and an incident-report network co-developed with public agencies and DIYbio / professional societies.

Based on this scoring, I would prioritize a combination of Option 1 and Option 3, with Option 2 as a complementary, medium-term measure.

Option 1 scores best on preventing high-consequence biosecurity incidents, especially if screening standards are coordinated internationally and made affordable for smaller providers. However, it is costly and risks concentrating DNA synthesis capacity in a few large actors. Option 3 scores best on lab safety, environmental protection, and promoting constructive applications in community labs and schools, but it is weaker for deterring sophisticated malicious actors. Option 2 could add an important technical layer of protection, yet it faces feasibility and “jailbreaking” challenges and could more easily impede legitimate research if designed too rigidly.

For a national science policy audience or major funders, I would recommend:

• Supporting shared, affordable sequence-screening tools and minimum standards (Option 1).
• Investing in training, codes of conduct, and incident-report networks for community labs and schools (Option 3).
• Encouraging research and early deployment of built-in safeguards, while monitoring how they affect usability and innovation (Option 2).

Key uncertainties include how quickly desktop DNA platforms will diffuse, how easy it will be to circumvent safeguards, and how governance choices in one country will shift risks and opportunities globally.

Reflecting on this week’s class, one ethical concern that became more salient to me is how routine DNA writing already is in modern biology. It no longer feels like a rare, “sci-fi” capability but a basic infrastructure, which makes dual-use risks more mundane and distributed. Another concern is equity: if governance relies only on heavy regulation and expensive compliance, advanced tools may become concentrated in a few wealthy institutions, while informal or under-resourced spaces are pushed into a gray zone with less support and oversight.

In the local context of MIT and Harvard, I think appropriate governance actions include: brief, practical training on DNA synthesis ethics for people who can place synthesis orders; centrally provided sequence-screening tools so individual labs do not each have to solve the problem; and safe channels to ask questions about “borderline” projects and to report concerns. These measures align with Option 1 and Option 3, and feel tractable at the institutional level.

Homework Questions:

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?

A:Polymerase is ~1 error per 10⁶ bases, which would mean thousands of errors across the 3.2×10⁹-bp human genome, so cells rely on proofreading plus mismatch repair to bring the effective error rate way down.

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?

A：Because many amino acids have multiple synonymous codons, an average-length protein can be encoded by an astronomically large number of DNA sequences, but many fail in practice due to codon bias/rare tRNAs, harmful mRNA structures, and unintended regulatory or splicing signals that reduce or disrupt expression.

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

A: Oligonucleotide synthesis

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

A:Its gonna have errors.

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

A:Its gonna have a lots of errors.

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

A:The “10 essential amino acids” mnemonic often used for animals is PVT TIM HALL: Phenylalanine, Valine, Threonine, Tryptophan, Isoleucine, Methionine, Histidine, Arginine, Leucine, Lysine.

Since lysine is already an essential amino acid (animals generally can’t synthesize it and must get it from diet), “making an animal lysine-dependent” is basically making it normal, so as a containment strategy it’s weak unless you also control lysine access or engineer dependence on something non-natural (a synthetic nutrient) rather than a widely available dietary essential.