Week 1 HW: Principles and Practices

Class Assignment

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 am interested in engineering bacteriophage (viruses which infect bacteria) in order to detect harmful bacterial pathogens by using the engineered viruses to deliver and express a certain reporter gene upon infection.

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.

Safety of the use of these viruses is critical. Establishing good manufacturing practices and regulatory principles are complex, as phage replication is not as ‘consistent’ as a manufacturing a certain chemical drug would be, and combinations of certain phage and hosts may have implications for transduction of antibiotic resistance genes. Additionally, for therapeutic applications, accessibility and efficiency will be a priority. Questions on patenting phage, for example, would have to balance investment into this innovation (particularly given emerging phage therapies will be competing against thet traditional pharmaceutical drug market) with preventing artifically-high healthcare costs.

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.). Purpose: What is done now and what changes are you proposing? Design: What is needed to make it “work”? (including the actor(s) involved - who must opt-in, fund, approve, or implement, etc) Assumptions: What could you have wrong (incorrect assumptions, uncertainties)? Risks of Failure & “Success”: How might this fail, including any unintended consequences of the “success” of your proposed actions?

1. Policymakers (after consulting with members from the scientific community and industry) could mandate a set of good manufacturing practices specifically for the complexities of engineered phage, which would be required for FDA (or similar) approval and could be punished with fines or in extreme cases criminal liability. For example, regulatory organizations could adopt a modular approval process, such as the process for mRNA vaccines, where certain base manufacturing and delivery processes are reviewed but once approved minor swapping of phage ‘parts’ could be incorporated with a less lengthy review time. Currently, in the US, phage are generally regulated as ‘biological/medicinal products’ in the same category as drugs, although none has been approved with full FDA approval (their applications are just as an ‘Investigative New Drug’). The UK Medicines and Healthcare Regulatory Agency recently just released a set of guidelines specifically for phage therapy, to help clarify manufacturing expectations and the path to approval, yet did not address applications for engineered phage nor set any legally binding mandates.
2. The scientific community could share data on engineered phage reactions when co-cultured with other hosts and phage in order to better accumulate safety information about possible combinations. Currently, PhagesDB stores detailed information about sequenced phage found from various environments and the American Society for Microbiology’s Phage Therapy Coordination Network is analyzing clinical trial and manufacturing quality data, but no similar dataset exists for phage with engineered constructs. It is more difficult with engineered constructs as many labs and industries want to keep said constructs proprietary (whereas one cannot patent natural phage as the case for PhagesDB), and so the biggest hurdle would be to garner interest into voluntary information sharing.
3. Engineered phage companies could adopt post-treatment screening practices after applying engineered phage therapies. This data may be collected in certain clinical trials but there is no evidence of a norm at scale for all treatments to be monitored for a substantive period of time, particularly in non-therapeutic cases. Greater investment into diagnostic and sequencing labs will be necessary for this option, although costs could be offset with monetary incentives for screening (either government subsidies or even a market label that could attract consumers).

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. The following is one framework but feel free to make your own:

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 think Option 1 is the most feasible option, given the early precedent set by MHRA’s ‘regular’ phage therapy guidelines released last Summer, and has the widest impact at the national level. It paves the way for approved engineered phage therapy use, which is important to address accessibility and trust as well as introducing more safety review. By making the path more clear with a modular approval process, engineered phage therapy becomes an economically viable opportunity for the private sector to invest in as well, which will help advance research. The biggest challenge will be that any proposed regulatory system will be incomplete, as there a wide range of applications and cases for engineered phage therapy, as well as the financial burden for hiring more regulators to review these proposals. My proposed target would be to Senator Young, who is the Commissioner of the National Security Commission for Emerging Biotechnology and is already leading on introducing and implementing biotech-related legislation in Congress.

Instructor 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?

The error rate of eukaryotic DNA polymerase is 1 error every 10^{6 bases. The human genome is approximately 3.2 x 10}9 base pairs long (6.4 billion is in most cells as they are diploid). This is problematic as this would introduce 3 errors for every two cells that replicate. There are thus other DNA repair polymerases that are dedicated to finding and fixing these errors.

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?

Due to codon degeneracy (where a single codon could be encoded by several different DNA/RNA sequences), there are about 3 different sequences on average for each amino acid (64 possible codons for 20 amino acids). If an average human protein is 1036 bp, and each codon is 3 bp long, there are about 345 codons and thus about 3^345 ways the protein could be sequenced. mRNA regulations (different folding, silencers, etc) may be one reason as to why all these different codes don’t work for a protein of interest.

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

Phosphoramidite DNA Synthesis Cycle, a four step cycle where the existing strand is ‘deprotected’ with an acid or light to prepare for addition, a nucleotide base (often modified to include this protector) is added one at a time, the strand is capped (this step is sometimes included after each base in order to prevent errors), and then the phosphate is oxidized.

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

The yield drops exponentially for long sequences as you are added bases one at a time, and shorter impurities become dominant.

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

Related to the answer above, the challenges in yield and purity for longer sequences makes directly synthesizing that long of a gene at once very difficult. But, you could synthesize it in smaller parts and use DNA assembly tools like Gibson to put the gene together!

6. 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 are arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. The Lysine Contingency refers to a fictional genetic modification in Jurassic Park, where scientists knocked out the ability for the dinosaurs to produce their own lysine in order to prevent their successful survival in the wild if there were to escape the part (as they would be dependent on the park’s food supplements). As proven though with animals in real life lacking the ability to produce their own lysine, there are many ways to supplement these amino acids in the wild (other animals, dairy products, or soybeans are all lysine-rich foods, for example).

Week 2 HW: DNA Read, Write, Edit

Class Assignment

Week 3: Automation

Class Assignment

Week 4: Protein Design 1

Class Assignment

Week 5: Protein Design II

Class Assignment

Week 6 - Genetic Circuits I

Class Assignment

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project