Week X HW: Test

• Hello ¹

Week 1 HW: Principles and Practices

Week 1 Biological Engineering Application Governance Exercise

• I’m interested in developing phage chassis capable of targeting bacteria that commonly cause infections during spaceflight. I’m interested in developing these phage chassis because:

  • They would give astronauts and future space travelers more autonomy in countering ad hoc novel infections that may occur during long-duration missions
  • They would help contribute to greater personalization of medical care for broader ranges/more diverse spacefaring populations, who will likely travel, work, and live in space for extended periods of time/longer than traditional space missions to date
  • This development may help counter novel terrestrial infections for medically underserved populations

• Governance Goal 1 (G1): Preventing/Mitigating Malicious Dual-Use (i.e., ensuring)

  • Appropriate biosecurity (including cyberbiosecurity) controls
  • Safe deployment conditions

• Governance Goal 2 (G2): Empowering Autonmous and Equitable Use

  • ‘Plug-and-play’ functionality (i.e., any mission or crew should be able to intuitively use solution – advanced technical acumen not required)
  • Solution costs and distribution should develop with access across wide range(s) of demographics and socio-economic strata in mind

• Governance Action 1: Phage Safety Refusal (PSR)

  Purpose:

  • Current State: There are no proactive mechansisms preventing malicious dual-use phage development (i.e., developing a phage speicifcally designed to degrade host mRNA in healthy cells).
  • Proposed Changes: Easily implementable phage production host ‘kill switches’ that can be deployed if n^th concentrations of healthy cells accidentally or deliberately targeted by phage therapy

  Design:

  • Existing global space health biotechnology base (consisting of private firms, academia, and government-affiliated research centers) need to opt-in and actively invest in space-based phage therapies at adequate enough levels to ensure this notion of a phage defensive ‘kill switch’ can be validated and deployed, or invalidated and no longer pursued
  • Diverse space health regulators (consisting of a variety of agencies across nation-state governments) would need to approve said ‘kill switches’ (ex. Food and Drug Administration in the United States)
  • Patients participating in clinical trials of the ‘kill switch’ would need to feel comfortable enough with the solution to participate
  • Investors and members of private industry must see enough potential in the ‘kill switch that they see it as worthy of their time and investment
  • Astronauts and future spacefarers must be comfortable enough with the ‘kill switches’ to consent to their use

  Assumptions

  • The underlying notion of malicious dual-use phage applications, particularly in a space biotechnology context. Assumptions underneath this assumption include:
    • Viable malicious dual-use phage applications within a space health context and
    • Malicious actors would see and act on the benefits of phage interventions for targeted action against healthy cells in adversarial/antagonistic persons
  • That defensive anti-phage ‘kill switches’ even make sense to pursue technically

  Risks of Failure & “Success”

  • No viable malicious dual-use phage application concern (terrestrially or in a space context)
  • No interest in developing anti-phage ‘kill switches’
  • Developing anti-phage ‘kill switches’ is too technically intensive/not scalable to address the diverse needs of potential future users
  • Not enough funding to develop necessary research body of knowledge to make anti-phage ‘kill switches’ viable and safe to use in a space health context
  • Anti-phage ‘kill switches’ successfully developed and deployed and become another chapter in the never-ending story of phages v. bacteria (i.e., phages adapt to the ‘kill switches’ over time, rendering them ineffective)

• Governance Action 2: Space Medicine Access Consortia (SMAC)

  Purpose

  • Current State: The field of space medicine is still in its relative nascency. While space health consortia exist, there are no consortia explicitly aimed at making space medicine advancements as broadly accessible as possible to both spacefaring and terrestrial populations.
  • Proposed Changes: Charter and develop a consortia explicitly aimed at making space medicine advancements as broadly accessible as possible to both spacefaring and terrestrial populations. Ideally this consortia should comprise members from private industry, academia, government-affiliated research centers, and allied partners

  Design:

  • Potential and future committed consortia partners from across private industry, academia, government-affiliated research centers, and allied partners need to see the value of the consortia’s mission (i.e., they need to see and align with how the consortia’s explicit charter to make space medicine advancements as broadly accessible as possible to both spacefaring and terrestrial populations would benefit their organization)
  • Consortia partners need to agree on:
    • Rules of the road (this will likely need to be contractual)
    • Research scope(s) for their organizations
  • Concrete milestones indicating consortia success, stagnation, or failure in achieving its goals
  • Adequate funding to see consortia from inception through the point where most of its charter has been fulfilled (a somewhat analogous example might be the pool of institutions the Information Processing Technology Office (IPTO) at the Defense Advanced Research Projects Agency (DARPA) pooled together when creating the ARPANET, which later evolved to become the modern Internet, and the shifts in IPTO’s mission over time as a result of these developments)

  Assumptions

  • Critical mass of stakeholders:
    • cares about making space medicine advancements accessible to spacefaring and terrestrial populations
    • can see the value of a dedicated consortia to make space medicine advancements more accessible for spacefaring and terrestrial populations
    • can agree to the rules of the road necessary to make consortia viable
    • see the value of making phage chassis capable of targeting bacteria that commonly cause infections during spaceflight ‘plug-and-play’ and cost-effective for end-users (i.e., they wouldn’t prioritize some other space medicine intervention)
  • Consortia can achieve its charter, with greater phage chassis accessiblity as a step on its path to success

  Risks of Failure & “Success”

  • No or not enough interest in:
    • making space medicine advancements more accessible for spacefaring and terrestrial populations
    • developing consortia to make space medicine advancements more accessible for spacefaring and terrestrial populations
  • SMAC not viable due to:
    • Too much burden/not enough return on investment for potential consortia members (i.e., they don’t see the value)
    • Disagreeements over rules of engagement
    • Disagreement over research scope for participating members (i.e. who does what)
    • Inadequate implementation pathways (i.e., most of SMAC’s work languishes in the ‘valley of death’)
  • SMAC prioritizes other space medicine interventions over making phage chassis capable of targeting bacteria that commonly cause infections during spaceflight ‘plug-and-play’ and cost-effective for end-users
  • SMAC might ‘succeed’ too much, and as a result, the loudest or wealthiest SMAC members might eventually see value in exercising disproportionate control over the entity, diluting its charter

• Governance Action 3: Space Applied Biomedicine Repository (SABR)

  Purpose

  • Current State: Numerous space medicine guides have been developed by NASA, including the NASA Astronaut Medical Operations Handbook, Advanced Diagnostic Ultrasound in Microgravity (ADUM) Protocols, and OCHMO-STD-100.1A, otherwise known as the NASA Medical Standard. Commercial space missions largely lean on these guides for their missions
  • Proposed Changes: While NASA’s precedent is useful and organizations like the Translational Research Institue for Space Health (TRISH) have proposed tailored guidance for commercial space travelers, there is no existing repository explicitly focused on lessons learned and best practices for applied biomedicine in a space context. As opposed to a static guide, this work be more like a git-based repo, that could be updated with lessons learned, remaining customaizable for large numbers of future spacefarers and their medicial needs

  Design

  • User base:
    • willing to contribute to and derive value from SABR
    • with enough technical know-how to contribute to and derive value from SABR
  • Stakeholder(s) willing to pay subscription costs to run (likely git-based) SABR technical back-end
  • Easy to understand guidance and lessons learned that can be easily ingested in text, video, or audio form on (likely) simple, non-bandwidth intensive network connected devices

  Assumptions:

  • A (likely git-based) repository is an optimal vehicle for distributing recursively improving or community-based applied biomedicine lessons-learned for the space medicine community and future missions
  • This repository would contain accumulated, useful insights regarding how phage chassis capable of targeting bacteria that commonly cause infections during spaceflight can be deployed or administered:
    • safely (i.e. without malicious dual-use) across a wide variety of space missions
    • in a ‘plug-and-play’ or affordable manner
  • Enough of a user base:
    • willing to contribute to and derive value from SABR
    • with enough technical know-how to contribute to and derive value from SABR
  • Stakeholder(s) willing to pay subscription costs to run (likely git-based) SABR technical back-end
  • Easy to understand guidance and lessons learned that can be easily ingested in text, video, or audio form on (likely) simple, non-bandwidth intensive network connected devices (i.e., SABR can adequately work even in very bandwidth constrained conditions)

  Risks of Failure & “Success”

  • Not enough interest in SABR (potential users or contributors don’t see its value)
  • SABR is:
    • too:
      • early/the timing’s not right
      • abstract and remote in its guidance (i.e., the actual users or contributors who might derive value from its content see its content as too over their heads, technical, jargon-filled, or not applicable for their specific use cases)
    • a useful application, just not for the safe, easy-to-use, or cost-efective deployment of phage chassis capable of targeting bacteria that commonly cause infections during spaceflight
    • bandwidth-constrained to such a degree that it’s untenable for all intensive purposes
  • Can’t find stakeholder(s) willing to pay subscription costs to run (likely git-based) SABR technical back-end
  • SABR works so well and grows to such an extent that discerning actual mission-relevant content of value from the repository becomes a challenge for uninitiated users (i.e., filtering is a challenge – hard to separate filler from useful content)

• Biological Engineering Application Governance Scoring Rubric

• Biological Engineering Application: Phage chassis capable of targeting bacteria that commonly cause infections during spaceflight

• The rubric below works as follows: Policy goals and sub-goals are listed vertically, while each of the governance actions are listed next to the respective column header titled ‘Option’. Governance actions are scored from 1-3 based on how well they fulfil each policy goal and sub-goal. A score of 1 indicates a governance action does a poor job at fulfilling a policy goal, a 2 indicated a governance action does an OK job at fulfilling a policy goal, and a 3 indicates a governance action is the best at fulfilling a policy goal.

• Based on the scoring above, I’d probably prioritize SABR. Given the difficulties around space-based governance or governance in remote conditions, I think an organization like a TRISH or the Organization for Space Medicine, Engineering, and Design (OSMED) might be a good starting point, promoter, or convener to begin making something like SABR a reality. The more I think about it, the varied jurisdictions and varied, unclear regualtory regimes at the nation-state level make the idea of a more open-source/tribal knowledge-based self-governing solution appealing (or at bare minimum it shows a gap that could potentially be filled). I also think that if the timing was right (i.e., enough useful information could be added by a community of contributors) this could actually help fulfill some of the policy goals associated with the phage chassis project, not by a lot of sanctioned formal policy-making perhaps, but by community contribution, input, and/or agreed-upon best practices. That said, I can see and understand the trade-offs between formal policy-making at the nation-state level and more grassroots normative development of best practices as a result of doing this exercise. The glaring uncertainties that remain are whether or not the repository’s timing is right and/or if a dedicated user and contributor base could coalesce around it

• Ethical Considerations: Given the mechanics of phages, specifically their ability to hijack host cell tRNAs, ribosomes, and amino acids, I was somewhat surprised that there wasn’t more mention of potential deliberate malicious dual-use of phages. Maybe it’s my relative nascent understanding of the life sciences, the limitations of my research on this topic, or maybe the topic itself is either not researched or considered extensively. If this is true and the notion of potential deliberate malicious dual-use of phages might be a little bit left field, not well understood, or not well defined, perhaps convening working groups might be a sensible governance action, as these groups can often help map areas of concern for emerging dual-use technologies. Maybe distributing outputs from these working groups (i.e., white papers) to relevant academic journals, technical standards bodies, or policymakers might also be a worthwhile governance action.

All supporting prompts for the governance exercise above listed below:

Week 1 Homework Questions

Professor Jacobson Questions

• Two widely used polymerases are thermus aquaticus (Taq) and pyrococcus furiosus (Pfu) ¹. Taq has error rates ranging between 1 x 10^-5 to 2 x 10^-4 errors per base pair per doubling while Pfu has error rates of 1.3 x 10^{6 2 3}. Compared to the length of the human genome, 3 x 10⁹ base pairs, this comes out to apprxoimately 3.3 x 10^-13%, 6.6 x 10^-12%, and 3.3 x 10^-2% ⁴. Biology deals with this discrepancy during DNA replication through proofreading when it detects inaccurate nucleotides. When the polymerase detects that an inccorect base has been added, the polmyerase enzyme makes a cut in the chemical bond, releasing the incorrect nucleotide ⁵. If errors are made after replication, a mismatch repair is initiated. This is where enzymes recognize incorrectly added nucleotides and dispose of them. Nucelotide excision repair is another way nature corrects these errors. This occurs when ezymes remove and replace incorrect bases via cuts at the 3 and 5 prime ends of the incorrect base ⁶.
• An average human protein is approximately 375 amino acids long ⁷. As each codon consists of 3 letters, rough math indicates there are approximately 3³⁷⁵ number of potential coding sequences, an extremely large number of combinations ⁸. Some of the reasons all these different codons don’t code for the protein of interest are:
  • Codon Bias: Some codons are represented during transcription at a far greater level than others, traditionally due to more abundant transcription RNA (tRNA), ensuring higher levels of expression ^{9 10}.
  • mRNA Structure: Certain mRNA structures can be impacted by certain codon expression (i.e., become less stable), and therefore become more susceptible to degradation ¹¹.
  • Translation Accuracy Issues: Non-optimal codons decrease protein translation efficiency, due to a form of crowding in the ribosome, the area in the cell where protein production takes place ¹².

Dr. LeProust Questions

• Solid-phase phosphoramidite synthesis is the most common currently used oligo synthesis method ¹³.
• It’s difficult to make oligos longer than 200nt via direct synthesis because coupling errors/inefficiencies compound to the point where one ends up with lots of short, incomplete fragments ¹⁴.
• A 2000bp gene has 4000 nucleotides ¹⁵. Based on the answer to the previous question, creating a 2000bp is not currently feasible due to the accumulation of coupling errors/inefficiencies, even when stitching together smaller oligos or using novel enzymatic methods are taken into account ^{16 17}.

George Church Question

• Question 3 Response: ARPA-H Biostablization Sytem (BoSS) Grant Response

  All supporting prompts listed below answer:

Concept Summary

The team behind Pyrococcus furiosus-Inspired Molecular Staples (PFIMS) seeks to develop small organic molecules capable of binding to the ‘grooves’ of DNA and proteins across a variety of temperatures. If successfully developed, PFIMS would allow heat-proofing a biologic across a variety of temperatures without the need for dehydration. By locking protein folds through ionic pull, we can stablize biologics for longer periods of time (TA1). Our work will scale this system to scalable cell processing across an array of temperatures and use cases (TA2).

Innovation and Impact

PFIMS is inspired by extremophile biology. Pyrococcus furiosus can survive at temperatures of 100 degrees Celsius in ocean vents. By mimicking pyrococcus furiosus’ molecular heat shield, we can keep cells alive and functioning for exteneded periods of time at refrigerator or room temperature. Unlike modern cryopreservation methods that employ various forms of freezing that can harm cells during thawing, our stabilization solution stabilizes proteins using byproducts proteins naturally produce. Not only are cold temperatures avoided entirely, but once scaled this solution will slash costs for biologics shipping. Most importantly, PFIMS can work for any cell type, as it builds off fundamental biological features, such as protein folding and membrane strength.

Proposed Work

We plan to develop a novel, functioning bench-top bioprocessing system inspired by pyrococcus furiosus. We will create a polyamine-based stabilization medium that will power this bioprocessing system for a standard biologic (ex. cell therapy or antibodies). PFMIS’ approach is grounded in existing literature on stablization for high temperature DNA/protein stabilization via polyamines, small organic molecules with muliple amino groups (Bae, 2018) (Despotović, 2020) (Oshima, 2007). These polymaines act as a form of ‘molecular staples’ in preliminary modeling efforts (Vieille, C.,2001).

Key Milestones and Deliverables

Phase 1: Synthesize the branched polyamine formulation. Deliverable: Optimized medium prototype based on a standard biologic.

Phase 2: Integrate the stabilization medium into bioprocessing hardware, likely a singlee-use bioreactor to for initial prototype followed by a larger testing and deplouyment within a media/buffer prep mixer. Deliverable: Protoyped biostabilization device.

Phase 3: Validate stability metrics for a model biologic using PFIMS at room temperature over time. Deliverable: Validation report and delivery of biostabilization system capable of scaled biostablization across nth biologics

Technical Risks and Mitigations

Risk: Polyamines may exhibit toxicity at necessary concentratioons. Mitigation: Screening polyamines for reduced toxicity levels; introducing wash and resuspension steps into bioprocessing.

Risk: Stabilization mechanism may exhibit difficulty transferring from archaic single-celled microbes like pyrococcus furiosus to eukaryotic cells (cells containing nuclei and organelles). Mitigation: Tests across multiple cell types

Use Case

PFIMS enables rapid delivery of life-saving biologics and therapeutics in low-resourced or contested conditions. This allows for dramatically cheaper shipment of biologics to locations such as rural communities without robust public health infrastructure, remote or relatively isolated geographies, or active conflict zones.

Sources

• Bae DH, Lane DJR, Jansson PJ, Richardson DR. The old and new biochemistry of polyamines. Biochim Biophys Acta Gen Subj. 2018 Sep;1862(9):2053-2068. doi: 10.1016/j.bbagen.2018.06.004. Epub 2018 Jun 8. PMID: 29890242.
• Despotović Dragana, Longo Liam, et. al. Polyamines mediate folding of primordial hyperacidic helical peptides into stable amyloid-like fibrils. Biochemistry, 60(4), 257–267.
• Oshima T. Unique polyamines produced by an extreme thermophile, Thermus thermophilus. Amino Acids. 2007 Aug;33(2):367-72. doi: 10.1007/s00726-007-0526-z. Epub 2007 Apr 12. PMID: 17429571.
• Vieille C, Zeikus GJ. Hyperthermophilic enzymes: sources, uses, and molecular mechanisms for thermostability. Microbiol Mol Biol Rev. 2001 Mar;65(1):1-43. doi: 10.1128/MMBR.65.1.1-43.2001. PMID: 11238984; PMCID: PMC99017.

All supporting prompts listed below:

Week 2 HW: DNA Read, Write, and Edit

Part 0: Basics of Gel Electrophoresis

• Per instructions for this part, I attended the 02/10 lecture and 02/11. Additionally I attended all 3 Bootcamp sessions.

Part 1: Benchling & In-silico Gel Art

• Make a free account at benchling.com

Benchling Account Creation Confirmation

• Import the Lambda DNA

Benchling Phage Lambda DNA Import Confirmation_02.12.26

• Simulate Restriction Enzyme Digestion with the following Enzymes:

  • EcoRI

  Benchling EcoRI Enzyme Digest Confirmation

  • HindIII

  Benchling HindIII Enzyme Digest Confirmation

  • BamHI

  Benchling BamHI Enzyme Digest Confirmation

  • KpnI

  Benchling KpnI Enzyme Digest Confirmation

  • EcoRV

  Benchling EcoRV Enzyme Digest Confirmation

  • SacI

  Benchling SacI Enzyme Digest Confirmation

  • SalI

  Benchling SalI Enzyme Digest Confirmation

• Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artowrks

  

  Mind the Gap (Or a Most Wondrous Cave) ➕

Part 2: Gel Art - Restriction Digests and Gel Electrophoresis

Part 3: DNA Design Challenge

3.1 Choose your protein

• I chose the Mantis Fibroin 1 protein because for some reason when I received this assignment, my mind flipped to an insect protein, and then from there, a praying mantis. Upon further research, I was pleased with where my intuition lead me. The Mantis Fibroin 1 protein helps comprise the mantis’ ootheca, otherwise known as its egg casing. What’s fascinating about these proteins is that they create this coiled yet flexible foam-like structure around the mantis’ eggs. This protein piqued my interest, as it might have biomimetic potential. The Mantis Fibroin 1 protein is listed below ¹²:

tr|I3PM87|I3PM87_9NEOP Mantis fibroin 1 OS=Pseudomantis albofimbriata OX=627833 GN=MF1 PE=2 SV=1 MDSKMLCVSLLLAVFCLWYTEASPLEEKYGEKYGDMEEYQRGTEDSRAVINDHTAKVASQ SARGMVNKAKTTEAAARSNEQLSKDRQYYYREYLKKADYHKKKALEYEQLSAAENAKIAY HESKQKDWETKARESDVQCRDAEAKYEQSYTRSRELKRESIIAYVQAAMHHAEASGDHMK ADRAKDIARDMMRKAESLRGDASNHYQRSEEDKNKARSEKVKAHQNADNSQRHHTACRAY DQEGLKTRLSSKANMMRQIHSSLLAERSHSLAREDGLAADLSHKLAEELARMSEESGAIS KINSGEERGYSNKVRQDEVKAHELAVSKRMMGAEVADNSEMISLAQAKDGSLDEGENYKL STFYADDSTKNMLPDSRGQMSYGDE

3.2 Reverse Translate: Protein (amino acid) sequence to DNA (nucleotide) sequence.

• A translated Mantis Fibroin 1 protein nucleotide sequence of most likely codons is below, as well as evidence showing how I inserted the Mantis Fibroin 1 protein UniProt information into the reverse translation tool

atggatagcaaaatgctgtgcgtgagcctgctgctggcggtgttttgcctgtggtatacc gaagcgagcccgctggaagaaaaatatggcgaaaaatatggcgatatggaagaatatcag cgcggcaccgaagatagccgcgcggtgattaacgatcataccgcgaaagtggcgagccag agcgcgcgcggcatggtgaacaaagcgaaaaccaccgaagcggcggcgcgcagcaacgaa cagctgagcaaagatcgccagtattattatcgcgaatatctgaaaaaagcggattatcat aaaaaaaaagcgctggaatatgaacagctgagcgcggcggaaaacgcgaaaattgcgtat catgaaagcaaacagaaagattgggaaaccaaagcgcgcgaaagcgatgtgcagtgccgc gatgcggaagcgaaatatgaacagagctatacccgcagccgcgaactgaaacgcgaaagc attattgcgtatgtgcaggcggcgatgcatcatgcggaagcgagcggcgatcatatgaaa gcggatcgcgcgaaagatattgcgcgcgatatgatgcgcaaagcggaaagcctgcgcggc gatgcgagcaaccattatcagcgcagcgaagaagataaaaacaaagcgcgcagcgaaaaa gtgaaagcgcatcagaacgcggataacagccagcgccatcataccgcgtgccgcgcgtat gatcaggaaggcctgaaaacccgcctgagcagcaaagcgaacatgatgcgccagattcat agcagcctgctggcggaacgcagccatagcctggcgcgcgaagatggcctggcggcggat ctgagccataaactggcggaagaactggcgcgcatgagcgaagaaagcggcgcgattagc aaaattaacagcggcgaagaacgcggctatagcaacaaagtgcgccaggatgaagtgaaa gcgcatgaactggcggtgagcaaacgcatgatgggcgcggaagtggcggataacagcgaa atgattagcctggcgcaggcgaaagatggcagcctggatgaaggcgaaaactataaactg agcaccttttatgcggatgatagcaccaaaaacatgctgccggatagccgcggccagatg agctatggcgatgaa

Mantis Fibroin 1 UniProt Information Inserted into Reverse Translation Tool

3.3 Codon Optimization

• We need to optimize codon usage so a particular sequence can be expressed with greater fidelity, reliability, and efficiency in a host organism. I’ve chosen to optimze the codon sequence for Saccharomyces cerevisiae (baker’s yeast), because it:
• is commonly used as a host in biotechnology applications
• folds in a manner closer to insect protein folding
• is apparently easier to work with than mammalian cells

A codon optimized Mantis Fibroin 1 nucleotide sequence is shown below, as well as evidence showing how I showing how I inserted the Mantis Fibroin 1 protein nucleotide sequence information into the codon optimization tool

ATGGACAGTAAGATGTTATGTGTCTCCTTATTGTTGGCTGTTTTTTGTTTATGGTATACTGAAGCTTCCCCATTAGAAGAAAAGTATGGTGAAAAGTACGGTGACATGGAAGAGTACCAAAGAGGTACTGAAGATTCAAGAGCAGTTATTAACGATCATACTGCTAAAGTTGCTTCCCAATCCGCCAGAGGTATGGTTAATAAGGCTAAGACTACAGAAGCTGCTGCTAGAAGTAATGAACAATTATCTAAAGATAGACAATACTATTACAGAGAATATTTGAAAAAGGCTGATTATCATAAGAAGAAAGCTTTGGAATATGAACAGCTTTCAGCTGCTGAAAATGCAAAAATTGCTTATCATGAATCTAAACAAAAAGACTGGGAAACGAAAGCCAGAGAATCCGATGTTCAATGTCGTGATGCTGAAGCAAAATATGAACAATCTTACACAAGGTCCAGAGAACTGAAAAGGGAATCTATTATTGCTTATGTTCAAGCTGCTATGCATCATGCTGAAGCTAGCGGTGATCACATGAAAGCTGATAGAGCTAAAGATATCGCTAGAGATATGATGAGAAAGGCAGAATCCTTAAGGGGTGACGCTAGCAACCATTATCAGAGATCCGAAGAAGATAAGAATAAGGCCAGATCTGAAAAGGTTAAAGCTCATCAAAACGCTGATAATTCTCAAAGACATCATACTGCATGCAGAGCGTATGACCAAGAAGGTTTAAAGACGAGATTGAGCTCAAAAGCCAACATGATGAGACAAATTCACTCCTCACTACTGGCTGAAAGATCTCATTCATTAGCAAGAGAAGACGGTCTTGCGGCCGATTTATCACATAAGTTGGCTGAAGAATTAGCTAGAATGTCCGAAGAATCAGGTGCTATATCTAAAATAAACTCAGGTGAAGAAAGAGGCTATTCGAATAAAGTGAGACAAGATGAGGTTAAAGCACATGAATTGGCTGTTAGCAAAAGAATGATGGGTGCTGAAGTTGCTGATAATTCGGAGATGATTAGTTTGGCACAAGCTAAAGACGGTTCTTTAGATGAAGGTGAGAACTATAAATTATCCACTTTTTATGCAGACGATTCTACAAAAAATATGCTACCAGATTCTAGGGGTCAAATGTCTTACGGTGATGAA

Mantis Fibroin 1 nucleotide sequence codon optimized for Saccharomyces cerevisiae (baker’s yeast)

3.4: You have a sequence! Now what?

• Several cell-dependent technologies could be used for producing the codon-optimized Mantis Fibroin 1 protein. One such technology, a yeast system, has already been pursued in the previous steps of this section, as Saccharomyces cerevisiae (baker’s yeast) is a form of yeast. Bacterial systems, such as E. coli could also be used for producing the protein in host cell culture, although this would require different codon optimization. Other cell-dependent technologies could have included insect or mammalian-based systems, although I’m not sure of the value of expressing an insect-associated protein in another insect-based host (although this may be a failure of imagination on my part). As mentioned previously, mammalian systems could also be used, but apparently mammalian cells are more difficult to work with than bacterial or yeast-based hosts. Cell-free methods for producing the codon-optimized Mantis Fibroin 1 protein would involve breaking open a cell, extracting relevant ribosomes, enzymes, tRNAs, etc., and then taking these contents and combinining them with a DNA template (in this case our Mantis Fibroin 1 protein nucleotide sequence), energy sourcesm relevant amino acids, and a reaction buffer. There’s a time advantage of cell-free methods over cell-dependent methods of protein expression.

3.5 Optional: How does it work in nature/biological systems?

• From my research in answering this question, I think the answer is that post-transcriptional process called alternative splicing occurs, where non-coding mRNA (introns) are cut and removed, while coding regions (exons) remain ³. It’s pretty fascinating because this splicing can create several different types of mRNA molecules, and therefore different proteins. This increases the efficiency with which different proteins can be expressed within a particular organism.
• See below

Attempted Mantis Fibroin 1 Alignment

All Section 3 Prompts Listed Below

Part 4: Prepare a Twist DNA Synthesis Order

4.1: Create a Twist account, and Benchling account

Twist Account Creation

Benchling Account Creation Confirmation

4.2: Build Your DNA Insert Sequence

Original Sequence Insertion NOTE: Think I may’ve started off inserting the wrong sequence. This may have been potentially fixed when I inserted a sfGFP sequence from NCBI*

Codon Optimization NOTE: Think I may’ve started off inserting the wrong sequence. This may have been potentially fixed when I inserted a sfGFP sequence from NCBI*

Corrected NCBI Sequence Insertion

Corrected NCBI Sequence Codon Optimization

Start Codon Annotation

Stop Codon Annotation

Promoter BBa_J23106 Insertion

RBS Insertion

Coding Sequence Insertion

7x His Tag Insertion

Terminator BBa_B0015 Insertion

Sequence Linear View

• Downloaded Sequence FASTA file (via Mac OS TextEdit). See below:

  HQ873313 (codon optimized) TTTACGGCTAGCTCAGTCCTAGGTATAGTGCTAGCCATTAAAGAGGAGAAAGGTACCatgAGCAAAGGAGAAGAACTTT TCACTGGAGTTGTCCCAATTCTTGTTGAATTAGATGGTGATGTTAATGGGCACAAATTTTCTGTCCGTGGAGAGGGTGA AGGTGATGCTACAAACGGAAAACTCACCCTTAAATTTATTTGCACTACTGGAAAACTACCTGTTCCGTGGCCAACACTT GTCACTACTCTGACCTATGGTGTTCAATGCTTTTCCCGTTATCCGGATCACATGAAACGGCATGACTTTTTCAAGAGTG CCATGCCCGAAGGTTATGTACAGGAACGCACTATATCTTTCAAAGATGACGGGACCTACAAGACGCGTGCTGAAGTCAA GTTTGAAGGTGATACCCTTGTTAATCGTATCGAGTTAAAGGGTATTGATTTTAAAGAAGATGGAAACATTCTTGGACAC AAACTCGAGTACAACTTTAACTCACACAATGTATACATCACGGCAGACAAACAAAAGAATGGAATCAAAGCTAACTTCA AAATTCGCCACAACGTTGAAGATGGTTCCGTTCAACTAGCAGACCATTATCAACAAAATACTCCAATTGGCGATGGCCC TGTCCTTTTACCAGACAACCATTACCTGTCGACACAATCTGTCCTTTCGAAAGATCCCAACGAAAAGCGTGACCACATG GTCCTTCTTGAGTTTGTAACTGCTGCTGGGATTACACATGGCATGGATGAGCTCTACAAAcgtaaaggcgaggagctgt tcactggtgtcgtccctattctggtggaactggatggtgatgtcaacggtcataagttttccgtgcgtggcgagggtga aggtgacgcaactaatggtaaactgacgctgaagttcatctgtactactggtaaactgccggtaccttggccgactctg gtaacgacgctgacttatggtgttcagtgctttgctcgttatccggaccatatgaagcagcatgacttcttcaagtccg ccatgccggaaggctatgtgcaggaacgcacgatttcctttaaggatgacggcacgtacaaaacgcgtgcggaagtgaa atttgaaggcgataccctggtaaaccgcattgagctgaaaggcattgactttaaagaagacggcaatatcctgggccat aagctggaatacaattttaacagccacaatgtttacatcaccgccgataaacaaaaaaatggcattaaagcgaatttta aaattcgccacaacgtggaggatggcagcgtgcagctggctgatcactaccagcaaaacactccaatcggtgatggtcc tgttctgctgccagacaatcactatctgagcacgcaaagcgttctgtctaaagatccgaacgagaaacgcgatcatatg gttctgctggagttcgtaaccgcagcgggcatcacgcatggtatggatgaactgtacaaatgaCATCACCATCACCATC ATCACtaaCCAGGCATCAAATAAAACGAAAGGCTCAGTCGAAAGACTGGGCCTTTCGTTTTATCTGTTGTTTGTCGGTG AACGCTCTCTACTAGAGTCACACTGGCTCACCTTCGGGTGGGCCTTTCTGCGTTTATA

4.3: On Twist, Select the Genes Option

Selected Genes

4.4: Select the ‘Clonal Genes’ Option

Clonal Genes Selected see results in subsections 4.5 and 4.6 below

4.5: Import your sequence

Imported Sequence (Step 1)

Imported Sequence (Step 2)

4.6: Choose Your Vector

Chose Vector

Downloaded Construct

Imported sequence into Benchling and viewed resulting plasmid

All Section 4 Prompts Listed Below

Part 5: DNA Read/Write/Edit

5.1 DNA Read

• (i) What DNA would you want to sequence (e.g., read) and why?

• I want to sequence the DNA of the bdelloid rotifer Adineta genus, a microscopic-sized invertebrate that kind of looks like a worm. I’m fascinated by its ability to sustain cryptobiosis for thousands (in the case of a bdelloid rotifer thawed out in Russia in 2015, more than 24,000!!) of years. Transgenesis of the bdelloid rotifer’s cryptobiotic abilities in mammalian organisms could have profound impacts on the future of the species, specifically the ability for groups of homo sapiens or other future sapiens forms to engage in interstellar travel over large durations of time and space. More information on the bdelloid rotifer Adineta genus and its cryptobiotic abilities can be found in the footnote at the end of this sentence ⁴.

• (ii) In lecture, a variety of sequencing technologies were mentioned. What technology or technologies would you use to perform sequencing on your DNA and why?

  • I’d use Next-Generation Sequencing (NGS) on my DNA because it’s well-suited for transgenesis. It’s fast, high-resolution, and allows for massively parallel sequencing (if desired). More importantly, it’s highly precise, meaning it can pinpoint transgene locations within a host genome.

• Is your method first-, second- or third-generation or other? How so?

  • It’s a second-generation sequencing method, as it emerged in the 2000’s after the advent of Sanger sequencing in the 1970’s and before the advent of single-molecule sequencing in the 2010’s.

• What is your input? How do you prepare your input (e.g. fragmentation, adapter ligation, PCR)? List the essential steps.

  • If the gene exists in an organism, the initial input is extracted genomic DNA from that particular organism. Otherwise, the initial input can be a plasmid (if the DNA’s already cloned) or complementary DNA (cDNA) if only mRNA is available. Essential preparation steps listed below (assuming gene exists in an organism):
    • Isolate or extract the gene; lyse cells or tissues from donor, remove proteins and contaminants
    • Fragment the isolated or extracted gene into fragments of apprxo. ~200-600bp
    • Convert ragged ends into blunt or sticky ends
    • Attach adapter sequences to ends of each fragment
    • Enrich fragments of the intended size (i.e., the size you want), removing any remaining small artifacts and excess adapters
    • Review fragement size distribution
    • Convert double-stranded library into single strands if necessary
    • Load into sequencing instrument

• What are the essential steps of your chosen sequencing technology, how does it decode the bases of your DNA sample (base calling)?

  • The essential NGS steps are listed below:
    • Preparation (see above)
    • Amplification: Many copies of each DNA fragment are created on flow cells. One end of each fragment sticks to a primer, gets copied to a complementary strand, and bends over to stick to a primer. This bridging repeats n^th times, forming amplified (hence the name) clusters of these identical grouped fragments
    • Sequencing: A polymerase enzymes adds 1 colored flourescent nucleotide to each strand in each cluster of grouped fragments. A camera takes a picture of recording the color for the given nucleotide (revealing its A, T, G, or C base) then chemicals are used to wash away any free-floating nucleotides that aren’t part of a given cluster.
    • Base Decoding/Base Calling: A computer analyzes these colored image clusters, assigning each cluster a sequence of bases based on its colors. This analysis then becomes a text string of DNA code, with confidence ratings per base sequence based on the resolution of the read ⁵

• What is the output of your chosen sequencing technology?

  • See above. NGS outputs a text string of DNA code, with confidence ratings per base sequence

5.2 DNA Write

• (i) What DNA would you want to synthesize (e.g., write) and why?)

  • See answer to 5.1 (i). I’m fascinated by the potential of transgenesis of the bdelloid rotifer Adineta’s cryptobiotic abilities for interstellar travel, and therefore, am very interested in reading and editing its sequence.

  NOTE: I found a bdelloid rotifer Adineta sequence in the link in the footnote. However, the raw FASTA information is so long that upon insertion into this webpage, it seemingly broke the webpage, or caused it to freeze up (pardon the unintentional cryptobiosis pun) ⁶

• (ii) What technology or technologies would you use to perform this DNA synthesis and why?

  • I’d use PCR amplification, chemical synthesis, and restriction enzymes and ligation to perform this DNA synthesis. I’d use PCR so I can make many copies of the original DNA, I’d use chemical synthesis so I can clone the DNA into a given plasmid, encapsulating the DNA for desired level expression in an appropiate vehicle, and I’d use restriction enzymes and ligation for precise synthesis.
  • What are the essential steps of your chosen sequencing methods?
    • PCR amplification:
      • Denaturation: Heat DNA so it breaks into stingle strands
      • Annealing: Cool the DNA, allowing primers to bind to sites in target gene
      • Extension: DNA polymerase adds nucleotides from the primer starting point, allowing each strand to fully copy
    • Chemical synthesis:
      • Deprotection: Remove protecting DMT group
      • Base Coupling: Add protected phosphoramidite nucleotide for phosphate linkage
      • Capping: Cap the chain to prevent errors
      • Oxidation: Stabilize phosphate triester bonds
    • Restriction enzymes and ligation:
      • Stitch oligos from prior chemical synthesis step into a complete gene for insertion into plasmid
      • Add flanking restriction enzymes at ends of oligos as needed
      • Clean the isolated DNA via gel extract
      • Use matching restriction enzymes to incubate the gene insert and its plasmid vector. This incubation process recognizes specific sequences in the gene insert and cut, creating blunt and sticky ends
      • Use DNA ligase enzyme to mix compatible ends
  • What are the limitations of your sequencing method (if any) in terms of speed, accuracy, scalability?
    • A scalability challenge is that it’s difficult to synthesize a sequence of more than 200nt via direct synthesis methods because at a certain point, too many errors accumulate in the synthesized sequence

5.2 DNA Edit

• (i) What DNA would you want to edit and why?
  • See answer to 5.1 (i). I’m fascinated by the potential of transgenesis of the bdelloid rotifer Adineta’s cryptobiotic abilities for interstellar travel, and therefore, am very interested in reading and editing its sequence.
• (ii) What technology or technologies would you use to perform these DNA edits and why?
  • I’d use CRISPR-Cas9 to perform these DNA edits because when performing transgenesis from an invertebrate to a mammalian vertebrate, it allows for non-random, precise insertion of large amounts of genetic data with reduced risk of unintended or off-target effects.
  • How does your technology of choice edit DNA? What are the essential steps?
    • CRISPR-Cas9 edits DNA through a multi-stage mechanism. This mechanism is broken down below:
      • Recognition: A single guide RNA (sgRNA) pairs with a Cas9 protein
      • This pair scans the genome for a 20bp DNA sequence if the sequence is next to a protospacer adjacent motif (PAM)
      • If there is a PAM next to the desired 20bp DNA sequence, the Cas9 makes a dobule-stranded break (DSB)
      • The DSB then triggers repair mechanisms (either non-homolgous end joining [NHEJ] or homology-directed repair [HDR]). These repair mechanisms allow the desired edited DNA to be incorporated into the sequence
  • What preparation do you need to do (e.g. design steps) and what is the input (e.g. DNA template, enzymes, plasmids, primers, guides, cells) for the editing?
    • Preparation:
      • Select target site(s)
      • Design and synthesize gRNA
      • Build DNA donor templates
      • Create mixture of recombinant Cas9 protein and purified gRNA
      • Preapre cells/embryos
    • Inputs to this process are gRNDA,Cas9 protein, donor DNA (usually linear templates), and a delivery vehicle (usually an injection buffer)
  • What are the limitations of your editing methods (if any) in terms of efficiency or precision?
    • HDR can have low efficiency in a transgenesis context
    • Off-target or unintended consequences can still occur
    • Need PAMs near target sequences for precise DSBs

All Section 5 Prompts Listed Below

Week 3 HW: Lab Automation

The Power of Lab Automation

Assignment: Python Script for Opentrons Artwork

• 0: Attended this week’s recitation and reviewed the lab information on programming Opentrons
• 1: Generated an artistic design using Ronan’s Opentrons GUI ¹
• 2: Artistic Design Python Script: See script in URL below:

  • https://colab.research.google.com/drive/1-pgSJt_aF9MydtG0szxz2YKoogNRLRhH#scrollTo=PsOgJ2DndZzt

• 3: Listing my sfgfp point coordinates from Ronan’s Opentrons GUI below (the shape is a rightward-facing green arrow):

  • [(6.6,11), (8.8,11), (11,11), (8.8,8.8), (11,8.8), (13.2,8.8), (11,6.6), (13.2,6.6), (15.4,6.6), (13.2,4.4), (15.4,4.4), (17.6,4.4), (15.4,2.2), (17.6,2.2), (19.8,2.2), (17.6,0), (19.8,0), (22,0), (-22,-2.2), (-19.8,-2.2), (-17.6,-2.2), (-15.4,-2.2), (-13.2,-2.2), (-11,-2.2), (-8.8,-2.2), (-6.6,-2.2), (-4.4,-2.2), (-2.2,-2.2), (0,-2.2), (2.2,-2.2), (4.4,-2.2), (6.6,-2.2), (8.8,-2.2), (11,-2.2), (13.2,-2.2), (15.4,-2.2), (17.6,-2.2), (19.8,-2.2), (22,-2.2), (24.2,-2.2), (-22,-4.4), (-19.8,-4.4), (-17.6,-4.4), (-15.4,-4.4), (-13.2,-4.4), (-11,-4.4), (-8.8,-4.4), (-6.6,-4.4), (-4.4,-4.4), (-2.2,-4.4), (0,-4.4), (2.2,-4.4), (4.4,-4.4), (6.6,-4.4), (8.8,-4.4), (11,-4.4), (13.2,-4.4), (15.4,-4.4), (17.6,-4.4), (19.8,-4.4), (22,-4.4), (24.2,-4.4), (26.4,-4.4), (-22,-6.6), (-19.8,-6.6), (-17.6,-6.6), (-15.4,-6.6), (-13.2,-6.6), (-11,-6.6), (-8.8,-6.6), (-6.6,-6.6), (-4.4,-6.6), (-2.2,-6.6), (0,-6.6), (2.2,-6.6), (4.4,-6.6), (6.6,-6.6), (8.8,-6.6), (11,-6.6), (13.2,-6.6), (15.4,-6.6), (17.6,-6.6), (19.8,-6.6), (22,-6.6), (24.2,-6.6), (17.6,-8.8), (19.8,-8.8), (22,-8.8), (15.4,-11), (17.6,-11), (19.8,-11), (13.2,-13.2), (15.4,-13.2), (17.6,-13.2), (11,-15.4), (13.2,-15.4), (15.4,-15.4), (8.8,-17.6), (11,-17.6), (13.2,-17.6), (6.6,-19.8), (8.8,-19.8), (11,-19.8)]

• 4: Used Gemini 2.5 Flash (built into Google Colab) to assist with completing the coding portion of the homework. I have some rough Python knowledge via a Codecademy course, which helped get things started (i.e., I did do some of the coding for this assignment).

All Gemini 2.5 Flash prompts are listed below:

• 5: Coordinating robot time slot with William & Mary node
• 6: Submitted Python file via assignment form (see screenshot below):

Python Form Submission Confirmation Screenshot

Post-Lab Questions

• Find and describe a published paper that utilizes the Opentrons or an automation tool to achieve novel biological applications.

  • The paper An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings was published in the journal Micromachines in 2024 and describes using simple Commercial Off-the-Shelf (COTS) reagents and lab equipment, along with an Opentrons robot, to create an automated workflow for detecting diseases in low-resource settings ². What’s interesting about the paper is that the workflow the researchers designed reduced the time for detecting a pathogen (in this case meningitis) by approx. 18% (total timne of 118 min.) with an almost 5.8x reduction in cost for sample processing ³. The total cost of to run 8 samples for meningitis detection was approx. $126 USD, a cost savings that matters in a low-resourced environments. The findings and extension of this paper’s workflow shows promise for decentralized disease detection in low-resource settings during future health security incidents. Except for opening and closing of tube lids, the following four steps of the autonated workflow were completed by the Opentrons robot:
    • DNA isolation with Dynabeads
      • Sample incubation
      • Washing step
      • DNA resuspension
    • DNA amplification
      • Recombinase Polymerase Amplification (RPA) mix preparatoon
      • RPA amplification
    • DNA digestion
      • Exonuclease digestion
    • DNA dtection
      • Preparation of Vertical Flow Microarray (VFM) solutions
      • Addition of samples to VFM
      • Signal enhancement

  Associated AI prompts to address this question included below:

• Write a description about what you intend to do with automation tools for your final project.
  • Phage isolation experiments generally require enriching bacterial strains, filtering out bacterial particles, pouring the phage-containing mixture in with fresh bacteria on agar, plating and re-plating phage plaques (areas of phage propagation and bacetrial destruction on agar), and characterizing the resulting phage plaques on the agar. My working thoughts are that I might actually be able to create a somewhat automated workflow a-la the paper referenced in the previous question to help with the filteration through characterization steps of a phage isolation experiment. This might involve using an Opentrons robot and COTS equipment to:
    • Handle bacterial liquids
    • (Maybe) use an Opentrons module to shake bacterial liquids and reagents
    • Operate centrifuge for spinning bacteria
    • Pour agar with phage plaques
    • Operate micropipettes for phage testing
    • Operate Thermocycler module for amplifying specific lysed areas
    • Rapidly run software to characterize novel phage DNA

Note: The maeterial above is not set in stone. It’s an outline of potential automation options for a potential final project (Space (LEO and beyond) or Suborbital Phage Isolation)

Associated AI prompts to address this question included below:

Final Project Ideas

• Submitted 3 Final Project ideas in my node’s section of the slide deck (see screenshot below):

All supporting prompts for Final Project Ideas Slide listed below

Week 4 HW: Protein Design Part 1

Part A: Conceptual Questions

5. Where did amino acids come from before enzymes that make them, and before life started?
   • Amino acids come from metabolic molecules within the cell. These metabolic molecules consist of carbon atom chemical backbone, inorganic nitrogen, and enzyme-facilitated chemical reactions. Before life as we know it started, amino acids originated from abiotic (not from living organisms) chemical reactions on Earth before the emergence of life as we know it. The chemical reactions occurred in the atmosphere, hydrothermal and oceanic vents, and via meteorite and comet (i.e., extraterrestrial) delivery

Supporting prompts for this section listed below:

Part B: Protein Analysis and Visualization

• I selected the beta-keratin 2 protein found in geckos, mainly because geckos seem really cool and I’m interested in the biomemetic properties of this protein for space-tolerant adhesives (gecko glues). The raw protein sequence is below:

  ABU98593.1 beta-keratin 2 [Gekko gecko] MAYCGPSFAIPSCASAPAIGFGSAGLGYGGYGGLHSGSIIGSGSPSFAIPSVASSPAVGFGSASFGHNSG VSSTSLGVLSGVNPSCINQIPPAEVLIQPPPSVVTLPGPILSATGEPVSVGGNTPCAVSYGGPGRVISGG SFGSLGGRLGSFGSGRRGSLILGRRGSFSNCYSPCN

• LOREM IPSUM *

Part C: Using ML-Based Protein Design Tools

Part D: Group Brainstorm on Bacteriophage Engineering