Week 1 HW: Final Project Ideas

Project ZP Freeze

(1) What you would like to biomanufacture and why? I would like to biomanufacture freezing responsive antifreeze proteins like Fr10 and Li16. I am interested in their use in helping to cryopreserve frogs, as well as their (or similar material) potential in helping to preserve animal tissues and organs. As a first stage, I merely wish to create more of them and similar. Source: Biggar KK, Kotani E, Furusawa T, Storey KB. Expression of freeze-responsive proteins, Fr10 and Li16, from freeze-tolerant frogs enhances freezing survival of BmN insect cells. FASEB J. 2013 Aug;27(8):3376-83. doi: 10.1096/fj.13-230573. Epub 2013 May 8. PMID: 23657819. https://pubmed.ncbi.nlm.nih.gov/23657819/ Cai, Q. and Storey, K.B. (1997) ‘Upregulation of a novel gene by freezing exposure in the freeze-tolerant wood frog (Rana sylvatica)’, Gene, 198(1–2), pp. 305–312. Available at: https://doi.org/10.1016/S0378-1119(97)00332-6. McNally, J.D., Wu, S.B., Sturgeon, C.M. and Storey, K.B. (2002) ‘Identification and characterization of a novel freezing-inducible gene, li16, in the wood frog Rana sylvatica’, The FASEB Journal, 16(8), pp. 902–904. Available at: https://doi.org/10.1096/fj.02-0017fje. Le Tri, D., Childers, C.L., Adam, M.K., Ben, R.N., Storey, K.B. and Biggar, K.K. (2019) ‘Characterization of ice recrystallization inhibition activity in the novel freeze-responsive protein Fr10 from freeze-tolerant wood frogs, Rana sylvatica’, Journal of Thermal Biology, 84, pp. 426–430. Available at: https://doi.org/10.1016/j.jtherbio.2019.07.030.

(2) What living system would you use? I would use a microbial system to produce my target, similar to how I produced these proteins via Project Z Freeze from HTBAA in the Spring of 2026. There’s already a wealth of knowledge towards use of microbial systems and prior work lists What’s required to go in would be a specified DNa sequence that encodes the target protein, and an expression plasmid would-d be used for this. Cells carrying this plasmid would receive media that supports their life functions. Outside of the bacteria growing and producing copies of said DNA, transcription would be be used to produce RNA from the tagert gene, followed by translation of the RNA into amino acids that could be further processed to produce to the anti-freeze proteins. The product would be recoeved through mechanical processes that break up the cell and separate the proteins from the rest of the cellular material. The output would hopefully be desired proteins in a defined, stabilizing buffer.

(3) How would you use automation? One automation technology that you would combine with your living system would be automated liquid handling, per tools like an Opentrons. I would appreciate the automation most to reduce variation in products produced through human error and save time. From there, automated screening is a given.

(4) How much would you need to make, and how long would it take? I do not know how much I would need, but I am fine with assuming a small batch and small set of labs. I’d estimate about a month, depending on the facilities available and quality of initial runs. (a) How much? A scale relevant for my project would be 10 labs, giving each 25 mg of purified Fr10 for a total of ~250 mg. Quick calc ~25 mg x 10 labs = ~250 mg.

(b) How long? For the production, it may follow based on this timeline: Preparation of cultures may take 1-4 days. Successful Expression and harvesting could take another 1-4 days. Purification to optimal values could take a solid week: 7 days. Nailing the entire process to a reasonable quality could take another 7 days. Preparing batches, testing shipping, and getting the packaging right could be worth another 2-5 days.
This timing puts us at about 18-27 days. I’m more comfortable saying a month to account for detours.

5. What don’t you know yet? 2-3 of the biggest technical unknowns might be, after answering if the product works in other physical systems tested:

• Have we produced enough for our target applications?
• What forms of the protein are best to construct?
• What are intentional products that could be made along the way to be wary about? After completing your analysis, identify the 2–3 biggest technical unknowns, bottlenecks, or assumptions in your proposed biomanufacturing system. What would you need to learn, measure, or experimentally determine to know whether your idea could actually work?

Week 2 HW: DNA Design

Part 0: Set up in Kernel Get oriented in the software tool before you design anything.

• Log in to Kernel and join the HTBAA 2026 workspace.

TBD

• Create a repository for your project, and inside it a folder named for you and your project, e.g. lastname-project.

Awaiting Kernel Access but the provisional name for the repository is: Palmer-Project_ZP_Freeze

• Spend some time exploring: open an existing part and an existing construct and notice the difference. Check out the different tools and ask Kernel AI some questions!

TBD

Deliverable for this part: a one-sentence note in your write-up with the name of your repository and folder, so we can find your work.

I’m awaiting Kernel Access but the provisional name for the repository is: Palmer-Project_ZP_Freeze

(TBD - Kernel Access needs to be supplied)

Part 1: Define your expression target

Start from the project you proposed in Homework #1 and pin down exactly what your cells need to make. Answer in your write-up:

• What molecule are you expressing?

A protein from Lithobates sylvaticus / Rana sylvatica (Wood Frog): FR10

Source: https://www.ncbi.nlm.nih.gov/protein/AAC60284.1

Paper:

Cai Q, Storey KB. Upregulation of a novel gene by freezing exposure in the freeze-tolerant wood frog (Rana sylvatica). Gene. 1997 Oct 1;198(1-2):305-12. doi: 10.1016/s0378-1119(97)00332-6. PMID: 9370296.

• What is the sequence? Give the protein or RNA sequence, or the specific gene, you will encode, and say where it comes from (a database accession such as UniProt or NCBI, a known part, or de novo). Cite it.

mkvlalvvlv iaisgleagv vkrdaqdplq qitdifqgis ktlqekfana eipsqtqelg akiqahgeti sasiqkwiee mvalskekls

Source: https://www.ncbi.nlm.nih.gov/protein/AAC60284.1

• What host or chassis? The living system from HW1, for example E. coli, S. cerevisiae, CHO or another mammalian line, or a cell-free system. Your host drives almost every part choice that follows.

The living system employed would be E. Coli.

• Where does the product need to go? Cytoplasm, secreted, membrane, or a compartment? This decides whether you need a signal peptide or targeting sequence.

The product needs to go to the cytoplasm.

Part 2: Design your genetic parts Every construct is built from parts. Decide which parts your target needs, then create or import each one in Kernel with the correct part type. At minimum, choose the elements below for your host.

[TBD]

For each part you use, record in Kernel (and note in your write-up):

The part type and a short name.

[TBD]

Its sequence and where it came from (a Kernel part, a database, or designed).

[TBD]

One sentence of justification, why this part, for this host, for this product.

[TBD]

You do not need to hand-design a backbone from scratch; you may reuse an existing one and say what it provides.

[TBD]

Part 3: Assemble your construct

Now put the parts together into a single construct in Kernel.

[TBD]

Create a new construct in your folder and add your parts in the correct 5’→3’ order for your host (for a basic expression cassette: promoter → RBS or 5’ UTR/Kozak → CDS → terminator, plus any signal peptide or tag, in the vector backbone).

[TBD]

Check the assembled sequence: the reading frame is intact, the start and stop codons are where you expect, and there are no accidental internal stops.

[TBD]

Look at the construct map Kernel renders and confirm the parts sit in the order and orientation you intended.

[TBD]

Deliverable for this part: your assembled construct in Kernel, plus an exported schematic of it in your write-up, with a brief description of the design.

[TBD]

Part 4: Optimize and quality-check

Use Kernel’s design tools on your coding sequence and construct, and interpret the results rather than just running them.

[TBD]

Codon-optimize your CDS for your chosen host. Compare before and after: what changed, and why does codon usage matter for expression in this organism? Note any constraints you applied (e.g. avoiding certain restriction sites, GC content).

[TBD]

Search your sequence (BLAST / sequence search) against known sequences. Is your CDS what you think it is? Is it identical to a natural gene, or novel? What is the closest match?

[TBD]

Run the safety screen on your construct. Summarize what it checks for and what it reports. If it flags something, explain whether it is expected for your design and how you would respond.

[TBD]

Deliverable for this part: a short paragraph per tool covering what you ran, what it returned, and what you concluded. Screenshots welcome.

[TBD]

Part 5: From design to build A sequence in software is not yet DNA. Using this week’s readings, reason about how your construct would actually be made. Answer in your write-up:

[TBD]

How would you build it? Would you order it as synthetic DNA, assemble it from smaller fragments (e.g. Gibson assembly), or build it from a pool of oligos synthesized on a chip? Justify your choice given your construct’s length and complexity.

[TBD]

What does synthesis constrain? Synthesis has error rates and struggles with certain sequences. Does your design contain anything hard to synthesize? How would error correction or fragment-based assembly change your approach?

[TBD]

Prototype vs. scale. Mirroring HW1: the way you’d build one construct to test your idea may differ from how you’d produce DNA at the scale your product needs. Briefly describe both if they differ.

Ground this in at least two of the assigned readings and cite them.

[TBD]

Part 6: What don’t you know yet?

[TBD]

As in Homework #1, close by naming the edges of your design. Identify the 2–3 biggest unknowns or risks in your construct. For example: Will the promoter give the right expression level? Will the protein fold and be active in this host? Will it be secreted? Is codon optimization enough, or do you need to tune it empirically?

[TBD]

For each, state how you would find out: the measurement, experiment, or design variant you would try next. A good answer here shows you know which decisions are still bets.

Week 3 HW: Cell-Free Protocols

Week 4 LAB: Cell-Free Manufacturing

Week 5 HW: Digital Microfluidics

Week 6 LAB: Microfluidic Manufacturing

Week 7 HW: Measurement & Assays

Week 8 LAB: Bacterial Cell Manufacturing

Week 9 HW: Genetic Circuit Design

Week 10 LAB: Mammalian Cell Manufacturing

Final Project