Week 1 HW: Final Project Ideas

(1) What you would like to biomanufacture and why?

With this project, I was really lost in what to make for a while, but I was definitely hoping to produce something within the realm of materials, so I ended up having a quick chat with some people in the lab about what I could do and was told about BC and how that could be a great starting point. I’m considering designing something related to tech, or improving it, whether that’s tactile interfacing, or extensions of HCI through hardware.

Describe the target product or output you would like to make. Why are you interested in making it?

I’ve recently noticed that if I work continuously using a trackpad or a traditional computer mouse (over 9 hours a day and longer than 3-4 days in a row), I get a clicking sound in my wrist. That is not a new issue (https://pmc.ncbi.nlm.nih.gov/articles/PMC12347275/), and there have been quite a few solutions, such as making more ergonomic designs, though that doesn’t entirely solve it.

Therefore, my hope is that there might be a possibility of improving upon the design of a current computer mouse. More specifically, turning it into a wearable(https://dl.acm.org/doi/abs/10.1109/38.250916, https://arxiv.org/html/2504.05983v1, https://appleinsider.com/articles/19/01/03/apple-researching-wearable-glove-input-device-to-simplify-interactions-with-ar-vr). I wouldn’t want it to be a full glove but rather something closer to a jewellery piece, possibly a nail ring with BC integrated as a sensor element (the bacterial cellulose pad would be housed inside a reusable metal ring casing and could be easily changed when degraded or the user would want a design refresh). That would allow for a solution to the fixed-position problem. My intent is not to create a new gestural way of communicating with computers but to use whatever familiarity users already have through using a mouse; keep it as simple and similar as possible, just move these gestures from the desk surface to mid air.

One interesting piece of reserach that I found as I was writingg out this proposal was the project called NailO: Fingernails as an Input Surface (https://www.hybridbody.human.cornell.edu/nailo). But within this research the actual product element is presented as a sticker which might make the product less durable long term. I think this could be easily improved by defining a structure around the sticker. As a part of my project, I also propose to unite the sensor and art layers through the use of BC

(2) What living system would you use? Propose at least one living-system manufacturing chassis that could produce your target—for example, a microbial, mammalian, or cell-free system. At a high level, describe how the system would make your target product. What goes into the system? What biological process or processes occur? What comes out?

For my product, I would use co-culture biomanufacturing: Komagataeibacter xylinus or rhaeticus (for the growth of the physical patch) and for the second one I would use an engineered melanin strain (chosen based on this paper https://www.sciencedirect.com/science/article/pii/S2772397626000407/ ).

So, for my bath I would need some cheap sugars to act as food then some copper to start the pigmentation process and some conductive salts so the final patch can conduct electricity and sense finger taps.

In terms of what’s gonna happen is that Komagataeibacter bacteria will hopefully eat that sugar then spin out the threads of cellulose at the surface and make a squishy sheet that I could use as a material. Another thing that’s going to happen is colouring the material directly inside the growth bath while it forms

(3) How would you use automation? Identify at least one automation technology that you would combine with your living system. This could include a large-scale Cloud Lab, a desktop liquid-handling robot such as an Opentrons, a programmable microfluidics platform such as Nuclera’s, or another automation technology. Describe what part of the biomanufacturing workflow you would automate and why. For example, you might automate liquid handling, culturing, assembly, screening, sampling, measurement, optimization, or another step.

In terms of automation, there are a few possible options here that I could use depending on availability

Route 1: Using remote access/programming, configuring a reconfigurable automation carts (RAC) module equipped with liquid-handling heads to automatically pipet different ratios of sugars, copper cofactors ($Cu^{2+}$), and conductive salts to multi-well plates. The hope is that its integrated microplate readers will automatically measure the electrical resistance and also(!) colour intensity (optical density) of each sample which would allow for easier ideation.

Route 2: Alternatively, I could use OT2 for a similar thing, though the measuring element would be more limited and manual

Route 3: Alternatively, I could also use chi.bio as the core culturing & screening Tool

(4) How much would you need to make, and how long would it take? Perform a back-of-the-envelope calculation estimating what it would take to manufacture your target at a meaningful scale.

For the proof of concept stage, I’d rather start small with 15 dual-finger gesture testing sets. For all 30 patches it would take 1 single 3.5-day cycle. + then for automated post-processing: glycerol plasticiser soaking, and precision laser cutting would take ~45 minutes. Though thats only the material stage for the ring insert tiles.

For the actual estimation element I do not have enough experience in production of a similar product so I ended up asking this question to Gemini in hopes to get a better answer Prompt: “Could you help me answer these questions for production of self-dyed, piezoresistive Bacterial Cellulose (BC) bio-Ring insert (a swappable biological sensor cartridge mounted within a reusable metallic ring chassis). Embedded with conductive biological dopants, where the grown BC pad acts as a strain/pressure sensor that converts subtle finger taps and pinches into Bluetooth mouse inputs (clicks, scrolls) without requiring a flat desk surface or restricting the wrist. For the manufacturing time can you combine both the biological material calculations and the parallel hardware fabrication timeline for a complete engineering assessment? (4) How much would you need to make, and how long would it take? Perform a back-of-the-envelope calculation estimating what it would take to manufacture your target at a meaningful scale. (a) How much? Define a scale relevant to your project and calculate approximately how much of your target product you would need to manufacture. For example, if you are producing a medicine, you might estimate the amount required to treat 1,000 people, everyone in Massachusetts, or everyone in the world. If you are producing a building material, you might calculate the amount required for one structure or an entire neighborhood. If you are producing an art or design artifact, define an appropriate scale yourself. Clearly show your calculation, including units, assumptions, and sources for important numbers.(b) How long? Using your proposed living system and automation technology, estimate how long it would take to manufacture that amount. Consider quantities such as production rate, yield, volume, number of parallel experiments or reactors, automation throughput, or whatever parameters are most appropriate for your system. You may discover that the automation technology you would use to prototype your system is very different from what you would use to manufacture at scale. If so, describe both. Again, we are looking for a reasonable engineering estimate. Show your assumptions and calculations.”

and here’s the answer that I got:

“(4) How much would you need to make, and how long would it take? (a) How Much?

Unit GeometryDimensions per Insert: $1.0\text{ cm} \times 1.0\text{ cm} \times 0.1\text{ cm}\text{ (1.0 mm wet thickness)} = \mathbf{0.10\text{ mL}}$ volume.Batch CalculationsPilot Prototype Scale (30 Units | 15 User-Testing Pairs):Volume: $30 \times 0.10\text{ mL} = \mathbf{3.0\text{ mL}}$ wet BC pellicle.Gross Area (with 20% laser scrap): $\frac{30\text{ cm}^2}{0.80} = \mathbf{37.5\text{ cm}^2} \quad (\approx 0.00375\text{ m}^2)$.Footprint: A single $6.2\text{ cm} \times 6.2\text{ cm}$ culture dish.Industrial Launch Scale (10,000 Units):Volume: $10,000 \times 0.10\text{ mL} = \mathbf{1.0\text{ Liter}}$ wet BC pellicle.Gross Area (with 20% laser scrap): $\frac{1.0\text{ m}^2}{0.80} = \mathbf{1.25\text{ m}^2}$.Footprint: 5 stacked $50\text{ cm} \times 50\text{ cm}$ static fermentation trays.

(b) How Long?

Parallel Manufacturing Pipeline (10,000 Units)Hardware fabrication and biological fermentation run concurrently:Biological Fermentation (Hours 0–84 | Primary Critical Path):Static Growth: Komagataeibacter + melanin co-culture incubates for 3.5 days (84 hours) in static tray racks to reach $1.0\text{ mm}$ thickness.Parallel Metal Ring & Electronics Fabrication (Hours 0–72):Metal Injection Molding (MIM) & Sintering: 48 hours.Anodizing & Surface Finishing: 12 hours.Flexible PCB & Contact Pins Assembly: 12 hours.Automated Post-Processing & Final Assembly (Hours 84–89):Washing, Glycerol Bath, & Laser Trimming: 3 hours.Robotic Ring Assembly: 2 hours.Total Turnaround TimeBecause metal hardware manufacturing (2.5 days) runs in parallel during biological growth, fermentation is the rate-limiting step.$$\text{Total Turnaround Time} \approx \mathbf{3.7\text{ days per 10,000-unit batch}}$$”

In terms of the volume, I would agree with the pilot prototype scale being 30 units, meaning 15 user-testing pairs and the industrial launch scale being 10,000 Units. For the manufacturing, I would, however be hesitant to say that 4 days would be realistic and would estimate it myself to take up to 3 months with all the sourcing.

5. What don’t you know yet? 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?

Okay, so there’s quite a few things I don’t entirely understand yet about using a nail bed as a surface. I’ve never done it before and I’d be curious to explore how actually compact the hardware can get. That will also define the design of the final product

Week 2 HW: DNA Design & Applications

Here’s a link to the created folder: https://kernel.asimov.com/htgaa-2026/repositories/repository/ac213b04-6666-415f-a63e-a313df44690a/folder/8dea22af-bfa2-4e02-9b92-9adb7c61c1a8 Repository: Lifefabs HTBAA 2026; folder: rakitina-bc.

Part 1: Define your expression target

Okay, so to reinstate it again what I want to do is to make a swappable bacterial cellulose (BC) sensor insert for a wearable, sort of mouse-like input device, with Komagataeibacter (possibly) producing the cellulose and an engineered melanin-producing organism providing pigmentation/conductive functionality. This also made me realise that I have 2 parts to my overall manufacturing system. One should be designed for enhancing/controlling bacterial cellulose production in Komagataeibacter xylinus, and then also there’s one for melanin production in engineered E. coli. As for the final material, I’m going to co-culture them to get a melanised BC sensor.

PATH A

Part 1

I’m expressing a protein called TyrMut_Pm, which type is an engineered acid-tolerant tyrosinase. What it does is catalyse reactions involved in melanin biosynthesis. The goal is to produce melanin during BC formation

https://researchportal.northumbria.ac.uk/en/publications/one-pot-production-of-melanised-bacterial-cellulose-through-ratio/

This sequence usually uses an E.coli https://www.sciencedirect.com/science/article/pii/S2772397626000407

So therefore it becomes: E. coli -> expresses TyrMut_Pm ->produces melanin -> melanin becomes incorporated into/associated with the BC-producing system -> melanised bacterial cellulose

Part 2

General plan here is to try to do this Promoter → RBS → TyrMut_Pm CDS → Terminator → Backbone

So for my promoter I’d probably want an inducable one so I could control it better and can’t really pick anything from the mammalian ones because that wouldnt make sense

So here are my present options BBa_R0062 pLambdaCI pLacI pTetR BBa_J23110 BBa_K346002 pTet BBa_J23101 BBa_J23119

Choices here are either inducable or constitutive like BBa_J23101 which would be a bit boring as it would start the reaction straight away but I would want it to be more customisable for use as a material. Therefore my choices are pLacI or pTetR.

I selected the characterized pTet promoter because it provides inducible control of TyrMut_Pm expression in E. coli. This allows melanin-producing enzyme expression to be initiated at a chosen stage of the biomanufacturing process instead of requiring constitutive expression throughout growth.

Then i needed rbs for which i chose BBa_B0034 because Kernel’s description specifically identifies it as an RBS used to define RBS efficiency and notes that there are no secondary structures within the provided RBS region. For my purposes, that’s a more straightforward generic translation-initiation part (more than an RBS specifically described as being for AmtR.)

for terminator BBa_B0015 — Terminator I selected BBa_B0015 because it is a characterized bacterial double terminator composed of BBa_B0010 and BBa_B0012, providing a pretty defined transcriptional endpoint for the TyrMut_Pm expression cassette.

For sequence search/part I found the original TyrMut_Pm from the paper and just used that.

Part 3

Here’s the design in Kernel that I ended up getting.

Part 4

For sequence search/part Match I searched the original TyrMut_Pm CDS against all available repositories and part types, requiring matches of at least 50 bp and 90% sequence identity. Kernel returned no matches under these criteria. Shorter searches produced only 7–8 bp matches, which were too short to establish identity. Thus, the Part Match search did not identify TyrMut_Pm as an existing Kernel part.

I then also optimised my protein

I simulated both the original and E. coli-codon-optimized TyrMut_Pm constructs under the same conditions. The predicted RNA and protein concentration profiles were essentially unchanged. This suggests that, within Kernel’s simulation model, the codon optimization did not substantially alter the predicted expression dynamics, even though it changed the underlying DNA sequence.

I also ran safety checks for both of these

Part 5

For an initial prototype, I would use TWIST or alternatively commercially synthesized DNA for the TyrMut_Pm coding sequence and assemble it with the expression backbone. Fragment-based assembly such as Gibson assembly would be better if the construct were divided into multiple fragments or if synthesis constraints made a single fragment inconvenient. (Gibson et al. (2009) and Carr et al. (2004))

Part 6

I haven’t done the other part of my manufacturing system yet a lot of questions about that

Week 3 HW: Cell-Free Protocols

A. COMPARE CELL-FREE REACTION COMPOSITIONS (20 minutes)

1. Why does the concentration of potassium glutamate and magnesium glutamate differ between compositions? Which is more sensitive?

Here’s how the data describes both on the https://coopetition.htgaa.org/cfps :

“Potassium is the main salt needed for ribosomes to work. Glutamate replaces chloride as the counter-ion because chloride inhibits some CFPS enzymes. Getting the right K⁺ concentration is one of the biggest tuning levers in CFPS. Reteplase Reteplase needs lower K(Glu) (~250 mM) than sfGFP (~354 mM) to reduce aggregation during synthesis”

“Magnesium holds ribosomes together and keeps tRNAs folded correctly. Too little and translation stalls; too much and proteins aggregate. One of the most sensitive optimization parameters in any CFPS formulation. Reteplase Oxidizing (DSB) conditions alter Mg²⁺ sensitivity — the reteplase target uses slightly less (~5.7 mM) than sfGFP (~7 mM).”

Magnesium one is more sensitive

2. Explain how a PEP+NTP reaction formulation is different from a Ribose+NMP reaction formulation.

So first things first what’s PEP. PEP is also known as “Phosphoenolpyruvate — a high-energy molecule that directly hands a phosphate group to ADP to make ATP via pyruvate kinase. The most direct and fast ATP regeneration system, used in PANOx-SP. It’s consumed stoichiometrically, so higher starting concentrations extend reaction time.”"

And Ribose is “a 5-carbon sugar that feeds into the pentose phosphate pathway, generating energy and nucleotide precursors. Identified as a major yield driver in RFopt at 50 mM — one of the highest concentrations of any supplement.”"

If NTP are using CTP GTP and UTP in the formulation; NMP are using AMP, CMP, GMP, UMP: they are a monophosphate precursor to the other ones. The second ones are cheaper but more lysete dependent -> needs more fine-tuning

3. Choose two cell-free reaction compositions from the literature, compare and contrast the choice of reagents and the concentration of reagents. Note: A recommended starting point would be to review a least one published formulation, such as PANOx-SP (Jewett & Swartz 2004), a cost-optimized formulation from Olsen et al. (2026), and/or an AI-designed formulation from Smith et al. (2026).

B. DESIGN ONE REACTION COMPOSITION FOR EACH OF THE THREE PROTEINS (40 minutes)

1. Sign in to coopetition.htgaa.org and publish your first unique 20 µL CFPS reaction composition for each of the following (don’t worry, you can resubmit later):

What if I add some ingredients that were not already in the mix to see whether there are some possible dependencies not entirely explored yet. I’ll keep the refrence baseline the same just add an additional reagent to see what happens OR Could combining successful strategies reveal a useful interaction that no individual reference recipe captures? will go about it purely visually might bring about more interesting results. One thing that stands out is Glucose in the references it might be worth it testing it separately

sfGFP

With this one, as I was looking at the other tables, I saw glucose used a lot. so I also added it to check whether adding glucose may provide an additional metabolic substrate that changes energy availability and sfGFP production.

PETase

..What if I test the glucose’s effect here too, as glucose might affect protein production too, but the important endpoint is functional enzyme activity. Though more protein doesn’t necessarily mean more active PETase.

Reteplase

Same here. Would adding glucose provide an additional metabolic substrate and improve reteplase production and functional activity?

3. As a HTBAA research team, we will have the opportunity to suggest new reagents to add to the cell-free reagent inventory. Contribute (or upvote) at least one reagent to the “Community Reagents” section of the website and provide a short rationale. Include in your homework documentation how you decided on that specific reagent and provide links to any relevant research.

Voted for FkpA (E. coli chaperone) seems fun!

Final Project