Week 1 HW: Principles and Practices

1. Glowing Leather as a pilot for decentralized biomanufacturing of goods Bacterially produced leather is currently in the stage of being scaled up in centralized biomanufacturing plants around the world utilizing waste feedstocks from agricultural sources. Smaller scale experiments utilize kombucha SCOBYs to produce bacterial leather however they face variability in leather quality due to different growing conditions, feedstock, and SCOBY relationships in regards to each individual member’s reaction to the feedstock/growing conditions. The genetic drift that the SCOBY undergoes specifically the K. xylinus also makes it unreliable for consistent bacterial leather production.

I am interested in exploring the development of an open source decentralized protocol to make growing bioleather easier, more climate resilient than growing cows, and more equitable than current centralized operations.

2. Policy goals Our application being more systems based, I would like to promote:
   1. equitable use
      1. making sure that this technology is developed to minimize regulatory/IP hurdles
      2. create this technology so that its deployment may be done frugally by the end users
   2. minimizing regulatory and physical harm to users
      1. create/implement unobtrusive and robust licensing to encourage use
      2. utilize GRAS and/or BSL-1 organisms to minimize negative effects due to possible user error
   3. creating eco friendly supply chains.
      1. Utilize existing waste streams
      2. seek to use processing methods that do not produce toxic byproducts
      3. carbon neutral power sources and manufacturing methods (blue-sky option)
3. Next, describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”)
   1. Govt Regulatory Agencies
      1. Establish regulations and standards for the importation and use of GMOs
      2. Existing monitoring infrastructure for registered users of GMOs
      3. Advocate for countries to utilize a simplified and straight forward regulations for BSL-1 organisms
   2. Distributed Operations Network + Strain Banks
      1. Create and distribute certified sachets with starter culture to create bacterial leathers
      2. utilize a fluorescent reporter to verify the status/activity/viability of any given strain
      3. propagate the strain bank to regional banks in order to establish supply chain resiliency.
   3. Global Academic researchers
      1. develop strains for bacterial leather production that comply with ease of use guidelines
      2. require publishing to open source databases and open source licensing
      3. create global networks of test labs for low throughput validations and characterization optimizing for low volume and rugged deployment
      4. iterate on protocols to promote cross-lab reproducibility

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.

Our action plan would first prioritize organizing a global collective of interested scientists and engineers (perhaps at HTGAA!) to develop the deployment protocol that takes into account regulatory actions, equitable use, and licensing considerations. This would allow us to organize the foundational work needed for deployment. Our main deliverable would be a published and verified protocol that would allow us to distribute our findings for use in an open source license.

We would then prioritize interfacing with regional regulatory bodies in order to further refine protocols for use in target regions using a BSL-1 organism.

In order to find revenue we would seek to target luxury goods and create a beachhead market and further fund distributed deployment of manufacturing. More research is needed but our main tradeoff would be international regulatory work would have to wait until initial revenue or funding is secured.

AI usage Summary can be found here

Week 2 Pre Reading

Homework Questions from Professor Jacobson: [Lecture 2 slides]

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 throughput error rate is 1:“10^6 and 10mS per base addition length of the human genome is 6.2 bil base pairs.

• Biology deals with this by having the polymerase be able to error correct in addition to having other proteins correct remaining errors. On slide 14 it describes the MutS repair system.

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?

• The average human protein is 1036bp (345 amino acids). Due to how the dna folds at different structures it can change the shape of the DNA and RNA cleavage sites are variable.

Homework Questions from Dr. LeProust: [Lecture 2 slides]

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

• Phosphoramidite.

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

• It is difficult to make because the coupling process process if it has an error it would be replicated 1 to 4 times and once you get up to 500 replications any errors would be increase the yield decay.

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

• Due to the replication issues one would make 40nt segments and stitch them together to create a 2000bp gene with less errors

Homework Question from George Church: [Lecture 2 slides]

Choose ONE of the following three questions to answer; and please cite AI prompts or paper citations used, if any.

[Using Google & Prof. Church’s slide #4] What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

• Phenylalanine, Valine, Threonine, Tryptophan, Isoleucine, Methionine, Histidine, Arginine, Leucine, Lysine

• Turns out in the Jurassic Park franchise they’re just eating Lysine from sources in the environment.

• Would be more prudent to use an amino acid that’s not available in nature and controllable.

Week 2 HW: DNA Read, Write, & Edit

Week 2 Homework

Part 1: Benchling & In-silico Gel Art

See this week’s lab protocol “Gel Art: Restriction Digests and Gel Electrophoresis” for details. Overview:

• Make a free account at benchling.com
• Import the Lambda DNA
• Simulate Restriction Enzyme Digestion with the following enzymes:
  • EcoRI
  • HindIII
  • BamHI
  • KpnI
  • EcoRV
  • SacI
  • SalI
• Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks
• You might find Ronan’s website a helpful tool for quickly iterating on designs!

Response

I was able to import all the restriction enzymes into benchling,

Part 3: DNA Design Challenge

3.1. Choose your protein.

In recitation, we discussed that you will pick a protein for your homework that you find interesting. Which protein have you chosen and why? Using one of the tools described in recitation (NCBI, UniProt, google), obtain the protein sequence for the protein you chose.

Example from group homework: >sp|P03609|LYS_BPMS2 Lysis protein OS=Escherichia phage MS2 OX=12022 PE=2 SV=1 METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLL EAVIRTVTTLQQLLT

Response

I used UniProt to source Cellulose synthase from Komagataeibacter xylinus as I wanted to investigate growing bacterial cellulose as leather substitute for my final project.

Source: UniProt P19449 — BCSA1_KOMXY

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

The Central Dogma discussed in class and recitation describes the process in which DNA sequence becomes transcribed and translated into protein. The Central Dogma gives us the framework to work backwards from a given protein sequence and infer the DNA sequence that the protein is derived from. Using one of the tools discussed in class, NCBI or online tools (google “reverse translation tools”), determine the nucleotide sequence that corresponds to the protein sequence you chose above.

Example: Get to the original sequence of phage MS2 L-protein from its genome — phage MS2 genome - Nucleotide - NCBI

Lysis protein DNA sequence: atggaaacccgattccctcagcaatcgcagcaaactccggcatctactaatagacgccggccattcaaacatgaggattacccatgtcgaagacaacaaagaagttcaactctttatgtattgatcttcctcgcgatctttctctcgaaatttaccaatcaattgcttctgtcgctactggaagcggtgatccgcacagtgacgactttacagcaattgcttacttaa

Response

I used the Sequence Manipulation Suite to do the reverse translation :)

Reverse translation of sp|P19449|BCSA1_KOMXY Cellulose synthase catalytic subunit [UDP-forming] OS=Komagataeibacter xylinus — 2262 base sequence of most likely codons:

atgagcgaagtgcagagcccggtgccggcggaaagccgcctggatcgctttagcaacaaa
attctgagcctgcgcggcgcgaactatattgtgggcgcgctgggcctgtgcgcgctgatt
gcggcgaccaccgtgaccctgagcattaacgaacagctgattgtggcgctggtgtgcgtg
ctggtgttttttattgtgggccgcggcaaaagccgccgcacccagatttttctggaagtg
ctgagcgcgctggtgagcctgcgctatctgacctggcgcctgaccgaaaccctggatttt
gatacctggattcagggcggcctgggcgtgaccctgctgatggcggaactgtatgcgctg
tatatgctgtttctgagctattttcagaccattcagccgctgcatcgcgcgccgctgccg
ctgccggataacgtggatgattggccgaccgtggatatttttattccgacctatgatgaa
cagctgagcattgtgcgcctgaccgtgctgggcgcgctgggcattgattggccgccggat
aaagtgaacgtgtatattctggatgatggcgtgcgcccggaatttgaacagtttgcgaaa
gattgcggcgcgctgtatattggccgcgtggatagcagccatgcgaaagcgggcaacctg
aaccatgcgattaaacgcaccagcggcgattatattctgattctggattgcgatcatatt
ccgacccgcgcgtttctgcagattgcgatgggctggatggtggcggatcgcaaaattgcg
ctgatgcagaccccgcatcatttttatagcccggatccgtttcagcgcaacctggcggtg
ggctatcgcaccccgccggaaggcaacctgttttatggcgtgattcaggatggcaacgat
ttttgggatgcgacctttttttgcggcagctgcgcgattctgcgccgcgaagcgattgaa
agcattggcggctttgcggtggaaaccgtgaccgaagatgcgcataccgcgctgcgcatg
cagcgccgcggctggagcaccgcgtatctgcgcattccggtggcgagcggcctggcgacc
gaacgcctgaccacccatattggccagcgcatgcgctgggcgcgcggcatgattcagatt
tttcgcgtggataacccgatgctgggcggcggcctgaaactgggccagcgcctgtgctat
ctgagcgcgatgaccagctttttttttgcgattccgcgcgtgatttttctggcgagcccg
ctggcgtttctgttttttggccagaacattattgcggcgagcccgctggcggtgctggcg
tatgcgattccgcatatgtttcatagcattgcgaccgcggcgaaagtgaacaaaggctgg
cgctatagcttttggagcgaagtgtatgaaaccaccatggcgctgtttctggtgcgcgtg
accattattaccctgatgtttccgagcaaaggcaaatttaacgtgaccgaaaaaggcggc
gtgctggaagaagaagaatttgatctgggcgcgacctatccgaacattatttttgcgggc
attatgaccctgggcctgctgattggcctgtttgaactgacctttcattttaaccagctg
gcgggcattgcgaaacgcgcgtatctgctgaactgcatttgggcgatgattagcctgatt
attctgctggcggcgattgcggtgggccgcgaaaccaaacaggtgcgctataaccatcgc
gtggaagcgcatattccggtgaccgtgtatgaagcgccggtggcgggccagccgaacacc
tatcataacgcgaccccgggcatgacccaggatgtgagcatgggcggcgtggcggtgcat
atgccgtggccggatgtgagcaccggcccggtgaaaacccgcattcatgcggtgctggat
ggcgaagaaattgatattccggcgaccatgctgcgctgcaaaaacggcaaagcggtgttt
acctgggataacaacgatctggataccgaacgcgatattgtgcgctttgtgtttggccgc
gcggatgcgtggctgcagtggaacaactatgaagatgatcgcccgctgcgcagcctgtgg
agcctgctgctgagcattaaagcgctgtttcgcaaaaaaggcaaaatgatggcgaacagc
cgcccgaaacgcaaaccgctggcgctgccggtggaacgccgcgaaccgaccaccattcag
agcggccagacccaggaaggcaaaattagccgcgcggcgagc

3.3. Codon optimization.

Once a nucleotide sequence of your protein is determined, you need to codon optimize your sequence. You may, once again, utilize google for a “codon optimization tool”. In your own words, describe why you need to optimize codon usage. Which organism have you chosen to optimize the codon sequence for and why?

Example from Codon Optimization Tool | Twist Bioscience while avoiding Type IIs enzyme recognition sites BsaI, BsmBI, and BbsI

Lysis protein DNA sequence with Codon-Optimization: ATGGAAACCCGCTTTCCGCAGCAGAGCCAGCAGACCCCGGCGAGCACCAACCGCCGCCGCCCGTTCAAACATGAAGATTATCCGTGCCGTCGTCAGCAGCGCAGCAGCACCCTGTATGTGCTGATTTTTCTGGCGATTTTTCTGAGCAAATTCACCAACCAGCTGCTGCTGAGCCTGCTGGAAGCGGTGATTCGCACAGTGACGACCCTGCAGCAGCTGCTGACCTAA

Response

Different organisms preferentially use certain codons over others due to varying tRNA availability. By optimizing the BcsA sequence for E. coli, we ensure the ribosomes can read the sequence efficiently and produce high yields of protein. I used Twist Bioscience’s Codon Optimization Tool, optimized for Escherichia coli, avoiding restriction sites BsaI, BsmBI, and BbsI.

Improved DNA[1]: GC=55.06%, CAI=0.93

ATGAGCGAAGTGCAGAGCCCGGTTCCGGCCGAAAGCCGCCTGGATCGTTTTAGCAACAAAATTCTGTCGCTGCGCGGCGCAAAC
TATATCGTGGGTGCGCTGGGCCTGTGCGCCCTGATTGCCGCGACCACCGTGACCCTGAGCATTAACGAACAGCTGATTGTGGCA
CTGGTGTGCGTGCTGGTGTTCTTCATTGTTGGTCGCGGCAAAAGCCGTCGTACCCAAATTTTTCTGGAAGTGCTTAGCGCCCTG
GTGAGCCTGCGCTATCTGACCTGGCGCCTGACCGAGACCCTGGACTTTGATACTTGGATTCAGGGTGGCCTGGGCGTGACCCTG
CTGATGGCAGAACTGTACGCGCTGTACATGCTGTTTCTGAGCTACTTTCAGACCATTCAGCCGCTGCATCGCGCCCCGCTGCCG
CTGCCGGATAACGTGGACGATTGGCCGACCGTGGATATCTTTATTCCGACCTATGATGAACAGCTGAGCATTGTTCGCCTGACC
GTGCTGGGCGCCCTGGGCATCGATTGGCCGCCGGATAAAGTGAACGTTTATATTCTGGATGATGGGGTTCGTCCGGAATTTGAA
CAGTTTGCGAAAGATTGCGGTGCGCTGTACATTGGCCGCGTGGATAGCAGCCATGCGAAAGCCGGCAATCTGAACCATGCCATT
AAACGCACCAGCGGCGATTACATTCTGATTCTGGATTGCGATCATATTCCGACCCGCGCCTTCCTGCAGATTGCGATGGGCTGG
ATGGTGGCCGACCGCAAAATTGCGCTGATGCAGACCCCGCACCATTTTTACAGCCCGGATCCGTTTCAACGCAATCTGGCCGTC
GGCTATCGTACCCCGCCGGAAGGCAACCTGTTTTACGGCGTTATTCAGGATGGCAATGATTTTTGGGATGCCACCTTCTTTTGC
GGTAGCTGCGCGATTCTGCGCCGTGAAGCCATTGAAAGCATTGGTGGCTTCGCGGTGGAAACCGTGACCGAAGATGCCCATACCG
CGCTGCGCATGCAGCGTCGCGGCTGGAGCACCGCCTATTTGCGCATTCCGGTGGCCAGCGGCCTGGCGACCGAACGTCTGACCA
CCCATATTGGTCAGCGCATGCGTTGGGCGCGCGGCATGATTCAGATTTTCCGCGTGGATAACCCGATGCTGGGCGGCGGTCTGA
AACTGGGCCAGCGCCTGTGCTATCTGAGCGCCATGACCAGCTTTTTTTTCGCGATTCCGCGCGTGATTTTTTTAGCCAGCCCAC
TGGCGTTTCTGTTCTTTGGCCAGAACATTATTGCCGCGTCGCCGCTGGCGGTGCTGGCCTATGCCATTCCGCATATGTTCCACA
GCATTGCGACCGCGGCGAAAGTGAACAAAGGCTGGCGTTACAGCTTTTGGAGCGAAGTGTACGAAACCACTATGGCCCTGTTTC
TGGTGCGTGTTACCATTATCACCCTGATGTTTCCGTCCAAAGGCAAATTCAACGTGACCGAAAAAGGCGGTGTTCTGGAAGAAG
AAGAATTTGATCTGGGCGCCACCTACCCGAACATTATTTTCGCCGGCATTATGACCCTGGGCCTGCTGATTGGTCTGTTTGAAC
TGACCTTTCATTTTAATCAGCTGGCGGGCATTGCGAAACGCGCGTACCTGCTGAATTGCATTTGGGCGATGATTAGCCTGATTAT
CCTGCTGGCGGCGATTGCCGTGGGCCGCGAAACCAAACAGGTGCGCTACAATCATCGTGTGGAAGCGCATATCCCGGTGACCGTA
TACGAAGCCCCGGTTGCCGGCCAGCCGAACACCTATCATAATGCAACGCCAGGTATGACGCAGGATGTCAGCATGGGCGGCGTGG
CGGTGCATATGCCGTGGCCGGATGTGAGCACCGGTCCGGTGAAAACCCGTATCCATGCGGTTCTGGACGGCGAAGAAATTGATAT
TCCGGCGACCATGTTACGCTGCAAAAATGGCAAAGCCGTTTTCACCTGGGATAACAACGATCTGGATACGGAACGTGATATTGTT
CGCTTTGTGTTTGGCCGTGCGGATGCGTGGCTGCAGTGGAACAATTATGAAGATGATCGCCCGCTGCGCAGCCTGTGGAGCCTGC
TGCTGAGCATTAAAGCACTGTTCCGCAAAAAAGGCAAAATGATGGCGAACAGCCGCCCGAAACGTAAACCGCTGGCACTGCCGGT
TGAACGTCGCGAACCGACGACCATTCAGTCGGGCCAAACCCAGGAAGGCAAAATTAGCCGTGCGGCCAGC

3.4. You have a sequence! Now what?

What technologies could be used to produce this protein from your DNA? Describe in your words the DNA sequence can be transcribed and translated into your protein. You may describe either cell-dependent or cell-free methods, or both.

Response

To produce cellulose synthase (BcsA) from Komagataeibacter xylinus in a lab setting, we can use a cell-dependent method with E. coli as the host organism. The codon-optimized BcsA gene is inserted into a plasmid, which is then introduced into E. coli via transformation. Once inside the cell, the E. coli transcription machinery reads the DNA and produces a messenger RNA (mRNA) copy of the BcsA gene. The ribosome then translates that mRNA into the BcsA protein by reading each 3-base codon and adding the corresponding amino acid. By cultivating the E. coli at scale, we can produce large quantities of cellulose synthase — and because we codon optimized the sequence for E. coli, this process happens efficiently. This approach also lets us modify the BcsA sequence to potentially engineer cellulose with different material properties for use in bacterial cellulose leather applications.

Part 4: Prepare a Twist DNA Synthesis Order

Response

Annotated Benchling insert fragment and Twist order below:

Twist Optimized Cellulose Synthase in Plasmid

Twist Optimized Order

Twist Optimized

Debugging DNA

Download BcsA Cellulose 2nd Try (.gb)

Download BcsA Cellulose Sequence (.pdf)

Part 5: DNA Read/Write/Edit

5.1 DNA Read

(i) What DNA would you want to sequence and why?

I want to read the sequence off of Komagataeibacter xylinus (the bacteria responsible for cellulose production in kombucha) to pull the cellulose synthase gene for further analysis.

I can also use this to validate my samples from Twist and QA my current batch of E. coli or other model bacteria I’m using.

(ii) What technology or technologies would you use to perform sequencing on your DNA and why?

I would use Oxford Nanopore sequencing to read my DNA.

1. Is your method first-, second- or third-generation or other? How so? Nanopore sequencing is a third generation technology that lets us read our DNA strands in one shot, without fragmentation or short-read reassembly.

2. What is your input? How do you prepare your input? List the essential steps.

   • Extract plasmid DNA from E. coli colonies
   • PCR amplify the insert region
   • Attach sequencing adapter molecules to DNA ends via ligation
   • Load onto the nanopore flow cell

3. What are the essential steps of your chosen sequencing technology — how does it decode the bases (base calling)? A protein nanopore sits in a membrane with an electrical current running through it. As a single DNA strand is ratcheted through the pore one base at a time, each base disrupts the current differently — A, T, G, C each produce a characteristic electrical signal. Software decodes this signal into a sequence.

4. What is the output of your chosen sequencing technology? Nanopore produces long reads up to 100kb+ at high accuracy, which means we can read our entire 2,472 bp plasmid insert in a single pass to verify the cellulose synthase gene transfer worked correctly.

5.2 DNA Write

(i) What DNA would you want to synthesize and why?

I want to write/manufacture the BcsA cellulose synthase expression cassette from Komagataeibacter xylinus, optimized for use in E. coli or yeast. I want to transfer the cellulose-producing capability into a faster but still cheap host organism to iterate on bacterial cellulose leather production.

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

I would perform my synthesis using phosphoramidite chemical synthesis via Twist Bioscience, cloned into the pTwist Amp High Copy vector.

1. What are the essential steps of your chosen synthesis method?

   • Split the DNA sequence into short overlapping oligonucleotides
   • Each oligo is synthesized chemically, one base at a time
   • Oligos are assembled via PCR-based assembly using overlapping regions
   • The assembled sequence is inserted into the plasmid vector
   • Colonies are sequence-verified and the correct clone is shipped

2. What are the limitations of your synthesis method in terms of speed, accuracy, scalability?

   • Cost scales up significantly for longer DNA sequences
   • Repetitive sequences and extreme GC content can cause synthesis failure — this is why our BcsA sequence was flagged as “Complex” initially
   • Error rate is roughly 1 per 500 bp before verification sequencing

5.3 DNA Edit

(i) What DNA would you want to edit and why?

I want to edit the BcsA gene to change how the amino acids control the polymerization of cellulose chains and how they form fibers. By making targeted mutations we could potentially change:

• Fiber diameter and crystallinity (affects texture and tensile strength)
• Production rate (catalytic efficiency)
• Surface chemistry (affects dyeability and water resistance for leather finishing)

(ii) What technology or technologies would you use to perform these DNA edits and why?

CRISPR-Cas9

1. How does your technology of choice edit DNA?

   • Design a guide RNA (gRNA) complementary to the target site in BcsA
   • The gRNA directs the Cas9 protein to the exact location in the DNA
   • Cas9 makes a double-strand break
   • Provide a repair template — a short single-stranded DNA oligo containing the desired mutation with homology arms flanking the cut site
   • The cell’s repair machinery integrates the changes automatically

2. What preparation do you need to do and what are the inputs?

   • Cas9 protein or plasmid expressing Cas9
   • Guide RNA designed to target the BcsA site (designed in Benchling, checked for off-target sites)
   • Repair template containing the desired mutation
   • Target cells (E. coli or K. xylinus directly)

3. What are the limitations of your editing method in terms of efficiency or precision?

   • Efficiency is low so we typically only 1-10% of cells receive the edit, requiring selection
   • Off-target cuts can introduce unintended mutations elsewhere in the genome
   • K. xylinus is significantly harder to work with than E. coli our transformation efficiency is low
   • For rapidly iterating BcsA variants, ordering new synthesized sequences from Twist may actually be more practical than CRISPR editing it gives us faster turnaround, no off-target risk, full sequence control

Week 3 HW: Lab Automation

Homework

Assignment: Python Script for Opentrons Artwork — DUE BY YOUR LAB TIME!

Assignees for this section

Your task this week is to Create a Python file to run on an Opentrons liquid handling robot.

0. Review this week’s recitation and this week’s lab for details on the Opentrons and programming it.
1. Generate an artistic design using the GUI at opentrons-art.rcdonovan.com.

Response

https://opentrons-art.rcdonovan.com/?id=32iqzh4w9m44o5k

2. Using the coordinates from the GUI, follow the instructions in the HTGAA26 Opentrons Colab to write your own Python script which draws your design using the Opentrons.

   • You may use AI assistance for this coding — Google Gemini is integrated into Colab (see the stylized star bottom center); it will do a good job writing functional Python, while you probably need to take charge of the art concept.
   • If you’re a proficient programmer and you’d rather code something mathematical or algorithmic instead of using your GUI coordinates, you may do that instead.

   Ask for help early!

   If you are having any trouble with scripting, contact your TAs as soon as possible for help.
   Do not wait until your scheduled robot time slot or you may not be able to complete this assignment!

3. If the Python component is proving too problematic even with AI and human assistance, download the full Python script from the GUI website and submit that:

   

   Use the download icon pointed to by the red arrow in this diagram.

4. If you use AI to help complete this homework or lab, document how you used AI and which models made contributions.

5. Sign up for a robot time slot if you are at MIT/Harvard/Wellesley or at a Node offering Opentrons automation. The Python script you created will be run on the robot to produce your work of art!

   • At MIT/Harvard? Lab times are on Thursday Feb.19 between 10AM and 6PM.
   • At other Nodes? Please coordinate with your Node.

6. Submit your Python file via this form.

Response

I utilized gemini pro 3.5 and I was able to have it create the nested for loops needed to dispense on a per color basis.

Colab available here: Open My Opentrons Colab Script

Post-Lab Questions — DUE BY START OF FEB 24 LECTURE

Assignees for this section

One of the great parts about having an automated robot is being able to precisely mix, deposit, and run reactions without much intervention, and design and deploy experiments remotely.

For this week, we’d like for you to do the following:

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

Response

https://pmc.ncbi.nlm.nih.gov/articles/PMC11933169/ Enhanced production of bacterial cellulose with a mesh dispenser vessel-based bioreactor.

From my reading of the paper the team created structures for the Komagataeibacter out of mesh and automated nutrient dispensing, the quality and speed of Komagataeibacter’s cellulose production were significantly improved over the control of pellicle formation to produce the bacterial leather.

Loh J, Arnardottir T, Gilmour K, Zhang M, Dade-Robertson M. Enhanced production of bacterial cellulose with a mesh dispenser vessel-based bioreactor. Cellulose (Lond). 2025;32(4):2209-2226. doi: 10.1007/s10570-024-06367-w. Epub 2025 Jan 29. PMID: 40144312; PMCID: PMC11933169.

2. Write a description about what you intend to do with automation tools for your final project. You may include example pseudocode, Python scripts, 3D printed holders, a plan for how to use Ginkgo Nebula, and more. You may reference this week’s recitation slide deck for lab automation details.

While your description/project idea doesn’t need to be set in stone, we would like to see core details of what you would automate. This is due at the start of lecture and does not need to be tested on the Opentrons yet.

Example 1: You are creating a custom fabric, and want to deposit art onto specific parts that need to be intertwined in odd ways. You can design a 3D printed holder to attach this fabric to it, and be able to deposit bio art on top. Check out the Opentrons 3D Printing Directory.

Example 2: You are using the cloud laboratory to screen an array of biosensor constructs that you design, synthesize, and express using cell-free protein synthesis.

1. Echo transfer biosensor constructs and any required cofactors into specified wells.
2. Bravo stamp in CPFS reagent master mix into all wells of a 96-well / 384-well plate.
3. Multiflo dispense the CFPS lysate to all wells to start protein expression.
4. PlateLoc seal the plate.
5. Inheco incubate the plate at 37°C while the biosensor proteins are synthesized.
6. XPeel remove the seal.
7. PHERAstar measure fluorescence to compare biosensor responses.

Response

For my final project I can see the possibility of the Opentrons helping by inserting the plasmids into my target organism, automating PCRs for sequencing, and being able to test different combinations of variables very quickly such as growth media or quantity of plasmids needed to successfully express the cellulose synthase within my target organism.

For broader automation goals I would like to also implement automated nutrient delivery systems and leather harvesting systems in order to reduce human oversight of microbial leather production. I am thinking of implementing fluid transfer pumps, temperature controls, and computer vision models to monitor the growth of bacterial leather in my target organism. This would be done with custom made hardware and implementing transfer learning for the vision policies.

Final Project Ideas — DUE BY START OF FEB 24 LECTURE

Assignees for this section

As explained in this week’s recitation, add 1-3 slides with 3 ideas you have for an Individual Final Project in the appropriate slide deck for MIT/Harvard/Wellesley students or for Commited Listeners. Be sure to put your name on your slide(s); for CLs, also put your city and country on your slide(s) and be sure you’re putting your slide(s) in your Node’s section of the deck.

Response

Automated microbial leather production

• Utilizing sensors to monitor target organism (Komagataeibacter) health and nutrient conditions in growth tank

• Leveraging fluidics automations for a custom nutrient delivery fluidics system

• Computer vision learning to develop contamination detection models

Expressing cellulose growth in model organisms

• Utilizing Twist Biosci gene synthesis we can take the Komagataeibacter’s cellulose synthase and then insert that plasmid into a model organism such as yeast or E. coli to test whether a fast-growing model organism can produce bacterial cellulose.

Adapting fluorescent protein expression in Komagataeibacter

• We can genetically modify Komagataeibacter to express a fluorescent protein and see if that might carry over and last into the bacterial leather after the post processing of the pellicle.
• We could use gene synthesis to produce the required DNA strands prepackaged in a plasmid from Twist Biosci.
• The transformation of the plasmid into the Komagataeibacter can be automated by the Opentrons system in order to test variations on how we approach gaining fluorescence within Komagataeibacter

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project