Week 2 HW: DNA Read, Write, and Edit

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Part 0: Basics of Gel Electrophoresis

Attend or watch all lecture and recitation videos. Optionally watch bootcamp

Part 1: Benchling & In-silico Gel Art

See the Gel Art: Restriction Digests and Gel Electrophoresis protocol 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!
  • In this part, I imported The complete 48,502 bp linear genome of bacteriophage lambda from NCBI GenBank into Benchling. This sequence corresponds to the Lambda DNA sold by NEB (N3011) and will be used for in-silico restriction digestion.
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  • Then simulated restriction enzyme digestion using EcoRI, HindIII, BamHI, KpnI, EcoRV, SacI, and SalI. By running in-silico gel electrophoresis . The resulting virtual gel shows discrete bands corresponding to these fragments, which demostrates how sequence information maps to physical separation in gel electrophoresis. Virtual digest gel Virtual digest gel

  • To create a pattern in the style of Paul Vanouse’s work, I experimented with different combinations of restriction enzymes to control the gel band patterns. By adjusting the number and length of the resulting DNA fragments, I explored how these parameters influence the final visual outcome. Through this process, I ultimately obtained a gel pattern resembling a butterfly shape. Image Image

Gel pattern in style of Paul Vanouse’s work Gel pattern in style of Paul Vanouse’s work
  • This helped me understand how restriction digests and gels work before doing any real lab experiment. I treated this as both a technical exercise and a creative exploration, inspired by DNA gel art concepts.
Part 2: Gel Art - Restriction Digests and Gel Electrophoresis

Assignees for the following sections MIT/Harvard students Required Committed Listeners Optional (for those with Lab access) Perform the lab experiment you designed in Part 1 and outlined in the Gel Art: Restriction Digests and Gel Electrophoresis protocol.

Part 3: DNA Design Challenge

Assignees for the following sections MIT/Harvard students Required Committed Listeners Required

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 our group homework, you may notice the particular format — The example below came from UniProt] sp|P03609|LYS_BPMS2 Lysis protein OS=Escherichia phage MS2 OX=12022 PE=2 SV=1 METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLL EAVIRTVTTLQQLLT

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

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

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.

3.5. [Optional] How does it work in nature/biological systems?

  1. Describe how a single gene codes for multiple proteins at the transcriptional level.
  2. Try aligning the DNA sequence, the transcribed RNA, and also the resulting translated Protein!!! See example below. [Example shows the biomolecular flow in central dogma from DNA to RNA to Protein] Special note that all “T” were transcribed into “U” and that the 3-nt codon represents 1-AA. Rearranged snapshot of MS2 L-protein information flow from DNA to RNA to Protein. Captured from Ice’s Benchling and stitched together in a ppt
  • For the DNA design challenge, I chose a protein related to my project interest in engineered probiotics and conditional enzyme release in the gut.The enzyme β-galactosidase is well-characterized and commonly expressed in Escherichia coli, making it an ideal candidate for computational DNA design and expression modeling.
  • I first searched online database UniProt to obtain the amino acid sequence of the protein.
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  • the amino acid equence was as follow:
>sp|P00722|BGAL_ECOLI Beta-galactosidase OS=Escherichia coli (strain K12) OX=83333 GN=lacZ PE=1 SV=2
MTMITDSLAVVLQRRDWENPGVTQLNRLAAHPPFASWRNSEEARTDRPSQQLRSLNGEWR
FAWFPAPEAVPESWLECDLPEADTVVVPSNWQMHGYDAPIYTNVTYPITVNPPFVPTENP
TGCYSLTFNVDESWLQEGQTRIIFDGVNSAFHLWCNGRWVGYGQDSRLPSEFDLSAFLRA
GENRLAVMVLRWSDGSYLEDQDMWRMSGIFRDVSLLHKPTTQISDFHVATRFNDDFSRAV
LEAEVQMCGELRDYLRVTVSLWQGETQVASGTAPFGGEIIDERGGYADRVTLRLNVENPK
LWSAEIPNLYRAVVELHTADGTLIEAEACDVGFREVRIENGLLLLNGKPLLIRGVNRHEH
HPLHGQVMDEQTMVQDILLMKQNNFNAVRCSHYPNHPLWYTLCDRYGLYVVDEANIETHG
MVPMNRLTDDPRWLPAMSERVTRMVQRDRNHPSVIIWSLGNESGHGANHDALYRWIKSVD
PSRPVQYEGGGADTTATDIICPMYARVDEDQPFPAVPKWSIKKWLSLPGETRPLILCEYA
HAMGNSLGGFAKYWQAFRQYPRLQGGFVWDWVDQSLIKYDENGNPWSAYGGDFGDTPNDR
QFCMNGLVFADRTPHPALTEAKHQQQFFQFRLSGQTIEVTSEYLFRHSDNELLHWMVALD
GKPLASGEVPLDVAPQGKQLIELPELPQPESAGQLWLTVRVVQPNATAWSEAGHISAWQQ
WRLAENLSVTLPAASHAIPHLTTSEMDFCIELGNKRWQFNRQSGFLSQMWIGDKKQLLTP
LRDQFTRAPLDNDIGVSEATRIDPNAWVERWKAAGHYQAEAALLQCTADTLADAVLITTA
HAWQHQGKTLFISRKTYRIDGSGQMAITVDVEVASDTPHPARIGLNCQLAQVAERVNWLG
LGPQENYPDRLTAACFDRWDLPLSDMYTPYVFPSENGLRCGTRELNYGPHQWRGDFQFNI
SRYSQQQLMETSHRHLLHAEEGTWLNIDGFHMGIGGDDSWSPSVSAEFQLSAGRYHYQLV
WCQK
  • After selecting the protein, I converted the amino acid sequence of β-galactosidase (1024 residues) into the corresponding DNA sequence using the Sequence Manipulation Suite Reverse Translate tool. Because the genetic code is degenerate, multiple codons can encode the same amino acid. The resulting 3072 bp DNA sequence represents one valid nucleotide sequence capable of encoding the β-galactosidase protein.
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  • the resulted DNA sequence was as follow:
>reverse translation of sp|P00722|BGAL_ECOLI Beta-galactosidase OS=Escherichia coli (strain K12) OX=83333 GN=lacZ PE=1 SV=2 to a 3072 base sequence of most likely codons.
atgaccatgattaccgatagcctggcggtggtgctgcagcgccgcgattgggaaaacccg
ggcgtgacccagctgaaccgcctggcggcgcatccgccgtttgcgagctggcgcaacagc
gaagaagcgcgcaccgatcgcccgagccagcagctgcgcagcctgaacggcgaatggcgc
tttgcgtggtttccggcgccggaagcggtgccggaaagctggctggaatgcgatctgccg
gaagcggataccgtggtggtgccgagcaactggcagatgcatggctatgatgcgccgatt
tataccaacgtgacctatccgattaccgtgaacccgccgtttgtgccgaccgaaaacccg
accggctgctatagcctgacctttaacgtggatgaaagctggctgcaggaaggccagacc
cgcattatttttgatggcgtgaacagcgcgtttcatctgtggtgcaacggccgctgggtg
ggctatggccaggatagccgcctgccgagcgaatttgatctgagcgcgtttctgcgcgcg
ggcgaaaaccgcctggcggtgatggtgctgcgctggagcgatggcagctatctggaagat
caggatatgtggcgcatgagcggcatttttcgcgatgtgagcctgctgcataaaccgacc
acccagattagcgattttcatgtggcgacccgctttaacgatgattttagccgcgcggtg
ctggaagcggaagtgcagatgtgcggcgaactgcgcgattatctgcgcgtgaccgtgagc
ctgtggcagggcgaaacccaggtggcgagcggcaccgcgccgtttggcggcgaaattatt
gatgaacgcggcggctatgcggatcgcgtgaccctgcgcctgaacgtggaaaacccgaaa
ctgtggagcgcggaaattccgaacctgtatcgcgcggtggtggaactgcataccgcggat
ggcaccctgattgaagcggaagcgtgcgatgtgggctttcgcgaagtgcgcattgaaaac
ggcctgctgctgctgaacggcaaaccgctgctgattcgcggcgtgaaccgccatgaacat
catccgctgcatggccaggtgatggatgaacagaccatggtgcaggatattctgctgatg
aaacagaacaactttaacgcggtgcgctgcagccattatccgaaccatccgctgtggtat
accctgtgcgatcgctatggcctgtatgtggtggatgaagcgaacattgaaacccatggc
atggtgccgatgaaccgcctgaccgatgatccgcgctggctgccggcgatgagcgaacgc
gtgacccgcatggtgcagcgcgatcgcaaccatccgagcgtgattatttggagcctgggc
aacgaaagcggccatggcgcgaaccatgatgcgctgtatcgctggattaaaagcgtggat
ccgagccgcccggtgcagtatgaaggcggcggcgcggataccaccgcgaccgatattatt
tgcccgatgtatgcgcgcgtggatgaagatcagccgtttccggcggtgccgaaatggagc
attaaaaaatggctgagcctgccgggcgaaacccgcccgctgattctgtgcgaatatgcg
catgcgatgggcaacagcctgggcggctttgcgaaatattggcaggcgtttcgccagtat
ccgcgcctgcagggcggctttgtgtgggattgggtggatcagagcctgattaaatatgat
gaaaacggcaacccgtggagcgcgtatggcggcgattttggcgataccccgaacgatcgc
cagttttgcatgaacggcctggtgtttgcggatcgcaccccgcatccggcgctgaccgaa
gcgaaacatcagcagcagttttttcagtttcgcctgagcggccagaccattgaagtgacc
agcgaatatctgtttcgccatagcgataacgaactgctgcattggatggtggcgctggat
ggcaaaccgctggcgagcggcgaagtgccgctggatgtggcgccgcagggcaaacagctg
attgaactgccggaactgccgcagccggaaagcgcgggccagctgtggctgaccgtgcgc
gtggtgcagccgaacgcgaccgcgtggagcgaagcgggccatattagcgcgtggcagcag
tggcgcctggcggaaaacctgagcgtgaccctgccggcggcgagccatgcgattccgcat
ctgaccaccagcgaaatggatttttgcattgaactgggcaacaaacgctggcagtttaac
cgccagagcggctttctgagccagatgtggattggcgataaaaaacagctgctgaccccg
ctgcgcgatcagtttacccgcgcgccgctggataacgatattggcgtgagcgaagcgacc
cgcattgatccgaacgcgtgggtggaacgctggaaagcggcgggccattatcaggcggaa
gcggcgctgctgcagtgcaccgcggataccctggcggatgcggtgctgattaccaccgcg
catgcgtggcagcatcagggcaaaaccctgtttattagccgcaaaacctatcgcattgat
ggcagcggccagatggcgattaccgtggatgtggaagtggcgagcgataccccgcatccg
gcgcgcattggcctgaactgccagctggcgcaggtggcggaacgcgtgaactggctgggc
ctgggcccgcaggaaaactatccggatcgcctgaccgcggcgtgctttgatcgctgggat
ctgccgctgagcgatatgtataccccgtatgtgtttccgagcgaaaacggcctgcgctgc
ggcacccgcgaactgaactatggcccgcatcagtggcgcggcgattttcagtttaacatt
agccgctatagccagcagcagctgatggaaaccagccatcgccatctgctgcatgcggaa
gaaggcacctggctgaacattgatggctttcatatgggcattggcggcgatgatagctgg
agcccgagcgtgagcgcggaatttcagctgagcgcgggccgctatcattatcagctggtg
tggtgccagaaa
  • After reverse translation, I verified the identity of the resulting nucleotide sequence by performing a BLASTn search against the reference lacZ gene from Escherichia coli K-12. The alignment showed 100% query coverage with an E-value of 0.0, confirming a highly significant match. The percent identity was ~84%, which is expected because reverse translation produces a synonymous DNA sequence that differs at the codon level while still encoding the same β-galactosidase protein. This result confirmed that the reverse-translated sequence correctly corresponds to the lacZ gene.
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Next, I performed codon optimization of the sequence originates from E. coli K-12 to improve expression efficiency in a Lactobacillus probiotic strain (delbrueckii subsp. Bulgaricus), as this organism is the intended chassis for conditional lactase expression in the human gut, to ensure efficient translation in the final probiotic host organism. Codon optimization was performed using a host-specific algorithm using the Vector Builder codon orimisation tool that adjusts synonymous codon usage to match the preferred codons of L. delbrueckii while preserving the original amino acid sequence.

Why codon optimization is necessary?

Codon optimization is required because different organisms preferentially use different synonymous codons. Optimizing the DNA sequence for the codon usage of the target host improves ribosome efficiency, protein yield, and reduces translational stalling.

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  • the resulted optimised sequence is as following:

Host organism: Lactobacillus delbruekii susbsp. Bulgaricus ATCC 11842 = JCM 1002 Original Sequence: GC=59.80%, CAI=0.72 Optimized Sequence: GC=60.16%, CAI=0.89

Improved DNA[1]: GC=60.16%, CAI=0.89
ATGACTATGATCACCGACAGCCTGGCAGTTGTTTTGCAACGGCGGGACTGGGAAAACCCGGGCGTCACTCAGTTGAACCGGCTGGCCGCCCACCCACCATTTGCCAGCTGGCGCAACTCCGAAGAAGCCCGGACCGACCGGCCGAGCCAGCAACTGAGAAGCTTGAACGGCGAATGGCGTTTCGCCTGGTTTCCGGCCCCGGAAGCCGTCCCAGAAAGCTGGTTGGAATGCGACCTCCCGGAAGCCGATACCGTCGTGGTGCCGAGCAACTGGCAAATGCACGGCTATGACGCCCCCATCTACACCAATGTTACCTACCCAATTACCGTCAACCCGCCATTTGTCCCGACCGAAAACCCGACTGGTTGCTATAGCTTGACCTTCAACGTTGACGAAAGCTGGCTGCAAGAAGGCCAGACCCGCATTATTTTTGACGGCGTTAACAGCGCCTTCCACTTGTGGTGCAACGGCCGCTGGGTCGGCTACGGCCAGGACAGCCGCTTGCCATCCGAATTTGACCTGAGTGCTTTCTTGCGGGCCGGCGAAAACCGTCTGGCCGTCATGGTCCTGCGCTGGAGCGACGGCAGCTACCTGGAAGACCAAGACATGTGGCGGATGTCCGGCATTTTCCGGGACGTCAGCCTGCTGCACAAGCCGACCACCCAGATTTCCGACTTTCACGTTGCAACCCGGTTCAACGACGACTTCTCTCGGGCTGTGCTGGAAGCTGAAGTCCAGATGTGCGGCGAATTGCGGGACTACCTGCGGGTTACTGTTTCATTGTGGCAGGGCGAAACCCAGGTTGCCTCAGGCACCGCCCCGTTTGGCGGTGAAATTATCGACGAACGCGGCGGGTACGCCGACCGGGTTACCTTGAGACTGAACGTGGAAAACCCGAAGTTGTGGAGCGCCGAAATCCCAAATCTGTACCGCGCCGTCGTCGAATTGCACACCGCTGACGGCACCCTGATCGAAGCCGAAGCCTGCGACGTTGGCTTCCGGGAAGTCCGCATCGAAAACGGCTTGCTGCTCCTGAACGGCAAGCCACTGCTGATCCGGGGCGTTAACCGGCACGAACACCACCCATTGCACGGCCAAGTCATGGACGAACAGACTATGGTCCAGGACATCCTGCTGATGAAGCAGAACAACTTCAACGCTGTTCGTTGCTCACACTATCCAAACCATCCACTGTGGTACACTCTGTGCGACCGGTACGGCCTGTACGTTGTGGACGAAGCCAACATCGAAACTCACGGCATGGTTCCGATGAACCGGCTGACCGACGACCCGAGATGGCTGCCAGCCATGAGCGAACGGGTTACTCGCATGGTTCAACGCGACCGGAACCACCCATCCGTTATTATCTGGAGCCTGGGGAACGAAAGCGGCCACGGCGCCAATCACGACGCTCTGTACCGGTGGATCAAGTCCGTCGACCCATCCCGCCCTGTTCAGTACGAAGGCGGCGGCGCCGATACGACCGCCACCGACATCATCTGCCCAATGTACGCCCGGGTTGATGAAGACCAGCCGTTTCCGGCTGTCCCAAAGTGGAGCATCAAGAAGTGGCTGAGCCTGCCAGGCGAAACTCGGCCGCTGATCCTGTGCGAATACGCCCACGCCATGGGCAACTCCCTGGGCGGCTTTGCCAAGTACTGGCAGGCTTTTCGCCAGTATCCACGGTTGCAGGGCGGCTTTGTTTGGGACTGGGTCGACCAAAGCCTGATCAAGTACGACGAAAACGGCAACCCGTGGAGCGCCTACGGCGGCGACTTTGGCGACACCCCGAACGACCGCCAGTTTTGCATGAACGGTCTGGTTTTCGCTGACCGGACGCCACACCCGGCCCTGACCGAAGCCAAGCACCAGCAGCAGTTCTTCCAGTTCCGGCTGTCAGGCCAGACCATCGAAGTGACTAGCGAATACCTGTTTCGCCACTCCGACAACGAATTGTTGCACTGGATGGTCGCCCTGGACGGCAAGCCACTGGCCAGCGGCGAAGTTCCGCTGGACGTTGCCCCACAGGGCAAGCAGCTGATCGAATTGCCGGAACTGCCGCAGCCGGAAAGCGCCGGCCAACTGTGGCTGACTGTTCGGGTCGTTCAGCCGAACGCCACTGCCTGGTCTGAAGCCGGGCACATCTCAGCCTGGCAGCAGTGGCGCCTGGCCGAAAACTTGAGCGTTACGCTGCCGGCCGCCAGCCACGCCATCCCACACCTGACTACTAGCGAAATGGACTTTTGCATCGAATTGGGCAACAAGCGGTGGCAATTCAACCGGCAGAGCGGCTTTCTGAGCCAGATGTGGATCGGCGACAAGAAGCAGTTGCTGACCCCACTGCGGGATCAGTTCACCCGGGCCCCGCTGGACAACGACATCGGCGTCAGCGAAGCCACTCGGATCGACCCAAACGCCTGGGTCGAACGCTGGAAGGCCGCCGGCCACTACCAGGCCGAAGCCGCTCTGCTGCAATGTACCGCTGATACGCTGGCTGACGCCGTCTTGATTACTACCGCTCACGCCTGGCAACACCAGGGCAAGACTTTGTTTATCAGCCGGAAGACCTACCGGATTGACGGCAGCGGTCAGATGGCCATCACAGTCGATGTCGAAGTTGCCAGCGACACCCCGCACCCGGCACGGATCGGCCTGAACTGCCAGCTGGCCCAGGTTGCCGAACGGGTTAACTGGCTGGGCCTGGGCCCTCAGGAAAACTACCCAGACCGTTTGACGGCTGCCTGCTTTGACCGGTGGGACTTACCGTTGAGCGATATGTACACTCCATACGTCTTTCCGTCCGAAAACGGCCTGCGGTGCGGCACCAGAGAACTGAACTATGGCCCGCACCAGTGGCGCGGTGACTTTCAATTCAACATCAGCCGGTACTCCCAGCAGCAGTTGATGGAAACCAGCCACCGCCACCTGCTGCACGCCGAAGAAGGGACGTGGTTGAACATCGACGGCTTTCACATGGGCATCGGCGGCGACGACTCATGGAGCCCGAGCGTTAGCGCTGAATTCCAGTTGAGCGCCGGCCGGTACCACTACCAGTTGGTTTGGTGCCAGAAG
  • To produce the protein from this DNA sequence, I would use a cell-dependent expression system based on bacterial transformation and expression. In this approach, This gene is then placed into an expression cassette with the necessary regulatory elements so it can be used by a biological system.
  • To produce the protein, I would use a cell-dependent expression system through bacterial cloning. The designed DNA sequence is inserted into a plasmid and introduced into a bacterial host by transformation. Inside the cell, the gene is transcribed into mRNA under the control of the selected promoter. The mRNA is then translated by ribosomes, which read the codons starting at the start codon and assemble the corresponding amino acids into the lactase protein. This approach follows the natural flow of genetic information (DNA to RNA to protein) and allows controlled production of the enzyme in living cells.
Part 4: Prepare a Twist DNA Synthesis Order

Assignees for the following sections MIT/Harvard students Required Committed Listeners Required This is a practice exercise, not necessarily your real Twist order!

4.1. Create a Twist account, and Benchling account

4.2. Build Your DNA Insert Sequence For example, let’s make a sequence that will make E. coli glow fluorescent green under UV light by constitutively (always) expressing sfGFP (a green fluorescent protein): In Benchling, select New DNA/RNA sequence Give your insert sequence a name and select DNA with a Linear topology (this is a linear sequence that will be inserted into a circular backbone vector of our choosing). Go through each piece of the given DNA sequences highlighted below (Promoter, RBS, Start Codon, Coding Sequence, His Tag, Stop Codon, Terminator) and paste the sequences into the Benchling file one after the other (replacing the coding sequence with your codon optimized DNA sequence of interest!). Each time you add a new piece of the sequence, make sure to annotate by right clicking over the sequence and creating an annotation that describes what each piece (e.g., Promoter, RBS, etc.) is (see image below). Promoter (e.g. BBa_J23106) TTTACGGCTAGCTCAGTCCTAGGTATAGTGCTAGC RBS (e.g. BBa_B0034 with spacers for optimal expression) CATTAAAGAGGAGAAAGGTACC Start Codon ATG Coding Sequence (your codon optimized DNA for a protein of interest, sfGFP for example) AGCAAAGGAGAAGAACTTTTCACTGGAGTTGTCCCAATTCTTGTTGAATTAGATGGTGATGTTAATGGGCACAAATTTTCTGTCCGTGGAGAGGGTGAAGGTGATGCTACAAACGGAAAACTCACCCTTAAATTTATTTGCACTACTGGAAAACTACCTGTTCCGTGGCCAACACTTGTCACTACTCTGACCTATGGTGTTCAATGCTTTTCCCGTTATCCGGATCACATGAAACGGCATGACTTTTTCAAGAGTGCCATGCCCGAAGGTTATGTACAGGAACGCACTATATCTTTCAAAGATGACGGGACCTACAAGACGCGTGCTGAAGTCAAGTTTGAAGGTGATACCCTTGTTAATCGTATCGAGTTAAAGGGTATTGATTTTAAAGAAGATGGAAACATTCTTGGACACAAACTCGAGTACAACTTTAACTCACACAATGTATACATCACGGCAGACAAACAAAAGAATGGAATCAAAGCTAACTTCAAAATTCGCCACAACGTTGAAGATGGTTCCGTTCAACTAGCAGACCATTATCAACAAAATACTCCAATTGGCGATGGCCCTGTCCTTTTACCAGACAACCATTACCTGTCGACACAATCTGTCCTTTCGAAAGATCCCAACGAAAAGCGTGACCACATGGTCCTTCTTGAGTTTGTAACTGCTGCTGGGATTACACATGGCATGGATGAGCTCTACAAA 7x His Tag (Let’s add a 7×His tag at the C-terminus of the protein to enable protein purification from E. coli) CATCACCATCACCATCATCAC Stop Codon TAA Terminator (e.g. BBa_B0015) CCAGGCATCAAATAAAACGAAAGGCTCAGTCGAAAGACTGGGCCTTTCGTTTTATCTGTTGTTTGTCGGTGAACGCTCTCTACTAGAGTCACACTGGCTCACCTTCGGGTGGGCCTTTCTGCGTTTATA Once you’ve completed this, click on Linear Map to preview the entire sequence. If you intend to have a TA review a sequence in the future, this is a good way to verify that all sections are annotated! (Optional) Share your final sequence link with a TA for review! This insert sequence you built is commonly referred to as an expression cassette in molecular biology (a sequence you can drop into any vector and it’ll perform its function). Go ahead and download the FASTA file for the sequence you made. It’s helpful to visualize DNA designs using SBOL Canvas (Synthetic Biology Open Language) to convey your designs. Here’s an example of what you just annotated in Benchling:

4.2. On Twist, Select The “Genes” Option

4.3. Select “Clonal Genes” option For this demonstration, we’ll choose Clonal Genes. You’ll select clonal genes or gene fragments depending on your final project. Historically, HTGAA projects using clonal genes (circular DNA) have reached experimental results 1-2 weeks quicker because they can be transformed directly into E. coli without additional assembly. Gene fragments (linear DNA) offer greater design flexibility but typically require an assembly or cloning step prior to transformation. An advantage is If designed with the appropriate exonuclease protection, gene fragments can be used directly in cell-free expression.

4.4. Import your sequence You just took an amino acid sequence of interest and converted it into DNA, codon optimized it, and built an expression cassette around it! Choose the Nucleotide Sequence option and Upload Sequence File to upload your FASTA file.

4.5. Choose Your Vector Since we’re ordering a clonal gene, you will need to refer to Twist’s Vector Catalog to choose your circular backbone. You can think of this as taking your linear expression cassette for your protein of interest, and completing the rest of the circle! The backbone confers many special properties like antibiotic resistance, an origin of replication, and more. Discuss with your node to decide on appropriate antibiotic options. At MIT/Harvard, you can use Ampicillin, Chloramphenicol, or Kanamycin resistance. Twist vectors do not contain restriction sites near the insert fragment, so make sure to flank your design with cut sites if you are intending to extract this DNA insert fragment later. For this demonstration, choose a Twist cloning vectors like pTwist Amp High Copy. Click into your sequence and select download construct (GenBank) to get the full plasmid sequence: Go back to your Benchling account. Inside of a folder, click the import DNA/RNA sequence button and upload the GenBank file you just downloaded. This is the plasmid you just built with your expression cassette included. Congratulations on building your first plasmid! Important For your final projects, remember to include:

  1. Fully annotated Benchling insert fragment
  2. Desired Twist cloning vector
  • A lactose-inducible promoter was selected to enable conditional expression of lactase in response to lactose availability in the gut. The PlacA promoter region was extracted from the Lactococcus lactis lac operon upstream of the native ribosome binding site, with preserving lactose-responsive regulation.
AATCGTCGTTTTTTGTTCATATGAAGACTTTCTTTCATAAAGTAATTTTTTTCCAAAGATAATTCTCTTT
TAATTGTATCATAAAAGATAATATTTTCAAGGTAAAACAAACAATTTCAAACAAAAACAAACGTTAGATG
ATGAAATAAGAACAGAGGATTGACGTATATTAGCTTAGGTCAGATTTTGTATAAGACGAAAATAAAGTAG
GACCTCTTAATCAGTAAGTTATAGAAAGTAAAAGACTTTTGTAATACCTGAATAGATATTTCACGTCCAT
TTTGTGATGGATTAAATGAACAAAAATGAACAATAATTTAACGGTGTTATCTATTTTTTAAAAAAACAAA
TAAAAAAAAACAAAAAATTAACAAAAATAGTTGCGTTTTGTTTGAATGTTTGATATCATATAAACAAAGA
AATGATGAAAACGTTATCTTGAACATTTTGCAAAATATTTTCTACTTCTACGTAGCATTTCTTTTTAAAA
TTTAGGAGGTAGTCCAA

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  • For the RBS, I chose to keep the native Lactococcus lactis ribosome binding site (RBS) derived from the lacA operon which is the region immediately upstream of the coding sequence (CDS) and preserved its original spacer length to ensure efficient translation initiation in the probiotic host. Maintaining native RBS spacing is critical in Gram-positive bacteria, as ribosome binding and translation efficiency are highly sensitive to the distance between the Shine–Dalgarno sequence and the start codon.

  • the RBS sequence is as follow:

AGGAGGTAGTCCAA
  • I selected the transcription terminator from the tpi gene of Lactococcus lactis, a highly expressed native housekeeping gene, to ensure efficient and reliable transcription termination in the probiotic host. While two related annotations are present in GenBank for this region, both correspond to the same rho-independent transcription terminator. Therefore, I chose the complete annotated terminator region (positions 958–988), which includes both the inverted repeat and the downstream poly-T tract, to ensure proper formation of the termination hairpin and robust termination of transcription.

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  • A transcription terminator was included downstream of the lactase coding sequence to ensure proper termination of transcription. This prevents transcriptional read-through into adjacent sequences and improves the stability and predictability of gene expression, independent of promoter regulation.

  • ATG used as start codon and AAG as stop codon

  • From the selected elements, I built a linear expression cassette in Benchling containing a lactose-regulated promoter, native LAB ribosome binding site, codon-optimized lacZ, and a native transcription terminator. I exported this sequence as a FASTA file. Cassette_link_to_Benchling

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  • When I first uploaded my expression cassette FASTA file to Twist Bioscience, I encountered an initial error related to the FASTA header name. The header exceeded the maximum allowed length (32 characters), which caused the sequence to be rejected. I fixed this issue by shortening the header name and re-uploading the file. After this correction, the sequence was accepted for further analysis.
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However, after re-uploading the corrected file, additional synthesis warnings appeared. These warnings were related to large GC content variation, repetitive regions, and overall sequence complexity. These issues are mainly due to the codon-optimized lacZ gene and the presence of multiple regulatory elements such as the ribosome binding site and transcription terminator. Twist flagged these features as potential manufacturability risks. Unfortunately, I was not able to resolve these additional issues at this stage. Fixing them would have required re-optimizing the enzyme sequence, possibly changing the host organism for codon optimization, and redesigning the regulatory architecture of the cassette. Due to time constraints and because this assignment focuses on learning the design and ordering workflow rather than producing a synthesis-ready construct, I chose not to redesign the sequence further.

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For this exercise, I proceeded by selecting a Twist clonal vector (pTwist Amp High Copy) to complete the plasmid design. Although the insert sequence still contained manufacturability warnings. However, In a real DNA synthesis order, additional sequence optimization would be required to reduce GC content extremes and repetitive regions to meet synthesis constraints.

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Part 5: DNA Read/Write/Edit

Assignees for the following sections MIT/Harvard students Required Committed Listeners Required

5.1 DNA Read (i) What DNA would you want to sequence (e.g., read) and why? This could be DNA related to human health (e.g. genes related to disease research), environmental monitoring (e.g., sewage waste water, biodiversity analysis), and beyond (e.g. DNA data storage, biobank). DNA-based digital data storage technology. Source: Archives in DNA: Workshop Exploring Implications of an Emerging Bio-Digital Technology through Design Fiction - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/DNA-based-digital-data-storage-technology_fig1_353128454 [accessed 11 Feb 2025]. (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? Also answer the following questions:

  1. Is your method first-, second- or third-generation or other? How so?
  2. What is your input? How do you prepare your input (e.g. fragmentation, adapter ligation, PCR)? List the essential steps.
  3. What are the essential steps of your chosen sequencing technology, how does it decode the bases of your DNA sample (base calling)
  4. What is the output of your chosen sequencing technology?

5.2 DNA Write (i) What DNA would you want to synthesize (e.g., write) and why? These could be individual genes, clusters of genes or genetic circuits, whole genomes, and beyond. As described in class thus far, applications could range from therapeutics and drug discovery (e.g., mRNA vaccines and therapies) to novel biomaterials (e.g. structural proteins), to sensors (e.g., genetic circuits for sensing and responding to inflammation, environmental stimuli, etc.), to art (DNA origamis). If possible, include the specific genetic sequence(s) of what you would like to synthesize! You will have the opportunity to actually have Twist synthesize these DNA constructs! :) (ii) What technology or technologies would you use to perform this DNA synthesis and why? Also answer the following questions:

  1. What are the essential steps of your chosen sequencing methods?
  2. What are the limitations of your sequencing method (if any) in terms of speed, accuracy, scalability?

5.3 DNA Edit (i) What DNA would you want to edit and why? In class, George shared a variety of ways to edit the genes and genomes of humans and other organisms. Such DNA editing technologies have profound implications for human health, development, and even human longevity and human augmentation. DNA editing is also already commonly leveraged for flora and fauna, for example in nature conservation efforts, (animal/plant restoration, de-extinction), or in agriculture (e.g. plant breeding, nitrogen fixation). What kinds of edits might you want to make to DNA (e.g., human genomes and beyond) and why? (ii) What technology or technologies would you use to perform these DNA edits and why? Also answer the following questions:

  1. How does your technology of choice edit DNA? What are the essential steps?
  2. 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?
  3. What are the limitations of your editing methods (if any) in terms of efficiency or precision?

DNA read:

  • I would want to sequence DNA used for digital data storage. In my knowledge, this technology enables the storage of digital information such as text, images, or files by encoding them into DNA sequences instead of being stored on hard drives. DNA is extremely stable and can store a huge amount of information in a very small space, which makes it interesting for long-term data storage. Reading this DNA by sequencing is necessary to retrieve the stored information and check that the data has not been damaged or changed over time.
  • For this porpose, I would use Illumina sequencing because it is very accurate and well suited for reading short DNA fragments, which is how DNA data storage is usually organized. this strategy can be performed following 4 crusial steps: Image_adress
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  1. Generation This method is a second-generation sequencing technology. It sequences millions of short DNA fragments in parallel, which makes it fast and reliable, but it cannot read very long DNA molecules in one piece.

  2. Input and preparation The input is DNA that contains the encoded digital data. To prepare it: The DNA is fragmented into short pieces, Adapters are added to both ends of the fragments, The fragments are amplified using PCR, The prepared DNA is loaded onto a flow cell

  3. How the technology reads DNA (base calling) Each DNA fragment is copied one base at a time using fluorescently labeled nucleotides. A camera records the color added at each step, and the machine translates these signals into DNA letters (A, T, C, G).

  4. Output The output is a large number of short DNA sequence reads saved as digital files. These reads are then assembled and decoded to recover the original stored data.

DNA write:

  • I am particularly interested in the genes in human genomic DNA related to pharmacogenomics and pharmacogenetics. These fields study how genetic variation affects how people respond to drugs. So, I would want to synthesize genes encoding drug-metabolizing enzymes, like human cytochrome P450 enzymes. Since, these genes are central to pharmacogenetics as variations in them strongly influence how drugs are processed in the body. Synthesizing these genes allows them to be studied, expressed, and tested in controlled systems.

  • So in order to synthetizing them , I would use chemical DNA synthesis combined with gene assembly, which is the standard approach used by commercial DNA synthesis companies.

  1. Essential steps

  • DNA synthesis starts with the digital design of the DNA sequence. This is followed by the chemical synthesis of short oligonucleotides, which are then assembled into full-length genes (for example, using Gibson Assembly). The synthesized genes are cloned into plasmids and finally sequence-verified to confirm their accuracy before use.

  • This DNA synthesis method is easy to use and works well for many projects.However, it can sometimes make mistakes during the process. Parts of DNA that have lots of G and C letters or repeated sequences are harder to make. Very long DNA pieces also need to be built from many shorter fragments, which can be tricky and may cause errors.

DNA Edit:

  • I would want to edit DNA in human cell lines used for drug testing, focusing on genes that affect how drugs work. Changing these genes helps researchers see how different genetic variants influence drug effects and side effects, which is useful in pharmacogenomics.

  • The modification can be realised by CRISPR for editing because it allows precise and programmable changes to DNA. this stratigy works by using a guide RNA to find a specific DNA sequence. The Cas enzyme then makes a cut or nick, and the cell repairs it, introducing the change we want.

  • To use CRISPR, you need to design guide RNAs, prepare the CRISPR components (DNA, RNA, or protein), deliver them into cells, and then check which cells were correctly edited.

  • However, there are some limitations, like different editing efficiencies depending on cell type, and ethical or regulatory concerns when working with human cells.

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