Week-02-HW:-dna-read-write-and-edit

Insulin gene information

1. First, I created an account on Benchling, after which I inserted the Lambda sequence and added the restriction digestive enzymes. By combining them, I obtained the following result:

Lambda digestion Lambda digestion

2. Unfortunately, I did not have access to a laboratory equipped with all the necessary materials to perform the experiment.

3.1 The human insulin (INS) gene is located on chromosome 11 and encodes a precursor protein called preproinsulin, which contains 110 amino acids. This precursor undergoes post-translational processing to produce the active insulin hormone, consisting of two peptide chains (A and B chains) connected by disulfide bonds.

The cDNA sequence for human preproinsulin is approximately 330 base pairs long and encodes a protein essential for glucose metabolism and regulation of blood sugar levels.

I used UniProt to find the amino acid sequence for human insulin.

Example insulin precursor sequence (preproinsulin):

MALWMRLLPLLALLALWGPDPAAA FVNQHLCGSHLVEALYLVCGERGFFYTPKT RGIVEQCCTSICSLYQLENYCN

3.2 Nucleotide sequence

After identifying the insulin gene, the nucleotide sequence encoding human insulin can be obtained from genetic databases such as NCBI.

This sequence can be used for recombinant protein production in suitable expression systems.

3.3 Codon optimization

After determining the nucleotide sequence encoding insulin, codon optimization is necessary to ensure efficient expression in the chosen host organism.

Although the genetic code is universal, different organisms prefer specific codons. If rare codons are present, translation efficiency may decrease.

By optimizing codons for the host organism, protein expression can be improved without changing the amino acid sequence of insulin.

Organism chosen for optimization: Escherichia coli

E. coli is widely used in recombinant insulin production because:

  • It grows quickly
  • It is inexpensive
  • Genetic manipulation is well established
  • It is already used industrially to produce recombinant human insulin

Codon optimization improves:

  • Translation efficiency
  • mRNA stability
  • Protein yield
  • Reduced ribosome stalling

The optimized DNA sequence would include:

  • Start codon
  • Stop codon
  • Preferred E. coli codons
  • Compatibility with expression vectors

3.4 Protein production methods

The optimized insulin DNA sequence can be used to produce protein using either cell-dependent or cell-free systems.

  1. Cell-dependent (in vivo) production

The insulin gene would be inserted into an expression vector containing:

  • Promoter
  • Ribosome binding site
  • Terminator

After transformation into E. coli:

  • DNA is transcribed into mRNA
  • mRNA is translated into insulin precursor
  • Protein is folded and processed
  • Insulin is purified from bacterial culture

This method is widely used for industrial insulin production.

  1. Cell-free (in vitro) production

Cell-free systems use extracted transcription and translation machinery.

Advantages:

  • Faster production
  • No cellular toxicity
  • Controlled conditions

Limitations:

  • Higher cost
  • Lower yield

4.1 I have created an account

4.2 Linear Map Linear Map

PART 5 – Therapeutic genetically modified bacteria for intestinal diseases

5.1 DNA sequencing

(i) What DNA would I sequence and why?

I would sequence DNA from gut microbiota and from patients with intestinal diseases such as:

  • Inflammatory bowel disease (IBD)
  • Crohn’s disease
  • Ulcerative colitis

The goal is to:

  • Identify harmful bacterial strains
  • Identify beneficial bacteria
  • Detect genes involved in inflammation
  • Understand microbiome imbalance

This information helps design therapeutic genetically modified bacteria.

5.2 DNA synthesis

(i) What DNA would I synthesize and why?

I would synthesize DNA constructs for therapeutic genetically modified bacteria designed to treat intestinal diseases.

Example constructs:

  1. Anti-inflammatory protein expression Engineered bacteria producing:
  • IL-10 (anti-inflammatory cytokine)
  • Protective peptides
  1. Biosensor bacteria Bacteria engineered to detect inflammation and release therapeutic molecules.

Construct components:

  • Promoter activated by inflammation
  • Therapeutic gene
  • Reporter gene
  • Terminator

Purpose:

  • Reduce intestinal inflammation
  • Restore microbiome balance
  • Provide targeted therapy inside the gut

(ii) What technology would I use?

I would use:

  • Chemical DNA synthesis
  • Gene assembly
  • Plasmid cloning

Steps:

  • Design synthetic gene
  • Synthesize oligonucleotides
  • Assemble into plasmid
  • Transform into bacteria
  • Verify by sequencing

Verification:

  • Sanger sequencing
  • Illumina sequencing

Limitations:

  • Cost
  • Possible synthesis errors
  • Need for verification

5.3 DNA editing

(i) What DNA would I edit and why?

I would edit bacterial genomes to create therapeutic strains capable of treating intestinal diseases.

Goals:

  • Insert anti-inflammatory genes
  • Remove harmful genes
  • Improve survival in gut environment
  • Add safety kill-switch mechanisms

Example: Engineering bacteria to produce IL-10 only during inflammation.

(ii) What technology would I use?

I would use CRISPR-Cas9 genome editing.

CRISPR allows:

  • Precise gene insertion
  • Gene knockout
  • Genome modification

Steps:

  1. Design guide RNA
  2. Deliver Cas9 and DNA template
  3. Insert therapeutic gene
  4. Validate edited bacteria

Delivery methods:

  • Electroporation
  • Plasmid vectors

Limitations:

  • Off-target effects
  • Editing efficiency
  • Regulatory and safety concerns

Conclusion

By combining DNA sequencing, synthesis, and genome editing, genetically modified therapeutic bacteria can be developed to treat intestinal diseases.

These bacteria could:

  • Detect inflammation
  • Produce therapeutic molecules
  • Restore gut balance
  • Provide targeted and personalized treatment for patients.