ToeGen: Toehold Switch Generator with Homology Ranking

ToeGen is a Python package designed to generate toehold switches for gene expression control, including the ability to rank homologous sequences. This is useful for applications like synthetic biology and gene expression analysis.

Features

• Generate eukaryotic and prokaryotic toehold switches.
• Perform homology searches against custom genome sequences.
• Rank homologous sequences based on mfe (minimum free energy) and distance.

Installation

Step 1: Install Required Dependencies

Ensure you have the following dependencies installed in your Python environment:

• Biopython
• pandas
• joblib
• fuzzysearch
• ViennaRNA

These can be installed using pip:

pip install biopython numpy pandas joblib fuzzysearch viennarna

Step 2: Install Nupack

nupack is a special requirement that cannot be installed via pip. Please follow the official installation guide here.

Instructions to Install NUPACK:

1. Visit the official NUPACK download page.
2. Download the appropriate version for your operating system.
3. Follow the installation instructions on the Getting Started Guide.
4. After installation, ensure that nupack is properly added to your environment.

Step 3: Install ToeGen

Once the dependencies are installed, you can install ToeGen:

pip install toegen

Usage

Once installed, you can use ToeGen to generate eukaryotic and prokaryotic toehold switches with homology ranking.

• Use Case: Generating a Eukaryotic Toehold Switch

from toegen import SwitchGenerator

# Example trigger sequence for eukaryotic systems (23 nucleotides)
trigger_sequence = "AUGGCCUAGCGCUAUGCCCUAGG"

# Example reporter gene sequence
reporter_gene = "AUGGCCUAGCGCUAUGCCCUAUGGGAUGCUUCGGAUAG"

# Initialize the SwitchGenerator for eukaryotic systems
switch_generator = SwitchGenerator(translated_gene_sequence=reporter_gene)

# Generate the toehold switch
switch_strand, ensemble_defect, concentration, mfe_structure = switch_generator.get_switch(trigger_sequence)

# Display the results
print(f"Eukaryotic Switch Strand: {switch_strand}")
print(f"Ensemble Defect: {ensemble_defect}")
print(f"Complex Concentration: {concentration}")
print(f"MFE Structure: {mfe_structure}")

• Use Case: Generating a Eukaryotic Toehold Switch

from toegen import ProkaryoticSwitchGenerator

# Example trigger sequence for prokaryotic systems (30 nucleotides)
trigger_sequence = "AUGGCUCGAUUGCCCUUCUAGGAUCGUAGC"

# Example reporter gene sequence
reporter_gene = "AUGGCCUAGCGCUAUGCCCUAUGGGAUGCUUCGGAUAG"

# Initialize the ProkaryoticSwitchGenerator for prokaryotic systems
prokaryotic_switch_generator = ProkaryoticSwitchGenerator(translated_gene_sequence=reporter_gene)

# Generate the toehold switch
switch_strand, ensemble_defect, concentration, mfe_structure = prokaryotic_switch_generator.get_switch(trigger_sequence)

# Display the results
print(f"Prokaryotic Switch Strand: {switch_strand}")
print(f"Ensemble Defect: {ensemble_defect}")
print(f"Complex Concentration: {concentration}")
print(f"MFE Structure: {mfe_structure}")

• Use Case: Generating Toehold Switches with Homology Ranking

from toegen import HomologySwitchGenerator

# Example genome data simulating transcript sequences (replace with real data if available)
transcripts_dict = [
    {
        'gene': 'GeneA',
        'protein': 'ProteinA',
        'sequence': 'AUGGCCUAGCGCUAUGCCCUAUGGGAUGCUUCGGAUAG'
    },
    {
        'gene': 'GeneB',
        'protein': 'ProteinB',
        'sequence': 'AUGGCUCGAUUGCCCUUCUAGGAUCGUAGCUAGGAUC'
    }
]

# Example list of trigger sequences
triggers = [
    "AUGGCCUAGCGCUAUGCCCUAGG",  # Eukaryotic trigger (23 nucleotides)
    "AUGGCUCGAUUGCCCUUCUAGGAUCGUAGC"  # Prokaryotic trigger (30 nucleotides)
]

# Example reporter gene sequence
reporter_gene = "AUGGCCUAGCGCUAUGCCCUAUGGGAUGCUUCGGAUAG"

# Initialize the HomologySwitchGenerator class for Homo sapiens (eukaryotic)
homology_switch_generator = HomologySwitchGenerator(
    cell_type="Homo sapiens",  # Specify the cell type
    reporter_gene=reporter_gene,  # Specify the reporter gene sequence
    transcripts_dict=transcripts_dict  # Pass in mock genome data
)

# Generate toehold switches with homology search and ranking
results = homology_switch_generator.generate_switch_with_homology(triggers, homology_switch_generator.transcripts_dict)

# Display the results (ranked homology matches and switch generation)
print(results)

License

This project is licensed under the terms of the MIT license.