CrispHunter

A tool for designing highly specific CRISPR-Cas12a crRNAs targeting user-defined bacterial genera.

Overview

CrispHunter is a comprehensive bioinformatics pipeline that integrates pan-genome analysis with CRISPR-Cas12a targeting to identify highly specific guide RNAs for bacterial detection and targeting. The tool identifies conserved regions across a genus of interest and designs crRNAs that provide maximum coverage with minimal off-target effects.

Features

• Automated genome retrieval from NCBI GenBank database
• Pan-genome analysis to identify core genes across all genomes of a genus
• Intelligent crRNA design that ensures 100% coverage across target genomes

Installation

Setup

# Clone the repository
git clone https://github.com/2021JohnSheng/CrispHunter.git
cd CrispHunter

# Create and activate the Conda environment
conda env create -f environment.yml
conda activate CrispHunter

Detailed Usage Guide

This document provides detailed instructions for using the CrispHunter tool.

Pipeline Overview

The tool works in several distinct stages:

1. Genome retrieval and processing

   • Download genomes from NCBI GenBank (optional)
   • Extract and decompress genome files

2. Genome annotation

   • Annotate genomes using Prokka
   • Extract GFF files for pan-genome analysis

3. Pan-genome analysis

   • Identify core genes across all genomes using Panaroo
   • Extract core gene sequences

4. crRNA design

   • Design candidate crRNAs using CaSilico
   • Extract designed crRNAs from web interface results

5. Target coverage analysis

   • Evaluate crRNA coverage across all target genomes
   • Select crRNAs with 100% coverage

6. Off-target evaluation

   • Build database of potential off-target genomes
   • Analyze potential off-target binding sites using FlashFry
   • Filter crRNAs based on off-target analysis

7. Output generation

   • Combine target coverage and off-target information
   • Generate final list of optimal crRNAs

Command Options Explained

Required Arguments

• -g, --genus: The target bacterial genus (and species) to design crRNAs for. Example: "Burkholderia pseudomallei"

• -offg, --offgenomes: Path to the FASTA file containing genomes to check for off-target effects. This should include genomes of organisms that you want to ensure your crRNAs do NOT bind to (e.g., human genome, closely related bacterial species).

• -firedriver, --firefox_driver_path: Path to the GeckoDriver executable. This is required for web scraping the CaSilico results. Download from: https://github.com/mozilla/geckodriver/releases

• -ffry, --flashfry_path: Path to the FlashFry JAR file. Download from: https://github.com/mckennalab/FlashFry/releases

Optional Arguments

• -i, --input_path: If you already have downloaded genome files, provide the path to the directory containing them. This will skip the download step.

• -gff, --gff_file: If you have already annotated your genomes with Prokka, provide the path to the directory containing the GFF files.

• -coregene, --core_gene_folder: If you have already performed pan-genome analysis and identified core genes, provide the path to the directory containing those results.

• -m, --memory: Memory allocation for FlashFry. Format: "30g" for 30 gigabytes. Increase for larger genomes.

• -maxOff, --maximumOffTargets: Maximum number of off-target sites to consider during FlashFry analysis. Default is 12000.

• -PAM, --PAM_sequence: The PAM sequence to use for crRNA design. Default is "TTTN" for Cas12a.

• -t, --threads: Number of CPU threads to use for parallel processing steps. Default is 8.

Interpreting Results

The final output file "off_target_and_target_coverage.tsv" contains the following columns:

1. gRNA ID: Unique identifier for the guide RNA
2. gRNA Sequence: The sequence of the guide RNA
3. Number of Targeted Genomes: How many of the input genomes this gRNA can target
4. Total Genomes Analyzed: Total number of genomes that were analyzed
5. Targeting Coverage (%): Percentage of analyzed genomes that can be targeted
6. Potential Off-target Sites: Number of potential off-target binding sites

The best crRNAs will have:

• 100% Targeting Coverage
• 0 Potential Off-target Sites

Customization

Modifying GC Content Filtering

The default GC content filter is set to 40-65%. If you need to modify this range, you can edit the R code in the summarize_crawler_results function.

Changing PAM Sequence

To target different Cas enzymes, you can modify the PAM sequence using the -PAM parameter. Default is "TTTN" for Cas12a.

Troubleshooting

Common Issues

1. Memory Errors in FlashFry: Increase the -m parameter value
2. WebDriver Issues: Ensure GeckoDriver version is compatible with your Firefox version
3. Pan-genome Analysis Failures: Reduce thread count to 16 using the -t parameter