ORI-marker-screen

Analyses and data for identifying and quantifying abundances of origins of replication in a pooled ORI-marker screen

Overview

This repository contains code and data for reproducing the analyses described in "A scalable framework for high-throughput identification of functional origins of replication in non-model bacteria". It also contains scripts and examples for how to identify and quantify the origins of replications present in a pool of plasmids, either after or before a selective screen.

Finally, it contains scripts and reference data for analyzing amplicon data from screens using the MACKEREL (Modular, NGS-trACKable ExpRession ELement) promoter library, which is a collection of genetic parts consisting of 426 bacterial promoter-RBS sequence variants. These scripts can be found in the ./promoter_screen/ directory.

Conducting a plasmid pool screen and having issues with these scripts? Open an issue and we will respond to help ASAP!

Requirements

1. Python library requirements are listed in requirements.txt.
2. BBDuk (both amplicon and whole plasmid sequencing)
3. Bowtie2 (whole plasmid sequencing)
4. BBmerge (amplicon sequencing)
5. VSEARCH (amplicon sequencing)

Install and quick start

git clone https://github.com/cultivarium/ORI-marker-screen.git
pip install -r requirements.txt
python barcode_quantification.py -d ms_data/amplicon_fastq/ -m ./ms_data/barcode_mapping_test.csv

Data

Data files specific for the Cultivarium Possum Toolkit library of ORIs are available as follows:

• barcode_references.fasta - Barcode sequences associated with each ORI in the library in FASTA format.
• barcodes.csv - A list of the Barcodes associated with each ORI in the library.
• origins.tsv - Start and stop locations of each ORI region on each plasmid in the library.
• ./pool_data/* - FASTA and Genbank files describing the plasmids (and their respective ORIs) within the Cultivarium Possum Toolkit.
• Raw sequencing data for our preprint can be obtained through AWS S3: aws s3 cp --recursive s3://cultivarium-sequencing/ORI-MARKER-RAW-DATA-MAY2023/ .

Amplicon sequencing for barcoded ORI quantification

For identifying the presence of amplicon barcodes from the Cultivarium Possum Toolkit. Each barcode is linked to an ORI within the library, and therefore the barcodes are used to identify the presence and abundances of each ORI within the pool.

Example usage: python barcode_quantification.py -d ms_data/amplicon_fastq/ -m ./ms_data/barcode_mapping_test.csv.

All arguments:

usage: barcode_quantification.py [-h] -d FASTQ_DIRECTORY -m MAPPING_FILE [-b BBMAP_FOLDER]

Whole plasmid sequencing of a plasmid ORI pool.

optional arguments:
  -h, --help            show this help message and exit
  -d FASTQ_DIRECTORY, --fastq_directory FASTQ_DIRECTORY
                        Directory of FASTQ files. File names must take the form: sample_*_R1_*.fastq.gz
  -m MAPPING_FILE, --mapping_file MAPPING_FILE
                        Mapping file of comma separated columns Sample,Pool.
  -b BBMAP_FOLDER, --bbmap_folder BBMAP_FOLDER
                        Directory containing BBTools on your system

Example outputs:

./ms_data/barcode_stats.tsv - Provides statistics on read filtering, merging, and matching for each sample. Have a look at this file to understand general quality of your run and identify any potential issues.

./ms_data/barcode_results.tsv - The read pair / amplicon counts for each ORI within each sample.

Whole plasmid sequencing ORI quantification

For identifying the presence of ORIs within a pool with whole plasmid (or whole genome) sequencing, use the script whole_plasmid_quantification.py. The inputs for this script are the directory of gzipped FASTQ files (a forward and reverse read file per sample) and a mapping file linking samples to their respective pools.

Example usage: python whole_plasmid_quantification.py -d ./ms_data/fastq/ -m ./ms_data/mapping.csv.

All arguments:

usage: whole_plasmid_quantification.py [-h] -d FASTQ_DIRECTORY -m MAPPING_FILE [-b BBMAP_FOLDER]

Whole plasmid sequencing of a plasmid ORI pool.

optional arguments:
  -h, --help            show this help message and exit
  -d FASTQ_DIRECTORY, --fastq_directory FASTQ_DIRECTORY
                        Directory of FASTQ files. File names must take the form: sample_*_R1_*.fastq.gz
  -m MAPPING_FILE, --mapping_file MAPPING_FILE
                        Mapping file of comma separated columns Sample,Pool.
  -b BBMAP_FOLDER, --bbmap_folder BBMAP_FOLDER
                        Directory containing BBTools on your system

Example outputs:

./ms_data/plasmid_library_breadth.tsv - Provides breadth of coverage for each ORI region in each sample. Recommend a breadth cutoff of at least 50% to call an ORI as present in a given sample.

./ms_data/plasmid_library_coverage.tsv - The mean coverage of each ORI region in each sample.