PhageTB
PhageTB is a multilevel prediction method for predicting interactions between bacteriophages and pathogenic bacterial hosts. This study develops a novel host prediction method for predicting hosts of query phages by their genome sequences utilizing alignment-based and alignment-free features.
Installation
git clone https://github.com/raghavagps/phagetb.git
cd phagetb/
pip install -r requirements.txt
You need to change the following paths in the respective files:
temp_path: where the temporary files are stored
base_path: where the source files are stored
blastn_path: where the blastn executable is stored
Additionally you need the blastdb files and genome files (in fasta format) for the respective bacterial hosts which can be downloaded here and unzip them in the base path.
unzip blastdb_and_genome.zip
You can run the model using the following command:
python model.py -i input.fasta -o output.csv -l 1 2 3 4
Getting Started
This project is hosted on PhageTB and can be accessed by clicking on the link above or can be used as a standalone application by downloading the source code from this GitHub repository.
There are 3 prediction methods available in this model.
- Predict The Bacterial Host For A Query Phage (model.py) This Module Allows Users To Predict The Bacterial Hosts Corresponding To The Query Phages using the genome sequence of the phage.
- Predict Interaction Of Query Phage-Bacteria Pair (model_phage_host_pair.py) This Module Allows Users To Predict Whether Given Phage And Bacterial Hosts Are Likely To Interact With One Another. The prediction from this module for the phage is used as a query for the BLAST task (blastn) against the query bacterial host. The BLAST task is performed using the NCBI BLAST+ tool. The BLAST output is parsed and if the predicted host and query host have a similarity higher than the threshold, then the phage-host pair is predicted to interact.
- Predict The Lytic Phage For Query Bacteria (model_bacteria.py) This Module Allow Users To Predict The Target Phage Likely To Infect Query Bacteria.
Usage
Following is the complete list of all options, (with default values) that can be used to run the model. you may get these options by "python model.py -h" (and similarly for other modules).
model.py
usage: model.py [-h] -i INPUT [-o OUTPUT] [-l LEVELS [LEVELS ...]]
Please provide following arguments
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: genome sequence of the phage in FASTA format or
single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]
Levels: 1: Blast against phage reference DB, 2: Blast
against host reference DB, 3: Integrated model, 4:
CRISPR
model_phage_host_pair.py
usage: model_phage_host_pair.py [-h] -v INPUT_PHAGE -b INTPUT_BACTERIA
[-o OUTPUT] [-l LEVELS [LEVELS ...]]
[-t THRESHOLD]
Please provide following arguments
optional arguments:
-h, --help show this help message and exit
-v INPUT_PHAGE, --input_phage INPUT_PHAGE
Input: genome sequence of the phage in FASTA format or
single sequence per line in single letter code
-b INTPUT_BACTERIA, --intput_bacteria INTPUT_BACTERIA
Input: genome sequence of the bacteria in FASTA format
or single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]
Levels: 1: Blast against phage reference DB, 2: Blast
against host reference DB, 3: Integrated model, 4:
CRISPR
-t THRESHOLD, --threshold THRESHOLD
Threshold: evalue threshold for similarity score
model_bacteria.py
usage: model_bacteria.py [-h] -i INPUT [-o OUTPUT] [-l LEVELS [LEVELS ...]]
[-n NUM_OF_REF_HOSTS] [-t THRESHOLD] [--only_blast]
Please provide following arguments
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: genome sequence of the bacteria in FASTA format
or single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]
Levels: 1: Blast against phage reference DB, 2: Blast
against host reference DB, 3: Integrated model, 4:
CRISPR
-n NUM_OF_REF_HOSTS, --num_of_ref_hosts NUM_OF_REF_HOSTS
Number of reference hosts to consider
-t THRESHOLD, --threshold THRESHOLD
Threshold: evalue threshold for similarity score
File descriptions
blastdb: The database of the hosts, phages and CRISPR sequences.
extras: The directory containing the extra files required for predictions.
pretrained: The directory containing the pretrained models.
genome_data: The directory containing the genome data of reference hosts
input.fasta: The input file containing the query sequences.
getKmerProfiles.py: The python script for generating kmer profiles.
readFasta.py: The python script for reading fasta files.
model.py: The python script for predicting hosts.
model_bacteria.py: The python script for predicting target phages for a bacteria.
model_phage_host_pair.py: The python script for predicting interaction for a phage and host pair.
Address for contact
In case of any query, feel free to reach out to us at
Prof. G. P. S. Raghava, Head Department of Computational Biology,Indraprastha Institute of Information Technology (IIIT),
Okhla Phase III, New Delhi 110020 ; Phone:+91-11-26907444; Email: raghava@iiitd.ac.in Web: http://webs.iiitd.edu.in/raghava/
Reference: Aggarwal et al. (2023) An ensemble method for prediction of phage-based therapy against bacterial infections. Front. Microbiol., DOI: https://doi.org/10.3389/fmicb.2023.1148579
