gromdimon / CRtagFinder

Semi-automated pipeline for finding critical residues (CR) in sigma-factors proteins.

CRtagFinder

Table of Contents

• General Overview
• Prerequisites
• Skript Execution
• Additional Information

General Overview

CRTagFinder is an automated pipeline for finding critical residues (CR) in sigma-factors proteins. This skript is essential for semi-automated pipeline of bacterial genomes annotation in SigmoID distributive. One of the essential prerequisites for this pipeline is custom database with Transkription Factors and their critical residues tags. CR-tag is an order of positions of amino-acid residues within DNA binding domain, which direktly contact DNA bases. For the construction of database the data from this script was used.

Prerequisites

For running this script some third-side packages and applications are required. They are: -Biopython -HMMER HMMER is a complete application, that has to be installed and setted up. See hints here.

Input Files

You also need a "download.fa" file in the directory where the script is located. This file should consist of protein sequences in fasta format with UniProt identificators.

Example:

>D0LGP0_HALO1/3-191
RRERALIRKLRDRDERAFRELVTQFGDRIFNLTFRMLGSREEAEDISQEVFITVFKSIDS
FRGDAKFSTWMYRIAVNHCKNRIKYLARRHDRSRDEYDDMSGQQQAAGATAVPSTPARPD
LQLEGVQLEQIMQRCIASLDEEHRVLIVLRDIEDLSYEEICTITNLPTGTVKSRLHRARL
ALRKKMLTK
>A0A5B8XTY0_9DELT/1-188
MSLSDRKLVRNLRRRDEDAFRELVRVYQHRVFNIVYRILGDREEAEDVAQEVFVAIFKHI
DSFRGDAKFSTWVYRIATNQARNRLKYHARRHRRDHQNYEDAPESAHQDSDFAGTIPQPE
DAVLGRELEKIIQEGLAELGEIHRTIIVLRDVEHLSYQEIAEIVELPEGTVKSRLFRARV
ALKEYVEK
>Q2IIH1_ANADE/32-211
AWTRSAARGDRQAFSRLVDLHKRTVFALCVRLLRDQDEAQDAAQEAFARAYASLAAFDPS
QPFAPWLLRIARNHCLDVIRRRLPQAQRVELDAAPEDGAPRDLADPDAPRGDDALERREL
ARTLEAAVAALPANYREVVHLFHVEHLSYKEIAAAMDVPIGTVMTWLHRARARLKATLDA

Skript Execution

Quick Mode:

You have to copy only script itself CRTagExtractor and move 'download.fa' file in the same directory. The execusion will be performed by running skript with python command:

python3 CRTagExtractor.py

Developer mode:

After cloning the CRtagFinder repository you can run quick skript, but also debug some other files. The real pipeline is in CRtagFinder folder.

1. bioinformatics_utils.py

This module contains functions specific to bioinformatics tasks. It includes methods for parsing DNA sequences, finding gene locations in genomes, and other sequence-related operations.

Key Functions:

• make_labels_for_ncbi_from_hmmer: Converts EMBL UniProt labels from HMMER output into NCBI labels.
• find_places: Extracts locations of proteins in a genome from a GenBank file.
• parce_dna: Parses DNA sequences from NCBI based on given genome locations.

2. config.py

Central configuration module that stores global settings, API keys, file paths, and URLs. This module simplifies the management of constants used across the application.

Contains:

• API keys (e.g., NCBI API key).
• File paths for input and output data.
• URLs for downloading HMM models.
• Global settings like the sigma factor.

3. hmm_analysis.py

Focuses on tasks related to Hidden Markov Model (HMM) analysis, particularly for protein and DNA sequences.

Key Functions:

• find_regions: Analyzes protein and DNA sequences using HMM.
• protdnakorr_adaptation: Adapts data for subsequent analysis steps.

4. net_file_utils.py

A utility module for network requests and file operations. It includes functions to handle downloading files, creating sessions with retry capabilities, and basic file reading and writing.

Key Functions:

• create_session_with_retries: Creates a requests session with retry capabilities.
• download_file: Downloads a file from a given URL.
• read_file, write_file, append_to_file: Utility functions for file operations.

5. main.py

The entry point of the application. It orchestrates the workflow by calling functions from other modules in the required sequence. The main.py script manages the overall data processing pipeline, ensuring that each step is executed in order and the data is passed correctly between functions.

Results

After all you will have many files in different formats, with different information etc. For purposes of SigmoID we handled special final files "final_r2.txt" and "final_r4.txt". They are made in special table for ProtDnaKorr application. This app made special heatmaps, that illustrated correlations. With help of it we constructed CR-tags and protein database.

Additional Information

Should be ready for CPU consumption, Internet stability and time! This script is not well-optimised for big data, but works actually with it.. So be ready!

Usage

1. Ensure all required Python packages are installed.
2. Set up the config.py module with the correct API keys, file paths, and other configurations.
3. Execute main.py to run the pipeline.

Requirements

• Python 3.x
• Biopython
• Requests
• Other dependencies as required by the specific functions within the modules.