🦠 In Silico Analysis of Bacterial Genomes to Identify and Characterize Antibiotic Resistance Genes (ARGs)

📌 Overview

Antibiotic resistance is one of the most critical public health threats globally. Antibiotic Resistance Genes (ARGs) enable bacteria to survive antibiotic exposure through mechanisms such as enzymatic drug degradation, target site modification, efflux pumps, and reduced membrane permeability.

This project presents a web-based bioinformatics tool built with Python (Flask) + BLAST+ for real-time detection of ARGs from bacterial genome sequences — supporting precision antibiotic therapy and AMR surveillance.

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🎯 Objectives

1. Collect and curate bacterial genome sequence datasets from NCBI GenBank and RefSeq
2. Retrieve 135 essential bacterial genes from the DEG Database for reference
3. Develop a web-based ARG detection tool using Python (Flask), HTML/CSS/JS, and BLAST+
4. Enable real-time sequence matching against CARD and ResFinder databases
5. Support comparative genomic analysis of ARG distribution

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🧬 ARG Resistance Mechanisms

Mechanism	Example	Gene(s)
Enzymatic degradation	β-lactamase hydrolyzes penicillin	blaTEM, blaSHV, blaOXA
Target site alteration	Modified DNA gyrase	gyrA, parC
Efflux pumps	Active drug expulsion	tetA, mexAB-oprM
Reduced permeability	Porin loss	oprD
Ribosomal modification	16S rRNA methylation	aac(6')-Ib

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🛠️ Tools & Databases

Tool / Database	Purpose
NCBI GenBank / RefSeq	Bacterial genome sequence retrieval
CARD (card.mcmaster.ca)	Main ARG reference database
ResFinder	Supplementary ARG detection
DEG (Database of Essential Genes)	135 essential gene reference set
BLAST+	Sequence alignment and homology search
Python (Flask)	Backend web application
HTML / CSS / JavaScript	Frontend interface

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⚙️ Methodology

Step 1 — Dataset Collection

• Bacterial gene sequences retrieved from NCBI GenBank and RefSeq in FASTA format
• ARG families included: β-lactamases, aminoglycoside-modifying enzymes, efflux pumps, target modification genes

Step 2 — Essential Gene Reference (DEG Database)

• 135 essential genes curated from DEG Database (experimentally verified)
• Covers DNA replication, transcription, translation, and cell wall synthesis
• Used to cross-reference ARG hits and prevent misclassification

Step 3 — ARG Detection Tool

Backend (Python / Flask):

• BLAST-based local alignment against CARD ARG sequences
• Threshold: ≥85% sequence identity + e-value ≤ 1×10⁻⁵
• Resistance class mapping: β-lactams, aminoglycosides, macrolides, fluoroquinolones, tetracyclines

Frontend (HTML/CSS/JavaScript):

• FASTA sequence input
• Gene name input
• Real-time results display

Tool Output:

• Matched ARG Name
• ARG ID (ARO ID from CARD)
• Resistance Class
• Percent Identity
• Database Source (CARD / ResFinder)
• Confidence Score

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📊 Key Results

Essential Gene Reference — DEG Database (M. tuberculosis)

Category	Example Genes	Function
DNA replication	Rv0005 (GyrA), Rv0004 (GyrB)	DNA gyrase — fluoroquinolone target
Transcription	Rv0667 (RpoB)	RNA polymerase β-subunit — rifampicin target
Catalase-peroxidase	Rv1908c (KatG)	Isoniazid activation
ATP synthesis	Rv3794 (AtpA)	Energy metabolism

ARGs Identified — M. tuberculosis (CARD Database)

Resistance Mechanism	Genes	Antibiotic Class
KatG mutations	katG	Isoniazid
RpoB mutations	rpoB	Rifampicin
Efflux pump	mmpS5-mmpL5	Bedaquiline, Clofazimine
Aminoglycoside modifying	aac(6')-Ib	Aminoglycosides
β-lactamase	bla genes	β-lactam antibiotics

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🖥️ How to Run Locally

# Clone the repository
git clone https://github.com/Shubham9845/arg-detection-tool.git
cd arg-detection-tool

# Install dependencies
pip install flask biopython

# Run the app
python app.py

Open browser at http://localhost:5000

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📁 Repository Structure