Metagenomic Analysis of AMR and HGT
“Uncovering the Hidden World of Resistance: AI Meets Metagenomics.”
About This Course
Antimicrobial resistance and horizontal gene transfer are critical public health challenges, as they facilitate the emergence of multidrug-resistant pathogens. Metagenomics offers a powerful way to uncover resistance mechanisms and gene exchange within complex microbial ecosystems.
This workshop provides hands-on training in metagenomic sequence analysis, gene prediction, resistome profiling, and mobile genetic element identification. Participants will learn to use tools and databases such as CARD, MEGARes, ResFinder, and ICEberg for AMR detection, and employ AI and machine learning approaches for classifying and visualizing gene transfer events.
Aim
This workshop aims to introduce participants to advanced computational and AI-driven approaches for analyzing antimicrobial resistance (AMR) and horizontal gene transfer (HGT) using metagenomic datasets. The program will focus on data processing, functional gene annotation, and network-based prediction to understand the spread and evolution of resistance genes in microbial communities.
Workshop Structure
Day 1: Introduction & Data Pre-Processing
- Overview of Metagenomics, Resistome, and HGT Mechanisms.
- NGS data formats, Quality control using FastQC and Trimmomatic.
- Hands-on: Metagenomic assembly using MEGAHIT / SPAdes.
- Contig annotation using Prokka or MGnify workflows.
- Outcome: Participants gain a foundation in raw data handling and gene annotation.
Day 2: ARG and MGE Detection
- Lecture: Introduction to databases — MEGARes, CARD, DeepARG, and ResFinder.
- Hands-on: Running DeepARG for ARG detection and abundance estimation.
- Hands-on: Identifying plasmids and transposons using PlasFlow and MobileElementFinder.
- Discussion: Integrating ARG and MGE profiles for HGT potential assessment.
Outcome: Participants perform comprehensive resistome and MGE profiling.
Day 3: Visualization & Interpretation
- Hands-on: Visualization of ARG abundance using R (ggplot2) and Python (matplotlib/seaborn).
- Case Study: Comparative analysis of environmental vs. clinical resistomes.
- Workshop Output: Resistome diversity plots and HGT network maps.
- Panel Discussion: Applications of metagenomic AMR monitoring in One-Health and policy contexts.
Who Should Enrol?
- Undergraduate/Postgraduate degree in Microbiology, Biotechnology, Bioinformatics, Computational Biology, or related fields.
- Professionals working in genomics, clinical microbiology, environmental microbiology, or infectious disease research.
- Data scientists and AI/ML engineers aiming to apply computational models in biological and public health data.
- Individuals interested in understanding microbial evolution, antibiotic resistance, and bioinformatics workflows.
Important Dates
Registration Ends
11/25/2025
IST 7:00 PM
Workshop Dates
11/25/2025 – 11/27/2025
IST 8:00 PM
Workshop Outcomes
- Mastery of workflows for metagenomic analysis of AMR and HGT.
- Ability to detect, annotate, and visualize resistance genes in microbial communities.
- Understanding of AI-driven predictive modeling for resistance and transfer events.
- Hands-on experience with CARD, MEGARes, and related databases.
- Competence in integrating biological insights with computational results.
Meet Your Mentor(s)
Prof. Kumud Malhotra
Prof. Kumud Malhotra, Dean of the University Institute of Physical and Life Sciences with 30 years of experience is an academician and administrator and has attained the highest echelons in the educational sector by managing senior positions, like Director, Dean, Managing Editor, or Editor-in-Chief . . .
Fee Structure
Student Fee
₹1499 | $55
Ph.D. Scholar / Researcher Fee
₹2499 | $65
Academician / Faculty Fee
₹3499 | $80
Industry Professional Fee
₹4499 | $90
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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