Gut Microbiome Bioinformatics: 16S Analysis, Biomarker Discovery & Precision Probiotics

• Understand the structure, organisation, and analysis of 16S rRNA and metagenomic datasets.
• Analyse microbial diversity and taxonomic-abundance patterns across healthy and disease groups.
• Explore microbial metabolic pathways, short-chain fatty acids, and microbiome–immune interactions.
• Evaluate probiotic strains and identify disease-associated microbial signatures.
• Develop an interactive microbiome report integrating diversity, functional, and network analyses.

Workshop Structure

📅 Day 1: Microbiome Profiling and Diversity Analysis

Topics Covered

• Introduction to gut microbiome analysis and precision health
• Overview of 16S rRNA and shotgun metagenomic datasets
• Organisation of sequence data, sample metadata, and experimental groups
• Quality-control and preprocessing principles for microbiome datasets
• Generation and interpretation of taxonomic-abundance profiles
• Relative-abundance analysis across microbial taxonomic levels
• Alpha-diversity analysis for within-sample richness and diversity
• Beta-diversity analysis for between-group community variation
• Comparative microbiome profiling across healthy and disease cohorts

🛠️ Hands-on Activities

• Import and organise a curated microbiome dataset with associated metadata
• Generate taxonomic-abundance summaries and composition plots
• Calculate and visualise alpha-diversity metrics
• Perform beta-diversity analysis and group-level comparison
• Identify major taxonomic differences between study groups

🧰 Tools Covered:

📅 Day 2: Functional Microbiome, Metabolomics and Pathway Interpretation

Topics Covered

• Principles of functional inference from microbiome data
• Prediction of microbial gene families and metabolic pathways
• Gut-microbiota-derived metabolites and their biological significance
• Short-chain fatty acids and their roles in host metabolism and immune regulation
• Introduction to microbial-metabolite datasets
• Functional signatures associated with inflammation and gut dysbiosis
• Comparison of pathway and metabolite profiles between study groups
• Integration of microbial taxa, functional pathways, and metabolite information
• Interpretation of microbiome–metabolite associations

🛠️ Hands-on Activities

• Generate predicted functional profiles using PICRUSt2
• Compare pathway-abundance patterns between study groups
• Explore a curated microbial-metabolite dataset
• Analyse selected short-chain fatty acid and metabolite patterns
• Link key microbial taxa with predicted pathways and metabolite changes

🧰 Tools Covered:

📅 Day 3: Microbiome Biomarker Discovery and Probiotic Prioritisation

Topics Covered

• Principles of microbiome-based biomarker discovery
• Identification of taxa associated with health and disease phenotypes
• Prioritisation of candidate microbial biomarkers
• Evaluation of biomarkers based on abundance, functional relevance, and group discrimination
• Probiotic-candidate prioritisation using ecological and functional evidence
• Microbial co-occurrence and interaction-network analysis
• Identification of hub taxa and key microbial relationships
• Integration of taxonomic, functional, and metabolomic signatures
• Patient or population stratification using microbiome features
• Translation of microbiome findings into precision-nutrition and personalised-health applications

🛠️ Hands-on Activities

• Identify candidate microbial biomarkers from comparative microbiome data
• Rank selected taxa using abundance and functional relevance
• Construct and interpret a microbial interaction network
• Prioritise taxa with potential probiotic relevance
• Integrate taxonomic, functional, metabolomic, and biomarker findings into a final microbiome interpretation

🧰 Tools Covered:

• Organise sequence, metadata, and taxonomic-abundance data for microbiome analysis.
• Calculate and interpret alpha diversity, beta diversity, and group-level microbiome differences.
• Predict microbial functions and identify biologically relevant metabolic pathways.
• Construct microbial interaction networks and prioritise potential microbiome biomarkers.
• Prepare an interactive precision-health report for a selected population or disease condition.

• Graduate and postgraduate students in microbiology, biotechnology, bioinformatics, nutrition, pharmacy, and life sciences
• PhD scholars, research fellows, academicians, and faculty members
• Clinicians and healthcare researchers interested in microbiome-based precision health
• Nutrition, probiotic, food-technology, biotechnology, and pharmaceutical-industry professionals
• Researchers working in gut health, metabolic disorders, immunology, probiotics, or personalised nutrition