Workshop Structure
📅 Day 1: Microbiome Profiling and Diversity Analysis
Focus: Processing gut-microbiome data, generating taxonomic profiles, and comparing microbial diversity across study groups.
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:
QIIME 2, MicrobiomeAnalyst, phyloseq, R, and curated microbiome datasets
📅 Day 2: Functional Microbiome, Metabolomics and Pathway Interpretation
Focus: Linking microbial-community profiles with predicted functional pathways and microbiome-derived metabolites to understand host–microbiome interactions.
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:
PICRUSt2, MicrobiomeAnalyst, MetaboAnalyst, R, Python, and functional/metabolite datasets
📅 Day 3: Microbiome Biomarker Discovery and Probiotic Prioritisation
Focus: Identifying disease-associated microbial signatures, prioritising potential probiotic candidates, and integrating microbiome findings for precision-health applications.
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:
MicrobiomeAnalyst, Cytoscape, phyloseq, R, Python, Plotly, and biomarker-ranking templates
