Next-Generation Microbiome Therapeutics: Probiotic Genomics, Prebiotic Interactions & Postbiotic Profiling

The gut microbiome plays a vital role in digestion, metabolism, immune regulation, and overall human health. Probiotics, prebiotics, postbiotics, and fecal microbiota transplantation (FMT) are emerging as important microbiome-based therapeutic approaches. These strategies offer opportunities to restore microbial balance, enhance beneficial microbial functions, and support personalized healthcare through targeted microbiome modulation. This 3-day virtual hands-on workshop focuses on probiotic strain characterization and safety assessment, prebiotic–microbe interactions, postbiotic functional analysis, and FMT-associated microbiome restoration. Participants will use Google Colab, Python, bioinformatics databases, and computational tools to analyze microbial datasets, explore metabolic pathways, assess microbial diversity, and evaluate microbiome-based therapeutic strategies through practical workflows.

The workshop aims to enable participants to assess microbial functional traits, prebiotic–microbe interactions, postbiotic-associated metabolites, and FMT-related microbial community changes using bioinformatics tools and publicly available datasets. It emphasizes data-driven interpretation and evidence-based evaluation of microbiome interventions for next-generation therapeutic development.

• Understand the scientific principles, mechanisms, and therapeutic applications ofprobiotics, prebiotics, postbiotics, and fecal microbiota transplantation (FMT)in gut microbiome modulation.
• Evaluateprobiotic functional traits, genomic characteristics, antimicrobial resistance (AMR), and safety profiles to identify promising probiotic strains.
• Analyzeprebiotic–microbe interactions,substrate utilization patterns, and microbial metabolic pathways to understand their roles in gut microbiome modulation.
• Explore postbiotic preparations, microbial metabolites, short-chain fatty acids (SCFAs), and bioactive components associated withgut health and host–microbiome interactions.
• InvestigateFMT-associated microbiome restorationby comparing donor–recipient microbiome profiles, microbial diversity, taxonomic composition, and functional changes.
• ApplyGoogle Colab, Python, Pandas, NumPy, Matplotlib, and bioinformatics databasesto analyze microbial datasets, visualize microbiome responses, and evaluate microbiome-based therapeutic strategies.

📅 Day 1: Probiotic Discovery, Functional Characterization & Safety Assessment

• Exploring probiotic strain functionality, genome-based characterization, safety assessment, and computational prioritization for microbiome-based therapeutic applications. Explore commonly studied probiotic genera, including Lactobacillus, Bifidobacterium, and Bacillus. Examine strain-specific functional traits, including acid tolerance, bile resistance, adhesion, and gastrointestinal survival. Identify antimicrobial activity, bacteriocin production, and other probiotic-associated functional properties. Explore genome-based characterization and functional annotation of candidate probiotic strains. Investigate antimicrobial resistance (AMR) genes, virulence-associated factors, and genomic safety indicators. Analyze probiotic genomic annotations and functional trait datasets using Python. Compare functional characteristics, genomic safety profiles, and available scientific evidence across selected probiotic strains. Prioritize potential probiotic candidates using computational scoring, comparative matrices, and data visualization.

📅 Day 2: Prebiotic–Microbiome Interactions, Metabolic Pathways & Functional Modulation

• Investigating prebiotic substrate utilization, microbial community responses, metabolic pathways, and computational analysis of prebiotic–microbiome interactions. Examine substrate utilization patterns and microbial responses among beneficial gut microorganisms. Investigate carbohydrate fermentation, microbial cross-feeding, and substrate-associated metabolic pathways. Explore changes in microbial abundance, community composition, and functional potential following prebiotic interventions. Examine microbial production of short-chain fatty acids (SCFAs), including acetate, propionate, and butyrate. Identify microbial metabolic pathways and functional genes associated with prebiotic utilization and fermentation. Analyze prebiotic–microbe interaction datasets using Python, Pandas, and NumPy. Visualize microbial response patterns, substrate utilization profiles, and potential metabolic relationships using Matplotlib, Seaborn, and NetworkX. Compare prebiotic substrates based on microbial responses, metabolic potential, and reported functional outcomes.

📅 Day 3: Postbiotic Profiling, Fecal Microbiota Transplantation & Integrated Therapeutic Evaluation

• Exploring postbiotic functionality, microbiome restoration through fecal microbiota transplantation (FMT), and integrated computational evaluation of microbiome-based therapeutic strategies. Differentiate probiotics, prebiotics, postbiotics, and fecal microbiota transplantation (FMT) based on their composition, mechanisms, and therapeutic applications. Explore postbiotic-associated microbial cell components, functional characteristics, and reported host-health effects. Understand the principles of FMT, including donor screening, microbial community transfer, safety considerations, and established clinical applications. Analyze microbiome intervention datasets using Python to compare microbial abundance, alpha diversity, beta diversity, and functional profiles. Compare probiotics, prebiotics, postbiotics, and FMT using intervention-specific functional, safety, clinical-evidence, and microbiome-response parameters. Develop an evidence-weighted computational framework to visualize and evaluate microbiome-based therapeutic strategies.

• Understand the therapeutic applications and mechanisms ofprobiotics, prebiotics, postbiotics, and FMTin gut microbiome modulation.
• Characterize and assess probiotic strainsbased on genomic features, functional traits, antimicrobial resistance (AMR), and safety indicators.
• Analyze prebiotic–microbe interactions,fermentation pathways, and SCFA production using bioinformatics databases and computational tools.
• Evaluate postbiotic preparations, microbial metabolites, and bioactive components involved inhost–microbiome interactions and metabolic functions.
• Investigate FMT-associated microbiome restorationby comparing donor–recipient profiles, microbial diversity, community composition, and functional changes.
• ApplyGoogle Colab, Python, Pandas, NumPy, Matplotlib, and bioinformatics toolsto analyze microbiome datasets, generate heatmaps, and develop an Integrated Microbiome Therapeutic Scorecard for evaluating therapeutic strategies

PhD Scholars & Research Scholars Academicians & Faculty Members Microbiome & Microbial Ecology Researchers Probiotic & Prebiotic Research Scientists Bioinformatics & Computational Biology Researchers Drug Discovery & Development Scientists Biotechnology & Life Science Professionals Microbiology & Molecular Biology Researchers Nutraceutical & Functional Food Researchers Clinical Research Professionals Pharmaceutical & Biotechnology Industry Professionals