
Next-Generation Microbiome Therapeutics
From Microbiome Modulation to Next-Generation Therapeutic Strategies
Skills you will gain:
About Workshop:
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.
Aim: 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.
Workshop Objectives:
- Understand the scientific principles, mechanisms, and therapeutic applications of probiotics, prebiotics, postbiotics, and fecal microbiota transplantation (FMT) in gut microbiome modulation.
- Evaluate probiotic functional traits, genomic characteristics, antimicrobial resistance (AMR), and safety profiles to identify promising probiotic strains.
- Analyze prebiotic–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 with gut health and host–microbiome interactions.
- Investigate FMT-associated microbiome restoration by comparing donor–recipient microbiome profiles, microbial diversity, taxonomic composition, and functional changes.
- Apply Google Colab, Python, Pandas, NumPy, Matplotlib, and bioinformatics databases to analyze microbial datasets, visualize microbiome responses, and evaluate microbiome-based therapeutic strategies.
What you will learn?
📅 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.
🧪 Hands-On Learning Activity:
- Retrieve and analyze probiotic strain datasets, screen AMR and virulence genes, and use Google Colab to develop a Probiotic Functional–Safety Matrix, visualize heatmaps, and rank candidate strains.
🧰 Tools Covered: NCBI Genome | NCBI BLAST | BAGEL4 | AMRFinderPlus | VFDB | Google Colab | Python | Pandas | NumPy | Matplotlib | Seaborn
📅 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.
🧪 Hands-On Learning Activity:
- Analyze prebiotic substrates, microbial responses, and metabolic pathways using Google Colab to generate comparative visualizations and construct a Prebiotic–Microbe–Function Interaction Matrix.
🧰 Tools Covered: PubMed | KEGG | NCBI Taxonomy | gutMGene | Google Colab | Python | Pandas | NumPy | Matplotlib | Seaborn | NetworkX
📅 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.
🧪 Hands-On Learning Activity:
- Analyze postbiotic functional evidence and pre-/post-FMT microbiome diversity using Google Colab to generate comparative visualizations and construct an Integrated Microbiome Therapeutic Evaluation Matrix.
🧰 Tools Covered: PubMed | KEGG | HMDB | gutMGene | NCBI SRA | Google Colab | Python | Pandas | NumPy | Matplotlib | Seaborn | Plotly | Scikit-learn
Mentor Profile
Fee Plan
Important Dates
28 Oct 2026 Indian Standard Timing 4:30 PM IST
26 Oct 2026 to 28 Oct 2026 Indian Standard Timing 5:30PM
Get an e-Certificate of Participation!

Intended For :
- 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
Career Supporting Skills
Workshop Outcomes
- Understand the therapeutic applications and mechanisms of probiotics, prebiotics, postbiotics, and FMT in gut microbiome modulation.
- Characterize and assess probiotic strains based 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 in host–microbiome interactions and metabolic functions.
- Investigate FMT-associated microbiome restoration by comparing donor–recipient profiles, microbial diversity, community composition, and functional changes.
- Apply Google Colab, Python, Pandas, NumPy, Matplotlib, and bioinformatics tools to analyze microbiome datasets, generate heatmaps, and develop an Integrated Microbiome Therapeutic Scorecard for evaluating therapeutic strategies
