Workshop Registration End Date :26 Oct 2026

Virtual Workshop

Live Microbiome Engineering for Circular Bioprocessing: Metagenomics & Predictive Optimization

From Microbial Communities to Predictive Bioprocesses through Metagenomics, Community Engineering & Virtual Live-Lab Simulation

Skills you will gain:

About Workshop:

This 5-day hands-on workshop explores how metagenomics, microbial ecology, functional guilds, microbial interactions and predictive analytics can be integrated for microbiome engineering and circular bioprocessing.
Participants will progress from microbial-community profiling and interaction analysis to microbiome–process prediction and bioreactor modelling. The workshop concludes with a MicrobeAI Virtual Live Lab, where participants apply the complete workflow through microbial-community analysis, perturbation, virtual bioreactor simulation and predictive optimization.

Aim: To develop practical skills for connecting microbiome composition, microbial functions and community interactions with bioprocess performance, and to apply these concepts through computational analysis and virtual experimentation.

Workshop Objectives:

Participants will learn to:

  • Analyse taxonomic and functional microbiome profiles
  • Interpret microbial interactions and metabolic relationships
  • Understand syntrophy and functional microbial guilds
  • Explore synthetic microbial-community design
  • Connect microbiome characteristics with bioprocess performance
  • Apply predictive analytics to microbiome–process datasets
  • Understand microbial perturbation and bioreactor modelling
  • Apply virtual experimentation for microbiome optimization

What you will learn?

📅 Day 1 – Metagenomics to Functional Microbiome Intelligence

  • Introduction to microbiome engineering and microbial-community analysis
  • Understanding shotgun metagenomics and microbiome sequencing data
  • Microbial abundance and taxonomic profiling
  • Functional profiling of genes and metabolic pathways
  • Connecting microbial identity with biological function
  • Core and variable microbiome concepts
  • Functional redundancy and microbial ecosystem resilience
  • Identification of important microbial groups and functional signatures

Hands-On Activity:

  • Explore a microbiome dataset and generate microbial-abundance profiles
  • Compare taxonomic and functional characteristics across samples
  • Visualize major microbial-community patterns

Hands-On Tools: Python, Pandas, Matplotlib, Google Colab, MetaPhlAn/HUMAnN concepts

📅 Day 2 – Microbial Interaction Networks, Syntrophy & Synthetic Consortia

  • Microbial cooperation, competition, mutualism and commensalism
  • Cross-feeding and metabolite exchange between microorganisms
  • Syntrophic interactions in microbial ecosystems
  • Metabolic dependencies and division of labour
  • Identification of potential keystone microorganisms
  • Microbial interaction-network concepts
  • Principles of synthetic microbial-consortium design
  • Community stability, resilience and bioaugmentation strategies

Hands-On Activity:

  • Construct and analyse a simplified microbial interaction network
  • Identify important microbial groups and functional relationships
  • Design a conceptual synthetic microbial consortium

Hands-On Tools: Python, NetworkX, Pandas, Google Colab, Microbial Interaction Dataset

📅 Day 3 – Microbiome–Bioprocess Integration & Predictive Analytics

  • Introduction to microbiome-driven circular bioprocessing
  • Hydrolysis, acidogenesis, acetogenesis and methanogenesis
  • Functional microbial guilds in anaerobic bioprocesses
  • Integration of microbiome and reactor-performance data
  • VFAs, methane production and process-stability indicators
  • Identification of microbiome features associated with process outcomes
  • Machine-learning approaches for bioprocess prediction
  • Feature importance and biological interpretation of predictive models

Hands-On Activity:

  • Integrate microbiome and reactor-performance datasets
  • Build a basic machine-learning model for process prediction
  • Identify microbial features associated with predicted bioprocess performance

Hands-On Tools: Python, Pandas, Scikit-learn, Matplotlib, Google Colab

📅 Day 4 – Functional Microbial Guilds & Predictive Bioreactor Modelling

  • Functional guilds and their roles in microbial bioprocesses
  • Hydrolytic and fermentative microbial communities
  • Acidogenic and acetogenic microbial functions
  • Syntrophic microbial cooperation and metabolite transfer
  • Methanogenic pathways and methane formation
  • Microbial-community perturbation concepts
  • Introduction to ADM1-based anaerobic digestion modelling
  • Scenario analysis, process stability and bioaugmentation strategies

Hands-On Activity:

  • Map major microbial guilds to anaerobic digestion stages and process outputs
  • Compare microbial-community scenarios and predicted reactor responses
  • Evaluate potential microbial or process interventions for improved performance

Hands-On Tools: Python, Pandas, Google Colab, ADM1 Modelling Concepts

📅 Day 5 – MicrobeAI Virtual Live Lab: Microbiome Engineering & Predictive Optimization

  • Introduction to the MicrobeAI integrated virtual workflow
  • Microbiome input assessment and community analysis
  • Functional microbial-guild interpretation
  • Analysis of hydrolytic, fermentative, acetogenic and methanogenic groups
  • Microbial-community perturbation and scenario design
  • Connecting community changes with virtual bioreactor behaviour
  • Analysis of VFAs, H₂, CO₂, CH₄ and process-stability responses
  • Comparison of baseline, perturbed and alternative scenarios
  • Identification of microbial and process bottlenecks
  • Predictive interpretation and microbiome-engineering recommendations

Hands-On Activity: MicrobeAI Integrated Virtual Live Lab

  • Perform the complete microbiome analysis → guild interpretation → community perturbation → bioreactor simulation workflow
  • Compare baseline and intervention scenarios and interpret predicted biological and process responses
  • Develop a microbiome-engineering recommendation for improved virtual bioprocess performance

Hands-On Tools: MicrobeAI Virtual Live Lab, Functional Guild Analysis, Bioreactor Simulation Environment, Predictive Analysis

Mentor Profile

Fee Plan

StudentINR 4999/- OR USD 99
Ph.D. Scholar / ResearcherINR 5999/- OR USD 119
Academician / FacultyINR 6999/- OR USD 139
Industry ProfessionalINR 8999/- OR USD 179

Important Dates

Registration Ends
26 Oct 2026 Indian Standard Timing
Workshop Dates
26 Oct 2026 to
30 Oct 2026  Indian Standard Timing 5:30 PM

Get an e-Certificate of Participation!

Intended For :

  • Microbiology and Biotechnology students
  • Bioinformatics and Computational Biology researchers
  • Microbial Ecology researchers
  • Environmental Biotechnology researchers
  • Synthetic Biology researchers
  • Bioprocess and Biochemical engineers
  • Wastewater and Anaerobic Digestion researchers
  • Bioenergy and Circular Bioeconomy researchers
  • Industrial microbiologists
  • Ph.D. scholars and research fellows
  • Faculty members and academicians
  • Industry professionals working in microbial and bioprocess technologies

Career Supporting Skills

Workshop Outcomes

After completing the workshop, participants will be able to:

  • Analyse taxonomic and functional microbiome profiles
  • Interpret microbial interactions and metabolic relationships
  • Identify major functional microbial guilds
  • Understand syntrophy and synthetic-community design
  • Connect microbial-community features with bioprocess performance
  • Integrate microbiome and reactor-performance datasets
  • Build basic predictive models for microbiome–process analysis
  • Interpret microbial perturbation strategies
  • Understand microbiome-to-bioreactor relationships
  • Compare baseline and alternative microbial scenarios
  • Identify potential microbial and process bottlenecks
  • Apply virtual experimentation for predictive microbiome engineering

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