Genome-Scale Metabolic and Pathway Modeling

Genome-scale metabolic and pathway modeling provides a quantitative framework for simulating cellular metabolism based on the organism's complete genomic information. By reconstructing large-scale metabolic networks, researchers can predict metabolic fluxes, assess pathway activity, optimize strain engineering strategies, and explore complex biological behaviors under different environmental or genetic conditions.

Genome-scale metabolic and pathway modeling has wide applications in microbiology, synthetic biology, metabolic engineering, drug target discovery, and bioprocess development. With the integration of omics data and advanced computational methods, GEM-based simulations have become a cornerstone technology for predictive microbial modeling.

1-1-7-2 Genome-Scale Metabolic and Pathway Modeling-1.webp Fig. 1 Applications of GEMs for the production of chemicals and materials, drug targeting in pathogens, the prediction of enzyme functions, and pan-reactome analysis. (Changdai Gu, et al., 2019)

Modeling Principles

Genome-Based Network Reconstruction: Metabolic reconstruction begins with genome annotation to identify metabolic genes, enzymes, and reaction pathways. Well-organized databases and literature enable the construction of structured metabolic networks covering thousands of reactions.
Stoichiometric and Constraint-Based Modeling: Using mass balance and stoichiometric constraints, metabolic networks are represented as mathematical systems.
Integration of Multi-Omics Data: Genetic engineering models (GEMs) can integrate transcriptomics, proteomics, metabolomics, and phenotypic data to improve the prediction and simulation of metabolic states under specific conditions.
Pathway Design and Optimization: Computational tools simulate genetic perturbations, identify bottlenecks, and guide pathway enhancement or rewiring for metabolic engineering.

The modeling principles combine systems-level metabolic reconstruction, constraint-based simulation, and rigorous data integration to ensure accurate, predictive, and biologically meaningful insights.

Our Services

CD Biomodeling provides a comprehensive range of modeling solutions and simulation services designed to analyze, predict, and optimize microbial community behaviors and interactions under diverse conditions.

Reconstruction of multi-species metabolic networks and community models.

Simulation of interspecies interactions, cross-feeding, and competition.

Dynamic modeling of community growth, succession, and metabolic fluxes.

Prediction of ecosystem responses to environmental changes or perturbations.

Identification of keystone species, functional roles, and potential synthetic consortia.

Custom modeling for engineered microbial communities in bioprocessing, wastewater treatment, or synthetic ecology.

Integration of multi-omics data for condition-specific community analysis.

Tools & Resources

To support accurate and scalable metabolic simulations, we employ a comprehensive suite of state-of-the-art computational tools, databases, and modeling frameworks.

COBRA Toolbox / COBRApy
BacArena, COMETS, and MICOM
MetaCyc, KEGG, BioCyc, and ModelSEED

OptCom and d-OptCom
AI-assisted tools
Agent-based modeling platforms (NetLogo, MASON)

Deliverables

Our final deliverables provide fully validated models, clear analytical outputs, and actionable insights to support your research, engineering, or bioprocess development goals.

Genome-scale Metabolic Model (SBML, JSON, MATLAB formats)

Metabolic Pathway Diagrams and Map Visualizations

Engineering Target Recommendations and Optimization Strategies

Application Areas

Metabolic Engineering

Enhancing microbial production efficiency through optimized pathways and targeted genetic modifications.

Industrial Biotechnology

Improving large-scale fermentation performance via metabolic flux prediction and process refinement.

Microbial Physiology Research

Predicting microbial behavior under varying nutrients and stress to understand cellular physiology.

Synthetic biology

Designing synthetic pathways and optimizing host chassis for efficient metabolic performance.

Drug Discovery

Identifying critical metabolic genes and weak points to support antimicrobial target discovery.

Environmental Microbiology

Modeling microbial roles in elemental cycles and predicting biodegradation of environmental pollutants.

By integrating genome-scale metabolic modeling with advanced simulation and data-driven analysis, CD Biomodeling empower researchers and industry partners to accelerate discovery, optimize microbial systems, and design more efficient, sustainable biotechnological solutions. Whether for fundamental research or large-scale application, our modeling platform provides the precision, depth, and flexibility needed to transform ideas into measurable outcomes. If you would like to learn more about the service details or get technical support, please feel free to contact us.

Reference

Changdai Gu, et al. Current status and applications of genome-scale metabolic models. Genome Biology. 2019, 121.

For Research Use Only!

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