Metabolic Pathway Modeling & Analysis Service

Metabolic Pathway Modeling and Analysis are indispensable tools in synthetic biology and metabolic engineering. They provide a quantitative, systems-level understanding of cellular physiology, enabling researchers to rationally design and predict the outcomes of genetic modifications before moving to the costly and time-consuming "Build" and "Test" phases. These models transform genomic data into functional insights, acting as a crucial bridge in the Design-Build-Test-Learn (DBTL) cycle.

CD Biosynsis offers comprehensive computational services specializing in the construction and analysis of Genome-scale Metabolic Models (GEMs) . Utilizing cutting-edge constraint-based modeling techniques like Flux Balance Analysis (FBA) and 13C Metabolic Flux Analysis (13C-MFA) , our expert team helps you identify optimal gene knockout/knock-in targets, predict maximum theoretical yields for target compounds, and tune metabolic fluxes to enhance the productivity of your chassis organism (microbes, yeast, or plants).

Highlights

Leverage our computational expertise to move beyond trial-and-error in metabolic engineering:

• Rational Design: Replace costly random screening with mathematically predicted gene modification strategies, identifying the most effective targets (e.g., knockout, overexpression) to redirect flux.
• GEM Expertise: Benefit from our experience in constructing, curating, and analyzing high-quality Genome-scale Metabolic Models (GEMs) for various chassis organisms (E. coli, Yeast, Plant, etc.).
• Multi-Omics Integration: Seamlessly integrate metabolomics, transcriptomics, and proteomics data into constraint-based models to refine predictions and validate the model's accuracy.
• Predictive Power: Quantitatively predict maximum theoretical yields, minimum nutrient requirements, and the impact of environmental perturbations on target product synthesis.

Applications

Our modeling services are crucial for optimizing biocatalytic processes across various industries:

Chemical & Biofuel Production

           

Identifying bottlenecks and optimal engineering targets for maximizing the yield of target chemicals, commodity chemicals, and advanced biofuels.

Drug Precursor Synthesis

Designing and optimizing microbial hosts for the de novo synthesis of complex natural products and pharmaceutical intermediates.

Chassis Strain Improvement

Predicting modifications that enhance cell growth, improve robustness under industrial conditions, or reduce the formation of unwanted byproducts.

Disease Metabolomics Interpretation

Using pathway analysis (e.g., enrichment and topology analysis) to interpret metabolomics data and understand disease mechanisms.

Solutions

We provide a suite of computational tools and analyses for deep pathway insight and engineering strategy design.

Genome-Scale Metabolic (GEM) Model Construction

De novo reconstruction or refinement of metabolic networks based on genomic annotation, biochemical data, and literature.

Flux Balance Analysis (FBA) & Optimization

Predicting optimal pathway fluxes, identifying reaction knockouts (e.g., FBA with Gene/Reaction Deletions) and calculating yield limits.

Metabolic Control Analysis (MCA)

Pinpointing rate-limiting steps and sensitive enzymes in a pathway to determine which step has the greatest influence on overall flux and production.

Strain Design Algorithm Execution (e.g., OptKnock)

Utilizing advanced algorithms to suggest the optimal set of genetic modifications (knockouts) that maximize product yield while maintaining cell viability.

Metabolic Flux Analysis (13C-MFA) Support

Designing optimal labeling experiments, processing mass spectrometry data, and calculating in vivo flux distributions for detailed kinetic understanding.

Workflow

Our service follows a rigorous, data-driven workflow for predictive metabolic engineering:

• Initial Data Collection and Model Curation: Collect all available genomic, transcriptomic, and biochemical data. If a GEM exists, we perform quality control; if not, we construct a preliminary GEM based on the chassis genome annotation.
• Constraint Definition and Model Simulation: Define relevant constraints (nutrient uptake, oxygen limits, growth rates) based on experimental conditions. Perform FBA to simulate growth and product formation, ensuring the model accurately reflects known biological behavior.
• Target Prediction and Engineering Strategy Design: Apply advanced computational tools (e.g., OptKnock, MOMA, regulatory analysis) to systematically identify genetic modification targets (gene deletion, upregulation, pathway insertion) that maximize the desired metabolic objective.
• Model Refinement with Omics Data: Integrate experimental data (e.g., proteomics, metabolomics, 13C-MFA derived fluxes) to constrain the model, refine predicted fluxes, and improve the accuracy and predictive power of the model.
• Final Report and Recommendation: Deliver a comprehensive report including the curated GEM (in SBML format), predicted flux maps, calculated maximum theoretical yields, and a prioritized list of genetic engineering targets ready for the "Build" phase of your project.

We provide a reliable foundation for your metabolic engineering success:

• Validated Models: All constructed or refined GEMs are rigorously tested against published literature and client-provided experimental data to ensure high predictive accuracy.
• Actionable Insights: We don't just provide data; we deliver a prioritized list of genetic targets with clear scientific rationale for the subsequent molecular biology work.
• Industry Standard Tools: We utilize industry-leading computational platforms and proprietary in-house scripts for optimal analysis speed and reliability.
• Clear Visualization: All results are presented with clear pathway maps and flux visualizations to aid in decision-making and project reporting.