CD Biosynsis offers advanced Mammalian Cells-Based Assay and Modeling Services, integrating cutting-edge experimental analysis with powerful computational modeling to facilitate rational cell line and bioprocess optimization. Mammalian cells, particularly CHO (Chinese Hamster Ovary) cells and HEK293 cells, are key hosts for producing complex biotherapeutics, such as monoclonal antibodies (mAbs), which require accurate folding and human-like post-translational modifications (PTMs). Our services move beyond empirical methods by providing a deep, quantitative understanding of the host's metabolic and regulatory behavior under industrial conditions. We combine high-precision In Vitro and In Vivo assays (metabolomics, proteomics, glycan analysis) with Constraint-Based Metabolic Modeling (CBM) and Dynamic Kinetic Modeling to accurately predict metabolic flux, optimize gene expression timing, and pinpoint systemic bottlenecks within the mammalian bioproduction system. This integrated approach minimizes trial-and-error, ensuring rapid and predictable development of high-performance mammalian cell lines for commercial manufacturing.
Get a QuoteOptimizing the mammalian expression system requires managing the metabolic demands and stress imposed by high-level protein expression, especially minimizing the accumulation of toxic byproducts like lactate and ammonia. Our Assay and Modeling platform bridges the gap between genotypic edits and phenotypic outcomes. By experimentally characterizing key cellular metrics (Assays) and using this data to parameterize predictive Models, we can accurately simulate the effects of genetic modifications before they are built in the lab. This is crucial for controlling energy supply, redox balance, and the protein processing capacity (ER/Golgi). This integrated approach allows our clients to prioritize the most effective genetic targets (e.g., in the lactate pathway or PTM genes) and drastically reduce the development timeline.
Metabolomics & Fluxomics
GC-MS/LC-MS analysis of central carbon metabolism and amino acid consumption, including C-13 tracing, to quantify flux distribution (e.g., lactate production) and identify metabolic limitations in fed-batch culture.
Proteomics & Secretomics
Quantification of ER folding machinery (e.g., BiP, PDI) and analysis of the host secretome (HCPs) and product stability, linking folding capacity and stress response to productivity.
Glycan & CQA Analysis
High-resolution analysis of N-glycan profiles (fucosylation, sialylation), charge variants, and aggregation states, providing essential feedback for glycosylation engineering efforts.
Constraint-Based Metabolic Modeling (CBM)
Utilization of host genome-scale models (e.g., CHO-specific) to predict maximum theoretical yields, optimize nutrient feeding strategies, and propose effective gene modifications (KO/KI) to enhance ATP yield and reduce byproduct formation.
Dynamic Kinetic Modeling
Development of dynamic models to simulate time-dependent changes in cell viability, substrate consumption, and product titer under fed-batch conditions, optimizing feeding schedules and harvest time.
PTM Pathway Modeling
Specialized models simulating the flux through the N-glycosylation pathway based on nucleotide sugar availability and enzyme expression to predict and control the final product glycoprofile.
Optimal Target Recommendation
Using model outputs (e.g., CBM/Kinetic) to recommend the most impactful genetic targets for knockout (e.g., pro-apoptotic genes, FUT8), or Base Editing (e.g., LDHA promoter tuning).
Bioprocess Strategy Prediction
Simulating the effect of culture conditions (temperature shifts, pH) and nutrient inputs on cell growth and productivity, optimizing industrial fed-batch protocols.
Folding Bottleneck Identification
Integrating proteomics data with folding rate models to pinpoint limitations in the ER/Golgi machinery, guiding targeted chaperone overexpression or tuning strategies.
We connect high-quality experimental data with predictive simulation to deliver highly efficient strain optimization.
1. Initial Modeling & Target Identification
2. Experimental Cell Culture & Sampling
3. Quantitative Data Assays
4. Model Validation & Refinement
Establish a compartmentalized CBM and Dynamic Kinetic Model based on the mammalian host (CHO/HEK) and target product (mAb/fusion protein).
Simulate effects of potential edits (KO/KI/tuning) and predict optimal feeding/harvest time.
Generate initial hypothesis on bottlenecks (e.g., lactate accumulation, nucleotide sugar limits, apoptosis onset).
Cultivate wild-type and engineered Mammalian Cell lines under controlled lab-scale bioreactor conditions (e.g., DASbox, shaker flasks) simulating fed-batch.
Collect samples (cells and supernatant) at specific time points reflecting growth and production phases.
Integrate new experimental assay data to validate and refine the computational model parameters.
Identify prediction errors, extract new design rules specific to host stress and PTM requirements, and recommend the final optimization strategy (e.g., Base Edit for LDHA promoter).
Delivery of the predictive model and data-driven optimization strategy.
Metabolic Byproduct Control
Modeling accurately predicts the impact of genetic edits on lactate and ammonia production, guiding the engineering needed to shift metabolism toward efficient TCA cycle utilization.
Precision Glycoengineering
Models the complex relationship between host metabolism (nucleotide sugar pools) and product glycoprofiles, essential for controlling fucosylation and sialylation for enhanced therapeutic efficacy.
Folding & Secretion Analysis
Proteomics and folding models map the capacity and limitations of the ER/Golgi machinery under high secretion load, guiding targeted host factor tuning (e.g., BiP, PDI).
Data-Driven Rational Design
Assay data (Fluxomics, Glycan analysis) directly parameterizes the CBM, ensuring every subsequent genetic edit (KO/KI/BE) is based on quantitative, empirical cellular performance data.
1. How does modeling help reduce lactate accumulation?
CBM identifies key control points (genes) in the glycolytic pathway (e.g., LDHA or PDK) that, when targeted for repression or knockout, shift carbon flux from lactate production into the efficient TCA cycle, reducing accumulation.
2. How is therapeutic fucosylation controlled through modeling?
The model simulates the flux of fucose-precursor nucleotide sugars. By correlating this flux data with FUT8 expression levels, we predict the optimal genetic modification (e.g., FUT8 KO/BE) needed to achieve the desired level of afucosylation for enhanced ADCC.
3. What is the role of Fluxomics in CHO optimization?
Fluxomics quantifies the actual rates of biochemical reactions. This is crucial for verifying if genetic edits successfully redirect carbon flow, confirming whether a metabolic bottleneck has truly been eliminated.
4. Can the model predict cell longevity under stress?
Yes. Dynamic Kinetic Models integrate data on cell death rates, stress protein expression (proteomics), and toxic metabolite accumulation, allowing the model to predict the onset of apoptosis and the viable culture lifespan.
5. How does the model help with feeding strategy optimization?
CBM and Dynamic Modeling simulate the effect of adding specific nutrients (e.g., amino acids, glucose) at various time points, predicting the optimal feeding schedule that balances cell growth and product synthesis without accumulating toxic levels of byproducts.
6. What experimental input is required to build a model for a Mammalian Cell line?
Model building requires growth kinetics, nutrient uptake/excretion rates, Qp, metabolomics, proteomics, and detailed glycan profiles of the specific cell line (CHO/HEK) under fed-batch production conditions.
7. What type of output recommendations are provided?
We provide a prioritized list of actionable targets, including specific KO targets (pro-apoptotic genes), Base Editing sites for promoter tuning, and optimized bioprocess parameters (feeding strategy, temperature/pH control).
8. How do you ensure the modified traits are stable?
All permanent modifications (KO/KI/BE) are designed to be integrated into the host chromosome, ensuring the optimized traits are genetically stable, avoiding the risk of gene silencing over long-term culture.
CRISPR-Cas9 technology represents a transformative advancement in gene editing techniques. The main function of the system is to precisely cut DNA sequences by combining guide RNA (gRNA) with the Cas9 protein. This technology became a mainstream genome editing tool quickly after its 2012 introduction because of its efficient, simple and low-cost nature.
The CRISPR gene editing system with its Cas9 version stands as a vital instrument for current biological research. CRISPR technology enables gene knockout (KO) through permanent gene expression blockage achieved by sequence disruption. Various scientific domains including disease modeling and drug screening employ this technology to study gene functions. CRISPR KO technology demonstrates high efficiency and precision but requires confirmation and verification post-implementation because unsatisfactory editing may produce off-target effects or incomplete gene knockouts which impact experimental result reliability. For precise and efficient Gene Editing Services - CD Biosynsis, Biosynsis offers comprehensive solutions tailored to your research needs.
The CRISPR-Cas9 knockout cell line was developed using CRISPR/Cas9 gene editing to allow scientists to remove genes accurately for research on gene function and disease models and pharmaceutical discovery. Genetic research considers this technology essential due to its high efficiency together with simple operation and broad usability.
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CD Biosynsis is a leading customer-focused biotechnology company dedicated to providing high-quality products, comprehensive service packages, and tailored solutions to support and facilitate the applications of synthetic biology in a wide range of areas.