CD Biosynsis offers advanced CHO (Chinese Hamster Ovary) Cells-Based Assay and Modeling Services, integrating cutting-edge experimental analysis with powerful computational modeling to facilitate rational cell line development. CHO cells are the established host for producing complex biotherapeutics, including monoclonal antibodies (mAbs), requiring accurate mammalian post-translational modifications (PTMs) and stable expression. Our services move beyond empirical methods by providing a deep, quantitative understanding of the host's behavior. 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 levels, and pinpoint systemic bottlenecks within the CHO cell system. This integrated approach minimizes trial-and-error, ensuring rapid and predictable development of high-performance CHO cell lines for commercial manufacturing.
Get a QuoteOptimizing CHO cell performance requires balancing cell viability, specific productivity (Qp), and product quality attributes (CQAs) within the complex, dynamic environment of a fed-batch bioreactor. 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 in CHO cells, where lactate/ammonia accumulation, apoptosis, and glycosylation critically influence bioprocess performance. This integrated approach allows our clients to prioritize the most effective genetic targets (e.g., in the TCA cycle or glycosylation pathway) and drastically reduce the development timeline.
Metabolomics & Fluxomics
GC-MS/LC-MS analysis of central carbon metabolism and amino acid consumption, including ${}^{13}\text{C}$ tracing, to quantify flux distribution (e.g., lactate shunt) and identify bottlenecks under fed-batch conditions.
Proteomics & Secretomics
Quantification of enzyme levels, chaperone expression, and analysis of host cell proteins (HCPs) and secreted product stability, linking protein machinery to productivity.
Glycan & CQA Analysis
High-resolution analysis of N- and O-glycan profiles, charge variants (IEF), and aggregation states, providing essential feedback for product quality engineering.
Constraint-Based Metabolic Modeling (CBM)
Utilization of the comprehensive CHO genome-scale model to predict maximum theoretical yields, optimize nutrient feeding, and propose effective gene knockouts/suppressions for lactate and ammonia reduction.
Dynamic Kinetic Modeling
Development of dynamic models to simulate time-dependent changes in cell growth, viability, apoptosis onset, and substrate feeding profiles under fed-batch bioreactor conditions.
Glycosylation Modeling
Specialized models simulating the N-glycosylation pathway flux based on enzyme expression (Proteomics) and nucleotide sugar availability (Metabolomics) to predict product glycoprofiles.
Optimal Target Recommendation
Using model outputs (e.g., CBM/Kinetic) to recommend the most impactful genetic targets for knockout (e.g., pro-apoptosis), Base Editing (e.g., LDHA tuning), or chaperone overexpression.
Bioprocess Strategy Prediction
Simulating the effect of controlling $\text{pH}$ or $\text{temperature}$ shifts during the culture to optimize the balance between growth and production phases, maximizing final titer.
Risk Assessment
Identifying critical nutrient limitations (e.g., manganese for glycosylation) or byproduct accumulation points (lactate/ammonia) that pose the highest risk to product quality or titer.
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 CHO cell line and target protein.
Simulate effects of potential edits (KO/tuning) and predict optimal nutrient feeding/cell-specific productivity ($\text{Q}_\text{p}$) targets.
Generate initial hypothesis on bottlenecks (e.g., lactate shunt, glycosylation stress).
Cultivate wild-type and initially engineered CHO cell lines in highly controlled lab-scale bioreactors (e.g., DASbox, ambr® 15).
Collect samples (cells and supernatant) at specific time points reflecting key bioprocessing phases (e.g., exponential growth, stationary phase, decline).
Integrate new experimental assay data to validate and refine the computational model parameters.
Identify prediction errors, extract new design rules specific to CHO glycosylation and apoptosis constraints, and recommend the final optimization strategy (e.g., Base Editing of a specific glycosyltransferase).
Deliver the predictive model and data-driven optimization strategy.
Integrated CQA Modeling
Models the complex relationship between cellular metabolism (nucleotide sugar pools) and critical quality attributes (CQAs) like glycosylation, charge variants, and aggregation, a unique mammalian requirement.
Bioprocess Dynamics
Dynamic Kinetic Modeling simulates fed-batch kinetics, apoptosis onset, and nutrient feeding strategies, allowing for in silico optimization of industrial production protocols.
Lactate/Apoptosis Focus
Assay platform and models are specialized in pinpointing and resolving the Warburg effect (lactate shunt) and anti-apoptosis bottlenecks, the two major hurdles in high-titer CHO bioprocessing.
Data-Driven Rational Design
Assay data (Fluxomics, Glycan analysis) is used to directly parameterize the CBM, ensuring that every subsequent genetic edit is based on quantitative cellular flux measurements, not assumptions.
1. How does modeling help control lactate and ammonia accumulation?
Modeling identifies metabolic control points (e.g., LDHA, glutaminase) and simulates the effect of reduced activity, predicting the optimal degree of repression (CRISPRi/BE) required to safely minimize toxic byproduct accumulation while maintaining cell growth.
2. What types of critical quality attributes (CQAs) can be modeled?
We model N-glycosylation profiles (based on nucleotide sugar and enzyme availability), as well as general protein folding stress (based on ER chaperone expression), which influence aggregation and charge variants.
3. How is the complex CHO genome handled in metabolic modeling?
We utilize highly curated, compartmentalized genome-scale models specific to CHO cells. These models track fluxes in the cytosol, mitochondria, and other organelles, which is essential for accurate nutrient and energy budgeting.
4. What is the benefit of Dynamic Kinetic Modeling for bioprocess optimization?
Dynamic modeling simulates time-dependent changes (e.g., glucose consumption and lactate consumption phase). This allows for in silico optimization of industrial protocols, such as precise fed-batch feeding schedules and temperature shift timing.
5. How is apoptosis onset predicted and optimized?
The model integrates expression data (proteomics) for pro- and anti-apoptotic genes (e.g., Bax, Bcl-2) to predict the timing of culture decline. This guides gene editing strategies (KO/CRISPRi) to safely extend cell viability.
6. What experimental input is required to build a model?
Model building requires comprehensive input: cell-specific productivity ($\text{Q}_\text{p}$) data, nutrient uptake/excretion rates, metabolomics (intracellular and extracellular), and proteomics/glycan profiles of the specific cell line under production conditions.
7. Can you analyze the flux through a heterologous therapeutic pathway?
Yes. The therapeutic gene is integrated into the model, and ${}^{13}\text{C}$-Fluxomics is performed to quantify the amino acid and energy cost associated with the final product's synthesis, folding, and secretion.
8. What type of output recommendations are provided?
We provide a prioritized list of actionable targets, including specific Base Editing sites for metabolic enzymes, gRNA sequences for KO/CRISPRi of pro-apoptotic genes, and optimized feeding or temperature shift protocols for the bioreactor.
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.