CD Biosynsis offers advanced Bacillus subtilis-Based Assay and Modeling Services, integrating cutting-edge experimental analysis with powerful computational modeling to facilitate rational strain design and optimization. Our services move beyond simple genetic modification by providing a deep, quantitative understanding of the host's behavior. We combine high-precision In Vitro and In Vivo assays (metabolomics, protein activity) with Constraint-Based Modeling (CBM) and Kinetic Modeling to accurately predict metabolic flux, optimize gene expression levels, and pinpoint systemic bottlenecks. This integrated approach minimizes trial-and-error experimentation, ensuring rapid and predictable development of high-performance B. subtilis strains for metabolic engineering and biomanufacturing.
Get a QuoteThe complexity of the Bacillus subtilis metabolic network demands sophisticated tools to guide engineering efforts. 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 capability is central to the Design-Build-Test-Learn (DBTL) cycle, allowing our clients to make informed decisions, prioritize the most effective genetic targets, and drastically reduce the number of iterative experiments required to achieve optimal product yield and purity.
Metabolomics Profiling (Targeted/Untargeted)
Comprehensive GC-MS/LC-MS analysis of intracellular and extracellular metabolites to quantify pathway intermediates and measure fluxes.
Fluxomics (Isotope Tracing)
Measurement of metabolic fluxes via 13C labeling and mass spectrometry to accurately determine carbon flow through central metabolism.
Transcriptomics & Proteomics
Quantification of mRNA (RNA-seq) and protein levels to map gene expression and enzyme concentrations in response to engineering and environmental changes.
Constraint-Based Modeling (FBA)
Using Flux Balance Analysis (FBA) based on the B. subtilis genome-scale model to predict maximum theoretical yields and knockout effects.
Metabolic Control Analysis (MCA)
Identifying the rate-limiting steps and determining the sensitivity of metabolic fluxes to changes in enzyme activity or concentration.
Kinetic Modeling
Development of dynamic models to simulate time-dependent changes in cell growth, substrate uptake, and product formation under various fermentation strategies.
Optimal Target Recommendation
Using model outputs (e.g., FBA predictions) to recommend the most impactful genetic targets for knockout, knock-in, or overexpression.
Predictive Promoter Tuning
Calculating the optimal expression level for each enzyme in a pathway to maximize flux, guiding the selection of promoter strength and RBS optimization.
Fermentation Condition Simulation
Simulating the strain's performance under different media compositions, oxygen levels, and nutrient feeding strategies to optimize industrial process parameters.
We connect high-quality experimental data with predictive simulation to deliver highly efficient strain optimization.
1. Design (Modeling & Prediction)
2. Build (Strain Construction)
3. Test (Assay & Data Generation)
4. Learn (Re-Modeling & Optimization)
Establish a computational model (FBA, Kinetic) based on the target pathway.
Simulate effects of potential edits (e.g., knockouts) and predict optimal genetic design.
Generate initial hypothesis and experimental plan.
Execute CRISPR-Cas9 gene editing to construct engineered strains.
Build genetic libraries (e.g., promoter libraries) based on model recommendations.
Integrate new experimental data to validate and refine the computational model.
Identify prediction errors, extract new design rules, and recommend the next set of rational edits.
Deliver the predictive model and data-driven optimization strategy.
Integrated Flux Analysis Capabilities
Expertise in both experimental 13C-Fluxomics and computational FBA modeling for accurate flux determination and visualization.
Data-Driven Rational Design
Computational modeling is performed before and after strain construction to ensure that all genetic edits are maximally effective and guided by data.
High-Resolution Multi-Omics Data
Generation of comprehensive metabolomics, proteomics, and transcriptomics data, fully compatible with genome-scale models.
Accelerated DBTL Cycle
The synergy between assay and modeling dramatically reduces the number of required R&D iterations, leading to faster time-to-market.
"The Flux Balance Analysis (FBA) clearly predicted the exact combination of knockouts needed to maximize our product yield. It was the most data-efficient approach we've ever used for metabolic engineering."
Dr. Chen, Head of Strain Engineering, Biocatalysis R&D
"The Metabolomic Profiling combined with the Metabolic Control Analysis (MCA) pinpointed a key, previously unknown regulatory bottleneck in our upstream pathway. The insight was invaluable."
Mr. David Smith, Project Manager, Metabolic Pathway Optimization Group
"Their computational model accurately simulated the optimal promoter strength we needed for three different pathway enzymes, guiding our promoter library selection and minimizing our building phase."
Dr. Lena Koo, R&D Scientist, Synthetic Biology Startup
"We used their Kinetic Modeling to simulate different fed-batch strategies for our fermenter. The resulting protocol immediately improved our volumetric productivity by 15%."
Dr. Alan Rivas, Lab Director, Applied Microbiology Institute
What is Flux Balance Analysis (FBA) and how is it used?
FBA is a computational technique used in Constraint-Based Modeling (CBM) that predicts the flow of metabolites (flux) through a network. We use it to simulate metabolic changes (e.g., gene knockouts) and predict the maximum theoretical yield of a product.
How do you obtain the data to parameterize your computational models?
Model parameters are derived from high-resolution experimental assays, including metabolite concentrations (Metabolomics), gene expression levels (Transcriptomics), and measured metabolic fluxes (Fluxomics/13C labeling).
Is your modeling compatible with my specific B. subtilis strain?
Yes. We use the comprehensive B. subtilis genome-scale model as a base and then customize it with experimental data unique to your specific engineered or wild-type strain, ensuring the model is highly predictive for your system.
What is the benefit of Kinetic Modeling over FBA?
FBA provides steady-state flux predictions. Kinetic Modeling is a more advanced technique that incorporates time-dependent enzyme kinetics, allowing us to simulate dynamic processes like substrate feeding and lag-phase behavior during fermentation.
Can the model help optimize promoter strength?
Yes. Using Metabolic Control Analysis (MCA), the model identifies how sensitive the final product flux is to the concentration of specific enzymes. This guides us in recommending the optimal promoter strength (expression level) for maximal pathway efficiency.
How long does a typical assay and modeling cycle take?
A typical integrated cycle, from initial modeling to experimental validation and model refinement (Learn phase), can take approximately 6 to 10 weeks, depending on the complexity of the target metabolic pathway.
What deliverables do I receive from the modeling service?
Deliverables include the validated computational model file, a Detailed Optimization Report with recommended genetic targets, prediction vs. experimental results comparisons, and all raw assay data.
Do you offer customized reporting for regulatory filings?
Yes. We can tailor our final data reports and documentation to meet the standards required for certain regulatory submissions (e.g., detailed evidence supporting metabolic rationale and stability claims).
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.