CD Biosynsis offers specialized Nannochloropsis spp.-Based Assay and Modeling Services, providing an advanced analytical and computational framework for the development of high-lipid algal cell factories. Nannochloropsis species are globally recognized for their superior eicosapentaenoic acid (EPA) and triacylglycerol (TAG) accumulation, yet their metabolic networks are governed by complex regulatory responses to light, nutrients, and CO2. Our platform bridges the gap between high-throughput laboratory experimentation and predictive systems biology by integrating high-resolution phenotypic assays with sophisticated genome-scale metabolic models (GEMs).
Our integrated platform is designed to accelerate the "Design-Build-Test-Learn" cycle in industrial microalgal biotechnology. By combining multi-omics data—including transcriptomics, proteomics, and lipidomics—with quantitative physiological measurements, we create a digital twin of the Nannochloropsis metabolic network. This allows researchers to simulate the impact of genetic modifications or environmental shifts in silico before committing to large-scale cultivation trials. Whether you are investigating the dynamics of the Carbon Concentrating Mechanism (CCM), the impact of nitrogen starvation on oil synthesis, or the metabolic requirements for peak photosynthetic efficiency, our assay and modeling services provide the quantitative depth needed for rational strain design and process optimization.
Get a QuoteAchieving a mechanistic understanding of Nannochloropsis spp. requires the integration of diverse biological data streams. Our platform addresses the unique architecture of these microalgae, such as their compact genomes and their highly efficient yet complex lipid biosynthetic pathways. We employ automated assay systems to capture high-resolution temporal data on biomass growth, fatty acid composition, and intracellular flux. These measurements serve as the ground truth for our computational models, ensuring that simulations reflect the actual physiological constraints of industrial algal strains.
By utilizing advanced analytical tools such as Pulse-Amplitude-Modulation (PAM) fluorometry and comprehensive lipidomic profiling via GC-MS/LC-MS, we generate a multidimensional map of the cell's metabolic state. This data-driven approach is particularly valuable for projects aiming to redirect carbon flux away from secondary cell wall components toward neutral lipids. Our modeling services identify metabolic bottlenecks and competitive nodes that are often invisible to standard molecular biology techniques, providing a holistic view of the algal factory’s efficiency and resilience under the variable conditions of outdoor photobioreactors or large-scale fermentation tanks.
We provide a wide array of standardized and customized assays to quantify the performance of your Nannochloropsis strains across multiple physiological parameters.
PAM Fluorometry
Quantification of Fv/Fm, non-photochemical quenching (NPQ), and electron transport rates (ETR) to evaluate light utilization and photo-protection efficiency.
Pigment Analysis
High-resolution HPLC quantification of chlorophylls and carotenoids to assess light-harvesting capacity and oxidative stress response.
Fatty Acid Profiling
Detailed quantification of EPA (C20:5) content and total fatty acid methyl esters (FAMEs) via GC-MS to determine bioproduct quality.
TAG Analysis
Monitoring triacylglycerol accumulation and molecular species distribution during growth and nitrogen deprivation cycles.
Growth Kinetics
High-resolution growth curve analysis and determination of specific growth rates across varied salinities and nutrient regimes.
Stress Biomarkers
Measurement of reactive oxygen species (ROS) and cellular viability markers under industrial stressors like high pH or ammonia toxicity.
Our computational platform converts raw experimental data into predictive models that guide engineering decisions and process control.
1. GEM Reconstruction
2. Flux Balance Analysis (FBA)
3. Dynamic Flux Simulation
4. Multi-Omics Integration
Refinement of Genome-Scale Metabolic Models (GEMs) specific to Nannochloropsis, incorporating all primary and secondary metabolic reactions and organelle transport.
Utilizing FBA to predict theoretical maximum yields of lipids and identify the optimal genetic targets for metabolic engineering projects.
Integrating transcriptomic and proteomic datasets into metabolic models to increase the biological accuracy of flux predictions and identify regulatory constraints. Delivery of comprehensive modeling reports.
Nannochloropsis Expertise
Dedicated models that account for the specific fatty acid biosynthetic pathways and carbon fixation mechanisms unique to oleaginous algae.
Predictive Accuracy
Our models are validated against high-quality experimental data, significantly reducing the time spent on trial-and-error strain construction.
Multi-Omics Support
Deep integration of transcriptomics and lipidomics into the modeling workflow to provide a holistic view of the cellular phenotype.
Scalable Process Insights
Assays and models are designed to reflect the stresses of industrial cultivation, facilitating successful scale-up from lab to field.
Technical insights for your Nannochloropsis assay and modeling project.
Contact Us1. What is a Genome-Scale Metabolic Model (GEM)?
A GEM is a mathematical representation of all metabolic reactions in an organism. In Nannochloropsis, it allows us to simulate how carbon flows through different pathways under various conditions to predict product yield.
2. Can you model the metabolic response to nitrogen starvation?
Yes. Nitrogen starvation is the primary trigger for lipid accumulation in Nannochloropsis. Our models specifically account for the metabolic shifts that occur when growth slows and oil synthesis accelerates.
3. What is the benefit of Flux Balance Analysis (FBA)?
FBA identifies the "flux" or rate through metabolic pathways. It helps determine which genetic edits (e.g., knocking out a competitive pathway) will best increase the accumulation of target bioproducts like EPA.
4. How do you validate the computational predictions?
We compare model predictions with empirical assay data (e.g., actual lipid profiles or growth rates). Discrepancies are used to refine the model in an iterative "learning" process.
5. How does PAM fluorometry help industrial production?
PAM fluorometry non-invasively monitors the efficiency of photosynthesis. It can detect early signs of stress or nutrient depletion, allowing for real-time adjustments to culture conditions.
6. Do you provide software or just the final report?
We provide a comprehensive report detailing all findings. For modeling projects, we also provide the model files (e.g., in SBML format) so you can continue simulations in your own facility.
7. Can you simulate the impact of high-intensity light on pigment production?
Yes. Our models can simulate photo-acclimation and the induction of photoprotective pigments, helping to optimize lighting regimes for maximal antioxidant production.
8. What is the typical lead time for an integrated project?
Depending on the scope of the metabolic network and the number of assay points, projects typically range from 12 to 18 weeks.
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