Performance Evaluation in Synthetic Biology
In the rapidly advancing field of synthetic biology, the performance evaluation of strains plays a pivotal role in optimizing biological systems for various applications. Synthetic biology combines principles from biology, engineering, and computer science to design and construct new biological parts, devices, and systems with enhanced functionalities.
Figure 1: Graphical abstract of evaluation of strains. (Sadukha S., et al. 2023)
CD Biosynsis, a leading company with years of experience in the industry, offers high-end services for the performance evaluation of strains, catering to the diverse needs of synthetic biology researchers and industries.
Our Services for Performance Evaluation of Strains
Strain Characterization and Validation
- Growth Rate Analysis: We determine the growth kinetics of strains by monitoring cell density over time.
- Metabolic Activity Assessment: We evaluate the metabolic activity of strains by measuring key metabolites, such as glucose consumption, product formation, and byproduct accumulation.
- Genetic Stability Testing: We ensure the genetic stability of engineered strains by analyzing the persistence of desired genetic modifications over multiple generations.
- Rational Design: We employ computational modeling and simulation tools to design and predict the performance of engineered strains.
- Directed Evolution: Through iterative rounds of mutagenesis and screening, we harness the power of natural selection to evolve strains with improved characteristics. Our high-throughput screening platforms enable the identification of high-performing variants, leading to the selection of strains with enhanced productivity, stability, and robustness.
- Library Construction: We generate diverse strain libraries through techniques such as random mutagenesis, DNA shuffling, or error-prone PCR. These libraries enable the exploration of genetic diversity and provide a resource for screening high-performing variants.
- Automated Screening Platforms: We utilize advanced liquid handling robotics and high-throughput analytics to streamline the screening process. By automating sample handling and data acquisition, we increase throughput, reduce human error, and expedite the identification of strains with desired characteristics.
- Data Analysis and Interpretation: Our bioinformaticians apply powerful statistical analysis and data visualization tools to interpret the large datasets generated from high-throughput screening.
Data Analysis and Interpretation
- Bioinformatics Analysis: We employ advanced bioinformatics tools to analyze genomic, transcriptomic, and metabolomic data.
- Statistical Modeling: We apply statistical modeling techniques to analyze experimental data, assess variability, and determine the significance of observed differences.
- Comprehensive Reporting: We provide detailed reports summarizing the results of strain evaluation, including graphical representations, statistical analyses, and actionable recommendations.
Benefits of Our Approachs
- Extensive Industry Experience.
- Multidisciplinary Expert Team.
- Tailored Solutions.
- Commitment to Quality and Confidentiality.
By leveraging our extensive industry experience, cutting-edge technology, multidisciplinary expertise, tailored solutions, and commitment to quality and confidentiality, CD Biosynsis is a trusted partner for strain evaluation needs. Contact us today to learn more about our services for strain evaluation.
- Khaw T.S., et al. Evaluation of performance of different surface-engineered yeast strains for direct ethanol production from raw starch. Applied Microbiology and Biotechnology, 2006, 70(5): 573-579.
- Dey P., et al. Comparative performance evaluation of multi-metal resistant fungal strains for simultaneous removal of multiple hazardous metals. Journal of Hazardous Materials, 2016, 318: 679-685.
- Sadukha S., et al. Performance evaluation of microalgal strains for concurrent production of high-value bio-actives lutein and phytol: A step forward towards the multi-product paradigm. Biocatalysis and Agricultural Biotechnology, 2023, 50: 102737.