We engineer optimized microbial cell factories through AI-driven chassis development. Enginoma combines genome-scale modeling, metabolic engineering, and synthetic biology to create production strains with improved performance.
Traditional strain development relies on iterative random mutagenesis and screening, which is time-consuming and resource-intensive. Our AI platform accelerates chassis optimization by predicting optimal genetic modifications before experimental validation.
AI-driven metabolic modeling predicts optimal gene targets for modification. Virtual screening of genetic modifications reduces experimental cycles dramatically.
Genome-scale models enable comprehensive analysis of metabolic networks. Balance carbon flux between growth and production for optimal yield.
Strategic genome reduction removes non-essential genes. Streamlined chassis redirect resources toward product synthesis for improved productivity.
Reduced genomes minimize unwanted recombination and plasmid instability. Engineered strains maintain production capacity through extended fermentations.
From chassis selection to production optimization, our platform covers the full strain development workflow.
We use constraint-based metabolic models to simulate cellular metabolism and predict optimal genetic modifications for production phenotypes.
Systematic identification and removal of non-essential genes creates streamlined chassis with reduced metabolic burden and improved genetic stability.
AI-guided pathway optimization balances precursor supply and cofactor regeneration. Multi-parameter optimization improves titer, yield, and productivity.
Our integrated design-build-test-learn workflow combines computational modeling with experimental validation.
We evaluate organism suitability based on your product, substrate, and process requirements to select the optimal chassis.
Genome-scale models predict genetic modifications for improved production. AI algorithms identify optimal targets.
CRISPR-based engineering enables precise genomic modifications. Multi-round editing builds complex phenotypes.
High-throughput screening evaluates strain performance. DBTL cycles refine the chassis for commercial production.
Our chassis engineering platform supports diverse applications across bio-manufacturing.
Engineer chassis for ethanol, biodiesel, and advanced biofuel production. Optimize metabolic flux for high yield biorefining.
Develop strains for succinic acid, lactic acid, and other building block chemicals from renewable feedstocks.
Optimize expression hosts for enhanced protein yield, proper folding, and improved product quality.
Our chassis engineering platform is built on peer-reviewed methodologies and established synthetic biology approaches.
Hutchison, C.A. 3rd et al. Design and synthesis of a minimal bacterial genome. Science 351, aad6253 (2016).
Liu, J. et al. Chassis engineering for microbial production of chemicals: from natural microbes to synthetic organisms. Curr Opin Biotechnol 66, 105-112 (2020).
Ravagnan, G. & Schmid, J. Promising non-model microbial cell factories obtained by genome reduction. Front Bioeng Biotechnol 12, 1427248 (2024).
Adams, B.L. The next generation of synthetic biology chassis: moving synthetic biology from the laboratory to the field. ACS Synth Biol 5, 1328-1330 (2016).
Chan, D.T.C., Bernstein, H.C. & Bjerg, J. Broad-host-range synthetic biology: rethinking microbial chassis as a design variable. ACS Synth Biol 14, 3815-3821 (2025).
We work with a broad range of chassis organisms including E. coli, Saccharomyces cerevisiae, Bacillus subtilis, Corynebacterium glutamicum, and non-model microorganisms. The Enginoma platform supports both model and non-model chassis engineering.
We combine genome-scale metabolic modeling with AI-driven analysis to identify optimal gene knockouts, overexpression targets, and regulatory modifications. Our DBTL cycles accelerate chassis optimization for production performance.
Yes. We perform systematic genome reduction to remove non-essential genes, creating streamlined chassis with improved genetic stability, metabolic efficiency, and reduced metabolic burden for heterologous expression.
We optimize for titer, yield, and productivity through balanced metabolic flux, reduced by-product formation, improved substrate utilization, and enhanced stress tolerance.
Yes. We offer comprehensive strain development from chassis selection and engineering through fermentation optimization and process scale-up. Our integrated approach accelerates strain improvement.
Contact us to discuss your strain development project. Our team will help you develop a customized chassis engineering approach for your target product.
Tell us about your project and we'll get back within 24 hours.
