Transforming Low Cost Feedstocks into High Value Sustainable Products
Calysta has applied its expertise in biological engineering along with core capabilities in DNA synthesis and directed evolution to enable development of metabolic pathways for the biotransformation of sustainable low-cost feedstocks into high value sustainable products.
BioGPS™ Bioengineering Platform
Calysta’s technology platform applies computational design, optimization, and machine learning methods routinely used in other engineering disciplines to biological engineering. The BioGPS bioengineering platform uses customized algorithms to design, test and optimize candidate genes.
PhyloGPS™: Finding Starting Activity
The Phylo GPS™ discovery platform enables rapid identification of a starting enzyme to serve as a basis for subsequent protein engineering activities. Calysta researchers can rapidly mine large sequence databases for candidate genes with high potential, enabling efficient synthesis and testing.
GeneGPS™: Ensuring Enzyme Expression
The GeneGPS™ codon optimization platform allows for efficient and predictable expression of heterologous genes in a target host. This technology is critical for functional testing of mined sequences and building synthetic pathways in industrial host organisms.
ProteinGPS™: Enzyme Activity Meeting Commercial Specifications
The Protein GPS™ protein engineering system quickly and efficiently designs proteins with specific, commercially-relevant characteristics. Using this system, significant performance improvements in target protein sequences can be obtained from sample sizes considerably smaller than those required with conventional directed evolution methods.
PathwayGPS™: Building Metabolic Systems for Industrial Performance
The Pathway GPS™ system builds on other GPS systems to create functionally improved genetic pathways. Using Calysta’s low-cost, high capacity gene synthesis technology, multi-component multi-gene pathways demonstrating optimal industrial-scale performance can be produced with a minimum number of assays.