Our research employs adaptive laboratory evolution (ALE) for optimizing microbial strains. Addressing the limitations of traditional strain design, ALE fosters the evolution of strains in a controlled setting, enhancing traits, boosting yields, and revealing new metabolic pathways. Our work has applications in industrial biotechnology, promoting efficient and sustainable processes, and in medicine, where we develop strains for therapy and diagnostics. We combine computational and systems biology with advanced genetic engineering to redefine the limits of microbial engineering.
In our quest to better understand the relationship between genotype and phenotype, we've designed a suite of computational tools tailored for detailed mutation analysis. These tools empower our team to effectively parse, categorize, and study genetic variations. Adding depth to our research is the ALEdb database—a unique and unparalleled public resource. It stands alone in its specialization, cataloging mutations derived directly from experimental evolution studies. This database is not just a repository; it's an invaluable tool for researchers aiming to decode the intricacies of evolutionary change.
Consistent, reproducible cellular growth is key to accurate measurements in microbiology. We are using our automated platform to measure biology accurately and collect omics data samples for studying biology through genome-wide and targeted assays. In doing so, we can delve deeper into the complexities of biology, honing in on specific areas of interest.