Diversity-driven discovery and characterization of metagenomic enzymes

The identification of robust and efficient biocatalysts remains a major challenge in sustainable industrial processes. Advances in high-throughput sequencing and metagenomics have created an opportunity for new enzyme discovery, however, their experimental characterisation is still limited. The screening capacity remains a critical bottleneck to representative enzyme selection.

In this talk, I will present an end-to-end computational and experimental framework for discovery of diverse enzymes. I will describe the algorithm for diversity optimization and the representative enzyme panel design using short-chain dehydrogenases. I will explain how the metagenomic panel was experimentally screened and analysed to explore functional diversity, solubility, and activity relationships. Finally, I will discuss the results and discuss how my framework can improve the enzyme panel design and become a foundation for future Design->Build->Test->Learn workflows.