Abstract

Synthetic biology aims to design novel or improved biological systems using engineering principles, which has broad applications in medical, chemical, food, and agricultural industries. Thanks to rapid advances in DNA sequencing and synthesis, genome editing, artificial intelligence/machine learning (AI/ML), and laboratory automation, synthetic biology has entered a new phase of exponential growth. In this talk, I will highlight our recent work on the development of a self-driving biofoundry, AI/ML tools, non-model organisms, and novel enzymes for synthetic biology applications. Examples include but are not limited to: (a) BioAutomata: a self-driving biofoundry for pathway engineering and protein engineering, (b) CLEAN : an AI tool for enzyme function prediction, (c) EZSpecificity: an AI tool for enzyme substrate specificity prediction, (d) engineered low-pH tolerant yeasts for cost-effective production of organic acids, and (e) repurposed enzymes with new-to-nature reactivity for asymmetric synthesis.

References M. HamediRad, et al. (2019) Nature Communications,10: 5150 T. Yu, et al. (2023) Science, 379, 1358–1363 V. Tran, et al. (2023) Nature Communications, 14:6152 X. Huang, et al. (2020) Nature, 584, 69–74 M. Li, et al. (2024) Science, 385, 416–421 N. Singh, et al. (2025) Nature Communications, 16: 5648 H. Cui, et al. (2025) Nature, 647, 639–647