Leveraging Autonomous Biological Oscillators for Directed Evolution of Switchable Proteins

Engineering proteins that can switch between states is of strong interest to biotechnology. These include multi-state transcription factors, membrane receptors, kinases, and synthetic molecular logic gates. While traditional directed evolution approaches excel at optimizing steady-state protein functionalities, they require substantial adaptation to treat transitions in states of proteins. This chapter describes how the emerging regulatory logic of autonomous biological oscillators can be used to impose time-varying selection pressure for evolving switchable proteins. We first review the challenges of evolving switchable proteins and examine past strategies, including fluorescence-activated cell sorting (FACS) screens, alternating chemical selection and counterselection methods, and phage display techniques. We then compare these with "optovolution," an approach recently developed by our lab, which couples a protein's activity to host cell cycle progression and leverages programmable light inputs to drive continuous evolution of proteins. To this end, we explain the design principles underlying the use of an autonomous oscillator for evolution and how it promotes selection for both "on" and "off" states, as well as switching between them. In a direct comparison with a conventional directed evolution method, we elucidate how optovolution proves more reliable by avoiding evolutionary routes that hinder counterselection. In conclusion we discuss how optovolution opens new avenues for creating proteins with complex logic and dynamic control, complementing latest advances in computational protein design.