Computational characterization of recombinase circuits for periodic behaviors

Judith Landau; Christian Cuba Samaniego; Giulia Giordano; Elisa Franco

doi:10.1016/j.isci.2022.105624

Computational characterization of recombinase circuits for periodic behaviors

iScience. 2022 Nov 21;26(1):105624. doi: 10.1016/j.isci.2022.105624. eCollection 2023 Jan 20.

Authors

Judith Landau¹, Christian Cuba Samaniego², Giulia Giordano³, Elisa Franco²

Affiliations

¹ California State University, Los Angeles, Los Angeles, CA, USA.
² University of California, Los Angeles, Los Angeles, CA, USA.
³ Department of Industrial Engineering, University of Trento, Trento, Italy.

Abstract

Recombinases are site-specific proteins found in nature that are capable of rearranging DNA. This function has made them promising gene editing tools in synthetic biology, as well as key elements in complex artificial gene circuits implementing Boolean logic. However, since DNA rearrangement is irreversible, it is still unclear how to use recombinases to build dynamic circuits like oscillators. In addition, this goal is challenging because a few molecules of recombinase are enough for promoter inversion, generating inherent stochasticity at low copy number. Here, we propose six different circuit designs for recombinase-based oscillators operating at a single copy number. We model them in a stochastic setting, leveraging the Gillespie algorithm for extensive simulations, and show that they can yield coherent periodic behaviors. Our results support the experimental realization of recombinase-based oscillators and, more generally, the use of recombinases to generate dynamic behaviors in synthetic biology.

Keywords: Biocomputational method; Bioengineering; Synthetic biology.