Research Article | Open Access

Volume 2024 |Article ID 0049 | https://doi.org/10.34133/bdr.0049

Dynamic Gene Expression Mitigates Mutational Escape in Lysis-Driven Bacteria Cancer Therapy

Filippo Liguori,^1,2 Nicola Pellicciotta,^1,3 Edoardo Milanetti,^1,2 Sophia Xi Windemuth,⁴ Giancarlo Ruocco,^1,2 Roberto Di Leonardo,^1,3 Tal Danino ^4,5,6

¹Department of Physics, Sapienza University of Rome, Rome, Italy
²Center for Life Nano- & Neuro-Science,Istituto Italiano di Tecnologia, Rome, Italy
³NANOTEC-CNR, Soft and Living Matter Laboratory, Institute ofNanotechnology, Rome, Italy
⁴Department of Biomedical Engineering, Columbia University, New York, NY,USA
⁵Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
⁶Data ScienceInstitute, Columbia University, New York, NY, USA

Abstract

Engineered bacteria have the potential to deliver therapeutic payloads directly to tumors, with synthetic biology enabling precise control over therapeutic release in space and time. However, it remains unclear how to optimize therapeutic bacteria for durable colonization and sustained payload release. Here, we characterize nonpathogenic Escherichia coli expressing the bacterial toxin Perfringolysin O (PFO) and dynamic strategies that optimize therapeutic efficacy. While PFO is known for its potent cancer cell cytotoxicity, we present experimental evidence that expression of PFO causes lysis of bacteria in both batch culture and microfluidic systems, facilitating its efficient release. However, prolonged expression of PFO leads to the emergence of a mutant population that limits therapeutic-releasing bacteria in a PFO expression level-dependent manner. We present sequencing data revealing the mutant takeover and employ molecular dynamics to confirm that the observed mutations inhibit the lysis efficiency of PFO. To analyze this further, we developed a mathematical model describing the evolution of therapeutic-releasing and mutant bacteria populations revealing trade-offs between therapeutic load delivered and fraction of mutants that arise. We demonstrate that a dynamic strategy employing short and repeated inductions of the pfo gene better preserves the original population of therapeutic bacteria by mitigating the effects of mutational escape. Altogether, we demonstrate how dynamic modulation of gene expression can address mutant takeovers giving rise to limitations in engineered bacteria for therapeutic applications.