A Multicolor Split-Fluorescent Protein Approach to Visualize Listeria Protein Secretion in Infection

Abstract : Listeria monocytogenes is an intracellular food-borne pathogen that has evolved to enter mammalian host cells, survive within them, spread from cell to cell, and disseminate throughout the body. A series of secreted virulence proteins from Listeria are responsible for manipulation of host-cell defense mechanisms and adaptation to the intracellular lifestyle. Identifying when and where these virulence proteins are located in live cells over the course of Listeria infection can provide valuable information on the roles these proteins play in defining the host-pathogen interface. These dynamics and protein levels may vary from cell to cell, as bacterial infection is a heterogeneous process both temporally and spatially. No assay to visualize virulence proteins over time in infection with Listeria or other Gram-positive bacteria has been developed. Therefore, we adapted a live, long-term tagging system to visualize a model Listeria protein by fluorescence microscopy on a single-cell level in infection. This system leverages split-fluorescent proteins, in which the last strand of a fluorescent protein (a 16-amino-acid peptide) is genetically fused to the virulence protein of interest. The remainder of the fluorescent protein is produced in the mammalian host cell. Both individual components are nonfluorescent and will bind together and reconstitute fluorescence upon virulence-protein secretion into the host cell. We demonstrate accumulation and distribution within the host cell of the model virulence protein InlC in infection over time. A modular expression platform for InlC visualization was developed. We visualized InlC by tagging it with red and green split-fluorescent proteins and compared usage of a strong constitutive promoter versus the endogenous promoter for InlC production. This split-fluorescent protein approach is versatile and may be used to investigate other Listeria virulence proteins for unique mechanistic insights in infection progression.