Characterizing host-microbe interactions with bacterial effector proteins using proximity-dependent biotin...

Bacterial pathogens have evolved diverse strategies to manipulate host cells to establish infection. At a molecular level, this is often mediated by virulence factors that are secreted into host cells (herein referred to as effectors), which target host cellular pathways by initiating host-pathogen protein-protein interactions that alter cellular function in the host. By establishing this network of host-pathogen protein-protein interactions, pathogenic bacteria modulate and hijack host cell processes for the benefit of the pathogen, ultimately promoting survival, replication, and cell-to-cell spread within the host. Effector proteins also mediate diverse host-microbe interactions in nature, contributing to symbiotic relationships spanning from mutualism to commensalism to parasitism. While effector proteins play crucial roles in nature, molecular properties such as the transient nature of the underlying protein-protein interactions and their affinity for targeting host biological membranes often presents challenges to elucidating host targets and mechanism of action. Proximity-dependent biotin identification (termed BioID) has proven to be a valuable tool in the field of cell biology to identify candidate protein-protein interactions in eukaryotic cells, yet has remained relatively underexploited by bacterial pathogenesis researchers. Here, we discuss bacterial effector function at a molecular level, and challenges presented by traditional approaches to host target identification. We highlight the BioID approach and its potential strengths in the context of identifying host-pathogen protein-protein interactions, and explore BioID's implementation to study host-microbe interactions mediated by bacteria. Collectively, BioID represents a powerful tool for the study of bacterial effector proteins, providing new insight into our understanding of pathogenesis and other symbiotic relationships, and opportunities to identify new factors that contribute to host response to infection.