ReviewCommunications biology2025
Characterizing host-microbe interactions with bacterial effector proteins using proximity-dependent biotin identification (BioID).
Review in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- GeoEPred: A multimodal structure-aware geometric deep learning framework for Gram-negative bacterial secreted effector prediction with sequence semantics.PLoS computational biology · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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Registered trials
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