ReviewPlants (Basel, Switzerland)2026
Control Targets in Plant-Pathogenic Bacteria: From Growth-Essential Processes to Anti-Virulence Strategies and Candidate Targets in
Review in Plants (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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8 authors.
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Abstract
Plant-pathogenic bacteria threaten crop productivity and quality, yet chemical options remain limited compared with those for fungal and oomycete diseases. Current management relies mainly on copper bactericides, limited antibiotics, induced-resistance agents, biocontrol and resistant cultivars. However, copper and streptomycin resistance, efflux-mediated multidrug tolerance and rapid pathogen adaptation have weakened these strategies. Target-oriented research provides a framework for exploring agricultural antibacterials, anti-virulence agents, anti-colonization strategies, resistance sensitizers and host-resistance interventions, but many of these approaches remain conceptual, model-system, greenhouse or medical-bacteriology-derived rather than proven field solutions. This review classifies bacterial control targets into two interconnected groups: growth-essential targets, including peptidoglycan biosynthesis, membrane/envelope systems, nucleic-acid processes, protein synthesis, metabolism, nutrient transport and cell division; and anti-virulence/anti-adaptation targets, including secretion systems, quorum sensing, biofilms, motility, adhesion, cell-wall-degrading enzymes, tolerance systems, oxidative-stress responses and host susceptibility factors. Using "
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.