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Cell wall dynamics and their regulation by biomolecular condensates in plants.

Jul 2026 · Plant Communications · pp. 102024 · 0 citations
Medicine

TL;DR

This review surveys cell wall biogenesis and integrity pathways during development and under stress and critically evaluates where condensates plausibly participate, and assesses how computational and artificial intelligence approaches might complement experimental work, alongside their present limitations for plant systems.

Abstract

Plant cell walls are dynamic composite structures whose biogenesis, remodelling, and integrity maintenance require coordinated regulation across biosynthetic, trafficking, sensing, and signalling pathways. Plasma membrane-localised receptor kinases and mechanosensitive channels monitor wall status and transduce perturbations into intracellular responses, whilst biomolecular condensates, membrane-less or membrane-associated assemblies formed through liquid-liquid phase separation and related processes, have emerged as candidate organisational features of several of these pathways. Direct experimental evidence linking condensates to cell wall function nonetheless remains sparse, and for many systems it is unclear whether observed puncta represent bona fide phase-separated assemblies. In this review we survey cell wall biogenesis and integrity pathways during development and under stress and critically evaluate where condensates plausibly participate. To keep claims proportionate to the evidence, we apply an explicit hierarchy, classifying each system as direct, indirect, contextual, or speculative. On this basis, the RALF-pectin system, in which extracellular phase separation generates signalling platforms that recruit the receptor kinase FERONIA and its co-receptor LLG1 as client proteins, remains the only directly validated example; most other associations, including P-bodies, stress granules, and nuclear transcriptional condensates, appear to respond to osmotic stress or molecular crowding arising as secondary consequences of wall perturbations. We further assess how computational and artificial intelligence approaches might complement experimental work, alongside their present limitations for plant systems.

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