The glycosyl transferase encoded by the cellulose synthase-like gene CSLD3/KJK/RHD7 (At3g03050) is required for cell wall integrity during root hair formation in Arabidopsis thaliana but it remains unclear whether it contributes to the synthesis of cellulose or hemicellulose. We identified two new alleles, root hair-defective (rhd) 7-1 and rhd7-4, which affect the C-terminal end of the encoded protein. Like root hairs in the previously characterized kjk-2 putative null mutant, rhd7-1 and rhd7-4 hairs rupture before tip growth but, depending on the growth medium and temperature, hairs are able to survive rupture and initiate tip growth, indicating that these alleles retain some function. At 21°C, the rhd7 tip-growing root hairs continued to rupture but at 5ºC, rupture was inhibited, resulting in long, wild type-like root hairs. At both temperatures, the expression of another root hair-specific CSLD gene, CSLD2, was increased in the rhd7-4 mutant but reduced in the kjk-2 mutant, suggesting that CSLD2 expression is CSLD3-dependent, and that CSLD2 could partially compensate for CSLD3 defects to prevent rupture at 5°C. Using a fluorescent brightener (FB 28) to detect cell wall (1 → 4)-β-glucans (primarily cellulose) and CCRC-M1 antibody to detect fucosylated xyloglucans revealed a patchy distribution of both in the mutant root hair cell walls. Cell wall thickness varied, and immunogold electron microscopy indicated that xyloglucan distribution was altered throughout the root hair cell walls. These cell wall defects indicate that CSLD3 is required for the normal organization of both cellulose and xyloglucan in root hair cell walls.
Microtubule dynamics are critically important for plant cell development. Here, we show that Arabidopsis thaliana ARMADILLO-REPEAT KINESIN1 (ARK1) plays a key role in root hair tip growth by promoting microtubule catastrophe events. This destabilizing activity appears to maintain adequate free tubulin concentrations in order to permit rapid microtubule growth, which in turn is correlated with uniform tip growth. Microtubules in ark1-1 root hairs exhibited reduced catastrophe frequency and slower growth velocities, both of which were restored by low concentrations of the microtubule-destabilizing drug oryzalin. An ARK1-GFP (green fluorescent protein) fusion protein expressed under its endogenous promoter localized to growing microtubule plus ends and rescued the ark1-1 root hair phenotype. Transient overexpression of ARK1-RFP (red fluorescent protein) increased microtubule catastrophe frequency. ARK1-fusion protein constructs lacking the N-terminal motor domain still labeled microtubules, suggesting the existence of a second microtubule binding domain at the C terminus of ARK1. ARK1-GFP was broadly expressed in seedlings, but mutant phenotypes were restricted to root hairs, indicating that ARK1's function is redundant in cells other than those forming root hairs.
Highlights d Microtubules are persistent at cell contours exposed to high mechanical stress d Absence of both KATANIN and CLASP results in cells resembling soap bubbles d CLASP, unlike KATANIN, largely influences mechanoresponse only at the subcellular scale d Microtubule response to subcellular mechanical stress does not influence tissue shape
Cell shape is crucial for the function and development of organisms. Yet, versatile frameworks for cell shape quantification, comparison, and classification remain underdeveloped. Here, we introduce a visibility graph representation of shapes that facilitates network-driven characterization and analyses across shapes encountered in different domains. Using the example of complex shape of leaf pavement cells, we show that our framework accurately quantifies cell protrusions and invaginations and provides additional functionality in comparison to the contending approaches. We further show that structural properties of the visibility graphs can be used to quantify pavement cell shape complexity and allow for classification of plants into their respective phylogenetic clades. Therefore, the visibility graphs provide a robust and unique framework to accurately quantify and classify the shape of different objects.
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