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. 2023 May 2;42(9):e111885.
doi: 10.15252/embj.2022111885. Epub 2023 Feb 6.

An actin remodeling role for Arabidopsis processing bodies revealed by their proximity interactome

Chen Liu  1 , Andriani Mentzelopoulou  2   3 , Amna Muhammad  1   4 , Andriy Volkov  5 , Dolf Weijers  5 , Emilio Gutierrez-Beltran  6   7 , Panagiotis N Moschou  1   2   3
Affiliations

An actin remodeling role for Arabidopsis processing bodies revealed by their proximity interactome

Chen Liu et al. EMBO J. .

Abstract

Cellular condensates can comprise membrane-less ribonucleoprotein assemblies with liquid-like properties. These cellular condensates influence various biological outcomes, but their liquidity hampers their isolation and characterization. Here, we investigated the composition of the condensates known as processing bodies (PBs) in the model plant Arabidopsis thaliana through a proximity-biotinylation proteomics approach. Using in situ protein-protein interaction approaches, genetics and high-resolution dynamic imaging, we show that processing bodies comprise networks that interface with membranes. Surprisingly, the conserved component of PBs, DECAPPING PROTEIN 1 (DCP1), can localize to unique plasma membrane subdomains including cell edges and vertices. We characterized these plasma membrane interfaces and discovered a developmental module that can control cell shape. This module is regulated by DCP1, independently from its role in decapping, and the actin-nucleating SCAR-WAVE complex, whereby the DCP1-SCAR-WAVE interaction confines and enhances actin nucleation. This study reveals an unexpected function for a conserved condensate at unique membrane interfaces.

Keywords: ARP2-ARP3; LLPS; SCAR-WAVE; condensates; plasma membrane domains.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1. The pipeline of the APEAL approach

  1. Overview of the APEAL pipeline. Upon 24 h biotin feeding and treatment (supplied with 50 μM biotin directly into leaves of 4‐week‐old plants by syringe infiltration), total proteins are extracted from infiltrated leaves. The proteome is subjected to AP‐immunocapture of the FLAG tag. In the AP step, some of the captured proteins will be biotinylated. The PDL step uses the leftover supernatant from the AP step and captures biotinylated proteins with streptavidin beads. PPI, protein–protein interactions; AP, affinity purification; PDL, proximity‐dependent biotin ligation; FLAG IP, FLAG‐beads immunoprecipitation; DYNA‐IP, streptavidin‐bead immunoprecipitation. We use the term “proxitome,” to describe the proteins captured by the PDL step of APEAL. These proteins may not physically interact with DCP1.

  2. Heatmap showing the “core processing body (PB)” (magenta) components identified and other linked proteins. RBP47 is a stress granule marker (SGs; blue). RH52 is a new helicase identified as a PB component (green arrow). The scale on the right shows log2FC of protein abundance. Note that only the PB core components were enriched in the PDL (i.e., the proxitome, log2FC ~ 1 or above) but not in AP. Furthermore, heat stress (HS) increased the enrichment of some PB core components.

  3. Comparison of AP/PDL interacting networks produced from APEAL. STRING density plots of pairwise interactions between proteins obtained from the AP or PDL steps (combined interactions found in non‐stress [NS]/[HS]). Note that PDL produces an overall denser interaction network (under standard parameters, the same number of proteins was selected for AP/PDL).

  4. Venn diagram showing the proteins identified for PDL and AP in NS and HS samples (PPIs fulfilling the criterion log2FC > 1).

Source data are available online for this figure.
Figure EV1
Figure EV1. Establishment of a functional DCP1 bait for PDL

  1. The DCP1‐TurboID‐HF construct efficiently rescues the adult dcp1‐3 mutant phenotype. Phenotypes (3‐week‐old) of adult plants expressing 35Spro:DCP1‐TurboID‐HF and RPS5apro:HF‐mScarlet‐DCP1 in the dcp1‐3 mutant background. In a semi‐controlled greenhouse setting (temperature control 22°C), the dcp1‐3 mutant showed a smaller adult stature. Lower: complementation quantification (rosette diameter), N, biological replicates = 4, n = (pooled data of 3 biological replicates) 5–7 rosettes, error bars are (mean + SD) and RT‐qPCR analyses for the quantification of DCP1 expression levels. PP2A and Actin7 were used for normalization (1‐week‐old) seedlings (N, biological replicates = 2, n (pooled data of 3 biological replicates) = 3, error bars are mean + SD). When DCP1 was driven by the RPS5a promoter (stem cell‐specific promoter), we observed partial complementation, suggesting that DCP1 is important also in non‐meristematic cells.

  2. Immunoblot analyses of lines expressing sGFP‐TurboID‐HF or DCP1‐TurboID‐HF upon NS or HS conditions (same as used for APEAL). The immunoblots also show the accumulation of auto‐biotinylated sGFP‐TurboID‐HF or DCP1‐TurboID‐HF in a time course of biotin administration (as detected with streptavidin‐HRP, which captures biotinylated proteins). 50 μM Biotin was delivered in leaves by syringe infiltration and diffusion. Note that HS did not increase the biotinylation efficiency of DCP1‐TurboID‐HF: at 24 h, compare samples “2” with “4” in the “DynaIP”. HF, 6xhis‐3xFLAG. The red arrowhead indicates the position of DCP1‐TurboID‐HF and green for sGFP‐TurboID‐HF (N, biological replicates = 2). We used the same scheme for biotin application as determined in (Arora et al, 2020). The 2 h NS/HS corresponds to the timing after the administration of biotin for 24 h (t = 0 corresponds to 24 h biotin administration in NS conditions). The red asterisk indicates non‐specific band. α‐FLAG was used for the detection of DCP1‐TurboID‐HF and sGFP‐TurboID‐HF (similar size ~ 130 kDa). α‐Tubulin and ponceau staining were used for loading control.

  3. Representative confocal micrographs showing that the localization of DCP1 (α‐FLAG, 5‐day‐old seedlings, root cap cells) to PBs is retained in lines expressing DCP1‐TurboID‐HF. As a control, the GFP‐TurboID‐HF line was used that does not show localization to PBs. Right: number of DCP1‐positive foci in the corresponding lines expressing DCP1 (N, biological replicates = 1, n = 32–60 cells).

Data information: In (A and B), P values were determined by ordinary one‐way ANOVA. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure EV2
Figure EV2. Biotinylated proteins evade purification from the AP step in APEAL
Immunoblot analyses from lines expressing GFP‐TurboID‐HF or DCP1‐TurboID‐HF (denoted as GFP or DCP1, respectively) showing the presence of biotinylated proteins in the flow‐through after the AP‐step (for flow‐through 1, see DYNA‐IP here). The blot was overexposed to detect the faint streptavidin smear in flow‐through 1. The baits in these experiments undergo auto‐biotinylation, as reported previously. The results are representative of one experiment performed three times. Note that the immunodetectable biotinylation levels did not correlate well with the hits identified in Fig EV5 (compare GFP to DCP1). GFP and DCP1 are of similar molecular weight, while the bands below the upper band (~ 130 kDa) likely correspond to proteolytic cleavage products.
Figure EV3
Figure EV3. Hits from the APEAL approach (AP and PDL steps)
Total protein hits from mass spectrometry under NS or HS conditions following the AP (left) or PDL (right) steps of APEAL. We used the same scheme for biotin application, as described (Arora et al, 2020). The results presented are unfiltered, containing the noisy portion of the proteome. Note that the free diffusion of GFP in vivo led to increased proteins identified. sGFP‐TurboID‐HF, GFP; DCP1‐TurboID‐HF, DCP1 (N, biological replicates = 3, error bars are mean ± SD). Note the increased numbers of hits in GFP/PDL reflect the noisy proteome. GFP is expected to produce more noise (translated as hits in the context of the proteome), due to the increased diffusion over the specifically and topologically restricted DCP1 (confirmed in Fig EV1, localizations). The decreased number of hits for HS conditions corresponds mainly to proteins of signal transduction and metabolism, as well as vesicle trafficking proteins (see also Fig 2 and below for an explanation: HS reduces the DCP1 association with the PM). Furthermore, DCP1, as described below, loses localization at the PM during HS. Data information: AP/PDL GFP samples did not differ at P < 0.005 (determined by an unpaired t‐test); ***P ≤ 0.05, as determined by an unpaired t‐test for comparison between HS and NS GFP samples.
Figure 2
Figure 2. APEAL captured the PB proteome and proxitome
  1. A

    Volcano plots showing significantly enriched proteins in NS and HS conditions from the AP and PDL APEAL steps. Selected proteins are indicated in magenta and are encoded by genes that belong to the identified subnetworks described in (C) and (D). Magenta indicates enrichment in HS samples; cyan indicates depletion in HS samples.

  2. B–E

    Gene Ontology (GO) enrichment analyses of the APEAL results, divided into four subnetworks. Note the terms related to vesicle trafficking and actin remodeling. A more detailed description is provided in Fig EV5 and in the Appendix text. Note that signal transduction proteins, metabolism‐related proteins, and vesicle trafficking proteins evade PBs during HS (Fig EV5, reduced hit number), while the opposite pattern is observed for actin and RNA metabolism subnetworks. FDR, false discovery rate. Important links described below are indicated (i.e., to the SCAR–WAVE/ARP2–ARP3 (and the component NAP1 which is part of the SCAR–WAVE and links to autophagy), cytoskeleton, PB core, and cell‐wall‐related metabolism).

Source data are available online for this figure.
Figure EV4
Figure EV4. DCP1 colocalization and association with novel and known interactors in transient expression of N. benthamiana leaves

  1. Bimolecular fluorescence complementation (BiFC) assay of the indicated proteins. Left: the cartoon depicts the BiFC concept and YFP reconstitution caused by protein–protein interaction in vivo. When two proteins interact, the cYFP and nYFP halves are brought in proximity and produce a fluorescent signal. For protein selection, we classified the associations with DCP1, in both AP and PDL steps, according to their relative enrichment (log2FC). We selected proteins presenting moderate relative enrichment in the AP step, while having high predictability in the PDL step (log2FC > 0 in both steps). As an additional filter, we selected proteins rich in IDRs (half of the proteins from the list have high prion‐like domain (PRD) scores and high Finum [aa]/total [aa] ratios as defined through the PLAAC algorithm; Source File 8), and as such proteins would be likely to localize to condensates. We tested the association between PBs (using DCP1 as one representative component) and selected five proteins from these bins using BiFC and colocalization assays (Source File 8). These results suggested that the APEAL approach may help identify PB components or DCP1 interactors. These interactions should be further studied in Arabidopsis. BiFC efficiency was estimated from the reconstituted YFP raw signal intensity and YFP‐positive puncta per cell in maximum projections (N, biological replicates = 3, n = 4–12 cells). Lower left: representative confocal micrographs showing that YFP signal is reconstituted at cellular puncta that most likely correspond to PBs. XRN3 represents negative control (see also B), as it localizes in the nucleus. Right: number of cellular puncta per total cell volume (in maximum projection images; N, biological replicates = 3, n (pooled data of 3 biological replicates) = 20 cells, error bars are mean + SD). Scale bars: 10 μm.

  2. Colocalization of selected proteins with DCP1‐CFP‐positive puncta (35Spro:DCP1‐CFP transgene). The coding sequences of the corresponding “interactors” (PPIs; direct or indirect, defined in APEAL) were driven by the 35Spro and cloned in frame with mCherry at their 5′ end. Two‐color colocalizations were estimated by Pearson's correlation coefficients (PCC) using ultra‐fast super‐resolution microscopy combined with image deconvolution (~ 120 nm axial resolution). Numbers in “merge” indicate colocalization frequency between DCP1‐CFP and the corresponding interacting protein (N, biological replicates = 2, n = 5 cells). Yellow arrowheads indicate colocalization and red arrowheads lack of colocalization. Lower right: PCC of pixel intensities between DCP1‐CFP and the corresponding putative interacting protein (N, biological replicates = 3, n = 4–12 cells, error bars are mean + SD). We confirmed the ECT domain‐containing proteins, MLN51, FLXL1, EIN2, VAP27‐1, uncharacterized AT1G33050 (hypothetical protein), and AT5G53330/AT2G26020 (ubiquitin‐associated/translation elongation factors EF1B) as novel PB components. By applying a pre‐selection criterion of enrichment (log2FC > 0.5) for the selection of prey, we significantly increased the probability of identifying successful binary interactions between PBs (i.e., cYFP‐DCP1) and the identified proteins. All preys were confirmed as PB components, while PDL had higher interaction predictive power than the AP step irrespective of whether proteins were enriched in NS or HS. XRN3 was used as a threshold control (log2FC = −0.58, PDL/NS conditions). The heatmap shows the enrichment of these proteins in the different conditions; the scale at right shows log2FC.

Data information: In (A and B), P values were determined by ordinary one‐way ANOVA (differences were all calculated compared to XRN3). Source data are available online for this figure.
Figure EV5
Figure EV5. Structure and density of the four interconnected networks
Subcluster analyses of APEAL reveal four interconnected subnetworks (center). The four networks were as follows: proteins related to RNA metabolism; signal attenuation, translation and metabolism; vesicle trafficking and actin remodeling. Heatmaps depict the abundance of selected proteins from the four subnetworks. Notably, the AP step in the “purple” heatmap did not lead to the identification of RNA metabolism proteins. In Appendix text, we summarize interesting hits from each network.Source data are available online for this figure.
Figure 3
Figure 3. DCP1 protein interfaces with the plasma membrane

  1. Diagram of a root showing the three developmental regions (1–3) under examination in this study: stem cell niche (SCN; region 1), meristematic zone (MZ; region 2), and transition zone (TZ)‐differentiation zone (DFZ; region 3). The different cell types are color‐coded. The region used in TIRF‐M experiments is highlighted by the dashed magenta rectangle (region 3, see also B).

  2. Representative TIRF‐M of DCP1‐GFP (DCP1pro:DCP1‐GFP transgene) in the lateral PM of epidermal cells showing the transient attachment of DCP1‐positive puncta to the PM. Yellow arrowheads denote a PB that shows motility at the PM focal plane; blue arrowheads show a PB that transiently localizes to the PM. Scale bars: 2 μm. The corresponding kymographs are shown to the right. Right: distribution of immobile and mobile DCP1 molecules relative to the motility log(D) value of −0.75 (threshold; see Materials and Methods for details), in NS or HS conditions (D, diffusion coefficient). Inset: individual trajectories of mobile DCP1‐GFP in NS and HS conditions (500 frames, n = 120), showing a combination of directional and Brownian motion for both NS/HS. The green arrowheads denote the beginning of the NS and HS tracks for DCP1‐GFP.

  3. Representative confocal micrographs from lines co‐expressing RPS5apro:HF‐mScarlet‐DCP1 and PIN2pro:PIN2‐GFP (epidermal cells, region 3, Scale bars: 5 μm). Bottom: polarity index of DCP1 in root meristematic cells (compared to propidium iodide (PI) and tubulin staining of root cells; N, biological replicates = 3 roots, n = 13 cells). Polarity index is calculated as the ratio of average of apical and basal VS lateral side of fluorescence signal intensity of the root epidemies cells. The arrowhead in PIN2 indicates the cell plate or PM in DCP1. Right: representative confocal micrographs showing that PM localization is independent of the promoter used (DCP1pro, 35Spro; region 2, epidermal cells, or RPS5apro on the lower right). The details from the inset show increased localization at the cell edge (discussed later). mSc, mScarlet. Scale bars: 7 μm.

Data information: In C, P values were determined by Wilcoxon. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure 4
Figure 4. DCP1 protein accumulates at edges and then vertices during development

  1. Left: Gradual edge or vertex accumulation of DCP1‐GFP in three different root regions. DCP1 signal intensity among the three different regions, at the edge/vertex (epidermis). Right: z cross‐sectional images of DCP1‐GFP (green) in the whole root compared to FM4‐64 staining (magenta, staining membranes). The circular plots indicate the average DCP1 localization (regions 1–3; N, biological replicates = 3, n = 10 cells; comparing regions 1–2 and 2–3). The 3D‐rendered images (PIN2‐GFP vs. mSCarlet‐DCP1) show the localization of mScarlet‐DCP1 at edges/vertices in two different regions (in comparison to PIN2‐GFP signal which decorated almost evenly the PM). Scale bars: 20 μm. Arrowhead denotes the edge (region 2) and the vertex (region 3) decorated by mScarlet‐DCP1 (also in the z cross‐sectional image). Note in a single cell file, how the localization from the PM changes to the edge, as indicated, along the proximodistal axis.

  2. Representative confocal micrograph of DCP1‐GFP (DCP1pro:DCP1‐GFP, transgene) in root meristematic cells under NS/HS conditions (region 2). Scale bars, 5 μm. Note the depletion of DCP1 from the PM upon HS, but the increased edge/vertex signal (yellow arrowheads denote the vertex signal). Right: DCP1 signal intensity at the PM or edge/vertex (N, biological replicates = 3, n (pooled data of 3 biological replicates) = 18–23 PMs or edges/vertices).

  3. Representative confocal images showing fusion (coarsening), fission, and growth of PBs (DCP1‐positive) at the PM (region 3). Right: states of PBs (dynamic: fusion and fission and non‐dynamic: stable; N, biological replicates = 2, n (pooled data of 3 biological replicates) = 6–8 PBs). As a cautionary note, the “stable” PBs may not show dynamicity in the imaging time used (~ 3–5 min) but later, may do.

Data information: In (A), *P < 0.05 was determined by a nested t‐test. In (B), P values were determined by the Kolmogorov–Smirnoff, while in (C) by one‐way ANOVA. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure 5
Figure 5. DCP1 interacts with DCP2 in a PLA assay occasionally in the cytoplasm but not at the PM
Confocal micrographs showing single optical sections PLA‐assays producing signal that resembles spots. The antibodies used were anti‐FLAG/anti‐GFP detecting the HF‐mScarlet‐DCP1/ DCP2‐YFP, respectively (RPS5apro:HF‐mScarlet‐DCP1 and 35Spro:DCP2‐YFP). Inset 1: magnification showing the colocalization of PLA spots with DCP1 or DCP2 signals (colocalization and Pearson's correlation coefficient PCC value for the spots shown). The dotted white line in the PLA channel corresponds to the PM plane. Inset 2: positive PLA signal for DCP1 and DCP2 in the nucleus. “n1‐n3” correspond to nuclei regions (green circles). On the right, note the PLA spot nearby the nucleus (“detail of PLA signal”). The chart shows the quantification of PLA spots per cell at puncta (cytoplasm) or on the PM (N, biological replicates = 3, n (pooled data of 3 biological replicates) = 16–33 cells). As a cautionary technical note, the cytoplasmic, nuclear or PM “spots” do not connote physiologically relevant puncta, condensates, or PM clusters. Scale bar: 20 μm / 10 μm for the insets. Data information: In (A), *P < 0.05 was determined by one‐way ANOVA. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values.
Figure 6
Figure 6. DCP1 cooperates with the SCAR–WAVE complex

  1. DCP1 colocalizes with the SCAR–WAVE components SCAR2 and BRK1. Representative confocal micrographs showing colocalization between DCP1 and SCAR2 or DCP1 and BRK1 (in lines coexpressing DCP1pro:DCP1‐GFP and SCAR2pro:SCAR2‐mCherry or RPS5apro:HF‐mScarlet‐DCP1 and BRK1pro:BRK1‐YFP; arrowheads indicate colocalization at cell edges or vertices) in root epidermal cells (regions 2–3). Right: relative signal intensity profiles of DCP1 or SCAR2 at vertices. Colocalization at these regions was also calculated (PCC; N, biological replicates = 2, n = 4–10 edges/vertices in regions 2–3; a slight increase was observed in HS, 0.78 in NS vs. 0.87 in HS). Scale bars: 10 μm.

  2. Representative confocal micrographs with acceptor photobleaching‐FRET efficiency between SCAR2‐mCherry (up) or BRK1‐mRuby (down) and DCP1‐GFP (epidermal cells, regions 1 and 3). Right: normalized FRET efficiency between SCAR2 or BRK1 and DCP1, respectively, among the different developmental root regions (N, biological replicates = 2, n = 16 cells). Scale bars: 3 μm.

  3. Representative confocal micrographs showing PLA spots produced by α‐GFP/α‐RFP in DCP1‐GFP/SCAR2‐mCherry lines and DCP1‐GFP/BRK1‐mRuby lines, α‐FLAG/α‐GFP in HF‐mScarlet‐DCP1/SPI‐YPet (SPIRRIG [SPI] is a negative control as it localizes to PBs only during salt stress and was not found in the APEAL). In the SPI PLA, a high contrast inset is presented. Right: number of PLA spots per cell (N, biological replicates = 3, n (pooled data of 3 biological replicates) = 14–33 cells). In the merged images, the cell contours are shown (light green transparent). Scale bars: 5 μm.

  4. Representative confocal micrographs showing DCP1 localization detected by α‐DCP1 in the wild type (WT) or the scar1 scar2 scar3 scar4 (scar1234) quadruple mutant or in live‐cell imaging of mScarlet‐DCP1 (RPS5apro:HF‐mScarlet‐DCP1) in WT or brk1 mutant (bottom right; epidermal cells, region 3 for α‐DCP1 and 2 for live‐cell imaging). The arrowheads denote the lack of robust DCP1 localization in scar1234 at the edge/vertex. Small panels (insets) at right show details corresponding to the regions delineated by dashed lines, where arrowhead denotes the edge signal of DCP1 in WT; scale bars, 1 μm. Bottom: percentage of cells with proper edge/vertex localization and quantification of PB numbers (DCP1‐foci; N, biological replicates = 3, n (pooled data of 3 biological replicates) = 18–35 cells). Scale bars, 5 μm.

Data information: In (B), P values were determined by Kruskal–Wallis, and the comparisons are among the scar1234 to the corresponding WT samples. In (C and D), P values were determined by Wilcoxon. PCCs are means ± s.d. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure 7
Figure 7. DCP1 Phosphostatus defines its localization at the edge or vertex where it regulates Actin remodeling

  1. Representative confocal micrographs showing colocalization between DCP1 or two DCP1 phosphovariants with LifeAct‐mCherry in lines co‐expressing DCP1pro:DCP1‐GFP (or variants) and UBQ10pro:LifeAct‐mCherry (cell edges are indicated by yellow arrowheads). Right: relative signal intensity of actin at cell edges/vertices (normalized to the PM) in epidermal cells (N, biological replicates = 3, n = 15–30, regions 2–3). Scale bars: 7 μm.

  2. Representative high‐resolution confocal micrographs showing the localization of DCP1‐GFP or phosphovariants (regions 2–3, epidermal cells). Left: signal at the vertex, expressed as a color‐coded edge/cytoplasmic signal ratio. Right: representative 3D projection from super‐resolution (120 nm axial, FM4‐64 counterstaining of PM) images of root meristematic cells captured from DCP1pro:DCP1‐GFP and phosphovariants (N, biological replicates = 4, n = 8). Circular insets show the differential vertex localization of DCP1 (absent in DCP1S237D‐GFP line), and arrowheads denote the vertex. Note the enhanced accumulation of DCP1S237A‐GFP at the vertex. Scale bars: 15 μm.

Data information: In (A), P values were determined by Kruskal–Wallis, while in (B), *P < 0.005 by ordinary one‐way ANOVA relative to unmutated DCP1. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure 8
Figure 8. DCP1 Phosphostatus regulates Actin remodeling at the edge

  1. Representative confocal 3D rendering micrographs of root meristematic cells from the WT or the dcp1‐3 mutant stained with phalloidin for actin visualization (N, biological replicates = 3, n = 4). Scale bars: 5 μm (z‐scale is 4 μm). Upper middle: the “Spectrum” micrographs indicate the maximum color‐coded signal intensity (scale on the right, middle inset). Note that the signal is evenly distributed in region 1 (left upper micrograph), whereas it mostly accumulates at the edge or vertex in regions 2 and 3 (see arrowheads; images on top). Lower middle: a detail of the higher actin accumulation at edges/vertices in region 2 (compare regions 1 and 2, Scale bars: 7 μm). Insets (details, Scale bars: 2 μm) indicate the loss of vertex actin accumulation in dcp1‐3. Right: plot profile from the actin signal in the WT or dcp1‐3. The vertices are indicated.

  2. Representative confocal micrographs showing actin localization in WT, dcp1‐1, dcp1‐3, scar1234, dcp2‐1, dcp5, and pat1 upon phalloidin staining and graph (right) indicating the percentage of cells in region 3 with an accumulation of actin at edges in various genotypes (N, biological replicates = 3, n = 7–9 roots, bars show means + s.d.). Scale bars: 7 μm.

Data information: In A, P values were determined by Kruskal–Wallis, while in (B), the exact P values were determined by Brown–Forsythe and Welch ANOVA. Source data are available online for this figure.
Figure 9
Figure 9. Mutual potentiation of DCP1 and SCAR‐WAVE localization at the edge/vertex

  1. SE‐FRET efficiency between DCP1‐GFP or its phosphovariants with SCAR2‐mCherry (among the three different root regions; mainly epidermal cells). Scale bar: 50 μm. The arrowhead denotes high FRET efficiency at edges/vertices of region 3. Right: signal quantification of SE‐FRET efficiency between the indicated combinations at the epidermis of 3 regions (N, biological replicates = 6, n (pooled data of 3 biological replicates) = 10).

  2. Actin nucleation site at an edge/vertex, as indicated by DCP1‐GFP and LifeAct‐mCherry localization. Right: correlation between DCP1 intensity, ACTIN, SCAR2, BRK1 and ARPC5 intensities (simple regression model). The R 2 values are shown, along with representative micrographs for DCP1/SCAR2 (N, biological replicates = 3, n = 6 for each point).

  3. Representative confocal micrographs showing SCAR2‐mCherry localization in WT and dcp1‐3 mutant, respectively (root region 2, epidermal cells) and quantification of edge/vertex with SCAR2 a confined signal (N, biological replicates = 3, n = 5–8 cells).

  4. Representative confocal micrographs showing the colocalization between DCP1‐GFP or phosphovariants and SCAR2‐mCherry in root meristematic cells (root region 2, epidermal cells). Scale bars: 10 μm. The insets show details of colocalization; the white arrowhead denotes the expansion of the SCAR2/DCP1 domain, while the yellow arrowheads the restricted edge/vertex SCAR2/DCP1 domains. Scale bars: 3 μm. The graph indicates the relative signal intensity for the indicated combinations (as Pearson's correlation coefficient; N, biological replicates = 3, n = 5 at edges/vertices: spread edges were not considered in calculations).

Data information: In (A and B), *P < 0.005 were determined by nested one‐way ANOVA relative to the WT in the respective region. In (B), a simple linear regression (best‐fitted model) with a 95% confidence interval is shown with dashed lines. In (C and D), P values were determined by an unpaired t‐test. Upper and lower lines in the violin plots when visible, represent the first and third quantiles, respectively, horizontal lines mark the median and whiskers mark the highest and lowest values. Source data are available online for this figure.
Figure 10
Figure 10. The SCAR–WAVE‐DCP1 nexus at the vertex can modulate growth anisotropy

  1. Representative images showing the phenotypes of dcp1 mutants and mutants in other PB core components or SCAR–WAVE components (5‐day‐old seedlings). The arrowheads show the growth defects of homozygous dcp1‐1 or dcp2‐1 mutants (denoted −/−; heterozygous denoted dcp1‐1/DCP1; details are also shown). Lower: graph showing relative root length (N, biological replicates = 3, n (pooled data of 3 biological replicates) = 3–4 roots, bars show means + s.d).

  2. DCP1 regulates cell expansion anisotropy. Representative confocal micrographs showing FM4‐64 staining of the WT, dcp1‐1 and dcp2‐1 mutants (2 μM, 10 min). Scale bars, 20 μm. Right: percentage of isotropic cells per root meristem (%, epidermal cells) in each genotype (N, biological replicates = 3, n (pooled data of 3 biological replicates) = 3–5 roots, bars show means ± s.d). Examples of isotropic or anisotropic cells are shown, along with the developmental axis offset at the x‐ and y‐axes.

Data information: In (A and B), P values were determined by ordinary one‐way ANOVA (Kruskal–Wallis produced similar results, with Dunn's or FDR corrections). Source data are available online for this figure.
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