Thrust 2
Cellular to Multicellular Communication and Coordination
Decoding how cells communicate and integrate mechanical and chemical signals across cellular boundaries.
Project 2A: Mechanochemical Signaling in Plant Immune Responses
Objectives
Project 2A determines how cells communicate and integrate mechanical and chemical signals by studying how plant cells sense microbial pathogens and organize a defense response. Objectives include: (1) quantitatively analyze Ca2+ signaling and determine how it functions upstream of actin dynamics or cytoskeletal remodeling during the plant defense response elicited by a local or global PAMP/DAMP stimulus; (2) identify plant mechanoreceptors involved in perception of fungal/oomycete attack and determine their role in Ca2+ signaling of actin organization/dynamics; and (3) investigate the impact of bacterial effector proteins on cytoskeletal organization in tobacco leaves, specifically focusing on RipU's effects on actin filaments and cortical microtubules.
Research Highlights
Local traveling waves of cytosolic calcium elicited by defense signals or wounding are propagated by distinct mechanisms
Live-cell imaging and modeling revealed that MAMP-induced calcium waves in plants propagate via distinct mechanisms from mechanical damage.
Fig. 1. MAMP-induced Ca²⁺ signatures and cell-to-cell signal propagation follow a defined spatial pattern.
(A) A representative timelapse image series of R-GECO1 fluorescence dynamics in Arabidopsis cotyledon epidermal cells following global treatment with 1 µM flg22. See also Supplemental Movie S1. Cytosolic Ca²⁺ elevations were first detected in initiator cells and then propagated to neighboring cells. Bar = 50 µm. (B) Annotation of initiator cells (N), N+1 and N+2 neighboring cells shown in (A). (C) Representative traces for the Ca²⁺ intensity ratio of an N, N+1 and N+2 cell, respectively. Additional representative traces are shown in Figure S5. Fluorescence intensity changes were calculated as the ratio ΔF/F₀. Black dashed lines indicate the time when flg22 was added. (D) Quantitative analysis of peak features for Ca²⁺ traces from N, N+1 and N+2 cells. Each data point in the box plots represents an average value measured from 5–15 cells from a single cotyledon; data from 8 cotyledons from 3 independent experiments denoted by different shapes are presented in each box plot. One-way ANOVA and Tukey’s HSD test, different letters indicate significant differences with P < 0.05.
Zhang, W., N. Kumar, J. Helwig, A. Hoerter, A.S. Iyer-Pascuzzi, D. Umulis, E. Pienaar, and C.J. Staiger. 2025. Local traveling waves of cytosolic Ca2+ elicited by defense signals or wounding are propagated by distinct mechanisms in Arabidopsis. Science Signaling, 18(915), eadw2270.
Cooperative actin filament nucleation by the Arp2/3 complex and formins maintains the homeostatic cortical array in Arabidopsis epidermal cells
Discovered that Arp2/3 and formins cooperatively maintain actin array architecture in plant cells, with unexpected compensatory nucleation upon dual inhibition.
Figure 1.
Genetic disruption of the Arp2/3 complex leads to reduced actin filament density and bundling. A) Representative images of epidermal cells from the apical region of 5-d-old etiolated hypocotyls expressing GFP-fABD2 imaged by VAEM are shown in the left columns. Scale bar: 20 μm. ROIs (boxes) were magnified and shown in the right columns. Scale bar: 5 μm. B to D) Quantitative analysis of the percentage of occupancy or density of actin filament arrays B) and the extent of filament bundling as measured by skewness C) and coefficient of variance D) analyses. Both the density and the bundling of actin arrays in arp2-1 and arpc2 cells were significantly decreased compared to those in the respective wild-type cells. In box-and-whisker plots, boxes show the interquartile range and the median, and whiskers show the maximum–minimum interval of 3 biological repeats with independent populations of plants. Individual biological repeats are represented with different shapes (n = 30 seedlings, 10 seedlings per biological repeat). Letters a and b denote groups that show statistically significant differences with other genotypes by 1-way ANOVA with Tukey’s post hoc test (P < 0.05). WT, wild type.
Xu, L., L. Cao, J. Li, and C.J. Staiger. 2024. Cooperative actin filament nucleation by the Arp2/3 complex and formins maintains the homeostatic cortical array in Arabidopsis epidermal cells. Plant Cell, 36: 764–789.
A Ralstonia solanacearum type III effector alters the actin and microtubule cytoskeleton to promote bacterial virulence in plants
The bacterial effector RipU was found to disrupt both actin and microtubule networks in plants, enhancing pathogen virulence.
Fig 3. RipUK60 physically associates with the cytoskeleton.
(A) RipUK60-GFP co-immunoprecipitates with actin and tubulin. The indicated constructs were transiently expressed in N. benthamiana leaves. All transgenes were under the control of a 35S promoter. Total protein was isolated 48 hpi, immunoprecipitated by GFP-Trap agarose bead slurry and immunoblotted with the indicated antibodies. (B) RipUK60 associates with tomato actin in a yeast two hybrid assay. Left, SC-Leu-Trp-His + 10 mM 3AT selection plates, right SC-Leu-Trp-His + 100 mM 3AT. Top two rows of each set of panels show that SlActin and RipU interaction promotes yeast growth when cloned as either bait (pDEST32) or prey (pDEST22). Four lower rows are negative controls with either SlActin or RipU and an empty bait or prey vector. Dilutions of indicated constructs were plated on yeast selective media (SC-Leu-Trp-His +3AT). All experiments were repeated at least three independent times. (C) Co-IP/MS analysis. Immunoprecipitation was done by GFP-Trap agarose bead slurry, and eluants were subjected to mass spectrometry. The volcano plots depict the differential enrichment of proteins between 35S:RipUK60-GFP and 35S:GFP. The blue dots are proteins with p-value ≤ 0.05 and log₂FC > 1. Actin and tubulin proteins are indicated in green and red respectively. Two tubulin alpha proteins and an actin protein with greater than 1.5-fold change (log₂FC > 0.585) are indicated. The result represents three independent experiments.
Hiles R., et al. 2024. A Ralstonia solanacearum type III effector alters the actin and microtubule cytoskeleton to promote bacterial virulence in plants. PLoS Pathogens, 20(12):e1012814.
Project 2B: Mechanochemical Control of Wound Healing in Developing Organs
Objectives
Project 2B decodes mechanosensation and chemical signal integration during wound healing in developing animal organs. Objectives: (1) characterize effects of perturbing Piezo expression and function on cell/tissue mechanics in Drosophila wing disc; (2) investigate shared mechanisms of encoding information through second messenger signaling; (3) explore connections between mechanosensors and innate immune response.
Research Highlights
Piezo regulates epithelial topology and promotes precision in organ size control
Piezo identified as modulator of lateral inhibition in Drosophila wing development.
Figure 1. Piezo determines size precision in bilateral organs (A and A′) Drosophila wings from a Piezo-knockout line do not exhibit significant changes in average wing size compared to the control line used to generate the knockout line. (B and B′) Adult Drosophila wings generated using RNAi-mediated knockdown of Piezo and a previously validated corresponding control cross. (C and C′) Overexpression of Piezo in the wing disc results in smaller wings compared to control discs targeting a non-expressed gene with no observed phenotype. The reduction in wing area is visualized by comparing the outline of control wings (orange) with that of Piezo-overexpressed wings (green). (D) Piezo-knockout wings exhibit significant heterogeneity in wing size compared to the original Piggybac lines used to generate the knockout. Bee-swarm plot showing the distribution of wing area for different perturbations to Piezo. KO represents the Piezo-knockout line p value comparing means, and variances of populations are indicated over the solid lines. (E) Bee-swarm plot showing the quantified distribution of wing area for overexpression of Piezo. Superscripts I and II against the Piezo label indicate two different overexpression lines (detailed in the STAR Methods). Bonferroni correction was employed for statistical analysis. For an explanation of the bee-swarm plots, see Figure S2. (F and F′) Sister wings belonging to the control and Piezo-knockout lines demonstrate significant variation between bilateral organs. Red lines have been used to outline the contour of a sister wing. The same contour has been overlaid as dashed red lines for the other sister wing. All scale bars, 1 mm. (G) Bar graph showing the distribution of differences in the area between sister wings of the Piezo-knockout versus knockdown lines. (H) Adult UAS-RyrRNAi fly (control) and (H′) adult ap>PiezoRNAi fly showing significant patterning and symmetry defects between every two wings. Piezo knockdown (KD) caused (H′i) a tumorous and pigmentation phenotype and (H′ii) a less severe blister phenotype using two independent RNAi lines. See also Figures S1–S3.
Mim, M.S., et al. 2024. Piezo regulates epithelial topology and promotes precision in organ size control. Cell Reports, 43(7), 114398.
Reverse engineering morphogenesis through Bayesian optimization of physics-based models
Novel inverse modeling approach using Bayesian optimization for calibrating physics-based models.
Figure 1. a) Apical view of a z-projection of a Drosophila 3rd instar wing imaginal disc. B) Cross-section of the tissue along the anterior-posterior (AP) axis offset from the dorsal-ventral (D, V) boundary. c) The initial geometry used for Surface Evolver simulations. d) Definition of subcellular cytoskeletal interactions used to define the system's total energy. e) Minimum energy configuration obtained after optimization for parameters in Table 3. Note: The loss function measures the error between the experimental shape and the predicted shape from the model.
Kumar, N., et al. 2024. Reverse engineering morphogenesis through Bayesian optimization of physics-based models. npj Systems Biology and Applications, 10, 49.