Characterization of cellular wound resistance in the giant ciliate Stentor coeruleus

Abstract

Resistance to mechanical stress is essential for cells to prevent wounding and maintain structural integrity. This capability is especially critical for free-living single-celled organisms, which routinely encounter mechanical stress from their natural habitats. We investigated Stentor coeruleus, a single-celled ciliate known for its remarkable wound repair capacity, as a model for studying mechanical wound resistance. While previous work focused on wound repair in Stentor, the structures that enable it to resist wounding remain poorly understood. We characterized how Stentor resisted mechanical stress during transit through a microfluidic constriction. Using high-speed imaging, we tracked the transit dynamics of the cells and linked them to wounding outcomes. Larger cells experienced longer transit times in the constriction and were more prone to rupture, often failing to recover shape due to membrane rupture and loss of cytoplasm. To elucidate the role of the Stentor cytoskeleton, we performed drug-mediated disruption of KM fibers, which are microtubule bundles in the Stentor cytoskeleton. Drug-treated cells exhibited an increased likelihood of membrane rupture at the constriction, implicating KM fibers in wound resistance. To investigate the resistance of Stentor cells to hydrodynamic stress, we injected the cells at increasing flow rates through the constriction. Interestingly, cells were more resistant to larger hydrodynamic stresses up to a threshold, potentially due to shear-thinning of the cytoplasm. Together, these results suggest that Stentor relies on both cytoskeletal architecture and cytoplasmic rheology to withstand mechanical stress, offering insights into cellular strategies for wound resistance in the absence of rigid extracellular structures.

Fig. 1.. Characterization of wounding outcomes.

A. Stentor cells injected into a microfluidic constriction showed three regimes of wounding outcomes. The cells were injected at 4 mL/h through a 70 μm constriction. The red arrows indicate sites of disruption in the plasma membrane. B. Top: Parameters extracted using image processing. Bottom: The trajectory of a cell, flowing through a 70 μm constriction at 4 mL/h, as a function of the position x along the microfluidic channel. The center of the constriction is at x = 0. The yellow curve shows the time and the green curve shows the variation of the cell aspect ratio (AR). The images of the cell at three different positions are shown. C. A compilation of all Stentor trajectories that flowed through a 70 μm constriction at 4 mL/h with time series data in the top panel and aspect ratio variation ($\overline{\alpha }(x)=\frac{AR(x)}{A{R}_{entry}}$) in the bottom panel. The trajectories are demarcated by the regime of wounding outcomes. The line and the shading indicate the mean and standard deviation for the trajectories for a given regime of wounding outcome within the region of interest. The insets show the cell deformation at the entry and exit for regimes 1 (blue), 2 (yellow) and 3 (red). The corresponding bounding boxes for the cells are shown. The scale bars represent 50 μm.

Fig. 2.. Relationship between cell size and wounding characteristics of Stentor.

A. Immunofluorescence images of Stentor cells stained against acetylated tubulin show disruption of the KM fiber network after being injected through varying constriction widths. The red arrows indicate sites of KM fiber disruptions. The top panel depicts an unwounded cell that did not flow through the microfluidic constriction. B. Plot showing the dimensionless transit time t* and the dimensionless cell size D* for the three wounding regimes. The distributions of the data points for the three regimes for t* and D* show statistically significant differences. C. Plot showing the dimensionless parameter $\alpha =\frac{◻{◻}_{◻◻◻◻}}{◻{◻}_{◻◻◻◻◻}}$ and the dimensionless cell size D* for the three wounding regimes. The distributions of the data points for $\alpha$ show statistically significant differences for the three wounding regimes.

Fig. 3.. Effects of nocodazole treatment on wounding outcomes.

A. Micropipette aspiration of a Stentor cell using a 20 μm diameter glass micropipette. The inset is a schematic diagram showing the relevant parameters for estimating the cortical tension of the cells. B. Plot comparing the cortical tension measured in untreated control cells and the nocodazole-treated cells (p < 0.05). C. Plot showing the dimensionless transit time t* and the dimensionless cell size D* for nocodazole-treated cells for the three wounding regimes, overlaid on top of the data (half transparent) for untreated control cells D. Plot showing the deformation parameter $\alpha$ and the dimensionless cell size D* for nocodazole-treated cells for the three wounding regimes, overlaid on top of the data (half transparent) for untreated control cells. E. Plot showing the probability of regime 3 outcomes for control and nocodazole-treated cells as a function of the dimensionless cell size D*. The curves represent the best fit sigmoid curve corresponding to the data. The black dotted lines represent probability values of 0.0 and 1.0. The panel at the top shows the control and the nocodazole-treated cells plotted as a function of D* for the three wounding regimes. The color scheme for the regimes is the same as the plots in C and D, where blue, yellow, and red represent wounding regimes 1, 2, and 3 respectively. Solid symbols represent nocodazole-treated cells. Faded symbols represent control cells. The bottom panels show representative immunofluorescence images of wounded cells: untreated control cells (left), and nocodazole-treated cells (right). In both conditions, cells were injected at 4 mL/h through a 70 μm constriction. The red arrow indicates the sites of wounds.

Fig. 4.. Wound resistance under large hydrodynamic stress.

A. Regime map showing the rupture (regime 3) and non-rupture (regimes 1 and 2) outcomes as functions of the cortex capillary number ${\text{Ca}}_{\mathrm{c}}$ and the dimensionless cell diameter D*. The curve in black denotes the decision boundary drawn at a rupture (regime 3) probability prediction of 0.1 based on logistic regression of the outcomes. B. Cumulative probability distribution of regime 3 outcomes (i.e., rupture wounds) as a function of the dimensionless cell size D* for ranges of the cortex capillary numbers ${\text{Ca}}_{\mathrm{c}}$. C. Plot showing the dimensionless transit time t* as a function of the dimensionless cell size D* for different ranges of the cortex capillary number.