Identifying network motifs that buffer front-to-back signaling in polarized neutrophils

Abstract

Neutrophil polarity relies on local, mutual inhibition to segregate incompatible signaling circuits to the leading and trailing edges. Mutual inhibition alone should lead to cells having strong fronts and weak backs or vice versa. However, analysis of cell-to-cell variation in human neutrophils revealed that back polarity remains consistent despite changes in front strength. How is this buffering achieved? Pharmacological perturbations and mathematical modeling revealed a functional role for microtubules in buffering back polarity by mediating positive, long-range crosstalk from front to back; loss of microtubules inhibits buffering and results in anticorrelation between front and back signaling. Furthermore, a systematic, computational search of network topologies found that a long-range, positive front-to-back link is necessary for back buffering. Our studies suggest a design principle that can be employed by polarity networks: short-range mutual inhibition establishes distinct signaling regions, after which directed long-range activation insulates one region from variations in the other.

Figure 1. Core neutrophil polarity network

A. Simplified schema of the core neutrophil network motif of mutual inhibition between the front (red shaded region) and back (green shaded region) signaling modules together with positive feedback at the front. B. Cartoon illustration of potential relationships between front and back signaling for the core network motif without (top) or with (bottom) a long-range positive link from front to back (blue arrow).

Figure 2. Microtubules buffer back polarity against varying front strength in polarized human neutrophils

A. Density plots suggest that depolymerization of microtubules with nocodazole reduces the ability of back spreadness to be buffered from changes in front intensity in fMLP-stimulated human neutrophils. (Density plots were derived from pooled data (n=10) with the top and bottom 1% trimmed; replicates are analyzed individually in D.) Regression lines: computed as described in Experimental Procedures. Legend: illustration of polarized neutrophils with varying degrees of intensity or spreadness for front and back signaling markers. B. Representative images of neutrophils treated with or without nocodazole (left to right: low to high F-actin intensity). Colors: red (F-actin); green (p-MLC2). Scale bar: 10µm. C. Summary of regression slope (top) and variability (bottom) between front intensity and back spreadness in replicates of control and drug-treated cells. Slope and variability: shown schematically in box at right and described in Supplemental Information. Box plots: median values (center lines) and 25^th and 75^th percentiles (box edges) across replicate experiments. The vertical lines extend to the most extreme data points not considered outliers (minima and maxima whiskers). Outliers are plotted individually (red “+”). The back spreadness slope values were expressed in percentages of their theoretical maximum (Supplemental Information). (*): Wilcoxon’s two-sided rank sum test with p-value < 0.01. D. Density plots (right column) of non-drug treated control cells (as in A, top right) overlaid with scatter plot of cells ranked in the bottom 5% (magenta points) or top 5% (blue points) based on intensity (bottom) or spreadness (top) of microtubule staining. Probability plots (left column) reflect densities of scatterplots at right. Gray curve reflects overall population density. See also Figures S1–3 and Table S1.

Figure 3. Mathematical model of microtubule interactions with front and back reveals a role for buffering back polarity

A. Illustration of the neutrophil polarity model featuring interactions among front (red), back (green) and microtubules (blue). (Top left) Two additional interactions were added to the “core” motif accounting for the exclusion of microtubules from the front and microtubule-mediated activation of the back. (Top right and table) Parameters used to model microtubule-mediated front-to-back interaction (Supplemental Information). See also Figure S4A and Table S2. B. Sample outcome of polarization from simulated model. Cell membrane is visualized with an annulus; blue dots represent the location of microtubule tips on the membrane. Red/green color map: spatial distribution of active front/back components. For visualization, the maximum values of front and back concentrations are both normalized to one. For each polarized cell, the front area and back width were measured as proxies of the front intensity and back spreadness (Supplemental Information). C. Scatter plots of back width versus front area obtained by sampling parameters. Top left/middle panels: without/with microtubules. Thick black lines: regression lines. Lower and upper gray lines: spreadness around regression line (Supplemental Information). Triangles and dotted lines refer to data points obtained by varying the front amount around its nominal value. Bar graph: regression slope and variability of back width versus front area.

Figure 4. Systematic assessment of the performance of different polarity network topologies in buffering back polarity

A. Set of possible additional links (blue dashed lines) to the core topology (black lines). B. Schema of additions: one, two, or three positive or negative links. C–D. Heat map of changes to the buffering performance upon addition of direct (C) or indirect (D) links. Heat map color scale: change to the buffering between the new and the original topologies (i.e. link vs. no link). Color bar: cyan or yellow indicates decreased or increased (respectively) buffering capability compared to the core topology. Green shaded background: topologies with best overall buffering performance for both direct and indirect model implementations. Gray shaded background: topologies where the back was excessively “squeezed” into a narrow region. See also Figure S4B–C and Table S3.