Convergent and Divergent Migratory Patterns of Human Neutrophils inside Microfluidic Mazes

Abstract

Neutrophils are key cellular components of the innate immune response and characteristically migrate from the blood towards and throughout tissues. Their migratory process is complex, guided by multiple chemoattractants released from injured tissues and microbes. How neutrophils integrate the various signals in the tissue microenvironment and mount effective responses is not fully understood. Here, we employed microfluidic mazes that replicate features of interstitial spaces and chemoattractant gradients within tissues to analyze the migration patterns of human neutrophils. We find that neutrophils respond to LTB4 and fMLF gradients with highly directional migration patterns and converge towards the source of chemoattractant. We named this directed migration pattern convergent. Moreover, neutrophils respond to gradients of C5a and IL-8 with a low-directionality migration pattern and disperse within mazes. We named this alternative migration pattern divergent. Inhibitors of MAP kinase and PI-3 kinase signaling pathways do not alter either convergent or divergent migration patterns, but reduce the number of responding neutrophils. Overlapping gradients of chemoattractants conserve the convergent and divergent migration patterns corresponding to each chemoattractant and have additive effects on the number of neutrophils migrating. These results suggest that convergent and divergent neutrophil migration-patterns are the result of simultaneous activation of multiple signaling pathways.

Figure 1

Microfluidics mazes to mimic the complexity of navigating through heterogeneous tissue microenvironments. (A) Image of the microfluidic device bound to a standard glass slide. Scale bar represents 10 mm. (B) Multiple mazes are connected to a single cell loading chamber, from where cells initiate their migration. The mazes are connected to a reservoir that generates a persistent chemokine gradient. (C) Schematic overview of the maze simulating the interstitium. The maze consists of 96 nodes 50 µm apart through which the cells can traffic, allowing cells to take different routes towards the source of chemoattractant. (D) The fluorescent intensity of a gradient inside the device persists for >3 hours for low molecular weight chemokines (<1 kDa, left panel) and for ~10 kDa chemokines (right panel). The gradient along the maze is visualized for t = 0, 1 and 3 hours. (E) The chemokine concentration is the lowest at the entrance of the maze (blue area with fluorescent intensity 0–10) and increases in a linear manner along the y-axis.

Figure 2

Convergent and divergent migration patterns induced by typical chemoattractants. (A) LTB4 elicits a strong directional migratory response at different chemokine concentrations. The bars represent the percentage of cells that migrated within 3 hours. White bars stand for neutrophils ending up in the maze and gray bars show cells migrating all the way through the maze, to the chemokine source. Total analyzed migrating cells is N = 1677. A heatmap representative of 3 hours migration shows most migratory activity around the chemokine source. (B) Migratory endpoints induced by fMLF at increasing concentrations. N = 1007 cells analyzed. C5a (C) and IL-8 (D) only minimally attract neutrophils to the chemokine source, regardless of concentration used. For C5a N = 414 and IL-8 N = 380 migrating cells were analyzed. Bars represent mean ± SEM. Heatmap documents the result of divergent migration patterns at the entrance of the maze. Graphs represent combined data of N = 3 independent experiments, and 10 nM concentration.

Figure 3

Single cell and average migration trajectories of human neutrophils towards, LTB4, fMLF, C5a, and IL-8 chemoattractants. (A–D) Representative trajectories of individual neutrophils encountering gradients of LTB4, fMLF, C5a or IL-8 respectively (10 nM). In the left panels, each color represents a different cell and its position is recorded every 40 seconds. In the right panels, human neutrophil navigation-probability maps representing trajectories that have been traversed by the cells. Travel frequency normalized to the total number of cells in the assay is represented in blue.

Figure 4

Characterization of migration signatures. (A) The average migratory speed of cells while migrating through the maze in response to either LTB4, fMLF, C5a or IL-8 (10 nM). (B) The average distance migrated by cells before coming to a final stop in various conditions. (C) Directional persistence of migrating cells when encountering a LTB4, fMLF, C5a or an IL-8 gradient (10 nM). (D) The percentage of the maze that was traversed by individual cells before it stops migrating. Combined data of N = 50 cells per condition, representative for N = 3 experiments.

Figure 5

Neutrophils predominantly respond to soluble chemoattractants vs. surface-bound chemokines inside microfluidic devices. (A) Graph demonstrates washing efficiently removes FITC-IL-8 from PDMS and glass surfaces. N = 7 FOV for Media and IL-8, N = 14 FOV for IL-8+ Wash. Error bars: mean ± SD. (B) Representative tracks from 4 hours of time-lapse imaging of neutrophils in channels containing Media (black tracks), IL-8 (magenta tracks) and IL-8+ Wash (blue tracks). N = 5 tracks per condition. (C) Graph shows average neutrophil velocities over 4 hours of time-lapse imaging. Soluble fMLF and IL-8 induce higher neutrophil velocities, which decline over time. Error bars: Mean ± SEM. (D) Box plot showing neutrophil velocities in the first hour of tracking. Soluble IL-8 and fMLF induce significantly higher migration velocity than the media control and washed channels. Neutrophils in washed channels did not exhibit significantly higher velocities than the media control (N > 90 cells per condition from N = 3 experiments).

Figure 6

Effect of migratory environment on migration characteristics. The migratory characteristics of neutrophils migrating in the presence of collagen (white bars) where compared with standard migration through fibronectin coated channels (grey bars) while responding to LTB4 (10 nM) or C5a (10 nM). Migratory characteristics that were analyzed were (A) migratory speed, (B) distance migrated by cells before coming to a final stop, (C) directional persistence of migrating cells and (D) the percentage of the maze that was traversed by individual cells. The box and whiskers show 5–95 percentile and represent combined data of N = 50 cells per condition, representative for N = 3 experiments.

Figure 7

Consequences of chemokine combinations on migration patterns through microfluidic mazes. (A,B) Combinations of different LTB4 and C5a concentrations show a migratory pattern that resembles the sum of each individual chemokine. (C,D) Combinations of fMLF and IL-8 enhance the convergent migration towards the reservoir, even though the total number of cells migrating is not increased. Bars represent percentage of cells migrating within 3 hours, with white bars representing neutrophils that just enter the maze and grey bars representing neutrophils that migrate through the maze all the way to the chemokine reservoir. Bars represent mean ± SEM and represent combined data of N = 3 independent experiments. Total number of analyzed cells in combined group for A is N = 1072, for B is N = 276, for D is N = 98 and for E is N = 101 migrating cells. (E) Heatmap shows increased migratory activity at the entrance of the maze and in the chemokine reservoir (LTB4 and C5a, 10 nM).

Figure 8

Effect of MAP kinase and PI3 kinase inhibitors on human neutrophil migration towards single and combinations of chemoattractants. Migration patterns were analyzed in the presence or absence of the p38 MAP kinase inhibitor SB203580 or the PI3 kinase inhibitor LY294002 while cells responded to (A) fMLF (10 nM) combined with IL-8 (10 nM), (B) LTB4 combined with C5a (10 nM), (C) LTB4 alone (10 nM), (D) fMLF (10 nM), (E) C5a (10 nM) and F) IL-8 (10 nM). Bars represent mean ± SEM and are data combined of N = 3 experiments run in duplicate.

Figure 9

Inhibition of LTB4 signaling reduces migration in cells responding to fMLF. (A) Inhibition of LTB4 signaling with MK866 significantly reduced the number of cells responding to an fMLF gradient. Inhibition of LTB4 signaling did not decrease the migratory speed of neutrophils (B), but the inhibition significantly reduced the distance travelled before coming to a final stop (C) and increased the directional persistence of migrating cells (D). Bars represent mean ± SEM and are data combined of N = 3 experiments. The dot plots have the average and standard deviation included and represent combined data of N = 50 cells per condition, representative for N = 3 experiments.