A platform for assessing chemotactic migration within a spatiotemporally defined 3D microenvironment

Abstract

While the quantification of cell movement within defined biochemical gradients is now possible with microfluidic approaches, translating this capability to biologically relevant three-dimensional microenvironments remains a challenge. We introduce an accessible platform, requiring only standard tools (e.g. pipettes), that provides robust soluble factor control within a three-dimensional biological matrix. We demonstrate long-lasting linear and non-linear concentration profiles that were maintained for up to ten days using 34.5 muL solute volume. We also demonstrate the ability to superimpose local soluble factor pulses onto existing gradients via defined dosing windows. The combination of long-term and transient gradient characteristics within a three-dimensional environment opens the door for signaling studies that investigate the migratory behavior of cells within a biologically representative matrix. To this end, we apply temporally evolving and long-lasting gradients to study the chemotactic responses of human neutrophils and the invasion of metastatic rat mammary adenocarcinoma cells (MtLN3) within three-dimensional collagen matrices.

Fig. 1

(a) Schematic representation of the gel filled PDMS device. The source reservoir is loaded with the desired soluble factor at concentration C = C₀ and the sink is loaded with deionized water C = 0. (b) The added factor diffuses into the gel and, after a setup time t_ss, develops a pseudo-steady gradient from source to sink. (c) The gradient is maintained by periodically replenishing the source reservoir with a concentration of C_s < C₀. The concentration C_s rather than C₀ is used to minimize disruption of the established gradient. Established gradients were maintained for extended periods of time by periodic replenishment of the source and sink reservoirs.

Fig. 2

(a) Exponential profile was developed and maintained within an agarose-filled microchannel for ten days using a total of 34.5 μL of Alexa 488 solution. Maximum RMS error from the predicted profile was 0.026. Scale bar = 400 μm. (b) A linear concentration profile was developed and maintained within a 3D agarose gel-filled channel for three days using a total of 9 μL of Alexa 488 solution. Maximum RMS error from the predicted profile was 0.029. Scale bar = 250 μm. (c) Opposing concentration profiles of dye were created within a 3D agarose-filled microchannel. The left reservoir contained yellow dye and the right contained blue dye. The combination of diffusing yellow and blue dye molecule resulted in green coloration within the region of overlap. Linear opposing profile, scale bar = 1 mm and exponential opposing profile, scale bar = 250 μm are shown. Dosing windows are used to introduce cells or additional soluble factors to the system. (d) A stable linear gradient (in yellow dye) was established from source to sink. Blue dye was then added to one of the dosing windows. The blue dye diffusing into the channel on top of existing yellow gradient appeared as a radially evolving green gradient. Windows can be dosed at different time points to superimpose dynamic gradients in different regions of the channel. Scale bar = 1mm.

Fig. 3

The 3D distribution of neutrophils is visible within the collagen matrix (fluorescence intensity of in-plane cells is brighter than out-of-plane cells). (a) Cell tracks are shown for neutrophils embedded within the unstimulated channel and (b) neutrophils embedded within a channel stimulated with an fMLP gradient. Scale bar = 50 μm. Contrast has been adjusted in order to improve clarity. (c) Average CI values for the stimulated (0.336 ± 0.048) and unstimulated cases (0.008 ± 0.041) are shown (n = 10 cells, p < 0.0001). Data reported as mean ± sem. See ESI videos 1 and 2 for migration videos with labeled tracks.

Fig. 4

(a) Schematic representation of the long-lasting gradient study using the invasive MTLn3 cancer cell line. (a) Comparison of cell numbers in the channel at 24 h post plating within the EGF-simulated and unstimulated channels. Cell numbers were normalized with respect to the unstimulated cell population and were found to be statistically significant with p = 0.007. (b) Comparison of cell numbers in the channel at 48 h post plating within the EGF-simulated and unstimulated channels. Cell numbers were normalized with respect to the unstimulated cell population and were found to be statistically significant with p = 0.011. Data reported as mean ± sem. Data tabulated from six total channels from three separate experiments. See ESI videos 3 and 4.