Individual Control and Quantification of 3D Spheroids in a High-Density Microfluidic Droplet Array

Abstract

As three-dimensional cell culture formats gain in popularity, there emerges a need for tools that produce vast amounts of data on individual cells within the spheroids or organoids. Here, we present a microfluidic platform that provides access to such data by parallelizing the manipulation of individual spheroids within anchored droplets. Different conditions can be applied in a single device by triggering the merging of new droplets with the spheroid-containing drops. This allows cell-cell interactions to be initiated for building microtissues, studying stem cells' self-organization, or observing antagonistic interactions. It also allows the spheroids' physical or chemical environment to be modulated, as we show by applying a drug over a large range of concentrations in a single parallelized experiment. This convergence of microfluidics and image acquisition leads to a data-driven approach that allows the heterogeneity of 3D culture behavior to be addressed across the scales, bridging single-cell measurements with population measurements.

Keywords: droplet microfluidics; liver toxicity; organoids; spheroids; tissue engineering.

Graphical abstract

Figure 1

Physical Principles of Differential Anchor Strengths (A) Side view and top view of a confined aqueous droplet near a capillary anchor. The brown arrows represent the direction of the external oil flow. (B) Two anchoring strengths can be distinguished: for narrow anchors (blue regions), the droplet only partially enters the anchor, whereas for wide anchors (red regions), the droplet entirely enters the anchors. This leads to an anchoring efficiency that depends on droplet size for the narrow anchors and to nearly irreversible trapping in the wide anchors. (C) Side view and top view of an asymmetric anchor. The wide (d₁ > 2h) and narrow (d₂ < 2h) regions can be combined into a single capillary anchor by designing asymmetric shapes. Thick dashed lines denote the planes of the corresponding side views.

Figure 2

Microfluidic Protocols for Pairing and Merging Different Droplet Populations (Aqueous Droplets in Oil) (A) Design of the microfluidic chips. (B–E) Images show portions of the trapping area. (B) First, a population of large droplets is injected and allowed to fill the large regions of each anchor, followed by a second population of smaller droplets. The small droplets (dark dye) then occupy the triangular regions of each anchor. Scale bar is 200 μm. (C) Flushing the device with an emulsion destabilization agent (PFO, perfluoro-octanol; Tullis et al., 2014, Akartuna et al., 2015) results in the merging of the touching droplets, which allows their contents to mix in a few seconds. Scale bar is 100 μm. (D and E) Droplet libraries can be produced in a different microfluidic device and re-injected into the trapping region. In the current example, the large droplet population contains variable concentrations of dye ranging from blue, to green, to yellow. The small droplets contain a gradient of red dye. Image of 80 anchors filled with 2 sets of colored droplets before (D) and after (E) merging. Scale bar is 1 mm. (F and G) Quantification of the droplet colors in red, green, and blue (RGB) space before (F) and after (G) the coalescence (dot color corresponds to RGB coordinates; n_chips = 1, n_droplets = 351). All corresponding flows can be found in Table S1.

Figure 3

Regulation of the Biological Environment in Droplets (A) Design of the asymmetric anchors adapted for the droplet spheroid formation and culture (side view corresponds to the thick dashed line in the top view). (B and C) Protocol for spheroid merging scheme (B) and corresponding micrographs showing 2 consecutive merging events with H4-II-EC3 spheroids (C, scale bar is 50 μm). (D) Micrographs of 2 heterospheroids with different configurations after the protocol shown in (C). Scale bar is 20 μm. (E–G) Selected micrographs showing co-culture experiments with: hMSCs CD146^bright (magenta) and hMSCs CD146^dim (green), which were sorted by flow cytometry (E, scale bar is 20 μm); Jurkat cells and A673 spheroids (F, scale bar is 20 μm); H4-II-EC3 spheroids and E. coli (G, scale bar is 50 μm). (H) Matrigel addition through the second droplet after spheroid formation. (I) B16-F0 cells (mouse melanoma) were imaged just after Matrigel addition (D+2) and the next day (D+3). Black arrows highlight some cell protrusions through the hydrogel matrix. Scale bar is 20 μm. Additional quantification is provided in Figure S2.

Figure 4

Multiplexed Conditions on Liver Spheroids (A and B) Timeline (A) and schematic top view of an anchor (B) showing the experimental protocol. (C–E) Chemical droplet library. Droplets with 27 color barcodes were randomly trapped in capillary anchors and merged with H4-II-EC3 spheroid droplets (C, montage of 224 droplets, n_chips = 2, scale bar is 1 mm). (D) Distribution of the 27 barcodes in all droplets. Each bar corresponds to one barcode, with matching colors. APAP was only added in the droplets with barcode 9. (E) Micrograph of 2 droplets 24 h after library merging. Barcode 9 corresponds to the APAP droplet. PI fluorescent intensity is shown in red. Scale bar is 100 μm. (F) Polydispersity histogram of the spheroids produced in this study (n_chips = 4, n_spheroids = 685). CV = standard deviation/mean. (G) Calibration of the fluorescent signal of the CF™488A dye (green, n_droplets = 429) and CF™647 dye (magenta, n_droplets = 455) for the drug concentration determination. The detailed protocol is explained in STAR Methods. The black circles and error bars represent the mean over all droplets of each concentration and the standard deviation, respectively. The colored lines represent a linear fit of the data. (H and I) Montages of 6 micrographs showing anchors with single liver spheroids (H4-II-EC3 cells) before (H, scale bar is 200 μm) and after (I) drug droplet trapping. The green and magenta fluorescent dyes correspond to the APAP stock solutions at low and high concentrations, respectively, used for creating the droplet library. (J) Micrograph of the entire chip array after droplet coalescence (n_spheroids = 252, montage of the cropped anchors). The white rectangle represents the location of the droplets displayed in (C) and (D). Scale bar is 1 mm.

Figure 5

Measurment of APAP Toxicity on H4-II-EC3 Spheroids (A and B) Time-lapse images showing a spheroid without drug (A, after merging with a control droplet) and a spheroid exposed to a 48.7 mM APAP concentration (B), in bright field (bottom) and with fluorescent viability staining (top). (C) Viability values at the spheroid level after a 24 h exposure (n_spheroids = 685). Each black dot represents one spheroid, and the red and blue curves represent the mean behavior and a sigmoidal fit of the data, respectively, with the blue dashed lines highlighting the IC₅₀ value of 18.0 mM. (D) Time-lapse images showing a spheroid exposed to a 22.1 mM APAP concentration with PI (red). White dots are the locations of the detected dead nuclei, and the cross represents the spheroid center. R is the equivalent radius of the spheroid, and r is the distance to the spheroid center. (E and F) Time evolution of the number of dead cells detected on one spheroid image (E) and of the mean normalized distance ${\left(r/R\right)}_{dead}$ of the dead cells to the spheroid center (F) depending on the drug concentration. Scale bars are 50 μm.

Figure 6

Analysis of the Viability (A) Toxicity values after a 24 h exposure. Data points corresponding to spheroids exposed to a 14–23 mM range of APAP concentrations are highlighted in purple (same dataset as Figure 5C). (B) Influence of the number of initial dead cells on the viability after a 24 h exposure for an APAP concentration between 15 and 23 mM (red, at least one initial dead cell; blue, no initial dead cell; n_spheroids = 98). (C) Correlation between the viability at t = 24 h and the mean normalized distance of the first detected dead cells (whatever its time of appearance) to the spheroid center ${\left(r/R\right)}_{firstdeadcells}$ (n_spheroids = 308), for an APAP concentration between 10 and 40 mM. (D) Dynamic evolution of the spheroid viability for an APAP concentration between 15 and 23 mM. Each thin line represents one spheroid (n_spheroids = 98); the red and blue curves correspond to the spheroids that had at least one detected dead cell and no detected dead cell at t = 0 h, respectively; and the thick black line represents the overall mean. (E) Definition of the time needed to reach a 75% viability ${\tau }_{75}$ and the time to go from a 75% to a 25% viability ($\Delta {\tau }_{75-25}$ = ${\tau }_{25}$ − ${\tau }_{75}$) on a viability followup corresponding to a spheroid exposed to a high APAP concentration (above 40 mM). (F) Low correlation (Pearson’s correlation coefficient = −0.06) between $\Delta {\tau }_{75-25}$ and ${\tau }_{75}$ (n_spheroids = 215) shows that the two parameters are independent. (G) Evaluation of ${\tau }_{75}$ (n_spheroids = 262) and $\Delta {\tau }_{75-25}$ (n_spheroids = 215). (H and I) Evolution of ${\tau }_{75}$ (H) and $\Delta {\tau }_{75-25}$ (I) with the APAP concentration. N.S., nonsignificant; ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 0.001. Statistical test details are provided in Table S2.