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. 2015 Jun;6(3):334.
doi: 10.4172/2155-9899.1000334. Epub 2015 Jun 20.

T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray

Affiliations

T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray

Saheli Sarkar et al. J Clin Cell Immunol. 2015 Jun.

Abstract

Objective: Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells.

Methods: The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring.

Results: Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals.

Conclusions: Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells.

Keywords: Calcium; Dynamics; Heterogeneity; Immune response; Lymphocytes; Microfluidics; Single cell analysis; Time-lapse microscopy.

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Figures

Figure 1
Figure 1
Microfluidic droplet generation and docking microarray platform. (A) PDMS nanoliter droplet array device showing inlets for oil (highlighted by arrows), T cells (inlet 1) and ionomycin or DCs (inlet 2). (B–D) Images of the flow of two input streams containing red and green fluorescent polystyrene beads (7 μm diameter) in the region indicated in (A). The aqueous and oil flow rates are 50 μl/hour and 300 μl/ hour. The fluorescent exposure was kept in the range of 500–700 msec, which precludes observation of individual beads in the serpentine region under flow. (E) Droplet generation at flow-focusing junction. Droplets containing T cells are indicated by arrowheads. (F) Generated droplets driven towards the docking microarray. (G) Droplet-filled microarray. (H) Droplets containing single T cells (indicated by arrowheads) labeled with Fluo-4. Scale bar: 50 μm.
Figure 2
Figure 2
T cell viability and signaling trends in droplets. (A) Time course of T cell viability. The primary y-axis indicates increase in cell death over time. The secondary y-axis indicates proportion of live cells in the same droplets. The error bars indicate ± 5% value. (B) Major calcium signaling trends observed in the cell population: consistent increase (red), consistent decrease (purple), rapid decrease (green) and unchanged (blue) levels.
Figure 3
Figure 3
T cell calcium signaling in response to ionomycin treatment. (A) Heat map showing calcium trends in T cells stimulated with ionomycin (3 μM) in droplets (time= 0–60 min). The data represents dynamic profiles from 98 cells. (B) Percentage of cells in each of the four signaling categories depicted in Figure 2B. The error bars indicate ± 5% value.
Figure 4
Figure 4
Comparative calcium signaling trends in control and ionomycin-stimulated cell populations. (A) Representative calcium trends in control (stimulated with media only) T cells in the first 30 minutes. The y-axis indicates Normalized Mean Fluorescent Intensity (N.F.I) of individual T cells as described in Materials and Methods. (B) Representative calcium trends in T cells stimulated with ionomycin (3 μM) in droplets. (C) Overlay of phase and fluorescent images of control T cells depicting decrease in Fluo-4 fluorescence over time. Inset: Magnified fluorescent image of the corresponding T cell. (D) Overlay of phase and fluorescent images of ionomycin-stimulated T cells depicting increase in Fluo-4 fluorescence over time. Inset: Magnified fluorescent image of the indicated T cell. (E,F) Intensity profiles of the cells shown in insets in C and D.
Figure 5
Figure 5
DC-T interaction and dynamic calcium signaling in droplets. (A) Co-encapsulation of naïve T cell and DC stimulated with OVA-FITC (100 μg/ml). DCs demonstrate morphological change in droplets over time. (B) Increase in calcium transient in T cell following contact with DC. (C) Non-contact mediated increase in T cell calcium level. Insets (B,C): Fluorescent images of the corresponding T cells. Scale bar: 50 μm. (D) Representative traces of normalized fluorescent intensity (N.F.I) of Fluo-4 in T cells under various states of conjugation with DC:(a) DC-T cells in contact throughout experimental duration; (b) Cell contact initiated at t=2min, indicated by the square (■) and dissociated at t=12min, indicated by the triangle (▲); (c,d) No contact observed between DC and T cells throughout experimental duration.

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