The experimental workflow to assess calcium responses in primary murine T-cells using an Indo-1 ratiometric dye with multiplexing surface stains is shown in Figure 1. After harvesting and processing the mouse splenocytes into a single cell suspension, the cells are stained with an Indo-1 AM ester and surface stained with fluorochrome-linked antibodies. Once the dye loading and antibody staining are completed, the lymphocyte samples are warmed up to a biological temperature (37 °C). The samples are then analyzed using full spectrum flow cytometry for Indo-1 fluorescence after gating on the individual cell types desired, without the need for sorting the samples prior to analysis. In order to use Avalanche Photo Diode (APD) detectors within the full spectrum flow cytometer, it is necessary to convert the peak emission wavelength from a bandpass filter wavelength measured in nm to its respective channel on the APD. The table shown in Figure 2 provides a guideline, but the optimum detectors for the two fluorescence signatures of Indo-1 (calcium-bound versus calcium-free) must be determined empirically. This is accomplished by preparing single stained Indo-1 samples using Ionomycin to generate the Indo-1 (calcium-bound) signal, and EGTA, a calcium chelating agent, to generate the Indo-1 (calcium-free) signal. After analysis using full spectrum flow cytometry, the channel displaying the peak fluorescence intensity for each Indo-1 signature can be visualized (Figure 3A). By normalizing the MFI of the positive populations to that of the negative populations, the shift in Indo-1 fluorescence from calcium-free to calcium-bound can be determined (Figure 3B). This display is generated in a workbook (.xls) using reference controls for both bound and free Indo-1, drawing a negative and positive interval gate with clear positive and negative gates for MFI normalization as shown in (Figure 3A). Sample MFI statistics can also be obtained by right clicking on the stats table. In the software, determine the MFI ratio by dividing the positive population with the negative population and overlay the two spectra on a single display (Figure 3B, right). The yellow dotted arrow shows the normalized spectral differences between the spectral signatures of both bound and free Indo-1.
To evaluate calcium responses following T-cell receptor stimulation, the Indo-1 fluorescence is assessed after gating on the cell populations of interest, as shown in Figure 4. First, a plot of time versus side scatter (SSC-A) is examined to assess fluidic stability; a stable consistent signal across the time axis indicates stability (Figure 4A). Next, the forward versus side scatter (FSC-A vs. SSC-A) is visualized, and the lymphocyte population is gated as shown in (Figure 4B). After the lymphocyte gate, a single cell discrimination gate is applied by generating a plot of side scatter height versus area (SSC-H vs. SSC-A), and the singlets, which fall on the diagonal, are gated as shown in Figure 4C. The singlets are then assessed for viability, by examining staining with the viability dye and gating on the negative population (Figure 4D). Finally, to analyze T-cells, a B-cell dump/internal negative control gate is applied by gating on the CD19-negative population (Figure 4E). The CD19-negative population is then assessed for T-cell subsets using antibodies to CD4 and CD8 (Figure 4F); the example shown examines CD4+ T-cells for calcium responses by visualizing Indo-1 (calcium-bound) fluorescence versus time (Figure 4G). After gating on a time segment, the Indo-1 (calcium-free) versus Indo-1 (calcium-bound) plot can also be generated (Figure 4H). This analysis will later be used to derive the Indo-1 ratio (see methods calcium influx curve analysis in flow cytometry analysis software).
At this point in the analysis, it may be useful to analyze moments in time within the two-dimensional plot of Indo-1 (calcium-bound) versus time in individual cell populations of interest. The optimal timepoints include the baseline calcium bound to Indo-1 prior to TCR stimulation, the peak response, a timepoint several minutes after the peak response as intracellular calcium levels decline, and finally the calcium response elicited by adding ionomycin (Figure 5A). In the baseline sample prior to anti-CD3 antibody addition, a weak Indo-1 (calcium-bound) signal is detected. During the peak response, the cells show a strong Indo- 1(calcium-bound) signal and a reduced fluorescence of Indo-1 (calcium-free). At 5 min post-peak, the Indo-1 fluorescence nearly returned to baseline. After ionomycin is added to the sample, a robust signal of Indo-1 (calcium-bound) can be visualized, ensuring adequate dye-loading of the cells. Rare cell populations (<1 %) can be difficult for derivative analysis; to overcome this limitation, analysis of the rare populations can be performed by plotting Indo-1 (calcium-bound) versus Indo-1 (calcium free) after gating on each population of interest, such as CD4+ cells, TCRb+ cells, TCRyg+ cells, CD25+ cells, iNKT cells, and CD19+ cells (Figure 5B,C). Note the readily detectable calcium response in TCRγδ+ T-cells and iNKT cells (CD1d/α-galcer+). For comparison of surface proteins within a mixed murine T-cell population, two-dimensional plots were created showing subsets of interest. Below, the analysis of the calcium response over the entire time course for each subset is displayed (Figure 5C).
This assay can also be used to establish biological differences in T-cells from wild-type versus gene-targeted mice or in T-cells untreated versus treated with pharmacological inhibitors. In the example shown in Figure 6, T-cells were treated with PRN694, a small molecule inhibitor of the T-cell tyrosine kinases, ITK and RLK9,10. Inhibition of ITK/RLK dampens T-cell receptor signaling, leading to a reduced calcium response following T-cell receptor stimulation11 (Figure 6A). To quantify the effects of ITK/RLK inhibition, the curves displaying the ratio of Indo-1 (calcium-bound) to Indo-1 (calcium-free) fluorescence can then be analyzed for the area under the curve (AUC) or slope of the curve for each condition (Figure 6B,C). This quantification is performed by sectioning the time course of the calcium response into discrete segments (Figure 6A), and assessing the area under the curve or the slope of the curve for each segment, as shown (Figure 6B,C). Overall, this protocol demonstrates that full spectrum flow cytometry can be used to measure calcium influx along with multiple cell surface markers in immune cell populations under investigation. These results show that cell subsets represented at greater than 1% of the total population can be assessed for calcium influx over time. In contrast, less abundant cell subsets require alternative analysis using moments of time.
Statistical analysis of calcium response data is specific to the experimental question and the biological assays that are being performed. In the data presented in the manuscript, experiments were performed with replicates to ensure experimental accuracy and the robustness of the methodology; however, multiple experiments on different biological samples over different days were not performed. Therefore, it would not be appropriate to perform statistical analyses on the data presented.

Figure 1: Schematic of calcium assay workflow. The use of the Indo-1 AM ester calcium indicator dye provides a tool to visualize the influx of calcium in immune cells and their sub-populations. This schematic outlines the workflow for analysis of calcium responses in murine splenic T-cells. Please click here to view a larger version of this figure.

Figure 2: Conversion of PMT wavelengths to APD channels. The full spectrum flow cytometer has 16 detectors to detect fluorescent emissions following excitation by the UV laser. The specifications of each detector are indicated in the table. Highlighted are the two detectors used for the assessment of Indo-1 fluorescence, as were determined empirically using single stained controls. Conversions to APD wavelength and user manual for spectral flow cytometer are available11. Please click here to view a larger version of this figure.

Figure 3: Visualization of the Indo-1 spectral signature. (A) Top: Spectral signature of Indo-1 fluorescence in CD8+ T-cells following ionomycin introduction to elicit a robust influx of calcium. The peak of Indo-1 (calcium-bound) can be visualized in UV1. Bottom: Spectral signature of Indo-1 (calcium-free) showing the peak fluorescence in UV7. This control sample was generated by treating Indo-1-loaded cells with EGTA12 to chelate any extracellular free calcium. (B) Combined five laser spectrum overlay of the Indo-1 signature, showing raw spectral MFI on the left and the normalized spectra of Indo-1 bound versus free Indo-1 on the right. Visualization of the shift from Indo-1 (calcium-free) in orange to Indo-1 (calcium-bound) in blue can be readily detected. Please click here to view a larger version of this figure.

Figure 4: Gating strategy for visualization of calcium responses. The workflow for sequential gating of the samples is outlined. (A) Fluidic stability is examined using a time versus SSC-A gate. (B) FSC-A versus SSC-A is used to gate on lymphocytes, thereby eliminating cell debris and residual red blood cells in the sample. (C) Single cells are gated on using a SSC-H versus SSC-A plot. (D). The singlet gate is then applied to a plot of live-dead Ghost540 versus SSC-A; gating on Ghost540-negative cells eliminate non-viable cells from subsequent analysis. (E) Live cells are analyzed for CD19 versus SSC-A, and CD19-negative cells (non-B cells) are gated on. (F) The CD19-negative cells are examined for CD4 versus CD8 staining. (G) CD4+ cells are then gated on to visualize time versus Indo-1 (calcium-bound). (H) A moment in time is selected to represent the initiation of the calcium influx response following anti-CD3 antibody addition by visualizing Indo-1 (calcium-free) versus Indo-1 (calcium-bound) fluorescence. Please click here to view a larger version of this figure.

Figure 5: Visualization of Indo-1 fluorescence in gated populations of murine thymocytes at discrete timepoints in the calcium response. Total thymocytes were stimulated with anti-CD3 antibody followed by ionomycin after 6 min of the sample collection. At four discrete timepoints, as indicated in the rectangular boxes outlined on the two-dimensional plots of time versus Indo-1 (calcium-bound), different subpopulations of thymocytes were examined for calcium responses. (A) Two-dimensional plots showing gating for the baseline Indo-1 signal, the peak response, 5 min post-peak response, and the response to ionomycin. Below each plot CD4 versus CD8 staining (left) and the plot of Indo-1 (calcium-free) versus Indo-1 (calcium-bound) on gated CD4 single positive (SP) thymocytes is shown. (B) Plots of Indo-1 (calcium-free) versus Indo-1 (calcium-bound) on gated subsets of thymocytes are shown at each of the four time-points, using the gating strategy shown in (A). (C) Two-dimensional plots were created showing staining of total thymocytes with the indicated antibodies. Specific subsets were gated (top row) on and examined for calcium responses versus time (bottom). Light blue (SP) CD8+ population, red (SP) CD4 population, which exhibits the greatest influx of calcium, orange CD4+CD8+ double-positive thymocytes, dark green iNKT cells, light green CD25+, purple TCRγδ+ T-cells, and black CD19+ B cells. Please click here to view a larger version of this figure.

Figure 6: Inhibition of the calcium response in CD8+ T-cells treated with a small molecule inhibitor of ITK/RLK. During the Indo-1 dye-loading, splenocytes were treated with two doses of PRN694, 100 nM (dark gray) and 200 nM (light gray). (A) Indo-1 ratio (calcium-bound/calcium-free) is shown versus time for untreated cells (red) and cells treated with PRN694. Curves show calcium response of gated CD8+ T-cells. The black line represents the negative control of splenocytes loaded with Indo-1 and surface stained, but not stimulated with anti-CD3 antibody. (B,C) The data can be analyzed by dividing the time axis shown in (A) into eight segments, visualized with black dotted lines, and calculating the area under the curve (AUC) (B), or the slope of each curve (slope) (C) at each time interval of the response. Please click here to view a larger version of this figure.