Evaluating expression patternsof multiple inhibitory and stimulatory
receptors on natural killer cells
using flow cytometry
Using the BD LSRFortessa™ X-20 cell analyzer andBD Horizon Brilliant™ Ultraviolet reagents enables detectionof up to 18 markers simultaneously and offers flexibility
in panel design

Features• Resolve natural killer (NK) cell heterogeneity• Simultaneously assess stimulatory and inhibitory
receptor expression on NK cells using an 18-color
flow cytometry panel• Reveal donor-specific differences in NK cell diversity
using high-dimensional data analysis tools
Natural killer cells are an important part of the innate immune
system and constitute a frontline defense in the killing of virally
infected and malignant cells through the secretion of cytotoxic
granules containing granzymes, perforin and granulysin. ActivatedNK cells also secrete a milieu of cytokines that regulate the functionof other cells that play roles in innate and adaptive immune
responses, including dendritic cells, macrophages, neutrophils
and antigen-specific T and B cells.

NK cell function is tightly regulated by stimulatory and inhibitory
receptors that recognize cellular stress ligands as well as humanleucocyte antigen class I (HLA class I). Inhibitory signals are
particularly important for the maintenance of self-tolerance in aclass-I–dependent manner while stimulatory signals drive NK-celleffector functions.
A series of stimulatory and inhibitory receptors can be expressedin a stochastic, variegated and overlapping way on the surface ofNK cells, with estimates of greater than 30,000 NK cell phenotypes
in a given individual. NK cells also display extensive phenotypic
diversity among individuals, with inhibitory receptor expression
being largely determined by genetics and stimulatory receptor
expression being heavily driven by environmental factors and/orstochastic influences.

In this data sheet, we describe a flow-cytometry-based immunophenotyping assay to define the major subsets of human NK cells
and to further characterize the expression of key stimulatory and inhibitory receptors. The expression of key stimulatory or inhibitory
receptors was first studied separately using two 12-color flow cytometry panels on the BD LSRFortessa™ cell analyzer. This enabledthe simultaneous assessment of a backbone panel of six NK cell lineage markers in combination with either six stimulatory or inhibitory
markers. We then combined these markers, creating an 18-color panel to simultaneously assess all markers in one tube and research
further into the NK cell heterogeneity across five donors. Using the 355-nm ultraviolet (UV) option on the BD LSRFortessa™ X-20 cellanalyzer and the associated BD Horizon Brilliant™ Ultraviolet (BUV) reagents allowed us to spread these 18 markers across an additional laser line and more spectral space which can simplify panel design due to more fluorochrome choice and less dye overlap.
To investigate multiple NK-cell phenotypes in a single individual, we used a modular panel-design strategy. This approach enabled
us to characterize the major NK-cell subsets using a 6-color backbone panel and to assess the expression of either stimulatory orinhibitory receptors by using two alternative 6-color drop-in panels (Table 1). This modular panel-design strategy provides researchers
the flexibility to swap the markers in the drop-in panel with their preferred markers.
Table 1. Modular 12-color panel with a 6-color backbone to identify major NK subsets and 6-color drop-in panels to assess stimulatory or inhibitory receptor expression
on NK cells

6-Color Backbone Panel
Specificity

Major
NK Subsets

6-Color Drop-In: Stimulatory Panel

Fluorochrome

Specificity

6-Color Drop-In: Inhibitory Panel

Fluorochrome

Specificity

Fluorochrome

CD94

BV480

CD314 (NKG2D)

BV421

CD158f (KIR2DL5)

BV421

CD16

BV786

CD159c (NKG2C)

BV605

CD158b (KIR2DL2/3)

BV605

CD337 (NKp30)

BV650

TIGIT

BV650

CD226 (DNAM-1)

BV711

CD159a (NKG2A)

BV711

CD57

FITC

CD56

PE-Cy™ 7

CD27

APC-R700

CD3

APC-H7

Stimulatory
Receptors

Inhibitory
Receptors

CD160

PE

CD158e1 (NKB1/KIR3DL1)

PE

CD244 (2B4)APC

CD158a (KIR2DL1)

APC

The 6-color backbone panel enabled the identification of developmentally and functionally distinct NK-cell subsets, based on theanalysis of CD56 and CD16 expression profiles. CD56brightCD16⁻ cells represent a small subset of immature, circulating NK cells
that are potent cytokine producers but have low cytotoxic capacity before activation. CD56dimCD16⁺ cells include terminally differentiatedNK cells that exert cytotoxic functions and have limited ability to produce cytokines (Figure 1A).
CD56bright cells are known to undergo a continuum of differentiation that ends with the CD56dim phenotype. Analysis of CD94
expression helped to identify developmental intermediaries, such as CD94highCD56bright, CD94highCD56dim and CD94lowCD56dim, thelatter being the most cytotoxic subset (Figure 1B). Maturation of NK cells could also be monitored by analysis of the loss of CD27
and gain of CD57 on the surface of CD56dimCD16⁺ cells, as compared to CD56brightCD16⁻ cells (Figure 1C).

CD3 APC-H7

CD56 PE-Cy7

CD3⁻47.5

Figure 1B

CD56brightCD16⁻
0.47+CD56dimCD1622.7

CD56 PE-Cy7

SSC-A

Figure 1A

CD16 BV786
072.2

0.10

CD94highCD56dim
7.83

CD94 BV480
3.58

0.049

56.1

40.3

CD27 APC-R700

27.7

CD27 APC-R700

Figure 1C

CD94highCD56bright0.93
CD94 CD56dim
13.9
low

CD57 FITC

CD57 FITC

Figure 1. Gating strategy for analysis of the major NK subsets
Fresh blood cells from a healthy donor (Donor 1) were stained with the antibody-fluorochrome conjugates listed in Table 1. Whole blood was stained with the panel along with BD
Horizon™ Brilliant Stain Buffer Plus for 30 minutes in the dark. Red blood cells were lysed for 15 minutes using the BD FACS™ Lysing Solution. Cells were washed twice using theBD Pharmingen™ Stain Buffer (FBS). Sample acquisition was completed on the BD LSRFortessa flow cytometer with a violet/blue/yellow-green/red laser configuration. A. Major NK-cellsubsets were defined within the CD3⁻ lymphocytes as CD56brightCD16⁻ or CD56dimCD16⁺ cells. B. CD94 expression identified developmental intermediaries of NK cells (CD94highCD56bright,
CD94highCD56dim and CD94lowCD56dim). C. NK cell maturation can be further assessed by analyzing the gain of CD57 expression and loss of CD27 expression on CD56dim CD16⁺ cells , ascompared to CD56brightCD16⁻ cells. Population statistics are indicated for each gate in the respective contour plots.

The CD94 receptor can associate with various NKG2 family receptors, such as CD159c (NKG2C) and CD159a (NKG2A) in the drop-inpanels, to form a heterodimer complex that recognizes nonclassical MHC class I molecules. Depending on the NKG2 family member, thiscomplex can stimulate or inhibit cytotoxic activity of NK cells. The 6-color drop-in stimulatory panel enabled the analysis of two NKG2
family members, CD159c (NKG2C) and CD314 (NKG2D), in addition to CD337, CD226, CD160 and CD244 (Figure 2). The inhibitory
panel contained an NKG2 family member, CD159a (NKG2A), in addition to TIGIT and killer immunoglobulin-like receptor (KIR) familymembers; CD158a, CD158b, CD158e1 and CD158f (Figure 3). Stimulatory and inhibitory receptors showed differential patterns ofexpression in CD56brightCD16⁻ cells compared to CD56dimCD16⁺ cells, such as higher levels of expression for stimulatory receptor CD160
and higher levels of inhibitory receptors TIGIT and KIR family members in the CD56dimCD16⁺ population.
CD56bright CD16 –
63.8

6.89

22.2

8.90

0.86

90.2

089.0

8.03

3.01

0CD160 PE

CD226 BV711

7.03

CD314 BV421

Figure 2ACD337 BV650

CD244 APC

CD159c BV605

CD56dim CD16 +80.7

2.52

10.2

80.8

1.97

17.0

0.17

92.9

2.70

4.26

0.11CD160 PECD226 BV711

6.61

CD314 BV421

Figure 2BCD337 BV650

CD244 APC

CD159c BV605

Figure 2. Evaluation of stimulatory marker expression on the major NK subsets
Major NK-cell subsets shown in Figure 1 (CD56brightCD16⁻ and CD56dimCD16⁺) were assessed for expression of stimulatory markers CD337, CD244, CD226 and CD160 in addition
to two members of NKG2 receptor family, CD159c (NKG2C) and CD314 (NKG2D), in the contour plots. A. Contour plots for the CD56brightCD16⁻ cells. B. Contour plots for theCD56dimCD16⁺ cells. Population statistics are indicated for each quadrant gate in the respective contour plots.
CD56bright CD16 –0.42

95.2

3.02

6.04

0.31

93.5

0.10

62.5

9.68

27.00.83

CD158e1 PE

CD159a BV711

1.35

CD158b BV605

Figure 3A

CD158a APC

CD158f BV421

TIGIT BV650

CD56dimCD16 +
20.9

37.7

18.9

28.9

1.49

68.5

1.15

4.47

17.2

40.2

38.1

CD158e1 PE

CD159a BV711

22.4

CD158b BV605

Figure 3B

CD158a APC

CD158f BV421

TIGIT BV650

Figure 3. Evaluation of inhibitory marker expression on the major NK subsets
Major NK-cell subsets shown in Figure 1 (CD56brightCD16⁻ and CD56dimCD16⁺) were assessed for expression of inhibitory markers CD158a, CD158b, CD158e1, CD158f, TIGIT and an
NKG2 receptor family member CD159a (NKG2A) in the contour plots. A. Contour plots for the CD56brightCD16⁻ cells. B. Contour plots for the CD56dimCD16⁺ cells. Population statistics
are indicated for each quadrant gate in the respective contour plots.

As mentioned, NK cells are highly heterogeneous; some individuals express a set of stimulatory and inhibitory receptors while others
do not. NK cell function is controlled by combinatorially expressed stimulatory and inhibitory receptors, thus making NK-cell diversity
and function closely linked. For simultaneous assessment of the combinatorial expression of stimulatory and inhibitory markers, we
combined all the markers in a single 18-color panel (Table 2). This simplified the analysis of the multiple phenotypes of NK cells
across different donors and provided a more comprehensive understanding of NK-cell diversity. In addition to CD94, CD57 andCD27, the surface expression of all the stimulatory and inhibitory markers was examined across five different donors revealing thedifferences in the expression of markers such as CD337, CD159a, CD158a and TIGIT (Figure 4).
Table 2. An 18-color panel for the analysis of 12 distinct stimulatory and inhibitory markers on subsets of human NK cells

Specificity

Major NK
Subsets

Fluorochrome

Specificity

Fluorochrome

CD3

BUV563

CD56

BUV737

CD94

BV480

CD57

FITC

CD27

APC-R700

CD244 (2B4)PE-CF594

CD16

APC-H7

CD314 (NKG2D)

PE-Cy7

Stimulatory
Receptors

CD226 (DNAM-1)

BV711

CD159c (NKG2C)

BV786

CD337 (NKp30)

BB700

CD160

PE

Specificity

Fluorochrome

CD158b (KIR2DL2/3)

BUV395

CD158e1 (NKB1/KIR3DL1) BUV805
Inhibitory
Receptors

CD158f (KIR2DL5)

BV421

CD159a (NKG2A)

BV605

TIGIT

BV650

CD158a (KIR2DL1)

APC

Figure 4Donor Number:
Donor 5
Donor 4
Donor 3
Donor 2
Donor 1

CD57 FITC

CD337 BB700

CD158f BV421

CD94 BV480

CD159a BV605

CD226 BV711

CD159c BV786

CD158b BUV395

CD158e1 BUV805

CD158a APC

CD160 PE

CD244 PE-CF594

CD314 PE-Cy7

CD27 APC-R700

TIGIT BV650

Figure 4. Assessment of stimulatory and inhibitory markers on the surface of NK cells using the 18-color flow cytometry panel
Fresh blood cells from healthy donors were stained as described in Figure 1 with the antibody-fluorochrome conjugates listed in Table 2. Sample acquisition was completed on the BD
LSRFortessa X-20 flow cytometer with an ultraviolet/violet/blue/yellow-green/red laser configuration. The expression of stimulatory and inhibitory markers, in addition to CD94, CD57
and CD27, was assessed in CD56dimCD16⁺ NK cells for different donors, as shown in the histogram layouts. Notable differences in the expression of markers, such as CD57, CD337,CD94, CD159a, CD158a and TIGIT were observed across donors.

For a comprehensive assessment of the NK-cell repertoire, t-Distributed Stochastic Neighbor Embedding (t-SNE) analysis was performedin FlowJo™ software. Use of the t-SNE algorithm enabled simultaneous assessment of independently run samples from different donors(Figure 5A) and simplified donor-to-donor comparison using the heat maps for one marker at a time (Figure 5B). The variable clustering
across the donors is driven by the differences in the expression of some of the tested markers such as CD57, CD94 and CD158a. Simplified
Presentation of Incredibly Complex Evaluations (SPICE) algorithm was used to identify distinct NK-cell subsets based on selected stimulatory
and inhibitory markers (CD94, CD159a {NKG2A}, CD160, CD337, CD158a and CD158b) (Figure 6). Thirty major subsets of NK cells wereidentified based on combinatorial expression of the selected markers. As indicated in SPICE analysis by the relative sizes of the wedges
and layout of arcs, this combinatorial analysis of the stimulatory and inhibitory markers in an 18-color panel reveals intrinsic differences inreceptor expression among healthy donors and provides a deeper understanding of the NK-cell diversity.
All Donorst-SNE 2Figure 5At-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 2t-SNE 2t-SNE 2t-SNE 2CD57t-SNE 2Figure 5BDonor 5t-SNE 2Donor 4t-SNE 2Donor 3t-SNE 2Donor 2t-SNE 2t-SNE 2Donor 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 2t-SNE 2t-SNE 2t-SNE 2t-SNE 2CD94t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 1t-SNE 2t-SNE 2t-SNE 2t-SNE 2t-SNE 2

CD158at-SNE 1t-SNE 1Figure 5. High-dimensional analysis of stimulatory and inhibitory markers on NK cells and comparison of different donors
Fresh blood cells from the five different donors stained and acquired as described in Figure 4 were used for high-dimensional data analysis using FlowJo software. NK cells were gatedas CD3⁻CD56⁺ for the analysis. A. t-SNE analysis for all donors and each individual donor projects donor-to-donor variability in NK-cell stimulatory and inhibitory receptor expression.
B. Expression of various receptors on the NK-cell surface across different donors, as shown by the heat maps on the donor-specific t-SNE projections. Significant differences in theexpression of some of the tested markers (such as CD57, CD94 and CD158a) drive the variable clustering across donors.

Figure 6

Donor 1

Donor 2

Donor 4

Donor 3

Donor 5

Arc Legend:
CD94+
CD159a+CD160+
CD337+
CD158a+
CD158b+Figure 6. Combinatorial analysis of selected stimulatory and inhibitory receptors across different donors
Fresh blood cells from different donors (stained and acquired as described in Figure 4) were used for high-dimensional data analysis by the SPICE algorithm. Thirty major subsetsof NK cells (pie wedges) were identified based on combinatorial expression of the six markers (arcs) selected: CD94, CD159a (NKG2A), CD160, CD337, CD158a and CD158b.
The pie-chart wedges show the relative sizes of the subsets of cells expressing a combination of markers, while the arcs show the expression of selected markers indicated in the arclegend in different subsets, revealing the intrinsic differences in NK-cell repertoire across five healthy donors.

The use of a high-performance instrument along with the proper tools and practices for high-dimensional data analysis provides arobust and efficient approach for comparative and simultaneous combinatorial analysis revealing intrinsic NK-cell diversity among
different healthy donors.
The BD LSRFortessa X-20 flow cytometer equipped with the 355-nm UV laser allows the simultaneous analysis of up to 18 markers
in a single tube. This is critical to properly characterize cell types with high heterogeneity and phenotypic complexity, such as the NKcells shown in this data sheet. Using this powerful instrument in combination with a series of BD Horizon Brilliant Ultraviolet reagents,
provides up to six additional commercially available dyes that are excited by the UV laser and are designed to have miminal overlap
with each other. This allows researchers more fluorochrome choices, spread across five spatially separated lasers when designingpanels, which can decrease spectral overlap and improve resolution of the specificities of interest. Moreover, when using BD OptiBuild™
custom reagents, the choice of antibody-fluorochrome conjugates greatly expands, enabling easier panel design.

Ordering information
Systems and software
Description
BD LSRFortessa™ X-20 Cell Analyzer–Special Order
BD LSRFortessa™ Cell Analyzer

Reagents

Reagents

Description

Cat. No.

Description

Cat. No.

BD FACS™ Lysing Solution 10X Concentrate

349202

BD Horizon™ BV421 Mouse Anti-Human CD158f Clone UP-R1

566330BD Pharmingen™ Stain Buffer (FBS)

554656

BD Horizon™ Brilliant Stain Buffer Plus

566385

BD Pharmingen™ FITC Mouse Anti-Human CD57 Clone NK-1555619

BD Horizon™ BUV737 Mouse Anti-Human CD56 Clone NCAM16.2612766

BD Pharmingen™ PE Mouse Anti-Human NKB1 (CD158e1) Clone DX9555967

BD OptiBuild™ BUV563 Mouse Anti-Human CD3 Clone SK7741448

BD Pharmingen™ PE-Cy™7 Mouse Anti-Human CD56 Clone B159557747

BD OptiBuild™ BV650 Mouse Anti-Human CD337 (NKp30) Clone p30-15743171

BD Pharmingen™ APC-H7 Mouse Anti-Human CD3 Clone SK7560176

BD OptiBuild™ BV605 Mouse Anti-Human CD158b Clone CH-L743453

BD Pharmingen™ APC-H7 Mouse Anti-Human CD16 Clone 3G8560195

BD OptiBuild™ BUV395 Mouse Anti-Human CD158b Clone CH-L743456

BD Pharmingen™ PE Mouse Anti-Human CD160 Clone BY55562118

BD OptiBuild™ BV421 Mouse Anti-Human CD314 (NKG2D) Clone 1D11743558

BD Pharmingen™ APC Mouse Anti-Human CD244 Clone 2-69562350

BD OptiBuild™ BB700 Mouse Anti-Human CD337 (NKp30) Clone p30-15745937

BD Pharmingen™ PE-Cy™7 Mouse Anti-Human CD314 (NKG2D) Clone 1D11562365

BD OptiBuild™ BV786 Mouse Anti-Human CD159c (NKG2C) Clone 134591

748170

BD Horizon™ BV786 Mouse Anti-Human CD16 Clone 3G8563690

BD OptiBuild™ BV480 Mouse Anti-Human CD94 Clone HP-3D9746737

BD Pharmingen™ APC Mouse Anti-Human CD158a Clone HP-3E4564319

BD OptiBuild™ BV650 Mouse Anti-Human TIGIT Clone 741182

747840

BD Horizon™ BUV737 Mouse Anti-Human CD56 Clone NCAM16.2564447

BD OptiBuild™ BV711 Mouse Anti-Human NKG2A (CD159a) Clone 131411

747919BD Horizon™ BV711 Mouse Anti-Human CD226 Clone DX11564796

BD OptiBuild™ BV605 Mouse Anti-Human NKG2A (CD159a) Clone 131411

747921BD Horizon™ PE-CF594 Mouse Anti-Human CD244 Clone 2-69

564881

BD OptiBuild™ BV605 Mouse Anti-Human CD159c (NKG2C) Clone 134591

748166565116

BD OptiBuild™ BUV805 Mouse Anti-Human CD158e1 (NKB1) Clone DX9748921

BD Horizon™ APC-R700 Mouse Anti-Human CD27 Clone M-T271

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