Solutions for High-Dimensional Flow Cytometry Deep Exploration Tools from BD Biosciences

Solutions for high-dimensional flow cytometry Deep exploration tools from BD Biosciences

BD presents the high-parameter solution

Figure 1: BD FACSymphonyTM flow cytometer

Figure 2: BD HorizonTM Brilliant dyes (Brilliant Figure 3: FlowJoTM version 10.5 advanced data Violet, Brilliant Ultraviolet and Brilliant Blue) analysis software

We support you with everything, from experimental design to analysis, to allow you to push your science to the limits. High-dimensional flow cytometry

Bring state-of-the-art technology into your science

More colours Optimising existing panels

Allow a better understanding of the complex functions of With high-dimensional flow cytometry, existing panels can the immune system. be optimised with better dyes to minimise compensation and data spreading. This will improve resolution and provide clearer information on receptor expression Broad lineage panels patterns.

Allow better insights into the cellular composition of organs or peripheral blood in a single tube for applications Our new broad phenotyping panel where the target population is not known before the experiment. A large number of cell lineages in peripheral blood can now be screened with our new broad phenotyping panel.

Deep phenotyping panels

Allow the analysis of multiple expression patterns on a defined cell subset to learn more about the biology of immune functions

Read on to discover the potential of the BD FACSymphonyTM and its associated new dyes. List of monoclonal antibodies and dyes for the 27-colour broad phenotyping panel

Antibody Clone Label P/N CD8 RPA-T8 BUV395 563796 CD4 SK3 BUV496 564651 CD19 SJ25C1 BUV563 565698 CD16 3G8 BUV615-P * CD38 HIT2 BUV661 565070 CD27 L128 BUV737 564302 CD45 HI30 BUV805 564915 CCR4 1g1 BV421 562579 IgD IA6-2 BV480 566187 CD11c B-ly6 BV570-P * CD20 2H7 BV605 563783 CD56 NCAM16.2 BV650 564057 CCR6 11A9 BV711 563923 CCR10 1B5 BV750-P * CD127 HIL-7R-M21 BV786 563324 CD45RA HI100 BB515 564552 CD32 FLI8.26 BB630-P * CD64 10.1 BB660-P * PD1 EH12.1 BB700 566461 CD14 MφP9 BB790-P * CD57 NK-1 PE 560844 CD25 M-A251 PE-CF594 562403 CXCR3 1C6/CXCR3 PE-Cy5 561731 CD123 7G3 PE-Cy7 560826 CCR7 150503 Alexa647 560816 HLA-DR G46-6 APC-R700 565128 CD3 SK7 APC-H7 560275

Table 1: List of monoclonal antibodies and dyes for the 27-colour broad phenotyping panel. P stands for ‘prototype dye’. The colours represent the excitation laser wavelengths

355 nm UV laser 405 nm violet laser 488 nm blue laser 561 nm yellow-green laser 637 nm red laser. * Custom conjugates available upon request

The spillover spread matrix (SSM) Buffy coats were obtained from the German red cross, from voluntary healthy donors. Samples were stained with mAbs in PBS with ETDA/FCS plus Brilliant stain buffer. mAbs were titrated for optimal stain concentration and minimal background. For the fully stained sample, a total of 900,000 events were recorded for analysis

For more information about the dyes, visit the BD Biosciences website at www.bdbiosciences.com/us/applications/research/multicolor-flow/m/745795/overview List of monoclonal antibodies and dyes for the 27-colour broad phenotyping panel

Dyes were matched to the markers using the spillover spread matrix (SSM) for the instrument generated from single colour stains in FlowJoTM. The spillover spread matrix shows the impact of a dye in all the other channels and helps in choosing the appropriate dye for any marker and lineage. Note that spreading is an issue only in strongly expressed markers. A medium or low expression will not have spreading issues. BB515 BB630-P BB660-P BB700 BB790-P Alexa647 Alexa700 APC-Cy7 BUV395 BUV496 BUV563 BUV615-P BUV661 BUV737 BUV805 BV421 BV480 BV570-P BV605 BV650 BV711 BV750 BV786 PE PE-CF594 PE-Cy5 PE-Cy7 BB515 BB630-P BB660-P BB700 BB790-P Alexa647 Alexa700 APC-Cy7 BUV395 BUV496 BUV563 BUV615-P BUV661 BUV737 BUV805 BV421 BV480 BV570-P BV605 BV650 BV711 BV750 BV786 PE PE-CF594 PE-Cy5 PE-Cy7

Table 2: The colour-coded SSM for the list of monoclonal antibodies. Green indicates no significant data spreading (<3), yellow a moderate effect (<6), and red indicates a strong data spreading (>6) into the affected channel.

For more information about the dyes, visit the BD Biosciences website at www.bdbiosciences.com/us/applications/research/multicolor-flow/m/745795/overview Experimental results Lymphocyte populations

250K 250K 5 5 250K 250K 10 10 105 105 105 105 105

200K 200K 200K 200K 4 4 4 10 10 104 104 10 104 104 150K 150K 150K 150K SSC

3 SSC-W 3 3 SSC-W SSC-A 3 3 10 3 3 100K 10 10 100K 100K 10 10 10 10 100K CD64 BB660 CD16 BUV615 CD32 BB630 CD8 BUV395 CD19 BUV563 CD45RA BB515 CD45RA 0 0

0 0 APC-R700 HLA-DR 0 0 50K 50K 50K 50K 0 -103 -103 -103 3 -103 -103 -10 0 0 0 0 0 50K 100K 150K 200K 250K 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 0 50K 100K 150K 200K 250K -10 0 10 10 10 -10 0 10 10 10 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 SSC-H CD45 BUV806 SSC-H CD14 BB790 HLA-DR APC-R700 CD45 BUV805 CD3 APC-Cy7 CD4 BUV496 CCR7 Alexa647 CD38 BUV661 CD38 BUV661

105 105 105 105

104 104 104 104 Gated on total CD8

250K 3 250K 3 5 3 5 250K 250K 5 5 5 5 5 10 10 10 10 10 10 10 10 10 10 103 CCR4 BV421 CD127 BV786

200K 200K CXCR3 PE-Cy5 200K 200K BB515 CD45RA 0 4 4 4 10 10 104 104 10 104 104 0 0 0 150K 150K 150K 150K -103 SSC

3 3 3 4 5 3 3 SSC-W 4 5 3 3 4 3 5 3 3 4 5 3 SSC-W SSC-A 3 3 10 3 3 -10 0 100K10 10 10 -10 0 10 100K10 10 -10 0 10 10 10 10 -10 0 10 10 10 10 100K 100K 10 10 10 10 CD64 BB660 CD16 BUV615 CD32 BB630 CD8 BUV395

CD19 BUV563 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711 CD45RA BB515 CD45RA 0 0

0 0 APC-R700 HLA-DR 0 0 50K 50K 50K 50K 0 3 3 3 3 3 3 -10 -10 -10 -10 -10 -10 0 0 0 0 3 3 4 5 3 3 4 5 0 50K 100K 150K 200K 250K 3 3 4 5 0 50K 100K 150K 200K 250K -10 05 10 10 10 5 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 10 SSC-H CD45 BUV806 SSC-H CD14 BB790 HLA-DR APC-R700 CD45 BUV805 CD3 APC-Cy7 CD4 BUV496 CCR7 Alexa647 CD38 BUV661 CD38 BUV661 104 104 104 Gated on total CD4

3 3 10 3 5 5 5 5 10 10 10 10 10 10 IgD BV480 CD19 BUV563 CD38 BUV661 0 0 4 4 4 0 104 10 10 10 -103 -103

-103 0 103 104 105 0 104 105 0 104 105 103 103 103 103 CD3 APC-Cy7 CD27 BUV737 CD20 BV605 CCR4 BV421 CD127 BV786 CXCR3 PE-Cy5 0 BB515 CD45RA 0 0 0 -103

-103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711

105 105 105

104 104 104 Figure 4:

Upper row: Lymphocytes were gated based on CD45 versus Side Scatter and singlets were gated based on Side Scatter-Width. CD3- 103 103 103 IgD BV480

positive T cells can be identified. CD19 BUV563 CD38 BUV661 0 0 Middle row: Identification and analysis of CD4/CD8 positive T cells. The CD8-positive cells are then separated into naïve/memory state 0 -103 -103

by CCR7/CD45RA staining. In the CD8 T cells, a CD38-positive subset can also be identified, and some of those cells express HLA-DR or 4 4 -103 0 103 104 105 0 10 105 0 10 105 CD32. CD3 APC-Cy7 CD27 BUV737 CD20 BV605 Lower row: Analysis of the CD4-positive T cells. Regulatory T-cells can be identified in a staining with CD127 and CD25. Also, in the CD4 subset, naïve/memory cells can be separated using CCR7/CD45RA staining. The last two plots show the expression of four chemokine receptors, CXCR3, CCR10, CCR4, and CCR6 for the CD4 T cells. With these parameters, the different T helper cell subsets can be identified.

105 105 105 105

104 104 104 104 105 105 105 105

4 4 4 4 103 103 103 103 10 10 10 10 CD56 BV650 CD19 BUV563 CD123 PE-Cy7

0 0 APC-R700 HLA-DR 0 0 103 103 103 103 3 3 3 3

-10 -10 -10 -10 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA

0 0 APC-R700 HLA-DR 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 -103 -103

-103 0 103 104 105 0 103 104 105 0 103 104 105 -103 0 103 104 105 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750

105 105 105 105 105 105

104 104 104 104 104 104 105 105 105 105

103 3 4 4 4 4 10 103 103 103 103 10 10 10 10 CD56 BV650 CXCR3 PE-Cy5 CXCR3 PE-Cy5 CD19 BUV563 CD123 PE-Cy7

0 0 APC-R700 HLA-DR 0 0 0 0 5 5 5 103 10 10 10 103 103 103 3 3 3 3

-10 -10 -10 -10 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA 3 3 4 5 3 3 4 5 0 0 APC-R700 HLA-DR 0 -10 0 10 10 10 -10 0 10 10 10 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 104 104 104 0 PD-1 BB700 CD38 BUV661 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 -103 -103

3 3 4 5 3 4 5 3 4 5 3 3 4 5 103 103 103 -10 0 10 10 10 0 10 10 10 0 10 10 10 -10 0 10 10 10 CD56 BV650 CD19 BUV563 CD16 BUV615 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750 0 0 0

-103 -103 -103

-103 0 103 104 105 0 104 105 -103 0 103 104 105 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700

105 105

104 104

105 105 103 103

4 4 10 10 CXCR3 PE-Cy5 CXCR3 PE-Cy5 0 0 105 105 105 103 103 3 3 4 5 3 3 4 5

CD16 BUV615 CD16 BUV615 -10 0 10 10 10 -10 0 10 10 10 104 104 104 0 0 PD-1 BB700 CD38 BUV661

-103 -103 103 103 103 3 3 4 5 3 3 4 5 CD56 BV650

CD19 BUV563 CD16 BUV615 -10 0 10 10 10 -10 0 10 10 10 0 0 0 HLA-DR APC-R700 HLA-DR APC-R700

-103 -103 -103

-103 0 103 104 105 0 104 105 -103 0 103 104 105 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700

105 105

104 104

103 103 CD16 BUV615 CD16 BUV615 0 0

-103 -103

-103 0 103 104 105 -103 0 103 104 105 HLA-DR APC-R700 HLA-DR APC-R700 250K 250K 5 5 250K 250K 10 10 105 105 105 105 105 200K 200K 200K 200K 4 4 4 10 10 104 104 10 104 104 150K 150K 150K 150K SSC

3 SSC-W 3 3 SSC-W SSC-A 3 3 10 3 3 100K 100K 10 10 100K 100K 10 10 10 10 CD64 BB660 CD16 BUV615 CD32 BB630 CD8 BUV395 CD19 BUV563 CD45RA BB515 CD45RA 0 0

0 0 APC-R700 HLA-DR 0 0 50K 50K 50K 50K Experimental results 0 3 3 3 3 3 3 -10 -10 -10 -10 -10 -10 0 0 0 0 0 50K 100K 150K 200K 250K 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 0 50K 100K 150K 200K 250K -10 0 10 10 10 -10 0 10 10 10 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 SSC-H CD45 BUV806 SSC-H CD14 BB790 HLA-DR APC-R700 MonocyteCD45 BUV805 populations CD3 APC-Cy7 CD4 BUV496 CCR7 Alexa647 CD38 BUV661 CD38 BUV661

250K 250K 5 5 250K 250K 10 10 105 105 105 105 105 200K 200K 5 5 5 5 200K 200K 10 10 10 10 4 4 4 10 10 104 104 10 104 104 250K 250K 5 5 250K 250K 5 5 5 5 5 150K 150K 10 10 10 10 10 10 4 4 4 4 150K 150K 10 10 10 10 10 SSC

3 200K 200KSSC-W 3 3 SSC-W 200KSSC-A 200K 3 3 10 3 3 100K 100K 10 10 100K 100K 10 10 10 10 4 4 4 4 4 4 4 10 10CD64 BB660

CD16 BUV615 3 3 3

10 CD32 BB630 10 10CD8 BUV395 10 10 10 10 10

CD19 BUV563 3 CD45RA BB515 CD45RA 150K 150K 0 10 0

150K 150K 0 0 APC-R700 HLA-DR 0 0 50K 50K CCR4 BV421

50K 50K CD127 BV786 SSC CXCR3 PE-Cy5 0 BB515 CD45RA

3 SSC-W 3 3 3 3

SSC-W 0 SSC-A 3 3 3 3 10 3 3 3 3 100K 100K 10 -10 10 -10 100K 100K 10 -10 10 -10 10 -10 10 -10 0 0 CD64 BB660 0 0 0 CD16 BUV615

0 0 CD32 BB630 CD8 BUV395 3 3 4 5 3 3 4 5 3 3 3 4 5 0 50K 100K 150K 200K 250K CD19 BUV563 -10 0 10 10 10 CD45RA BB515 CD45RA 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 0 50K 100K 150K 200K 250K -10 0 10 10 10 -10 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 0 0 0 0 APC-R700 HLA-DR 0 0 50K 50K 50K 50K SSC-H 0 CD45 BUV806 SSC-H CD14 BB790 3 3 HLA-DR4 APC-R7005 3 3 4 5 3 3 4 5 3 3 4 5 CCR7 Alexa647 CD38 BUV661 3 -10 3 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 CD45 BUV805 CD3 APC-Cy7 CD4 BUV496 CD38 BUV661 -10 -10 -103 -103 -103 -103 0 0 0 0 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711 0 50K 100K 150K 200K 250K 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 0 50K 100K 150K 200K 250K -10 0 10 10 10 -10 0 10 10 10 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 SSC-H CD45 BUV806 SSC-H CD14 BB790 HLA-DR APC-R700 CD45 BUV805 CD3 APC-Cy7 CD4 BUV496 CCR7 Alexa647 CD38 BUV661 CD38 BUV661 105 105 105 105 105 105 105

4 4 4 Monocytes were gated based on CD45 versus Side Scatter, and singlets were gated based on Side Scatter-Width. Classic 104 10 10 10 Figure 5: 4 105 105 105 105 monocytes are CD14-positive, but we can also identify a CD16-high intermediate population, and a CD14-neg/CD16-high non-classical 104 10 104 103 103 103 103 monocyte population. The three populations also differ in the expression levels of HLA-DR and CD64, which is depicted in the last plot. 4 4 4 4 3 3 10 3 10 10 10 10CCR4 BV421 CD127 BV786 10 10 CXCR3 PE-Cy5 CD45RA BB515 CD45RA 0 IgD BV480 CD19 BUV563 CD38 BUV661 0 0 0 3 3 3 0 0 3 10 10 10 103 -10 0 3 3 CCR4 BV421 CD127 BV786 -10 -10 CXCR3 PE-Cy5 3 3 4 BB515 CD45RA 5 3 3 4 5 3 3 4 5 3 3 4 5 0 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 3 3 4 5 4 5 4 5 0 0 0 B-cell populations -10 0 10 10 10 0 10 10 0 10 10 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711 3 -10 CD3 APC-Cy7 CD27 BUV737 CD20 BV605

-103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105

CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711 5 5 10 105 10

104 104 104 105 105 105

103 103 103 104 104IgD BV480 104 CD19 BUV563 CD38 BUV661 0 0 0 103 103 -103 103 -103 IgD BV480

CD19 BUV563 3 3 4 5 0 104 105 CD38 BUV661 0 104 105 0 -10 0 10 10 10 0 CD3 APC-Cy7 0 CD27 BUV737 CD20 BV605 -103 -103

-103 0 103 104 105 0 104 105 0 104 105 Figure 6: B-cellsCD3 wereAPC-Cy7 identified as CD19-positive cells from theCD27 lymphocyte BUV737 gate. They can be separated into naive/memoryCD20 BV605 state by staining with anti-IgD surface immunoglobulin expression and CD27. The class-switched memory B-cells have lost all IgD expression and are CD25-high. These cells also contain the actively antibody secreting cells (plasmablasts), which can be identified in the last plot as CD38-high/CD20-low cells.

Dentritic cell populations

105 105 105 105

104 104 104 104 105 105 105 105

4 4 4 4 103 103 103 103 10 10 10 10 CD56 BV650 CD19 BUV563 CD123 PE-Cy7

0 0 APC-R700 HLA-DR 0 0 103 103 103 103 3 3 3 3

-10 -10 -10 -10 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA

0 0 APC-R700 HLA-DR 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 -103 -103

-103 0 103 104 105 0 103 104 105 0 103 104 105 -103 0 103 104 105 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750 105 105 105 105 Figure 7: Dendritic cells (DC) can be identified by first gating on CD3/CD19/CD56 triple negative cells in the lymphocyte gate. In the next step, the gating is done on HLA-DR positive events and excludes any CD14-positive cells (contaminating monocytes in the lymphocyte 104 104 104 104 gate). The last105 plot shows those cells stained 10with5 CD123 and CD11c to identify10 5plasmacytoid DC (CD 123-positive)105 and myeloid DC 105 105 105 105

(CD11c-positive).4 4 4 4 103 103 103 103 10 10 10 10 4 4 4 4 5 5 5 5 10 10 CD56 BV650 10 10 10 10 10 CD19 BUV563 10 5 CD123 PE-Cy7 10 105

0 0 APC-R700 HLA-DR 0 0 103 103 103 103 3 3 3 3 4 4 4 4 3 3 3 3 10 10 10 10 4 10 -10 10 -10 10 -10 10 -10 CD127 BV786 4

CXCR3 PE-Cy5 10 CD45RA BB515 CD45RA 10 CD56 BV650 HLA-DR APC-R700 HLA-DR CD19 BUV563

CD123 PE-Cy7 0 0 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0

0 0 APC-R700 HLA-DR 0 0 3 3 3 3 10 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 103 -10 103 -10 103 -10 103 103 3 3 3 3 -10 -10 -10 -10 CD127 BV786 3 4 5 3 4 5 CXCR3 PE-Cy5 3 3 4 5 BB515 CD45RA 0 10 10 10 0 10 10 10 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 CXCR3 PE-Cy5 CXCR3 PE-Cy5

0 0 APC-R700 HLA-DR 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750 0 0 5 5 5 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 10 -103 10-103 10

3 3 4 5 3 4 5 3 4 5 3 3 4 5 -10 0 10 10 10 0 10 10 10 0 10 10 10 -10 0 10 10 10 3 3 4 5 3 3 4 5 4 4 4 -10 0 10 10 10 -10 0 10 10 10 CD25 PE-CF594 10 HLA-DR APC-R700 10 CCR4 BV421 10 CCR10 BV750 PD-1 BB700 CD38 BUV661

103 103 103

5 CD56 BV650 5 CD19 BUV563 10 10 CD16 BUV615 0 0 0

-103 104 -103 104 -103 105 5 -103 0 103 104 105 10 0 104 105 -103 0 103 104 105

3 3 10 CD3 APC-Cy7 10 CD57 PE HLA-DR APC-R700 104 104 CXCR3 PE-Cy5 CXCR3 PE-Cy5 0 0 5 5 5 10 10 10 103 103

CXCR3 PE-Cy5 -103 0 103 104 105 CXCR3 PE-Cy5 -103 0 103 104 105 104 104 104 0 0 105 105 105 105 105 PD-1 BB700 CD38 BUV661

3 3 3 10 10 10 3 3 4 5 3 3 4 104 5 104 4 4 4 -10 0 10 10 10 -10 0 10 10 10

10 10 CD56 BV650 10 CD19 BUV563 CD16 BUV615 0 0 0 PD-1 BB700 CD38 BUV661 103 103 103 -103 103 -103 103 -103 CD16 BUV615 CD16 BUV615 CD56 BV650 CD19 BUV563 -103 0 103 104 105 0 104 105 CD16 BUV615 -103 0 103 104 105 0 0 0 0 0 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700 -103 -103 -103 -103 -103 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 0 104 105 -103 0 103 104 105 HLA-DR APC-R700 HLA-DR APC-R700 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700

105 105

104 104 105 105

103 103 104 104 CD16 BUV615 CD16 BUV615 0 0

103 -103 103 -103

CD16 BUV615 3 3 4 5 CD16 BUV615 3 3 4 5 0 -10 0 10 10 10 0 -10 0 10 10 10 HLA-DR APC-R700 HLA-DR APC-R700 -103 -103

-103 0 103 104 105 -103 0 103 104 105 HLA-DR APC-R700 HLA-DR APC-R700 250K 250K 5 5 250K 250K 10 10 105 105 105 105 105

200K 200K 200K 200K 4 4 4 10 10 104 104 10 104 104 150K 150K 150K 150K SSC

3 SSC-W 3 3 SSC-W

SSC-A 10 10 10 100K 100K 103 103 103 103 100K 100K CD64 BB660 CD16 BUV615 CD32 BB630 CD8 BUV395 CD19 BUV563 CD45RA BB515 CD45RA 0 0

105 105 105 105

104 104 104 104

103 103 103 103 CCR4 BV421 CD127 BV786 CXCR3 PE-Cy5 0 BB515 CD45RA 0 0 0 -103

-103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711

105 105 105

104 104 104

103 103 103 IgD BV480 CD19 BUV563 CD38 BUV661 0 0 0 -103 -103

-103 0 103 104 105 0 104 105 0 104 105 CD3 APC-Cy7 CD27 BUV737 CD20 BV605

250K 250K 5 5 250K 250K 10 10 105 105 105 105 105 200K 200K 200K 200K 4 4 4 10 10 104 104 10 104 104 5 150K 5 150K 5 5 150K 150K 10 10 10 10 SSC

3 SSC-W 3 3 SSC-W SSC-A 3 3 10 3 3 100K 100K 10 10 100K 100K 10 10 10 10 4 4 4 4 5 5 5 CD64 BB660 5

10 10 10 CD16 BUV615 10 10 10 10 10 CD32 BB630 CD8 BUV395 CD19 BUV563 CD45RA BB515 CD45RA 0 0

0 0 APC-R700 HLA-DR 0 0 50K 50K 50K 50K 0 4 4 4 4 3 3 3 -103 3 -103 10 10 10 10 -103 -103 -103 -103 10 10 10 10

0 CD56 BV650 0 CD19 BUV563

0 0 CD123 PE-Cy7 0 50K 100K 150K 200K 250K 3 3 4 5 0 50K 100K 150K 200K 250K 3 3 4 5 -103 0 103 104 105 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 -10 0 100 10 10 0 APC-R700 HLA-DR 0 0 -10 -10 0 10 10 10 3 3 3 3 10 SSC-H CCR7 Alexa647 CD45 BUV806 SSC-H CD14 BB790 HLA-DR APC-R700 10 10 10 CD45 BUV805 CD3 APC-Cy7 CD4 BUV496 CD38 BUV661 CD383 BUV661 3 3 3

-10 -10 -10 -10 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA

0 0 APC-R700 HLA-DR 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 -103 -103 5 5 5 5 10 10 10 3 4 5 3 4 5 3 3 4 5 10 -103 0 103 104 105 0 10 10 10 0 10 10 10 -10 0 10 10 10 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750 104 104 104 104

103 103 103 103 CCR4 BV421 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA Experimental results 0 0 0 0 5 5 -103 10 10

-103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105 104 104 CD25 PE-CF594 CCR7 Alexa647 CCR10 BV750 CCR6 BV711 NK cell populations

103 103

105 105 105 CXCR3 PE-Cy5 CXCR3 PE-Cy5 0 0 105 105 105 104 104 104 -103 0 103 104 105 -103 0 103 104 105 104 104 104 PD-1 BB700 CD38 BUV661 103 103 103 IgD BV480

CD19 BUV563 103 103 103 CD38 BUV661 0 0 CD56 BV650 CD19 BUV563 0 CD16 BUV615 0 0 0 -103 -103

3 3 3 -103 0-10 103 104 105 -10 0 104 105 -10 0 104 105 CD3-10 APC-Cy73 0 103 104 105 0 CD27 10BUV7374 105 -103 0 103 104 105 CD20 BV605 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700

Figure 8: NK-cells can be identified by a CD56/CD57 stain in the cells that are CD3 105 105 and CD19 negative. There are three NK-cell populations visible: 104 104 CD56dim, CD56high and the CD56dim/CD57 pos fraction. 103 103 CD16 BUV615 CD16 BUV615 Those cells clearly differ in their 0 0

expression patterns for HLA-DR -103 -103

and CD16, shown in the three -103 0 103 104 105 -103 0 103 104 105 adjacent plots. HLA-DR APC-R700 HLA-DR APC-R700

Regulatory T-cell populations

105 105 105 105

104 104 104 104 105 105 105 105

4 4 4 4 103 103 103 103 10 10 10 10 CD56 BV650 CD19 BUV563 CD123 PE-Cy7

0 0 APC-R700 HLA-DR 0 0 103 103 103 103 3 3 3 3

-10 -10 -10 -10 CD127 BV786 CXCR3 PE-Cy5 CD45RA BB515 CD45RA

0 0 APC-R700 HLA-DR 0 -103 0 103 104 105 0 104 105 -103 0 103 104 105 -103 0 103 104 105 0 CD3 APC-Cy7 CD20 BV605 CD14 BB790 CD11c BV570 -103 -103 -103

-103 0 103 104 105 0 103 104 105 0 103 104 105 -103 0 103 104 105 CD25 PE-CF594 HLA-DR APC-R700 CCR4 BV421 CCR10 BV750

Figure 9: Regulatory T cells are not a homogeneous population. Three populations 105 105 can be identified in a plot of 104 104 HLA-DR versus CD45RA. Also

the expression of chemokine 103 103

receptors CXCR3 and CCR4, as CXCR3 PE-Cy5 CXCR3 PE-Cy5 0 0 105 105 105 well as PD-1 and CD38, reveal distinct subsets of those cells. -103 0 103 104 105 -103 0 103 104 105 104 104 104 PD-1 BB700 CD38 BUV661

103 103 103 CD56 BV650 CD19 BUV563 CD16 BUV615 0 0 0

-103 -103 -103

-103 0 103 104 105 0 104 105 -103 0 103 104 105 CD3 APC-Cy7 CD57 PE HLA-DR APC-R700

105 105

104 104

103 103 CD16 BUV615 CD16 BUV615 0 0

-103 -103

-103 0 103 104 105 -103 0 103 104 105 HLA-DR APC-R700 HLA-DR APC-R700 Experimental results t-SNE plots

In high-dimensional flow cytometry, two-dimensional gating in dotplots to spot any difference in the sample sets is very time-consuming. Additionally, populations may be hidden in complex datasets that get lost by two-dimensional gating. With data reduction algorithms it is possible to visualise the expression patterns in two dimensions (t-distributed stochastical neighbor embedding, tSNE). This technology, available also in FlowJoTM, allows the data pattern to be visualised in two- dimensional plots and enables an easier spotting of differences between different sample sets. Furthermore, this technology also eliminates the user bias in gating different subsets and the possibility of losing important cells that were not inside the parent gate for further analysis.

Heatmap for CD3 Heatmap for CD4 Heatmap for CD25 Overlay of the two CD25 high populations from the tSNE plot

40 40 40 5 10 105

20 20 20 4 10 104 0 0 0 tSNE Y tSNE Y tSNE Y tSNE 103 103

-19 -19 -19 CD127 BV786 0 BB515 CD45RA 0 -39 -39 -39 -103

3 3 4 5 -39 -19 02040 -39 -19 02040 -39 -19 02040 -10 0 10 10 10 -103 0 103 104 105 tSNE X tSNE X tSNE X CD25 PE-CF594 HLA-DR APC-R700 -1622,4269 40060,5709 -1622,4269 41640,8286 -1622,4269 37081,9557 Comp-APC-Cy7-A Comp-BUV496-A Comp-PE-CF594-A

Heatmap for CD19 Heatmap for CD56

40 40 105 105

20 20 104 104

0 0

3 Y tSNE tSNE Y tSNE 10 103 IgD BV480 -19 -19 CD56 BV650 0 0 -39 -39 -103

4 5 -39 -19 02040 -39 -19 02040 0 10 10 0 104 105 tSNE X CD27 BUV737 tSNE X CD57 PE

-1395,3424 27270,4398 -1622,4269 18660,077 Comp-BUV563-A Comp-BV650-A

Figure 10: The lymphocyte singlet gate was downsampled to 25000 events. tSNE calculation was performed in FlowJoTM 10.5 with 1000 iterations and a perplexity of 50. Upper row: The upper row shows colour coded heatmaps for CD3, CD4, and CD25. The two CD25 high populations from the tSNE plots were gated and are shown as overlay dotplots. While both populations are clearly CD25 high and CD127 negative, there is a striking difference in CD45RA and HLA-DR expression. Due to low event numbers the size of the dots has been enlarged for better visibility. Lower row: The lower row shows on the left the colour coded heatmaps for CD19 and a gated plot with CD27 and IgD. The three tSNE populations can be clearly seen in the dotplot and identified as naïve, non-switched memory and class switched memory B cells. On the right we have the colour coded heatmap for CD56, and the dotplot CD56 versus CD57 reveals the three distinct NK cell populations. These examples show the potential of unsupervised analyses for high-parameter flow cytometry data. Instrument configuration Starting configuration for a BD FACSymphonyTM A5

This configuration allows you to start your work immediately. Existing panels from a BD LSRFortessaTM or BD FACSAriaTM can be transferred without any change, and you can start to add markers or build panels from scratch using the spillover spread matrix.

Laser Power Detector Parameter Bandpass Dichroic 488 200mW 7 Colours A BB790-P 810/40 770LP B BB755-P 750/30 735LP C BB700 710/50 685LP D BB660-P 670/30 635LP E BB630-P 610/20 600LP F BB515 530/30 505LP G SSC 488/10 n.a.

405 200mW 8 Colours A BV786 810/40 770LP B BV750 750/30 735LP C BV711 710/50 685LP D BV650 677/20 635LP E BV605 605/40 595LP F BV570-P 586/15 550LP G BV510/BV480 525/50 505LP H BV421 431/28 410LP

355 100mW 7 Colours A BUV805 810/40 770LP B BUV737 735/30 690LP C BUV661 670/25 630LP D BUV615-P 605/20 595LP E BUV563 580/20 550LP F BUV496 515/30 450LP G BUV395 379/28 370LP

637 140mW 3 Colours A APC-H7 780/60 750LP B APC-R700 730/45 690LP C APC 670/30 655LP

561 200mW 5 Colours A PE-Cy7 780/60 750LP B PE-Cy5.5 710/50 685LP C PE-Cy5 670/30 635LP D PE-CF594 610/20 600LP E PE 586/15 570LP

Table 3: P stands for “prototype dye”. These dyes are not listed in the web catalogue. BD will supply FACSymphony users with mAbs labelled with them on request. Our dedicated high-parameter reagent team can couple those prototype dyes to any of the mAbs from our portfolio of clones. Depending on the choice, up to a maximum of 10 lasers of various wavelengths and with multiple power ratings can be selected. BD is also working on expanding the selection of dyes. The configuration above is only an example and can be adapted to your specific requirements.

355 nm 488 nm 592 nm 785 nm Table 4: 375 nm 505 nm 628 nm The 25 available lasers for the BD FACSymphony™ A5. 405 nm 514 nm 637 nm Each laser has multiple power ratings that can be adjusted 420 nm 532 nm 640 nm 445 nm 552 nm 647 nm and stored. Depending on the choice, up to ten lasers can 458 nm 561 nm 660 nm be selected and configured. Common laser choices are 460 nm 568 nm 685 nm highlighted. 473 nm 588 nm 730 nm Other custom products and services Delivering custom solutions

The BD Custom Technology Team (CTT) is a specialised contract research group with core competencies in flow cytometry and multiplexed protein assay development. Solutions include custom products, contract manufacturing, assay development and assay services that enable global biotechnology, pharmaceutical and contract research organizations to respond efficiently to the rapidly changing landscape of research and development. These solutions expand beyond typical offerings to essential resources such as protocol development, flexible delivery options and quality documentation. Typical assay services

BD has conducted cell and protein analysis studies for many major biotechnology and pharmaceutical companies. Examples of assay services include panel design* and manufacturing based on customer specifications. Thousands of samples have been processed in various studies for cancer, autoimmunity, infectious disease and HIV therapeutics and vaccines. Expertise in the typical study processes, combined with expertise in cell and protein analysis, can translate into efficient study completion for clients.

Solutions include: • Proposal development that outlines the assays to be used • Study protocol and SOP development that optimises collection and transport conditions in coordination with research and logistical teams • Feasibility studies using known positive and negative controls • Qualification studies to assess sample-to-sample variation, transport stability, intra-assay variability, inter-technician variability and normal range expectations • Using established SOPs to process and analyse study samples • Following assay protocols to process and analyse study samples • Providing a cumulative data file and comprehensive bioanalytical study report with all information necessary to properly interpret study results

Reliable and flexible service and support

• Building on BD’s immense experience with flow cytometers, reagents and data processing software • Evaluation processes that meet your needs using small-scale (pilot) evaluation lots • Panel development assistance for research use only (RUO) applications • A wide variety of reagents and dyes for cocktailing, including BD Horizon Brilliant dye reagents* • Options to add custom packaging, labeling and order management solutions, as well as accessory reagents, including counting beads

*Contact the BD custom team at [email protected] for multicolour cocktails containing >1 BD Horizon Brilliant dye as well as lot-matched compensation controls for tandem dyes. For more information, please visit: bdbiosciences.com or contact the BD custom team at [email protected]

Class I Laser Product. For Research Use Only. Not for use in diagnostic or therapeutic procedures.

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