Application Note
Immunology

In-Depth Characterization of the Major
Leukocyte Cell Subsets in Human
Peripheral Mononuclear Cells
Using the 45-color, full-spectrum Agilent NovoCyte
Opteon spectral flow cytometer

Authors

Abstract

Ming Lei,
Laurissa Ouaguia,
Garret Guenther,
Peifang Ye,
Nancy Li,
Agilent Technologies, Inc.

Flow cytometry is a powerful technique for in-depth analysis of different immune
cell subpopulations of immune cells to gather a comprehensive assessment of
the immune system. Spectral flow cytometry has led to advancements in ourcapabilities to support more markers, greater flexibility, and better data resolution.
In this application note, a 45-color spectral flow cytometry panel was designed for
the Agilent NovoCyte Opteon spectral flow cytometer to analyze the distribution of
immune cells in a peripheral blood mononuclear cell (PBMC) sample.

Introduction
An extraordinarily complex network of cells enables theimmune system to recognize and remove dead and faulty
cells while also defending the body from pathogens. As key
drivers of the immune system, peripheral blood cells undergo
activation, proliferation, and differentiation into various
subsets characterized by a set of specific marker expressions
and functions. Due to the simplicity and the noninvasivenessof its collection, peripheral blood has become a widely
accessible source of peripheral blood mononuclear cells(PBMCs) which are vastly used in basic research, translational
research, and clinical applications.1–3 In healthy donors,
PBMCs represent a heterogenous cell population comprisedof several immune cell types including but not limited to:lymphocytes (including T cells, B cells, natural killer (NK)cells, NKT cells, γδT cells, and innate lymphoid cells (ILCs)),
monocytes, basophils, and dendritic cells (DC).1,3,4
Most lymphocytes in peripheral blood are composed of
CD3+ expressing T cells (45 to 70% PBMCs). Based on theexpression of either an αβ TCR or a γδ TCR, two types of T
cells can be distinguished.5 αβ TCR expressing T cells canbe further subdivided into conventional CD4+ T helpers (25to 60%) and CD8+ T cytotoxic cells (5 to 30%). The CD4+T
cells and CD8+T cell ratio to healthy donor PBMCs is around2:1.3,6 CD4+T helpers are essential mediators of immune
homeostasis and inflammation. Based on the expression
profiles of specific surface markers/proteins, cytokines,
chemokine receptors, and specific transcription factors,
CD4+T cells can be further classified into Th1, Th2, Th17,
Th9, Th22, follicular helper (Tfh) cell, recent thymic emigrants(RTE) and regulatory T cell (Treg) subsets.7–10 In addition,
antigen-presenting cells, after presenting antigens to naive
T cells, become activated and undergo differentiation into
effector T cells and memory cells. Effector cells migrate to thesite of infection and eliminate the pathogen. These effector
cells are short-lived while the memory subsets formed havethe potential for long-term survival.7,11 Conventional CD8+T
cytotoxic cells are a key component of the adaptive immune
system that fights intracellular infections and tumor cells.
Similar to CD4+T cells, activation of naive CD8+ T cells
induces a largely autonomous program of proliferationand differentiation, generating both effector and memory
cells.7 Memory T cells are important drivers of immunity, as
immunological memory is critical for long-term immunityand protection from infection.7 Despite the mutually exclusive
CD4–CD8 paradigm, a small fraction of αβ T cells arecomposed of unconventional T cells. These unconventional
T cells are composed of double negative CD4–CD8-T cells5,122

and double positive CD4+CD8+T cells.13 Unconventional T
cells represent the least studied T cell subset and have been
identified as key players in various conditions where they
display either a cytotoxic function (chronic viral infections)or a regulatory role (malignancies). Similar to conventional T
cells, unconventional T cells also express activation markers
and exhibit memory-like features.13–15 CD3+T cells are also
composed of regulatory T cells (Treg), which constitute 3
to 5% CD4+T cells in healthy PBMCs.16 Tregs have been
identified using various approaches, including by the relative
expression of CD3, CD4, CD25, and CD127 markers. Treg
cells can be subdivided into natural Treg (nTreg), generated in
the thymus, or peripheral inducible Treg (iTreg).17,18 Treg cells
express many activation and memory features, are known tosuppress immune responses to self-antigens, and play a rolein peripheral tolerance maintenance.7,18 Another subset of
peripheral CD3+T cells are the CD56+NKT cells (0.04 to 1.3%
lymphocytes), capable of influencing the status of the innate
and adaptive immune response.19 Based on the expression
levels of CD16 and CD56 markers, NKT cells can be further
divided into subsets, and similar to T cells, engagementof costimulatory molecules affects NKT cell activationand function.19,20
Others unconventional T cells include γδT lymphocytes, which
possess both innate and adaptive-like properties, building
the bridge between innate and adaptive immunity.21 Theseabilities render γδT cells an attractive candidate for adoptive
cell immunotherapy due to their unique biology. Based on theexpression levels of specific factors and proteins, γδT cells
can be subdivided into different subtypes.22
Peripheral lymphocytes also include non-T cells such as B
cells, NK cells, and ILCs.3,23 B cells are CD19+ expressing cells
that secrete antibodies. As such, they are central elements inhumoral immunity and protect against an almost unlimited
variety of pathogens as part of the adaptive immune system.
B cells represent around 15% PBMC and can mature anddifferentiate into plasmablasts, plasma cells, transitional
B cells, memory B cells, follicular B cells, marginal zone B
cells, B regulatory, and B-1 cells. Each B cell subset can becharacterized based on the expression of a set of proteinsand factors including CD27, IgM, IgG, IgD, and CD38.24
PBMC composition also includes NK cells (approximately
10%) which are the cytotoxic natural killer cells representing
critical components of the innate immune system by directly
destroying pathogen infected cells. Based on the relative
expression of the CD16 and CD56 markers, NK cells canbe further divided into different subsets.3,20 PBMCs are also
composed of ILCs lacking expression of lineage markers andantigen-specific receptors. Despite these characteristics, ILCs
generate of cytokines and secreted proteins leading to an
improvement of the immune response in case of infection.
Some ILCs have been shown to have many parallels with
CD4+T cell subsets. Therefore, ILCs can be further divided
into specific subsets based on specific marker expression
and cytokine production.25,26
PBMCs also consist of DC cells (1 to 2%), which function as
professional antigen-presenting cells with the unique property
of inducing priming and differentiation of naive CD4+ andCD8+ T cells into helper T, cytotoxic effectors T, and memory
T cells. Based on their ontology, localization, surface marker
expression, cytokine production, antigen-processing, andpresentation capacity, DC can be further divided into myeloid
or conventional dendritic cells (CD1c/cDC2 and CD141/cDC1)
and plasmacytoid dendritic cells (CD123/pDCs).27,28 PBMCs
are also made of monocytes (10 to 20%) which represent ahighly plastic innate immune cell type that displays significant
heterogeneity in periphery. Distinct patterns of surface marker
relative expression (CD16, CD14) have become accepted as abasis for distinguishing three monocyte subsets: nonclassical,
intermediate, and classical monocytes.3,29 PBMC is also
comprised of a small fraction of cells called basophils (< 1%)based on PBMC isolation methods. These basophils can becharacterized based on relative expression of HLADR andCD123 markers.30
There is a growing interest in deciphering the complex role ofeach blood immune cell subset to assess how they shape theimmune response, impact cancer and disease progression,and affect drug efficacy. To overcome this challenge, there
is a significant need for methodologies and instruments thatprovide high-throughput, in-depth analyses of the immune
system at the single cell level and subset level. We developed
a 45-color spectrum flow cytometry immunophenotyping
panel to quantitate peripheral immune subset frequencies,
protein expression, activation markers, exhaustion markers,
and differentiation markers expressed on the major innate
and adaptive immune cells types in healthy PBMC. Common
surface markers expressed by each population were used todetermine population frequencies and further characterizationof each population was evaluated using markers associatedwith cell activation and proliferation (CD69, HLA-DR, CD38),
cell exhaustion and senescence (PD1, CD223, CD57), celldifferentiation (CCR7, CD27, CD28, CD45RA, CD45RO, CD127),
and cell plasticity or migration potential (CXCR3, CCR6, CCR5,CXCR5). This in-depth analysis was made possible using theAgilent NovoCyte Opteon spectral flow cytometer.

Contrary to conventional cytometry, which is limited in
obtaining the peak fluorophore emission from as many
fluorescent parameters as there are detectors, spectral
cytometry is set up with many detectors to capture the full
fluorescence spectrum for every fluorophore across alllaser lines. In doing so, spectral cytometry allows for moreparameters per fluorochrome in a single experiment.1,31,32

Experimental
Materials
Table 1 describes the materials used to prepare the
45-color samples.
Table 1. Reagents used.
Reagents
True-Stain Monocyte Blocker

Part Number

Manufacturer

426102

BioLegend

Brilliant Stain Buffer Plus

566385BD

CellBlox Blocking Buffer

B001T02F01

Thermo Fisher Scientific

Phosphate Buffer Saline (PBS)

GNM-14190

Genom Biomedical Technology

Fetal Bovine Serum (FBS)

10091148

Thermo Fisher Scientific

Staining procedure
The following protocol describes the sample preparation.
Preparation of PBMCsa.

Prewarm RPMI 1640 Complete Culture Medium at 37 °C
for at least 30 minutes.

b.

Thaw the PBMC cryo tube (approximately 15 x 106 cells)
in a 37 °C water bath until only a small piece of ice is left.

c.

Transfer the contents of the cryo tube to a 50 mL
conical tube.

d.

Add 1 mL preheated RPMI 1640 Complete Culture
Medium to the cryo tube and leave it for use in step g.

e.

Add 5 mL RPMI 1640 Complete Culture Medium drop bydrop to the cells in a 50 mL tube. When adding, gently
mix the 50 mL tube (hold the pipette in one hand and the
50 mL tube in the other, gently mix the tube while adding
RPMI 1640 Complete Culture Medium).

f.

After adding the first batch of 5 mL RPMI 1640 Complete
Culture Medium, the next 5 mL should be added slightly
faster (a few drops each time).

g.

After adding 10 mL, transfer the contents of the cryo tube
to the 50 mL tube.

3h.

Add an additional volume of RPMI 1640 Complete Culture
Medium to the 50 mL tube to reach 20 mL.

i.

Centrifuge at 400 g for 8 minutes.

j.

Carefully pour out the supernatant and do not disturb
the pellet.

k.
l.

CCR6

BV711

2.5

BUV563

2.5

Gently suspend the pellet in 2 mL of preheated RPMI
1640 Complete Culture Medium and complete to 20 mL.

3

TCRγδ

PerCP-eFluor 710

0.63

4

CXCR5

BV750

0.63

Repeat steps i and j.

5

IgG

BV605

0.63

6

CXCR3

7

CD223 (LAG-3)

89Mark four 1.5 mL Eppendorf tubes with: antibody mixture
A, B, C, and D. Cells need to be stained in four steps forbetter staining.
Add 10 μL Brilliant Stain Buffer and 5 μL True-Stain
Monocyte Blocker to each antibody mixtures tube, add
5 μL CellBlox Blocking Buffer to antibody mixture tube
A only.

d.

Prepare the antibody mixture according to the antibody
list (Table 2), add the antibodies from Group A to thetubes labeled with A, add the antibodies from Group B to
the tubes labeled with B, and so on.
Centrifuge all the mixture tubes at 16,000 g ~ 18,000 g
for 5 minutes. When using the antibodies, aspirate themixture from the top of the liquid, and do not touch thebottom of the tube. The antibody aggregates will be left inthe bottom.

e.

4Dosage (μL)

CCR5Thaw Zombie NIR Live/Dead dye, transfer 0.25 μL to alarger Eppendorf tube, and add 1000 μL of 1x PBS (final
dilution 1:4000), avoiding light until use.

c.

Fluorochrome2

Preparation of live/dead dyes and antibodies mixtureb.

Specificity
Staining Group A
1

m. Suspend the cell sediment in a certain volume of RPMI
1640 Complete Culture Medium for later use.

a.

Table 2. Antibody staining groups, except CD45RO SBUV445 antibody.

PE-Cy7

1.25

NovaFluor Blue 660/120S

1.25

CD69

StarBright Blue 765

1.25

CCR7

BV421

2.5

Staining Group B
1

CD20

Spark YG 593

1.25

2

CD1c

Alexa Fluor 647

2.5

3

CD28

BV650

5

4

PD-1

BV785

5

5

CD159cPE

10

Spark Red 718

1.25

Staining Group C
1

CD127

2

CD2

PerCP-Cy5.5

2.5

3

CD337

PE-Dazzle 594

2.5

4

CD3

BV510

2.5

5

CD27

APC-H7

2.5

6

CD25

PE-Alexa Fluor 700

5

7

CD11c

eFluor 450

5

Staining Group D
1

CD45RA

BUV395

0.32

2

IgD

BV480

0.32

3

CD4

CF594

0.32

4

CD14

Spark Blue 550

0.32

5

HLA-DR

PE-Fire 810

0.32

6

CD33

StarBright Blue 580

0.32

7

CD16

BUV496

0.63

8

CD57

FITC

0.63

9

CD24

PE-Alexa Fluor 610

0.63

10

CD95

PE-Cy5

0.63

11

CD38

APC-Fire 810

0.63

12

CD31

StarBright Blue 810

0.63

13

CD141

BB515

1.25

14

CD19

Spark NIR 685

1.25

15

CD8

BUV8051.25

16CD159a

APC

2

17

CD314

BUV615

2.5

18

CD56

BUV737

2.5

19

CD45

PerCP

2.5

20

IgM

BV570

2.5

21

CD39

BUV661

2.5

22

CD123

Super Bright 436

2.5

Stainingn.

Add antibody mixture B to all multicolor tubes, vortex, andplace on ice in the dark for 40 minutes.

o.

Wash all multicolor tubes once with 3 mL wash buffer.

p.

Repeat step d.

q.

Add antibody mixture C to multicolor tubes, vortex, andplace on ice in dark for 40 minutes.

r.

Wash all multicolor tubes once with 3 mL wash buffer.

s.

Repeat step d.

t.

Add antibody mixture D to multicolor tubes, vortex, andplace on ice in the dark for 40 minutes.

Centrifuge at 500 g for 5 minutes and carefully pour out
the supernatant.

u.

Wash all multicolor tubes twice with 3 mL wash buffer.

v.

Repeat step d.

e.

Add 100 μL zombie NIR diluent to the multicolor tube andLive/Dead single staining tube; vortex well and place on
ice in the dark for 30 minutes.

w. Add 300 μL wash buffer to the multicolor tubes, vortex,
and store on ice.

f.

At the same time, stain the other single staining tubes
with the optimal antibody levels shown in Table 2 andplace them on ice in the dark for 30 minutes. Add CellBlox
Blocking Buffer for anti-CD223 NovaFluor Blue 660/120S
single staining tube.

Results and discussiona.

Mark FACS tubes: unstained control tubes, single stained
tubes, and multicolor tubes.

b.

Add 100 μL of cell suspension to each multicolor tube,
approximately 3 x 106 cells, while adding 10 μL of cellsuspension to each unstained control tube and single
stained tubes, approximately 3 x 105 cells.

c.

d.

Wash multicolor tubes and Live/Dead single staining
tubes with PBS, while washing other single staining tubes
and unstained control tubes with wash buffer (PBS + 2%
FBS), 3 mL per tube.

g.

After 30 minutes of incubation, wash the multicolor
tubes, Live/Dead single staining tubes, and other single
staining tubes with 3 mL wash buffer.

h.

Repeat step d.

i.

Add 200 μL wash buffer to Live/Dead single staining
tubes, unstained control tubes, and other single staining
tubes, vortex mix, and store on ice.

j.

Add anti-CD45RO SBUV445 to all multicolor tubes, vortex,
and place on ice in dark for 30 minutes.

k.

No wash, add antibody mixture A to all multicolor tubes,
vortex, and place on ice in the dark for 30 minutes, thenroom temperature (RT) for 20 minutes (which will makethe staining of CCR and CXCR markers better).

l.

Wash all multicolor tubes once with 3 mL wash buffer.

m. Repeat step d.

Antibody titrations
In this application note, all marker and fluorochrome
combinations proposed in this 45-color panel (outlined inTable 3) are accessed by antibody titration analysis. The
required volume of each antibody shown in Figure 1 isdetermined according to the stain index, which is calculated
as follows: (MFI(positive)–MFI(negative))/(2*SD(negative)),
where MFI is mean fluorescence intensity. The optimal
titration is chosen as the lowest concentration of antibody
with a maximal or near-maximal stain index or lower
spreading error.
The main objective of this panel design was to build off of apreviously published 40-marker panel, OMIP-069. In addition
to the OMIP-069 panel, we included five other markers:
CD45RO, CD33, CD233 (LAG-3), CD69, and CD31. The entire
panel of antibodies and fluorochromes is shown in Table 3.
Due to the complex nature of staining with such a large
panel induced by steric hindrances, four staining groups
were identified to optimize the antibody-antigen binding andincubated with the sample in a sequential pattern (Table 2).

5

Table 3. Antibody information.
MarkerFluorochrome

Clone

Manufacturer

Part Number

BD Biosciences

740315

1

CD45RA

BUV3955H9

2CD45ROStarBright UltraViolet 445

UCHL1

Bio-RADMCA461SBUV445

3

CD16

BUV496

3G8

BD Biosciences

6129454

CCR5(CD195)

BUV563

2D7/CCR5

BD Biosciences

741401

5CD314(NKG2D)

BUV615

1D11

BD Biosciences

751232

6

CD39

BUV661

TU66

BD Biosciences

749967

7CD56

BUV737

NCAM16.2

BD Biosciences

6127668CD8BUV805SK1

BD Biosciences

6128899CCR7(CD197)

BV421

G043H7

BioLegend

35320810

CD123Super Bright 436

6H6

Thermo Fisher Scientific62-1239-42

11

CD11c

eFluor 450

3.9

Thermo Fisher Scientific48-0116-42

12

IgD

BV480

IA6-2

BD Biosciences

566187

13

CD3

BV510

SK7

BioLegend

344827

14

IgM

BV570

MHM-88

BioLegend

314517

15

IgG

BV605

G18-145

BD Biosciences

563246

16

CD28

BV650

CD28.2

BioLegend

30294517

CCR6(CD196)

BV711

G034E3

BioLegend

35343518

CXCR5(CD185)

BV750

RF8B2

BD Biosciences

74711119

PD-1(CD279)

BV785

EH12.2H7

BioLegend

329929

20

CD141

BB515

1A4

BD Biosciences

565084

21

CD57

FITC

NK-1

BD Biosciences

55561922

CD14Spark Blue 550

63D3

BioLegend

36714823

CD33

StarBright Blue 580

WM53

Bio-RADMCA1271SBB580

24

CD223(LAG-3)

NovaFluor Blue 660/120S

3DS223H

Thermo Fisher Scientific

H048T02B08

25

CD45

PerCP

HI30

Agilent Technologies

893101726

CD2

PerCP-Cy5.5

TS1/8

BioLegend

30922527

TCRγδ

PerCP-eFluor 710

B1.1

Thermo Fisher Scientific46-9959-41

28

CD69

StarBright Blue 765

FN50

Bio-RADMCA2806SBB765

29

CD31

StarBright Blue 810

WM59

Bio-RADMCA1738SBB810

30

CD159c(NKG2C)

PE

134591R&D Systems

FAB138P-100

31

CD20

Spark YG 593

2H7

BioLegend

30236732

CD337(Nkp30)

PE-Dazzle 594

P30-15

BioLegend

325231

33

CD4

CF594

C4/206

Biotium#BNC940206-500

34

CD24

PE-Alexa Fluor 610

SN3

Thermo Fisher Scientific

MHCD2422

35

CD95(FAS)

36

CD25

37

CXCR3(CD183)

38

HLA-DR

39

CD159a(NKG2A)

40

CD1c

41

CD19

42

PE-Cy5DX2

BioLegend

305610PE-Alexa Fluor 700

CD25-3G10

Thermo Fisher Scientific

MHCD2524

PE-Cy7

G025H7

BioLegend

353720PE-Fire 810

L243

BioLegend

307683APC

REA110

Miltenyi

130-113-563

Alexa Fluor 647

L161

BioLegend

331510Spark NIR 685

HIB19

BioLegend

302269

CD127

Spark Red 718

A019D5

BioLegend

35137643

Viability

Zombie NIR

N/A

BioLegend

423105

44

CD27

APC-H7

M-T271BD Biosciences

56022345

CD38

APC-Fire 810

HB-7

BioLegend

3566436

A. UV laser (349 nm)

D. Yellow laser (561 nm)

B. Violet laser (405 nm)

E. Red laser (637 nm)

C. Blue laser (488 nm)

Figure 1. Antibody titrations for the 45-color panel. All antibodies are titrated over six concentrations with a starting concentration ranging from 1 to 20 µL per
100 µL staining volume using the cryopreserved PBMC separated from leukopak collected from healthy individuals. All six dilutions are shown on the same plot
with the X-axis demonstrated the dilution series. The red square highlights the final selected titer used for the panel. The optimal titer is chosen based on stain
index (the lowest concentration of antibody with a maximal or near-maximal stain index or lower spreading error) and is indicated by the red box. All titration data
were unmixed by the Agilent NovoExpress 2.0.0 software; debris and doublets were excluded, and files are concatenated using FlowJo v10.10.0. (A) 349 nm laser
excited fluorochromes, (B) 405 nm laser excited fluorochromes, (C) 488 nm laser excited fluorochromes, (D) 561 nm laser excited fluorochromes, (E) 637 nm laser
excited fluorochromes. The stain index was calculated as follows: (MFI(positive)–MFI(negative))/(2*SD(negtive)), where MFI is mean fluorescence intensity.

7Reference spectra controls were run for each marker
used, including two populations for autofluorescence (AF)subtraction as visualized in Figure 2.
A. Spectral signatures of 45 fluorochromes

B. Spectral signatures of two autofluorescence
Figure 2. Spectral signatures (45 + 2 AF)
used for unmixing the 45-color panel data.
Single stained controls were acquired on
the Agilent NovoCyte Opteon spectral flow
cytometer at the default gain settings.
Fluorochrome spectral signatures(normalized emission spectra) are shown asspectral plots grouped by primary laser andautofluorescence. (A) 45 fluorochromes;(B) Two autofluorescence signatures.

8

The Similarity Index and Spillover Spreading Matrix were
calculated using the Agilent NovoExpress software for morepanel optimization (Figures 3 and 4).

Figure 3. Similarity Index Matrix of fluorochromes used in 45-color panel.

9Figure 4. Spillover Spreading Matrix for the 45-color panel.

10The distribution of immune cell types and subtypes wereidentified based on their marker expression, and hierarchicalgating was used to specify each, as outlined in Figure 5.

Unmixed data categorized with different cell types is shownin Figure 5, highlighting the complexity and depth in which weare able to characterize many subtypes in this panel.

Figure 5. Schematic overview of all the identified cell subsets.

11

Manual gating strategy used to identify the main immune
cell subsets
PBMCs are processed following protocols describing
the sequencing staining procedure, as shown in Figure
6. After platelets, debris, doublets and dead cells were
excluded, within the live CD45+ population, basophils (1)were delineated as CD45+CD123+HLA–DR–. Lymphocytes
and monocytes (2) were gated based on FSC-H/
BSSC-H properties. Monocytes (3) were then classified
by CD14 and CD16 expression as non-classical (CD14−
CD16+), intermediate (CD14+CD16+/low), and classical(CD14+CD16–). From the lymphocyte gate (2), the following
populations were identified: CD3−TCRγδ−, CD3+TCRγδ+,and CD3+TCRγδ− (4). The CD3+TCRγδ+ population (5) wascharacterized based on CD45RA and CCR7 expression.
The CD3+TCRγδ− population was divided in CD3+CD56+(NKT-like) and CD3+CD56− subsets (6). The inclusion of CD2
and CD8 enables further classification of the NKT-like cells,
CD69 and CD57 were used to detect the early activation andcytotoxicity of NKT-like cells (7). CD4+, CD8+, CD4+CD8+,
and CD4−CD8− T cells were identified from the CD3+CD56−
gate (8). Treg cells were identified from the CD4+ population
using CD127 and CD25 expression (CD127lo/-CD25hi), andCD39 and CD45RA were used to further classify these cells(9). CCR7, CD45RA, CD27, and CD28 allowed for further
classification of memory/effector CD4 and CD8 T cellsubsets, CXCR3 and CCR6 allowed for further classificationof Th populations, CD45RO and CD31 were used to detect
RTE cells within CD4 T cells, PD-1 and CD223 were used to

12detect the exhaustion status of CD4 and CD8 T cells (10, 11).
CD19+ and/or CD20+ cells (B cells) were gated out of theCD3−TCRγδ− population (12). CD19+CD20+/− cells were
further gated as IgD+CD27−, IgD+CD27+, or IgD−CD27+/−; theIgD−CD27+/− subset was divided into plasmablasts or IgD−
memory B cells based on CD20 expression, and IgG and IgM
expression were assessed within the IgD- memory B cells; theIgD+CD27− population was further divided into transitional
B cells; the IgD+CD27+ population was further divided
into MZ and IgD- Memory only B cells (13). NK cells were
defined as CD3−TCRγδ−HLA-DR− and classified as early
NK (CD56+CD16−), mature NK (CD56+CD16+), and terminal
NK (CD56−CD16+) cells (14). Dendritic cells (DCs, 15) wereidentified first by gating on CD3−CD19−CD56−CD14−HLADR+ and from there CD123+ (pDCs) and CD11c+ DCs wereidentified. CD11c+ DCs were further divided into CD16− andCD16+. CD1c and CD141 were then used to further classify
the CD11c+CD16− and CD11c+CD16+ DCs. Finally, innate
lymphoid cells (ILCs, 16) were identified as CD3−CD19−
CD20−CD14−CD123−CD127+ and further classified based on
CD2 and CD4 expression. All data presented is derived fromfrozen PBMCs of one healthy donor.

Figure 6. The cell types
characterized in a normal human
PBMC sample after removing
platelets, debris, doublets, and deadcells are as follows: monocytes,
basophils, natural killer cells,
dendritic cells, innate lymphoidcells, B-, T-, NKT-like, Treg, andTCRγδ lymphocytes. Other
markers were included to assess
differentiation, exhaustion, or
activation status were also included.

13

Conclusion
Spectral flow cytometry offers the ability to analyze moremarkers simultaneously with improved data resolution
and panel design flexibility. Used in this study, the Agilent
NovoCyte Opteon offers these benefits, along with theeasy-to-use Agilent NovoExpress data acquisition andanalysis software. With five lasers (UV, V, B, Y, R) and 73
total photodetectors, the NovoCyte Opteon is able to meetthe requirements of increasingly sophisticated experimental
panels and enable an efficient workflow to uncover answers
that may not be met with conventional flow cytometry.

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