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A Guide to Flow Cytometry Markers

 

Classically, host immunity is divided into innate and adaptive immune responses.1 Innate immune cells include myeloid cells (monocytes, macrophages, granulocytes and dendritic cells),  natural killer (NK) cells and innate lymphoid cells. Adaptive immune cells include the immunoglobulin family and cells such as B- and T-lymphocytes.1,2

 

Immunophenotyping utilises the unique ability of flow cytometry to simultaneously analyse mixed populations of immune cells through the presence or absence of multiple flow cytometry markers.3,4

 

It allows for the characterisation of cell populations and subpopulations, identification of the status of cell differentiation and quantification of surface or intracellular molecules associated with specific cellular functions.3

 

Flow cytometry markers lists

Most antigens are given "cluster of differentiation" (CD) numbers by the Human Leukocyte Differentiation Workshops, so that a common nomenclature is used to define monoclonal antibodies that are directed against specific cellular antigens.4 For example, CD3 is "cluster of differentiation number 3" and is used to define the T-cell co-receptor that is present on all T cells.4

 

Most immune cells have specific CD markers that define them as a population of cells.1 These cell markers are called lineage markers and are used to define specific cell populations for additional analysis in each immunophenotyping experiment.4

 

As well as lineage markers that define populations of immune cells, other markers are used to characterise each cell population, such as activation markers (CD69 CD25, and CD62L).4

 

Myeloid cell markers

For phenotypic identification of myeloid cell populations, markers CD33, CD123, CD14, CD16, HLA-DR, CD11c, CD141 and CD1c can be used.5 One study developed a 10-colour flow cytometry protocol for quantification of myeloid cells, monocytes and granulocytes.6

 

 

10-color flow cytometric protocols for quantification of all major leukocyte populations6
Myeloid cellsLIN2, CD123, HLA-DR, CD11c, CD11b, CD33, CD16
Monocytes-1CD80, CD143, CD14, CD32, CD64, CD86, CD16, HLA-DR, CD45
Monocytes-2B7H1, TNFR2, CD14, PD-1, CD40, CD16, HLA-DR, CD45
GranulocytesCD66b, CD63, CD14, CD44, CD203c, CCR3, CD16, CD49d, CD15, CD45

 

 

CD14, CD163 and CD68 can detect macrophages in human lung tumours, with CD163 being a macrophage-specific marker.7 In human synovial fluid, CD11c and CD206 identified M1 and M2 macrophages, respectively.8 CD38 is also a highly and consistently induced inflammatory marker in human macrophage responses, so may play a role in monitoring inflammatory disease status.9

 

There are three major dendritic cell (DC) subsets: plasmacytoid DC (pDC), myeloid/conventional DC1 (cDC1) and myeloid/conventional DC2 (cDC2).10 Original DC markers of CD141 and CD1c have limitations as both are induced on cDC and monocyte-derived cells in tissues and in culture.10

 

 

Myeloid cell marker10Function
CD15Granulocyte subsets
CD66b
CD16
CD45
FCeR1a
CD123
Siglec 8
CD14Monocyte subsets
HLA-DR
CD45
CD16
CD32
CD64
HLA-DRDC subsets
CD123
CD11c
CD1c
CD141
CD80Activation markers
CD86

 

 

Natural-killer cells

Common natural-killer (NK) cell markers are CD56 and CD161.4 CD56bright and CD56dim NK cells in peripheral blood were found to display an activated effector phenotype that is similar in nature to moderate and severe COVID-19 disease.11 NK-cell activation was assessed by analysing expression of Ki-67, HLA-DR (human leukocyte antigen-DR) and CD69.11

 

T-cell markers

CD4+ T-αβ helper cell subsets include Th1, Th2, Th9, Th17, Th22 and regulatory T cells (Tregs), while CD8+ T-αβ cell subsets include cytotoxic T lymphocytes (Tc)1, Tc2, Tc9, Tc17 and CD8+ Tregs.12

 

 

T-Cell marker12Function
CD3Lineage markers
CD4
CD8
CD45
CCR4T-helper subsets
CCR6
CCR10
CXCR3
CXCR5
CD25Treg
CD127
FoxP3
CD45RAMaturation
CD45RO
CCR7
CD27
CD95
CD28
PD-1Exhaustion
CTLA-4
TGIT
CD69Activation
HLA-DR
CD107Cytotoxicity (upon activation)
Granzyme B
Perforin

 

Specifically, for Treg cells, CD3, CD4, CD25, CD127 and Foxp3 markers as the minimally required markers to define human Tregs to allow for robust and undisputable gating.13 Ki67 and CD45RA are highly recommended for recently activated/proliferated Tregs and discriminating between naïve and TCR-triggered Tregs, respectively.13

 

B-cell markers

B cells are identified as CD19pos and can be further classified as transitional, mature-naïve, memory, atypical memory, activated B cells and plasmablasts; flow cytometry markers allow recognition of these subsets.14  


 

B-cell marker14Function
CD19Lineage marker
CD20
CD27
IgD
CD38T-helper subsets
IgM
IgG
CD24

 

References
  1. Netea MG, Schlitzer A, Placek K, et al. Innate and Adaptive Immune Memory: an Evolutionary Continuum in the Host’s Response to Pathogens. Cell Host Microbe 2019;25:13-26.
  2. Tercan H, Riksen NP, Joosten LAB, et al. Trained Immunity: Long-Term Adaptation in Innate Immune Responses. Arterioscler Thromb Vasc Biol 2021;41:55–61.
  3. Delmonte OM, Fleisher TA. Flow cytometry: Surface markers and beyond. J Allergy Clin Immunol 2019;143:528-537.
  4. McKinnon KM. Flow Cytometry: An Overview. Curr Protoc Immunol 2018;120:5.1.1-5.1.11.
  5. Draxler DF, Madondo MT, Hanafi G, et al. A flowcytometric analysis to efficiently quantify multiple innate immune cells and T Cell subsets in human blood. Cytometry Part A 2017;91:336-350.
  6. Gustafson MP, Lin Y, Maas ML, et al. A method for identification and analysis of non-overlapping myeloid immunophenotypes in humans. PLoS One 2015;10:e0121546.
  7. Frafjord A, Skarshaug R, Hammarström C, et al. Antibody combinations for optimized staining of macrophages in human lung tumours. Scand J Immunol 2020;92.
  8. Liu B, Zhang M, Zhao J, et al. Imbalance of M1/M2 macrophages is linked to severity level of knee osteoarthritis. Exp Ther Med 2018;16(6):5009-5014.
  9. Amici SA, Young NA, Narvaez-Miranda J, et al. CD38 Is Robustly Induced in Human Macrophages and Monocytes in Inflammatory Conditions. Front Immunol 2018;9.
  10. Collin M, Bigley V. Human dendritic cell subsets: an update. Immunology 2018;154:3-20.
  11. Maucourant C, Filipovic I, Ponzetta A, et al. Natural killer cell immunotypes related to COVID-19 disease severity. Sci Immunol 2020;5.
  12. Mousset CM, Hobo W, Woestenenk R, et al. Comprehensive Phenotyping of T Cells Using Flow Cytometry. Cytometry Part A 2019;95:647-654.
  13. Santegoets SJAM, Dijkgraaf EM, Battaglia A, et al. Monitoring regulatory T cells in clinical samples: consensus on an essential marker set and gating strategy for regulatory T cell analysis by flow cytometry. Cancer Immunology, Immunotherapy 2015;64:1271-1286.
  14. Carsetti R, Corrente F, Capponi C, et al. Comprehensive phenotyping of human peripheral blood B lymphocytes in pathological conditions. Cytometry Part A 2022;101:140-149.
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