Abstract
A multicolor flow cytometry panel was designed and optimized to define the following nine mouse T cell subsets: Treg (CD3+ CD4+ CD8− FoxP3+), CD4+ T naïve (CD3+ CD4+ CD8−FoxP3− CD44int/low CD62L+), CD4+ T central memory (CD3+ CD4+ CD8− FoxP3− CD44high CD62L+), CD4+ T effector memory (CD3+ CD4+ CD8− FoxP3− CD44high CD62L−), CD4+ T EMRA (CD3+ CD4+ CD8− FoxP3− CD44int/low CD62L−), CD8+ T naïve (CD3+ CD8+ CD4− CD44int/low CD62L+), CD8+ T central memory (CD3+ CD8+ CD4− CD44high CD62L+), CD8+ T effector memory (CD3+ CD8+ CD4− CD44high CD62L−), and CD8+ T EMRA (CD3+ CD8+ CD4− CD44int/low CD62L−). In each T cell subset, a dual staining for Ki‐67 expression and DNA content was employed to distinguish the following cell cycle phases: G0 (Ki67−, with 2n DNA), G1 (Ki67+, with 2n DNA), and S‐G2/M (Ki67+, with 2n < DNA ≤ 4n). This panel was established for the analysis of mouse (C57BL/6J) spleen.
Keywords: cell cycle, DNA content, flow cytometry, Ki‐67, mouse T cells, spleen
1. BACKGROUND
The periodicity of cell proliferation is a fundamental aspect of biology that, for example, discriminates neural stem cells from terminally differentiated neurons. Likewise, it is a key feature of adaptive immunity that depends upon clonal expansion of primed T and B cells with appropriate antigen specificity, thereupon generating a vast progeny of short‐lived effector cells and a few long‐lived memory cells. There are two main subsets of T cells, CD4+ and CD8+ T cells, having a predominant helper and cytotoxic effector function, respectively. Maintenance of memory CD4+ and CD8+ T cells over time is a dynamic process, relying on a fine equilibrium among cell death, survival, and low level of homeostatic proliferation [1, 2]. Under steady‐state conditions, most T cells in the spleen of untreated mice are quiescent cells, although a tiny proportion divides, possibly reflecting immune responses to unknown environmental antigens and/or cytokine‐driven homeostatic proliferation. Such cell cycling in the absence of intentional immunization is more prominent among the so‐called memory‐phenotype T cells, that share a set of membrane markers with antigen‐primed T cells [3]. Furthermore, some Treg cells (a subset of CD4+ T cells with regulatory function defined by the expression of the transcription factor FoxP3 [4]) have an activated/proliferative phenotype, possibly reflecting continuous self‐renewal in adult mice [5].
In fact, memory‐phenotype T cells comprise a heterogeneous pool of cells of undefined antigen‐specificity, that are considered to include T cells primed by environmental antigens, as well as some antigen‐inexperienced T cells having self‐ligand‐ and/or cytokine‐dependent development [6, 7]. In C57BL/6 mice memory‐phenotype T cells have a high expression of CD44, an adhesion molecule that binds to hyaluronic acid, and can thus be distinguished from naïve‐phenotype T cells, that have an intermediate/low CD44 expression [6]. Similarly, in humans naïve and memory‐phenotype T cells can be identified by high and low expression of CD45RA, respectively [8].
Proliferative potential is one of the features that, together with lymph node (LN) homing capabilities, and effector function, differentiates additional subsets among memory T cells. Thus, central memory (CM) T cells have a LN homing receptor typically expressed by naïve T cells, specifically CD62L, also named L‐selectin, a glycan receptor [9], whereas effector memory (EM) T cells lack it [10]. According to this classification, originally proposed for human blood T cells using CCR7, the chemokine receptor for CCL19/CCL21, as a marker [11], T CM are LN‐homing cells with high potential to expand after stimulation, while T EM cells are tissue‐homing cells able to display rapid effector function [12, 13]. An additional subset, the T EMRA cells, comprises effector memory T cells that re‐acquire a naïve phenotype (CD45RA+ in humans, CD44int/low in mice). Based on this, the following four naïve/memory T cell subsets can be identified among mouse CD4+ and CD8+ T cells: CD44int/low CD62L+ naïve, CD44high CD62L+ CM, CD44high CD62L− EM, and CD44int/low CD62L− EMRA [10, 14].
While identification of memory T cells with high proliferative potential can impact the success of adoptive transfers [15], accurate measurement of in vivo proliferation is essential to track the dynamics of T cell responses [16]. Proliferation of mouse T cells has been measured by a few cytofluorimetric methods, that can be divided into “static”—that is, those which provide a snapshot of the cell cycle phases at the time of analysis—and “dynamic,” that is, those which give information on the proliferation that occurred over a few hours or days prior to the analysis. The most widely used “static” method relies on the Ki‐67 marker, an intranuclear protein that supports chromosome architecture organization, and nucleus and nucleolar assembly after cell division [17, 18]. However, Ki‐67 is expressed by cells in any phase of cell cycle (i.e., in G1, S, G2, M), while it is only low or absent in quiescent cells (i.e., in G0 state). The “dynamic” methods include carboxyfluorescein succinimidyl ester (CFSE) and Bromodeoxyuridine (BrdU) labelling, which identify proliferating cells that have undergone cell division and S‐phase, respectively [2]. We chose to combine Ki‐67 staining and DNA content analysis, thereby to distinguish between cells in G1 and those in S‐G2/M phases of cell cycle, a discrimination that is relevant to the proliferative fate of the cell. Indeed, cells in S are duplicating their DNA and are committed to proceed into G2/M and divide. In contrast, cells that are in G1 might proceed into S‐G2/M, return to G0, or stay in G1 for a prolonged period. Thus, Ki‐67+ cells might not be actively proliferating if they are in G1 phase or are returning to G0. For example, this might be the case for antigen‐specific T cell progeny at the end of clonal expansion [19].
In this OMIP, we offer a staining panel for ex vivo cell cycle analysis of CD4+ and CD8+ naïve/memory‐phenotype T cell subsets, and of Treg cells from mouse spleen, using Ki‐67/DNA dual staining to distinguish cells in G0, G1, and S‐G2/M (Table 1; Figure 1). Panel optimization and protocol details are reported in the online Supporting Information. We used standard markers for T cell subset identification. CD3 expression was used to identify T cells, and the mutually exclusive expression of CD4 and CD8 to distinguish CD4+ and CD8+ T cells, respectively. Treg cells were identified among CD4+ T cells based on their expression of the intranuclear protein FoxP3, and by this marker distinguished from conventional CD4+ T cells, that is, FoxP3− CD3+ CD4+ CD8− cells. CD4+ and CD8+ naïve/memory T cell subsets were subsequently identified among conventional CD4+ and CD8+ T cells, respectively. The four classical naïve/memory subsets were defined based on their CD62L and CD44 membrane phenotype (see above). For each T cell subset, cells in G0, G1, and S‐G2/M were discriminated based on Ki‐67 and DNA staining (Table 2; Figure 1).
TABLE 1.
Purpose | Cell cycle analysis of CD4 and CD8 naïve/memory T cell subsets, and of Treg cells |
Species | Mouse |
Cell types | Splenocytes |
Cross‐references | No similar OMIPs |
TABLE 2.
Fluorochrome | Specificity | Clone | Function |
---|---|---|---|
FITC | CD3 | 145‐2C11 | Pan T cell marker |
APC | CD44 | IM7 | NaÏve/Memory subset identification |
Alexa Fluor 700 | Ki‐67 | SolA15 | Quiescence/cell cycle |
eFluor 780 | Dead cells | N/A | Live/Dead cell discrimination |
Hoechst 33342 | DNA | N/A | DNA content/cell cycle |
PE | FoxP3 | FJK‐16s | Treg identification |
PE‐CF594 | CD4 | RM4‐5 | Helper T cell identification |
PE‐Cy7 | CD62L | MEL‐14 | NaÏve/Memory subset identification |
BV785 | CD8 | 53‐6.7 | Cytotoxic T cell identification |
Abbreviation: N/A, not applicable.
This OMIP can be exploited for in depth‐analysis of T cell cycle in conditions characterized by altered proportions, numbers and proliferative state of spleen T cell subsets, for example in aged mice having higher percentages of memory CD4+ and CD8+ T cells, with or without oligoclonal expansion [21, 22, 23]; in lymphopenic mice having compensatory T cell proliferation [24]; or in genetically modified mice with abnormal Treg cells representation [25]. Furthermore, this panel may be instrumental in identifying hitherto overlooked changes in Treg and/or naïve/memory T cell subset cycling in a variety of settings such as vaccination, infection, autoimmunity, and cancer.
2. SIMILARITY TO PUBLISHED OMIPS
The new ground trodden by this OMIP is the examination of cell cycle of naïve/memory CD4+ and CD8+ T cell subsets and of Treg cells by Ki‐67/DNA dual staining, with no similarities to other OMIPs.
OMIP‐031 and ‐032 examined naïve/memory T cells, with different purposes. OMIP‐031 used a combination of CD44, CD62L, CD27, CD45RA for T cell subset definition, plus a panel of activation and exhaustion markers, with the aim to analyze inhibitor checkpoint expression. OMIP‐032 was designed for assessing innate and adaptive immune subsets from mouse organs, including naïve/memory T cell subsets, that were identified based on CD44 and CD62L expression. OMIP‐032 did not include any analysis of proliferation or cell cycle.
CONFLICT OF INTEREST
A.C.H. is a board member and equity holder in ImmunoQure, AG., and Gamma Delta Therapeutics, and is an equity holder in Adaptate Biotherapeutics.
AUTHOR CONTRIBUTIONS
Ambra Natalini: Conceptualization (lead); data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); writing – review and editing (supporting). Sonia Simonetti: Conceptualization (supporting); formal analysis (supporting); investigation (supporting); methodology (supporting); writing – review and editing (supporting). Gabriele Favaretto: Data curation (supporting); formal analysis (supporting); methodology (supporting); writing – review and editing (supporting). Giovanna Peruzzi: Data curation (supporting); formal analysis (supporting); writing – review and editing (supporting). Fabrizio Antonangeli: Data curation (supporting); formal analysis (supporting); writing – review and editing (supporting). Angela Santoni: Writing – review and editing (supporting). Miguel Munoz‐Ruiz: Methodology (supporting); writing – review and editing (supporting). Adrian Hayday: Supervision (supporting); writing – review and editing (supporting). Francesca Di Rosa: Conceptualization (lead); supervision (lead); writing – original draft (lead).
PEER REVIEW
The peer review history for this article is available at https://publons.com/publon/10.1002/cyto.a.24509.
Supporting information
ACKNOWLEDGMENTS
The authors wish to thank Hefin Rhys (Flow Cytometry Science Technology Platform, The Francis Crick Institute, London UK) for discussion, and Antonio Di Virgilio (Istituto Superiore di Sanità, Rome, Italy) for technical help in the mouse facility. Open Access Funding provided by Consiglio Nazionale delle Ricerche within the CRUI‐CARE Agreement.
Natalini A, Simonetti S, Favaretto G, Peruzzi G, Antonangeli F, Santoni A, et al. OMIP‐079: Cell cycle of CD4 + and CD8 + naïve/memory T cell subsets, and of Treg cells from mouse spleen. Cytometry. 2021;99:1171–1175. 10.1002/cyto.a.24509
[Correction added on 22 October 2021, after first online publication: The last name of the author has been updated from “Munoz‐Ruiz” to “Muñoz‐Ruiz”.]
Funding information Consiglio Nazionale delle Ricerche, Grant/Award Number: STM‐2019; Italian Minister of Research and University (MIUR), Grant/Award Number: 2017K55HLC
Contributor Information
Ambra Natalini, Email: ambra.natalini@ibpm.cnr.it.
Francesca Di Rosa, Email: francesca.dirosa@cnr.it.
REFERENCES
- 1. Farber DL, Netea MG, Radbruch A, Rajewsky K, Zinkernagel RM. Immunological memory: lessons from the past and a look to the future. Nat Rev Immunol. 2016;16:124–8. [DOI] [PubMed] [Google Scholar]
- 2. Di Rosa F. Two niches in the bone marrow: a hypothesis on life‐long T cell memory. Trends Immunol. 2016;37:503–12. [DOI] [PubMed] [Google Scholar]
- 3. Tough DF, Sprent J. Turnover of naive‐ and memory‐phenotype T cells. J Exp Med. 1994;179:1127–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Lahl K, Loddenkemper C, Drouin C, Freyer J, Arnason J, Eberl G, et al. Selective depletion of Foxp3+ regulatory T cells induces a scurfy‐like disease. J Exp Med. 2007;204:57–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Rubtsov YP, Niec RE, Josefowicz S, Li L, Darce J, Mathis D, et al. Stability of the regulatory T cell lineage in vivo. Science. 2010;329:1667–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Sprent J, Surh CD. Normal T cell homeostasis: the conversion of naive cells into memory‐phenotype cells. Nat Immunol. 2011;131:478–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. White JT, Cross EW, Kedl RM. Antigen‐inexperienced memory CD8+ T cells: where they come from and why we need them. Nat Rev Immunol. 2017;17:391–400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Beverley PC. Functional analysis of human T cell subsets defined by CD45 isoform expression. Semin Immunol. 1992;4:35–41. [PubMed] [Google Scholar]
- 9. Ivetic A, Hoskins Green HL, Hart SJ. L‐selectin: a major regulator of leukocyte adhesion, migration and signaling. Front Immunol. 2019;10:1068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Del Zotto G, Principi E, Antonini F, Baratto S, Panicucci C, Bruno C, et al. Comprehensive phenotyping of peripheral blood T lymphocytes in healthy mice. Cytometry A. 2020;99(3):243–50. [DOI] [PubMed] [Google Scholar]
- 11. Sallusto F, Lenig D, Forster R, Lipp M, Lanzavecchia A. Two subsets of memory T lymphocytes with distinct homing potentials and effector functions. Nature. 1999;401:708–12. [DOI] [PubMed] [Google Scholar]
- 12. Weninger W, Crowley MA, Manjunath N, von Andrian UH. Migratory properties of naive, effector, and memory CD8(+) T cells. J Exp Med. 2001;194:953–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Sallusto F, Geginat J, Lanzavecchia A. Central memory and effector memory T cell subsets: function, generation, and maintenance. Annu Rev Immunol. 2004;22:745–63. [DOI] [PubMed] [Google Scholar]
- 14. Unsworth A, Anderson R, Haynes N, Britt K. OMIP‐032: two multi‐color immunophenotyping panels for assessing the innate and adaptive immune cells in the mouse mammary gland. Cytometry A. 2016;89:527–30. [DOI] [PubMed] [Google Scholar]
- 15. Harris NL, Watt V, Ronchese F, Le Gros G. Differential T cell function and fate in lymph node and nonlymphoid tissues. J Exp Med. 2002;195:317–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Borghans JA, de Boer RJ. Quantification of T‐cell dynamics: from telomeres to DNA labeling. Immunol Rev. 2007;216:35–47. [DOI] [PubMed] [Google Scholar]
- 17. Takagi M, Natsume T, Kanemaki MT, Imamoto N. Perichromosomal protein Ki67 supports mitotic chromosome architecture. Genes Cells. 2016;21:1113–24. [DOI] [PubMed] [Google Scholar]
- 18. Cuylen‐Haering S, Petrovic M, Hernandez‐Armendariz A, Schneider MWG, Samwer M, Blaukopf C, et al. Chromosome clustering by Ki‐67 excludes cytoplasm during nuclear assembly. Nature. 2020;587:285–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Simonetti S, Natalini A, Folgori A, Capone S, Nicosia A, Santoni A, et al. Antigen‐specific CD8 T cells in cell cycle circulate in the blood after vaccination. Scand J Immunol. 2019;89:e12735. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Muñoz‐Ruiz M, Pujol‐Autonell I, Rhys H, Long HM, Greco M, Peakman M, et al. Tracking immunodynamics by identification of S‐G2/M‐phase T cells in human peripheral blood. J Autoimmun. 2020;112:102466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Ernst DN, Hobbs MV, Torbett BE, Glasebrook AL, Rehse MA, Bottomly K, et al. Differences in the expression profiles of CD45RB, Pgp‐1, and 3G11 membrane antigens and in the patterns of lymphokine secretion by splenic CD4+ T cells from young and aged mice. J Immunol. 1990;145:1295–302. [PubMed] [Google Scholar]
- 22. Pinchuk LM, Filipov NM. Differential effects of age on circulating and splenic leukocyte populations in C57BL/6 and BALB/c male mice. Immun Ageing. 2008;5:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Clambey ET, White J, Kappler JW, Marrack P. Identification of two major types of age‐associated CD8 clonal expansions with highly divergent properties. Proc Natl Acad Sci U S A. 2008;105:12997–3002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. King C, Ilic A, Koelsch K, Sarvetnick N. Homeostatic expansion of T cells during immune insufficiency generates autoimmunity. Cell. 2004;117:265–77. [DOI] [PubMed] [Google Scholar]
- 25. Levine AG, Arvey A, Jin W, Rudensky AY. Continuous requirement for the TCR in regulatory T cell function. Nat Immunol. 2014;15:1070–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
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