- Email: [email protected]
Siglec-10 expression is up-regulated in activated human CD4+ T cells
Human Immunology xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Human Immunology journal homepage: www.elsevier.com/locate/humimm
Siglec-10 expression is up-regulated in activated human CD4+ T cells E. Bandala-Sanchez, N.G. Bediaga, G. Naselli, A.M. Neale, L.C. Harrison
⁎
Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Victoria, Australia Department of Medical Biology, University of Melbourne, Parkville 3052, Victoria, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: CD4+ T cell Activation Siglec-10 Protein RNA CD52
Most sialic acid–binding immunoglobulin-like lectins (Siglecs) suppress immune cell function but are expressed at low levels on human T cells. We found that soluble CD52 inhibited T cell signalling by ligating Siglec-10, but the presence of Siglec-10 on human T cells has been questioned. To address this concern, we examined the expression of Siglec-10 at the RNA and protein level in human CD4+ T cells. Analysis by RNAseq, qPCR and flow cytometry demonstrated that, in contrast to other Siglecs, after activation of CD4+ T cells Siglec-10 was selectively upregulated in a subset of cells also high for CD52 expression. This observation is consistent with a homeostatic role for Siglec-10 in human CD4+ T cells.
1. Introduction Sialic acid–binding immunoglobulin-like lectins (Siglecs) are cell surface receptors of the I-type lectin family with a variable number of extracellular domains [1]. Siglecs are divided into two classes: 1) CD33related Siglecs (Siglec-3 [CD33], -5, -6, -7, -8, -9, -10, -11, -14 and -16) and 2) conserved Siglecs (Siglec-1 [sialoadhesin], Siglec-2 [CD22], Siglec-4A [myelin-associated glycoprotein or MAG] and Siglec-15) [2,3]. The expression of Siglecs is mostly restricted to hematopoietic cells and cells of the immune system [1–4]. In general, Siglecs mediate cellular suppression via immunoreceptor tyrosine-based inhibitory motifs (ITIMs) or ITIM-like regions in their intracellular domains that are phosphorylated upon ligand binding [4–7]. Siglec-10 is immune system-restricted and highly expressed in peripheral blood leukocytes [8]. We implicated Siglec-10 in T-cell regulation when we discovered that a population of T cells with high expression of the glycophosphatidylinositol (GPI)-anchored glycoprotein CD52 exerted suppressor activity through the release of soluble CD52, which bound to Siglec-10 on activated CD4+ T cells [9]. Subsequently, we found that a prerequisite for binding to Siglec-10 is the interaction of soluble CD52 with the danger-associated molecular pattern molecule, HMGB1 [10]. Although we detected Siglec-10 by flow cytometry on activated CD4+ T cells this finding was unexpected because human T cells were not thought to express Siglec-10 [11]. However, Siglec-7 and -9 [12–15] and indeed recently Siglec-10 [16] have been detected on subsets of
activated human T cells. The presence of Siglec-10 on activated human CD4+ T cells has important implications for T cell homeostasis. Our findings [9,11] indicate that it limits the population expansion of activated CD4+ T cells and may protect against autoimmune disease. Here, we describe upregulation of Siglec-10 RNA and protein expression in human CD4+ T cells in response to their activation. 2. Material and methods 2.1. Donors Heparinised venous blood samples were obtained from nine deidentified young adult healthy donors with informed consent, through the Volunteer Blood Donor Registry of The Walter and Eliza Hall Institute of Medical Research (WEHI), following approval by WEHI and Melbourne Health Human Ethics Committees (Project 88/02). Peripheral blood mononuclear cells (PBMCs) were isolated on Ficoll/ Hypaque (Amersham Pharmacia, Little Chalfont, UK), washed in phosphate-buffered saline (PBS) and re-suspended in Iscove’s Modified Dulbecco’s Medium (IMDM) medium (Gibco, Massachusetts, USA) containing 5% pooled, heat-inactivated human serum (PHS; Australian Red Cross, Melbourne, Australia), 100 mM non-essential amino acids, 2 mM glutamine (Gibco, Massachusetts, USA) and 50 μM 2-mercaptoethanol (Sigma, Missouri, USA) (IP5 medium).
Abbreviations: Siglec, Sialic acid-binding immunoglobulin-like lectin; ITIM, Immunoreceptor tyrosine-based inhibitory motif; PBMCs, Peripheral blood mononuclear cells; IMDM, Iscove’s Modified Dulbecco’s Medium; PHS, Heat-inactivated pooled human serum; PBS, Phosphate-buffered saline; qPCR, Quantitative real-time PCR; CPM, Count per million mapped reads; CD52, Cluster of differentiation 52 ⁎ Corresponding author at: Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia. E-mail address: [email protected] (L.C. Harrison). https://doi.org/10.1016/j.humimm.2020.01.009 Received 11 September 2019; Received in revised form 9 January 2020; Accepted 24 January 2020 0198-8859/ © 2020 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.
Please cite this article as: E. Bandala-Sanchez, et al., Human Immunology, https://doi.org/10.1016/j.humimm.2020.01.009
Human Immunology xxx (xxxx) xxx–xxx
E. Bandala-Sanchez, et al.
Fig. 1. Siglec-10 gene and protein expression in resting and activated CD4+ T cells. A) Heat map of Siglec genes expressed in human CD4+ T cells, from two young healthy adult donors, resting and after 72 h activation with CD3/CD28 antibody Dynabeads. The Z‐score represents log‐counts per million scaled to have mean 0 and standard deviation, and red and blue indicate increased and decreased expression, respectively. Samples (resting and activated naïve CD4+ T cells) and genes were arranged according to complete linkage hierarchical clustering with the function coolmap in the limma package. The asterisk denotes statistically significant differential expression upon activation (false discovery rate < 0.05). B and C) Time course of Siglec10 RNA and protein expression after activation of human CD4+T cells from five young healthy adult donors with anti-CD3/ CD28 antibody Dynabeads. Results are shown as box and whisker plots for normalized Siglec-10 mRNA expression (B) and percent of cells expressing Siglec-10 protein (C). For RNA, expression of Siglec-10 was normalised to the expression of the ribosomal protein L13A gene (RPL13A) as the reference. Samples were run in triplicate. Percent of cells expressing Siglec-10 protein were analysed using Flowjo FACS analysis software and isotype control antibody. Boxes show the median and interquartile range (IQR) and the whiskers are IQRs × 1.5.
Antibodies used for sorting were: anti-TCR_PerCP-eFluor710 (Invitrogen, 46-9986-42), -CD4-APC (BD Pharmingen, 55534), -CD45RAFITC (BD Pharmingen, 556626), -CD25-PECy7 (BD Pharmingen, 557741), -CD14-PE (BioLegend, 367104), -CD16-APC-Cy7 (BD Pharmingen, 557758) and -HLA-DR_eFluor450 (Invitrogen, 48-9952-42).
2.2. RNA-seq analysis RNA was isolated from CD4+ T cells (resting and activated for 72 h with Dynabeads coated with CD3/CD28 antibodies (Gibco, Massachusetts, USA) at a bead/cell ratio of 1:2, from two healthy donors using the miRNeasy Micro Kit (Qiagen, Hilden, Germany). RNA libraries were prepared with an Illumina’s TruSeq Total Stranded RNA kit with Ribo-zero Gold (Illumina, California, USA) according to the manufacturer’s protocol. rRNA-depleted RNA was purified and then reverse transcribed into cDNA using SuperScript II reverse transcriptase (Invitrogen, California, USA). Total RNA-Seq libraries were sequenced on the Illumina NextSeq 500 platform to produce 2 × 75 paired-end reads. All samples were aligned to the human genome, build hg38, using the Rsubead aligner version 1.24.1 [17]. The numbers of fragments overlapping each Entrez gene were summarised using featureCounts [17] and NCBI RefSeq annotation. The gating strategy for flow sorting naïve CD4+ T cells is shown in Supplementary Fig. 1.
2.3. Quantitative PCR (qPCR) CD4+ T cells (1 × 105) were flow-sorted from each of five healthy donors and activated for 0, 24, 48 and 72 h with Dynabeads coated with CD3/CD28 antibodies. RNA was isolated from cells with a miRNeasy Micro Kit (Qiagen; Hilden, Germany). RNA (500 ng) was reversed transcribed using SuperScript® III Reverse Transcriptase (Invitrogen, California, USA) following the manufacturer’s instructions. Quantitative real-time PCR was performed in triplicate using TaqMan® Fast Advanced Master Mix (Thermo Fisher Scientific, Massachusetts, USA) and pre-designed TaqMan Gene Expression Assays (Thermo Fisher 2
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at any time point only a proportion of the cells may be activated or express markers of activation. Although only a minor proportion of T cells expressed Siglec-10 if expression was a dynamic process then this proportion may comprise different cells at different times during activation. Siglecs in general act as inhibitory receptors on myeloid and lymphoid cells [2] and in all likelihood are tightly regulated. Razi and Varki [19] found that human Siglec-2 (CD22) on human peripheral B cells is occupied by endogenous sialoglycans and that a minor proportion is unmasked upon B cell activation. However, by interacting with the B cell receptor via protein-tyrosine phosphatase SHP1 bound to its ITIM, Siglec-2 inhibits B cell function more broadly [20]. T cell activation also induces changes in the nature and expression of surface sialoglycans and the Siglecs that they ligate [21]. If Siglecs on T cells are occupied by endogenous ligands in cis they could be unmasked and accessible to detection by antibodies only upon cell activation [21]. In light of the present findings, this process may occur only in a minor proportion of cells at any one time. Our previous studies on T cells [9,11] indicate that ligation of Siglec-10 by the CD52-HMGB1 complex inhibits phosphorylation of tyrosines in T cell receptor-associated Lck and Zap70 kinases, to inhibit T cell signalling by an ITIM-based mechanism similar to Siglec-2 in B cells [20]. Further studies are required to determine if Siglec-10 is unmasked and transiently expressed on only a minor proportion of cells at any one time, and how this leads to the observed inhibition of T cell function overall.
Scientific, Massachusetts, USA). The expression of Siglec-10 mRNA was quantified relative to expression of ribosomal protein L13A gene using the 2-ΔCt method. 2.4. Siglec-10 protein expression PBMCs from seven healthy donors were cultured in IP5 medium in the presence of Dynabeads coated with anti-CD3/CD28 antibodies for 0, 24, 48, and 72 h. Cells (2 × 105) from five of these donors were then incubated with anti-CD4-PE (RPA-T4; BD Biosciences, USA) and antiSiglec-10-APC (5G6; BioLegend, USA). Cells from two other donors were incubated with anti-CD4-Pacific Blue (RPA-T4; BD Biosciences, USA) anti-CD52-PE (CF1D12; Caltag, USA), anti-CD25-PE-Cy7 (BD Pharmingen, USA) and anti-Siglec-10-APC antibodies at 4 °C for 20 min in FACS buffer (PBS with 2 mM EDTA, 0.05% sodium azide, 0.25% BSA), followed by three washes in the same buffer. Propidium iodide (2 μg/ml) was added to the samples to identify dead cells immediately before analysis in a FACSVerse and Cytek® Aurora flow cytometers. Data were analyzed with FlowJo 10.0.6 software (Tree Star Inc.). 2.5. Statistics Differential expression analysis of the RNA-seq was undertaken with the limma [18] software package. Any gene that did not achieve a count per million mapped reads (CPM) greater than 1.5 in at least two samples was deemed to be unexpressed and removed from the analysis, as were all genes with no current annotation. Compositional differences between libraries were normalized using the trimmed mean of log expression ratios method (TMM). All counts were then transformed to log2-CPM with associated precision weights using voom. Differential expression between all cell types was assessed using linear models and robust empirical Bayes moderated t-statistics. P-values were adjusted to control the false discovery rate (FDR) below 5% using the Benjamini and Hochberg method. Heatmaps of the filtered and normalized logCPM values for Siglec genes were plotted with the coolmap function from the limma package [18]. Statistics were calculated with the nonparametric unpaired Wilcoxon rank test.
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was supported by an Australian National Health and Medical Research Council (NHMRC) Program Grant (10373210). LCH was the recipient of a NHMRC Senior Principal Research Fellowship (1080887).
3. Results and discussion Authors contributions Prior to our demonstration that soluble CD52 inhibits activated human CD4+ T cells by binding to Siglec-10 [9,10] primary human T cells were considered to express very little or no Siglec-10 [11]. Expression of Siglec genes in primary human T cells has not been documented and therefore we initially performed genome-wide transcriptional profiling in human resting and activated CD4+ T cells. We found that of the 15 members of the human Siglec family transcripts for Siglec-2, 9, 10, 14 15 and 16 were expressed in CD4+ T cells, with a selective increase upon activation only in Siglec-10 (Fig. 1A). As expected, T cell activation genes were also upregulated, e.g. IL2RA (CD25) by 79-fold, TNFRSF9 (CD137) by 125 -fold and CD38 by 2-fold (data not shown). Upregulation of Siglec-10 RNA was confirmed by qPCR (Fig. 1B). In a time-course analysis, Siglec-10 expression was low in resting CD4+ T cells but increased maximally by 48 h after activation, at both the mRNA (Fig. 1B) and protein (Fig. 1C and Supplementary Fig. 2B) levels. By flow cytometry, upregulation of Siglec-10 expression was confined to a subset of CD4+ T cells that also highly expressed CD52. Expression of Siglec-10 and Siglec-G (the murine homologue of Siglec10) was recently reported on a small proportion of T cells [16], similar to Siglecs-7 and -9 [12–15]. Why the expression of these Siglecs on activated T cells and also of Siglec 2 (CD22) on activated B cells [19,20] is apparently restricted to a low frequency of cells is unclear. Depending on conditions (e.g. concentration and duration of the stimulus, presence of accessory cells, concentration of IL-2), mitogenic stimulation may eventually lead to activation of the majority of human T cells. However,
EB-S, NGB and LCH designed the study. EB-S, GN and AMN performed most of the experiments. EB-S, NGB and LCH analysed data and drafted the manuscript. All authors discussed and commented on the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.humimm.2020.01.009. References [1] L.D. Powell, A. Varki, I-type lectins, J. Biol. Chem. 270 (1995) 14243–14246, https://doi.org/10.1074/jbc.270.24.14243. [2] P.R. Crocker, J.C. Paulson, A. Varki, Siglecs and their roles in the immune system, Nat. Rev. Immunol. 7 (4) (2007) 255–266, https://doi.org/10.1038/nri2056. [3] F. Schwarz, J.J. Fong, A. Varki, Human-specific evolutionary changes in the biology of Siglecs, Adv. Exp. Med. Biol. 842 (2015) 1–16, https://doi.org/10.1007/978-3319-11280-0_1. [4] M.S. Macauley, P.R. Crocker, J.C. Paulson, Siglec-mediated regulation of immune cell function in disease, Nat. Rev. Immunol. 14 (10) (2014) 653–666, https://doi. org/10.1038/nri3737. [5] C. Ding, L. Yan, Y. Wang, B.K. Park, C.-Y. Wang, P. Zheng, Y. Liu, Siglec-G limits the size of B1a B cell lineage by down-regulating NFkappaB activation, PLoS One 2 (10) (2007) e997, https://doi.org/10.1371/journal.pone.0000997. [6] A. Hoffmann, S. Kerr, J. Jellusova, J. Zhang, F. Weisel, U. Wellmann, T.H. Winkler, B. Kneitz, P.R. Crocker, L. Nitschke, Siglec-G is a B1 cell-inhibitory receptor that controls expansion and calcium signaling of the B1 cell population, Nat. Immunol. 8
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1158/2326-6066.CIR-18-0505. [14] M.A. Stanczak, S.S. Siddiqui, M.P. Trefny, D.S. Thommen, K.F. Boligan, S. Von Gunten, A. Tzankov, et al., Self-associated molecular patters mediate cancer immune evasion by engaging Siglecs on T cells, J. Clin. Invest. 128 (11) (2018) 4912–4923, https://doi.org/10.1172/JCI120612. [15] G. Nicoll, J. Ni, D. Liu, P. Klenerman, J. Munday, S. Dubock, M.G. Mattei, P.R. Crocker, Identification and characterization of a novel Siglec, Siglec-7, expressed by human natural killer cells and monocytes, J. Biol. Chem. 274 (48) (1999) 34089–34095, https://doi.org/10.1074/jbc.274.48.34089. [16] Y. Liao, G.K. Smyth, W. Shi, featureCounts: an efficient general purpose program for assigning sequence reads to genomic features, Bioinformatics 30 (2014) 923–930, https://doi.org/10.1093/bioinformatics/btt656. [17] M.E. Ritchie, B. Phipson, D. Wu, Y. Hu, C.W. Law, W. Shi, G.K. Smyth, limma powers differential expression analyses for RNA-sequencing and microarray studies, Nucleic Acids Res. 43 (2015) e47, , https://doi.org/10.1093/nar/gkv007. [18] T. Toubai, C. Rossi, K. Oravecz-Wilson, C. Zajac, C. Liu, T. Braun, H. Fujiwara, J. Wu, Y. Sun, S. Brabbs, H. Tamaki, J. Magenau, P. Zheng, Y. Liu, P. Reddy, SiglecG represses DAMP-mediated effects on T cells, JCI Insight 2 (14) (2017) e92293, , https://doi.org/10.1172/jci.insight.92293. [19] N. Razi, A. Varki, Masking and unmasking of the sialic acid-binding lectin activity of CD22 (Siglec-2) on B lymphocytes, Proc. Natl. Acad. Sci. USA 95 (1998) 7469–7474, https://doi.org/10.1073/pnas.95.13.7469. [20] S.J. Meyer, A.T. Linder, C. Brandl, L. Nitschke, B cell Siglecs-news on signaling and its interplay with ligand binding, Front. Immunol. 3 (9) (2018) 2820, https://doi. org/10.3389/fimmu.2018.02820 eCollection 2018. [21] Y. Naito-Matsui, S. Takada, Y. Kano, T. Iyoda, M. Sugai, A. Shimizu, K. Inaba, L. Nitschke, T. Tsubata, S. Oka, Y. Kozutsumi, H. Takematsu, Functional evaluation of activation-dependent alterations in the sialoglycan composition of T cells, J. Biol. Chem. 289 (3) (2014) 1564–1579, https://doi.org/10.1074/jbc.M113.523753.
(7) (2007) 695–704, https://doi.org/10.1038/ni1480. [7] G. Whitney, S. Wang, H. Chang, K.Y. Chen, P. Lu, X.D. Zhou, W.P. Yang, M. Mckinno, M. Longphre, A new Siglec family member, Siglec-10, is expressed in cells of the immune system and has signalling properties similar to CD33, Eur. J. Biochem. 269 (23) (2001) 6083–6096, https://doi.org/10.1046/j.0014-2956.2001. 02543.x. [8] F. Kitzig, A. Martinez-Barriocanal, M. Lopez-Botet, J. Sayos, Cloning of two new splice variants of Siglec-10 and mapping of the interaction between Siglec-10 and SHP-1, Biochem. Biophys. Res. Commun. 296 (2) (2002) 355–362, https://doi.org/ 10.1016/s0006-291x(02)00885-9. [9] E. Bandala-Sanchez, Y. Zhang, S. Reinwald, J.A. Dromey, B.-H. Lee, J. Qian, R.M. Böhmer, L.C. Harrison, T cell regulation mediated by interaction of soluble CD52 with the inhibitory receptor Siglec-10, Nat. Immunol. 14 (7) (2013) 741–748, https://doi.org/10.1038/ni.2610. [10] E. Bandala-Sanchez, N.G. Bediaga, E.D. Goddard-Borger, K. Ngui, G. Naselli, N.L. Stone, A.L. Neale, L.A. Pearce, A. Wardak, P. Czabotar, T. Haselhorst, A. Maggioni, L.A. Hartley-Tassell, T.E. Adams, L.C. Harrison, CD52 glycan binds the pro-inflammatory B box of HMGB1 to engage the Siglec-10 receptor and suppress Tcell function, Proc. Natl. Acad. Sci. USA 115 (30) (2018) 7783–7788, https://doi. org/10.1073/pnas.1722056115. [11] D.H. Nguyen, N. Hurtado-Ziola, P. Gagneux, A. Varki, Loss of Siglec expression on T lymphocytes during human evolution, Proc. Natl. Acad. Sci. USA 103 (20) (2006) 7765–77770, https://doi.org/10.1073/pnas.0510484103. [12] Y. Ikehara, S.K. Ikehara, J.C. Paulson, Negative regulation of T cell receptor signaling by Siglec-7 (p70/AIRM) and Siglec-9, 41, J. Biol. Chem. 279 (2004) 43117–43125, https://doi.org/10.1074/jbc.M403538200. [13] Q. Haas, K.F. Boligan, C. Jandus, C. Schneider, Siglec-9 regulates an effector memory CD8+ T cell subset that congregates in the melanoma tumor microenvironment, Cancer Immunol. Res. 7 (5) (2019) 707–718, https://doi.org/10.
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Contents lists available at ScienceDirect
Human Immunology journal homepage: www.elsevier.com/locate/humimm
Siglec-10 expression is up-regulated in activated human CD4+ T cells E. Bandala-Sanchez, N.G. Bediaga, G. Naselli, A.M. Neale, L.C. Harrison
⁎
Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Victoria, Australia Department of Medical Biology, University of Melbourne, Parkville 3052, Victoria, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: CD4+ T cell Activation Siglec-10 Protein RNA CD52
Most sialic acid–binding immunoglobulin-like lectins (Siglecs) suppress immune cell function but are expressed at low levels on human T cells. We found that soluble CD52 inhibited T cell signalling by ligating Siglec-10, but the presence of Siglec-10 on human T cells has been questioned. To address this concern, we examined the expression of Siglec-10 at the RNA and protein level in human CD4+ T cells. Analysis by RNAseq, qPCR and flow cytometry demonstrated that, in contrast to other Siglecs, after activation of CD4+ T cells Siglec-10 was selectively upregulated in a subset of cells also high for CD52 expression. This observation is consistent with a homeostatic role for Siglec-10 in human CD4+ T cells.
1. Introduction Sialic acid–binding immunoglobulin-like lectins (Siglecs) are cell surface receptors of the I-type lectin family with a variable number of extracellular domains [1]. Siglecs are divided into two classes: 1) CD33related Siglecs (Siglec-3 [CD33], -5, -6, -7, -8, -9, -10, -11, -14 and -16) and 2) conserved Siglecs (Siglec-1 [sialoadhesin], Siglec-2 [CD22], Siglec-4A [myelin-associated glycoprotein or MAG] and Siglec-15) [2,3]. The expression of Siglecs is mostly restricted to hematopoietic cells and cells of the immune system [1–4]. In general, Siglecs mediate cellular suppression via immunoreceptor tyrosine-based inhibitory motifs (ITIMs) or ITIM-like regions in their intracellular domains that are phosphorylated upon ligand binding [4–7]. Siglec-10 is immune system-restricted and highly expressed in peripheral blood leukocytes [8]. We implicated Siglec-10 in T-cell regulation when we discovered that a population of T cells with high expression of the glycophosphatidylinositol (GPI)-anchored glycoprotein CD52 exerted suppressor activity through the release of soluble CD52, which bound to Siglec-10 on activated CD4+ T cells [9]. Subsequently, we found that a prerequisite for binding to Siglec-10 is the interaction of soluble CD52 with the danger-associated molecular pattern molecule, HMGB1 [10]. Although we detected Siglec-10 by flow cytometry on activated CD4+ T cells this finding was unexpected because human T cells were not thought to express Siglec-10 [11]. However, Siglec-7 and -9 [12–15] and indeed recently Siglec-10 [16] have been detected on subsets of
activated human T cells. The presence of Siglec-10 on activated human CD4+ T cells has important implications for T cell homeostasis. Our findings [9,11] indicate that it limits the population expansion of activated CD4+ T cells and may protect against autoimmune disease. Here, we describe upregulation of Siglec-10 RNA and protein expression in human CD4+ T cells in response to their activation. 2. Material and methods 2.1. Donors Heparinised venous blood samples were obtained from nine deidentified young adult healthy donors with informed consent, through the Volunteer Blood Donor Registry of The Walter and Eliza Hall Institute of Medical Research (WEHI), following approval by WEHI and Melbourne Health Human Ethics Committees (Project 88/02). Peripheral blood mononuclear cells (PBMCs) were isolated on Ficoll/ Hypaque (Amersham Pharmacia, Little Chalfont, UK), washed in phosphate-buffered saline (PBS) and re-suspended in Iscove’s Modified Dulbecco’s Medium (IMDM) medium (Gibco, Massachusetts, USA) containing 5% pooled, heat-inactivated human serum (PHS; Australian Red Cross, Melbourne, Australia), 100 mM non-essential amino acids, 2 mM glutamine (Gibco, Massachusetts, USA) and 50 μM 2-mercaptoethanol (Sigma, Missouri, USA) (IP5 medium).
Abbreviations: Siglec, Sialic acid-binding immunoglobulin-like lectin; ITIM, Immunoreceptor tyrosine-based inhibitory motif; PBMCs, Peripheral blood mononuclear cells; IMDM, Iscove’s Modified Dulbecco’s Medium; PHS, Heat-inactivated pooled human serum; PBS, Phosphate-buffered saline; qPCR, Quantitative real-time PCR; CPM, Count per million mapped reads; CD52, Cluster of differentiation 52 ⁎ Corresponding author at: Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia. E-mail address: [email protected] (L.C. Harrison). https://doi.org/10.1016/j.humimm.2020.01.009 Received 11 September 2019; Received in revised form 9 January 2020; Accepted 24 January 2020 0198-8859/ © 2020 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.
Please cite this article as: E. Bandala-Sanchez, et al., Human Immunology, https://doi.org/10.1016/j.humimm.2020.01.009
Human Immunology xxx (xxxx) xxx–xxx
E. Bandala-Sanchez, et al.
Fig. 1. Siglec-10 gene and protein expression in resting and activated CD4+ T cells. A) Heat map of Siglec genes expressed in human CD4+ T cells, from two young healthy adult donors, resting and after 72 h activation with CD3/CD28 antibody Dynabeads. The Z‐score represents log‐counts per million scaled to have mean 0 and standard deviation, and red and blue indicate increased and decreased expression, respectively. Samples (resting and activated naïve CD4+ T cells) and genes were arranged according to complete linkage hierarchical clustering with the function coolmap in the limma package. The asterisk denotes statistically significant differential expression upon activation (false discovery rate < 0.05). B and C) Time course of Siglec10 RNA and protein expression after activation of human CD4+T cells from five young healthy adult donors with anti-CD3/ CD28 antibody Dynabeads. Results are shown as box and whisker plots for normalized Siglec-10 mRNA expression (B) and percent of cells expressing Siglec-10 protein (C). For RNA, expression of Siglec-10 was normalised to the expression of the ribosomal protein L13A gene (RPL13A) as the reference. Samples were run in triplicate. Percent of cells expressing Siglec-10 protein were analysed using Flowjo FACS analysis software and isotype control antibody. Boxes show the median and interquartile range (IQR) and the whiskers are IQRs × 1.5.
Antibodies used for sorting were: anti-TCR_PerCP-eFluor710 (Invitrogen, 46-9986-42), -CD4-APC (BD Pharmingen, 55534), -CD45RAFITC (BD Pharmingen, 556626), -CD25-PECy7 (BD Pharmingen, 557741), -CD14-PE (BioLegend, 367104), -CD16-APC-Cy7 (BD Pharmingen, 557758) and -HLA-DR_eFluor450 (Invitrogen, 48-9952-42).
2.2. RNA-seq analysis RNA was isolated from CD4+ T cells (resting and activated for 72 h with Dynabeads coated with CD3/CD28 antibodies (Gibco, Massachusetts, USA) at a bead/cell ratio of 1:2, from two healthy donors using the miRNeasy Micro Kit (Qiagen, Hilden, Germany). RNA libraries were prepared with an Illumina’s TruSeq Total Stranded RNA kit with Ribo-zero Gold (Illumina, California, USA) according to the manufacturer’s protocol. rRNA-depleted RNA was purified and then reverse transcribed into cDNA using SuperScript II reverse transcriptase (Invitrogen, California, USA). Total RNA-Seq libraries were sequenced on the Illumina NextSeq 500 platform to produce 2 × 75 paired-end reads. All samples were aligned to the human genome, build hg38, using the Rsubead aligner version 1.24.1 [17]. The numbers of fragments overlapping each Entrez gene were summarised using featureCounts [17] and NCBI RefSeq annotation. The gating strategy for flow sorting naïve CD4+ T cells is shown in Supplementary Fig. 1.
2.3. Quantitative PCR (qPCR) CD4+ T cells (1 × 105) were flow-sorted from each of five healthy donors and activated for 0, 24, 48 and 72 h with Dynabeads coated with CD3/CD28 antibodies. RNA was isolated from cells with a miRNeasy Micro Kit (Qiagen; Hilden, Germany). RNA (500 ng) was reversed transcribed using SuperScript® III Reverse Transcriptase (Invitrogen, California, USA) following the manufacturer’s instructions. Quantitative real-time PCR was performed in triplicate using TaqMan® Fast Advanced Master Mix (Thermo Fisher Scientific, Massachusetts, USA) and pre-designed TaqMan Gene Expression Assays (Thermo Fisher 2
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at any time point only a proportion of the cells may be activated or express markers of activation. Although only a minor proportion of T cells expressed Siglec-10 if expression was a dynamic process then this proportion may comprise different cells at different times during activation. Siglecs in general act as inhibitory receptors on myeloid and lymphoid cells [2] and in all likelihood are tightly regulated. Razi and Varki [19] found that human Siglec-2 (CD22) on human peripheral B cells is occupied by endogenous sialoglycans and that a minor proportion is unmasked upon B cell activation. However, by interacting with the B cell receptor via protein-tyrosine phosphatase SHP1 bound to its ITIM, Siglec-2 inhibits B cell function more broadly [20]. T cell activation also induces changes in the nature and expression of surface sialoglycans and the Siglecs that they ligate [21]. If Siglecs on T cells are occupied by endogenous ligands in cis they could be unmasked and accessible to detection by antibodies only upon cell activation [21]. In light of the present findings, this process may occur only in a minor proportion of cells at any one time. Our previous studies on T cells [9,11] indicate that ligation of Siglec-10 by the CD52-HMGB1 complex inhibits phosphorylation of tyrosines in T cell receptor-associated Lck and Zap70 kinases, to inhibit T cell signalling by an ITIM-based mechanism similar to Siglec-2 in B cells [20]. Further studies are required to determine if Siglec-10 is unmasked and transiently expressed on only a minor proportion of cells at any one time, and how this leads to the observed inhibition of T cell function overall.
Scientific, Massachusetts, USA). The expression of Siglec-10 mRNA was quantified relative to expression of ribosomal protein L13A gene using the 2-ΔCt method. 2.4. Siglec-10 protein expression PBMCs from seven healthy donors were cultured in IP5 medium in the presence of Dynabeads coated with anti-CD3/CD28 antibodies for 0, 24, 48, and 72 h. Cells (2 × 105) from five of these donors were then incubated with anti-CD4-PE (RPA-T4; BD Biosciences, USA) and antiSiglec-10-APC (5G6; BioLegend, USA). Cells from two other donors were incubated with anti-CD4-Pacific Blue (RPA-T4; BD Biosciences, USA) anti-CD52-PE (CF1D12; Caltag, USA), anti-CD25-PE-Cy7 (BD Pharmingen, USA) and anti-Siglec-10-APC antibodies at 4 °C for 20 min in FACS buffer (PBS with 2 mM EDTA, 0.05% sodium azide, 0.25% BSA), followed by three washes in the same buffer. Propidium iodide (2 μg/ml) was added to the samples to identify dead cells immediately before analysis in a FACSVerse and Cytek® Aurora flow cytometers. Data were analyzed with FlowJo 10.0.6 software (Tree Star Inc.). 2.5. Statistics Differential expression analysis of the RNA-seq was undertaken with the limma [18] software package. Any gene that did not achieve a count per million mapped reads (CPM) greater than 1.5 in at least two samples was deemed to be unexpressed and removed from the analysis, as were all genes with no current annotation. Compositional differences between libraries were normalized using the trimmed mean of log expression ratios method (TMM). All counts were then transformed to log2-CPM with associated precision weights using voom. Differential expression between all cell types was assessed using linear models and robust empirical Bayes moderated t-statistics. P-values were adjusted to control the false discovery rate (FDR) below 5% using the Benjamini and Hochberg method. Heatmaps of the filtered and normalized logCPM values for Siglec genes were plotted with the coolmap function from the limma package [18]. Statistics were calculated with the nonparametric unpaired Wilcoxon rank test.
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was supported by an Australian National Health and Medical Research Council (NHMRC) Program Grant (10373210). LCH was the recipient of a NHMRC Senior Principal Research Fellowship (1080887).
3. Results and discussion Authors contributions Prior to our demonstration that soluble CD52 inhibits activated human CD4+ T cells by binding to Siglec-10 [9,10] primary human T cells were considered to express very little or no Siglec-10 [11]. Expression of Siglec genes in primary human T cells has not been documented and therefore we initially performed genome-wide transcriptional profiling in human resting and activated CD4+ T cells. We found that of the 15 members of the human Siglec family transcripts for Siglec-2, 9, 10, 14 15 and 16 were expressed in CD4+ T cells, with a selective increase upon activation only in Siglec-10 (Fig. 1A). As expected, T cell activation genes were also upregulated, e.g. IL2RA (CD25) by 79-fold, TNFRSF9 (CD137) by 125 -fold and CD38 by 2-fold (data not shown). Upregulation of Siglec-10 RNA was confirmed by qPCR (Fig. 1B). In a time-course analysis, Siglec-10 expression was low in resting CD4+ T cells but increased maximally by 48 h after activation, at both the mRNA (Fig. 1B) and protein (Fig. 1C and Supplementary Fig. 2B) levels. By flow cytometry, upregulation of Siglec-10 expression was confined to a subset of CD4+ T cells that also highly expressed CD52. Expression of Siglec-10 and Siglec-G (the murine homologue of Siglec10) was recently reported on a small proportion of T cells [16], similar to Siglecs-7 and -9 [12–15]. Why the expression of these Siglecs on activated T cells and also of Siglec 2 (CD22) on activated B cells [19,20] is apparently restricted to a low frequency of cells is unclear. Depending on conditions (e.g. concentration and duration of the stimulus, presence of accessory cells, concentration of IL-2), mitogenic stimulation may eventually lead to activation of the majority of human T cells. However,
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