Id2 expression delineates differential checkpoints in the genetic program of CD8α + and CD103 + dendritic cell lineages
2011; Springer Nature; Volume: 30; Issue: 13 Linguagem: Inglês
10.1038/emboj.2011.163
ISSN1460-2075
AutoresJacob T. Jackson, Yifang Hu, Ruijie Liu, Frédérick Masson, Angela D’Amico, Sebastian Carotta, Annie Xin, Mary Camilleri, Adele M. Mount, Axel Kallies, Li Wu, Gordon K. Smyth, Stephen L. Nutt, Gabrielle T. Belz,
Tópico(s)T-cell and B-cell Immunology
ResumoArticle17 May 2011Open Access Id2 expression delineates differential checkpoints in the genetic program of CD8α+ and CD103+ dendritic cell lineages Jacob T Jackson Jacob T Jackson Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Yifang Hu Yifang Hu Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Ruijie Liu Ruijie Liu Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Frederick Masson Frederick Masson Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Angela D'Amico Angela D'Amico Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Sebastian Carotta Sebastian Carotta Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Annie Xin Annie Xin Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Mary J Camilleri Mary J Camilleri Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Adele M Mount Adele M Mount Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Axel Kallies Axel Kallies Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Li Wu Li Wu Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Gordon K Smyth Gordon K Smyth Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Stephen L Nutt Stephen L Nutt Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Gabrielle T Belz Corresponding Author Gabrielle T Belz Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Jacob T Jackson Jacob T Jackson Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Yifang Hu Yifang Hu Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Ruijie Liu Ruijie Liu Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Frederick Masson Frederick Masson Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Angela D'Amico Angela D'Amico Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Sebastian Carotta Sebastian Carotta Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Annie Xin Annie Xin Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Mary J Camilleri Mary J Camilleri Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Adele M Mount Adele M Mount Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Search for more papers by this author Axel Kallies Axel Kallies Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Li Wu Li Wu Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Gordon K Smyth Gordon K Smyth Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Stephen L Nutt Stephen L Nutt Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Gabrielle T Belz Corresponding Author Gabrielle T Belz Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia Search for more papers by this author Author Information Jacob T Jackson1, Yifang Hu2, Ruijie Liu2, Frederick Masson1, Angela D'Amico1, Sebastian Carotta1, Annie Xin1,3, Mary J Camilleri1, Adele M Mount1, Axel Kallies1,3, Li Wu1,3, Gordon K Smyth2,4, Stephen L Nutt1,3 and Gabrielle T Belz 1,3 1Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia 2Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia 3Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia 4Department of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia *Corresponding author. Molecular Immunology Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Melbourne, Victoria 3052, Australia. Tel.: +61 3 9345 2544; Fax: +61 3 9347 0852; E-mail: [email protected] The EMBO Journal (2011)30:2690-2704https://doi.org/10.1038/emboj.2011.163 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Dendritic cells (DCs) have critical roles in the induction of the adaptive immune response. The transcription factors Id2, Batf3 and Irf-8 are required for many aspects of murine DC differentiation including development of CD8α+ and CD103+ DCs. How they regulate DC subset specification is not completely understood. Using an Id2-GFP reporter system, we show that Id2 is broadly expressed in all cDC subsets with the highest expression in CD103+ and CD8α+ lineages. Notably, CD103+ DCs were the only DC able to constitutively cross-present cell-associated antigens in vitro. Irf-8 deficiency affected loss of development of virtually all conventional DCs (cDCs) while Batf3 deficiency resulted in the development of Sirp-α− DCs that had impaired survival. Exposure to GM-CSF during differentiation induced expression of CD103 in Id2-GFP+ DCs. It did not restore cross-presenting capacity to Batf3−/− or CD103−Sirp-α−DCs in vitro. Thus, Irf-8 and Batf3 regulate distinct stages in DC differentiation during the development of cDCs. Genetic mapping DC subset differentiation using Id2-GFP may have broad implications in understanding the interplay of DC subsets during protective and pathological immune responses. Irf8: 5′-CAG GAG GTG GAT GCT TCC ATC-3′5′-GCA CAG CGT AAC CTC GTC TTC-3′; Batf3: 5′-CAG AGC CCC AAG GAC GATG-3′5′-GCA CAA AGT TCA TAG GAC ACA GC-3′; Id2: 5′-ATG AAA GCC TTC AGT CCG GTG-3′5′-AGC AGA CTC ATC GGG TCGT-3′; Hprt: 5′-GGG GGC TAT AAG TTC TTT GC-3′5′-TCC AAC ACT TCG AGA GGT CC-3′; GFP: 5′-AGT CCG CCC TGA GCA AAG A-3′5′-TCA CGA ACT CCA GCA GGA CC-3′. Introduction CD11c+ dendritic cells (DCs) are essential in presenting antigen to initiate T-cell responses. They have critical roles in immunity because of their ability to recognize invading pathogens and mobilize immune cells to combat them. DCs can be categorized into a number of different subsets that largely reflect the pattern of expression of cell surface molecules and functional specializations (Geissmann et al, 2010; Steinman and Idoyaga, 2010). One major division of DCs is conventional DCs (cDCs) and plasmacytoid DCs (pDCs). In murine spleen, cDCs can be further divided into CD8α+ DCs, CD4+ DCs and CD8α−CD4− (termed double-negative, DN) DCs. DCs enter the spleen and lymph nodes (LNs) through the blood as either mature pDCs or immature precursors of cDCs known as pro-DCs (reviewed in Liu and Nussenzweig (2010)). LNs contain multiple populations of DCs which include CD8α+ DCs and CD8α− DCs, together with DCs that migrate from the peripheral tissues (tissue-derived DCs). CD8α+ DCs contribute significantly to CD8+ T-cell activation via presentation of exogenous (den Haan and Bevan, 2002) or pathogen-derived antigens (Allan et al, 2003; Belz et al, 2004) while CD8α− DCs preferentially drive the activation of CD4+ T cells (Allenspach et al, 2008; Mount et al, 2008). Tissue-derived DCs differ depending on the type of peripheral tissues they drain. Langerhans cells (LCs) and the dermal DCs are found in skin while migratory tissue-derived CD103+ DCs originate from cutaneous and mucosal tissues such as the lamina propria of respiratory and gastrointestinal tracts (reviewed in Geissmann et al (2010)). The latter two DC subsets have a critical role in transporting antigens from body surfaces to LNs such that DCs resident in the LN can gain access to antigens (Liu and Nussenzweig, 2010). Although a number of different DC subsets have been described, understanding how diverse DC subsets develop from a common progenitor is limited. Several factors have been identified as highly expressed in cDCs. These include inhibitor of DNA binding (Id)-2, interferon regulatory protein (Irf)-2 (Honda et al, 2004; Ichikawa et al, 2004), Irf-4 (Suzuki et al, 2004) and Irf-8 (Schiavoni et al, 2002, 2004; Tamura et al, 2005), PU.1 (Carotta et al, 2010), Ikaros, Gfi-1 (Rathinam et al, 2005), Batf3 (Hildner et al, 2008) and signal transducer and activator of transcription (Stat)-3 and Stat-5 (Wu and Liu, 2007; Merad and Manz, 2009). Id2, a member of the helix-loop-helix (HLH) transcription factor family, is upregulated during DC development and is required for the development of CD8α+ DCs and LCs (Hacker et al, 2003). Id proteins act by antagonizing the DNA binding of activating E proteins and Id2 has been postulated to repress pDC development by suppressing HEB and E2A as overexpression of these factors in haematopoietic progenitors led to enhanced pDC development (Schiavoni et al, 2002; Tamura et al, 2005). More recently, it was shown that a third HLH protein, E2-2, specifically regulates generation and maintenance of pDCs (Cisse et al, 2008). Irf proteins have broad effects in DC development. Loss of either Irf-2 or Irf-4 results in defects in the development of CD8α− DCs while the absence of Irf-4 also disrupts pDC development in the spleen. In contrast, Irf-8 (also known as ICSBP) is required for CD8α+ DCs and pDC development (Schiavoni et al, 2002; Tamura et al, 2005). Similar to the impact of Irf-8 deficiency, inactivation of the Jun dimerization protein p21SNFT, Batf3, has also been reported to result in the loss of CD8α+ and tissue-derived CD103+ DCs, but does not impair pDC development (Hildner et al, 2008; Edelson et al, 2010). CD103+ DCs found in peripheral LNs and lamina propria represent a heterogeneous group of cells in which those cells that express CD11b in the lamina propria do not appear to depend on Id2, Irf-8 or Batf3 for development (Ginhoux et al, 2009; Edelson et al, 2010). The analysis of compound knockout mice has led to a model in which conventional CD8α+ DCs and CD103+ DCs are thought to be developmentally related and possess similar functional and localization characteristics as both DC subsets are absent in mice lacking Id2, Irf-8 or Batf3 (Hildner et al, 2008; Ginhoux et al, 2009; Edelson et al, 2010). Such models, however, are unable to discriminate between the stepwise requirement for each of these transcription factors for differentiation nor their impact on modulating survival of DC subsets once DC precursors have developed. While much effort has focussed on the murine DC subsets, it is now becoming clear that many aspects of the human and mouse DC systems are closely aligned; and thus, murine models are likely to be highly informative in understanding human disease influenced by DC behaviour. DC subsets in the human blood can be distinguished by their expression of the surface molecules BDCA-1 (CD1c), BDCA-2 (CD303) and BDCA-3 (CD141) (Dzionek et al, 2000). BDCA-1+ cells represent a population of myeloid DCs; BDCA-2 marks pDCs, while BDCA-3 identifies the human counterpart of murine CD8α+ DCs which both share the high capacity to capture exogenous antigens for cross-presentation and the expression of chemokine receptor XCR1 (Bachem et al, 2010; Crozat et al, 2010; Jongbloed et al, 2010; Poulin et al, 2010). The interplay between these different DC subsets is of considerable interest as detailed understanding of their generation and responses offers opportunities for exploiting them as targets for vaccines and therapeutic interventions in cancer, autoimmunity and infection (Palucka et al, 2010). However, despite this significant progress, recovering sufficient human DC of the various subsets for molecular and transcriptional profiling remains challenging. To understand how the complex network of DC lineages is generated in a model system, we engineered an Id2-GFP mouse reporter strain that enabled us to track endogenous Id2 expression on a single cell level during DC differentiation. As Id proteins are concentration-dependent antagonists of E protein activity, we reasoned that Id2 expression would be tightly regulated in DCs. Indeed, this was the case as cDC subsets expressed a wide range of Id2-GFP with the highest expression in CD8α+ and CD103+ DC lineages in vivo. The equivalent DCs could also be identified in Flt3L-stimulated bone marrow cultures by correlating Id2 expression with surface expression of CD103 on DCs. By analysing Id2-GFP expression in the absence of Irf-8 and Batf3, we were able to delineate that Irf-8 is required for generation of both cDCs and pDCs, while in the absence of Batf3 Id2-GFP+Sirp-α− (CD8 equivalent) DCs develop but CD103+ DCs do not. Furthermore, GM-CSF is a potent stimulator of CD103 expression in vitro, even in the absence of Batf3; however, GM-CSF could not rescue cross-presenting potential from the same mice. Thus, the ability to map Id2-GFP expression in developing murine DC subsets has wide application in understanding the precise molecular regulation of DC differentiation. Results To define the expression of Id2 and its role in different haematopoietic lineages, we generated a reporter allele by inserting an internal ribosome entry site (IRES)-GFP cassette into the 3′ untranslated region of the Id2 gene (Figure 1A). The targeted reporter allele, Id2gfp, resulted in the transcription of a bicistronic mRNA that produced wild-type Id2 protein and GFP. This targeting strategy predicted that the IRES-GFP cassette would not affect the upstream Id2 mRNA transcript. To confirm this, homozygous Id2gfp/gfp mice were generated (Figure 1B). Id2gfp/gfp mice were indistinguishable in survival, haematopoietic cellularity and lineage composition from C57BL/6 controls (NK cells: C57BL/6, 2.3 × 105±6.7 × 104/spleen; Id2gfp/+, 1.94 × 105±4.2 × 104/spleen; Id2gfp/gfp, 1.94 × 105±1.9 × 104/spleen; total DCs: C57BL/6, 2.1 × 106±6.4 × 104/spleen; Id2gfp/+, 1.9 × 106±8.3 × 104/spleen; Id2gfp/gfp, 2.1 × 106±5.8 × 104/spleen; and data not shown). As predicted, Id2-GFP was abundantly expressed in NK cells and silenced in B cells (Figure 1C). Moreover, the expression of GFP correlated exactly with Id2 transcription in a variety of different haematopoietic lineages (Figure 1D). Figure 1.Generation and validation of Id2gfp reporter mouse strains. (A) The genomic locus of Id2. Exons are represented by boxes; introns are represented as black lines; coding regions are shaded yellow; non-translated regions are in white; arrows indicate the direction of translation. The alleles derived from the integration of the targeting vector and subsequent manipulations are shown. pA, polyadenylation signal sequence; circles, frt sites; triangles, loxP sites. The Id2-GFP reporter line was derived from an embryonic stem cell (ES) clone that lacked the 5′ LoxP site and was identified by PCR. The position and direction of the genotyping primers (a–c) and the SacI and XbaI sites used for Southern blotting are indicated. (B) Southern blot analysis of ES cell SacI-digested DNA showing the wild-type (12.6 kb) and targeted (8.9 kb) alleles (left panel). PCR genotyping of tail DNA using the primer set a/b/c showing the correct amplification of the wild-type (688 bp) and Id2gfp (959 bp) alleles (right panel). (C) Id2-GFP expression in B220+IgM+ B cells derived from peripheral LNs and splenic NK1.1+CD49b+ NK cells from naive wild-type (black line) and Id2gfp/gfp (green line) mice. (D) Quantitative PCR analysis for the indicated transcripts of live (PI−) mixed populations of cells from spleen, thymus and bone marrow purified on the basis of their expression of Id2-GFP. Data are the mean±s.e.m. of two experiments. Download figure Download PowerPoint Id2 expression in DCs in vivo Next, we investigated Id2-GFP in DCs in vivo to determine if the level of expression identified individual DC subsets. To track the expression of Id2 in cDCs and pDCs in vivo, we isolated DCs from thymus, spleen and peripheral and mesenteric LNs of Id2gfp/gfp mice (Figure 2A–E). This approach allowed the delineation of several populations of DCs not previously thought to express Id2 and showed that DCs isolated from different tissues expressed distinct amounts of Id2 (Figure 2A). Thymic DCs were divided into four populations with discrete fractions of both CD8α+Sirp-α− and Sirp-α+ DCs expressing Id2-GFP (Figure 2B). pDCs, which were identified by their intermediate expression of CD11c and high expression of CD45RA, were uniformly very low for Id2-GFP (Supplementary Figure S1). In spleen and LN, all cDCs (defined as CD11chigh) expressed Id2-GFP but varied in the level of expression among the different DC subsets (Figure 2C–E). Unexpectedly, CD4+ DCs in spleen and DN DCs in spleen and LN also expressed Id2-GFP (Figure 2C). Id2-GFP fluorescence in cells of the monocyte/macrophage lineages was at a level that was similar to DN DCs and dermal DCs, respectively (Figure 2C, D and F). Figure 2.Multiple DC subsets express Id2 in vivo. Id2gfp/gfp (green line) and wild-type (black line) cells were analysed by flow cytometry for GFP expression in different DC and myeloid populations. The different cell types were defined as described in Materials and methods. (A) Total DC (CD11c+) populations from thymus, spleen, peripheral LN and mesenteric LNs; (B) thymic DC populations; (C) splenic DC populations; (D) peripheral (pooled DCs from inguinal, brachial, axillary, superficial cervical LNs) and (E) mesenteric LN DCs; and (F) monocyte and macrophage (from peritoneal lavage) lineages. All plots are gated on CD11c+ cells and markers as indicated in the dot plots (left panels). In (D), the fluorescence intensity of Langerhans cells has been shown in red for comparison. Mean fluorescence intensity (MFI) is shown for GFP expression for each gated population. Data are representative of at least two to three independent experiments. Download figure Download PowerPoint Id2 expression in haematopoietic progenitors Given that all cDC subsets expressed some level of Id2-GFP, we wished to examine whether Id2 was induced during DC differentiation or alternately might be constitutively expressed in precursor DCs and down modulated as populations matured. Id2-GFP expression was negligible in lineage-negative scahighc-kithigh (LSK) cells (including the Flt3+ lymphoid primed multipotent progenitor, LMPP), common lymphoid progenitors and common DC progenitors (CDPs, also known as pro-DCs) (Figure 3A and B). Similarly, BM and splenic pre-cDCs had showed little upregulation of Id2 (Figure 3C) and analysis of CD11c+ bone marrow DCs revealed that a large fraction of cells were low or negative for Id2-GFP (Figure 3D) demonstrating that activation of the Id2 gene occurred relatively late in the differentiation of DCs. Thus, Id2 expression is induced in precursors that have been committed to the cDC pathway. Figure 3.Expression of Id2 in lymphoid progenitors. (A) Bone marrow progenitor cells were analysed by depletion of lineage expressing cells then stained for sca-1, c-kit, M-CSFR and Flt3 and analysed by flow cytometry for lin−sca-1+c-kit+ (LSK) cells, lymphoid primed multipotent progenitors (LMPPs, defined as LSKFlt3high), common lymphoid progenitors (CLPs) and (B) common DC progenitor (CDPs) as indicated. (C) Bone marrow and splenic DC progenitors were analysed by depletion of lineage expressing cells (CD19, NK1.1, CD3 and Ter119) then stained for CD11c, Flt3, MHC II and Sirp-α and analysed for the pre-cDC population by flow cytometry (Liu and Nussenzweig, 2010). Profiles show the gating strategy in which CD11c+MHC II− cells (region 1, R1) were then selected for expression of Flt3 and Sirp-α (region 2, R2). (D) CD11c+ cells were isolated from bone marrow by density gradient centrifugation. Gated populations from Id2gfp/gfp (green line) and wild-type (black line) mice were then assessed for GFP fluorescence. Data are representative of at least two experiments. Download figure Download PowerPoint Id2 expression in DCs in vitro The different amounts of Id2-GFP observed in different DC subsets in vivo led us to propose that distinct levels of Id2 expression could be used to define DC subsets and this hierarchy may also be maintained in vitro. If so, Id2-GFP mapping of DC subsets in vitro would enable the recovery of DC subsets in sufficient numbers for the detailed dissection of the functional and molecular aspects of DC development. It should be noted that although the surface molecule CD8α is expressed on DCs isolated directly ex vivo, this marker is not expressed on in vitro-derived CD8α-equivalent DCs. These cells have been previously identified by their lack of expression of Sirp-α, and as shown below, intermediate expression of CD45RA. As observed in vivo, DCs generated in vitro expressed graded levels of Id2-GFP allowing us to discriminate six distinct DC populations (Figure 4A–C). These could be divided into the Id2-GFP negative populations that also lack CD103 expression (1) CD45RA− DCs; (2) CD45RAint DCs that expressed the pDC markers Bst-2 and Siglec-H (Figure 4A, right panels); (3) CD45RAhigh (analogous to the previously described mature pDC); and the Id2-GFP expressing populations; (4) CD45RA− DCs; and (5) CD45RAint (Figure 4B). Further dissection of the Id2-GFP+ cDC populations revealed the presence of CD45RA−CD103+ DCs that expressed the highest amounts of Id2-GFP (population 6, Supplementary Table SI). Tissue-derived CD103+ cDCs have not been previously identified in vitro but this staining was specific as it was not detected in similar cultures derived from Itgae−/− (CD103-deficient) mice (Supplementary Figure S2). This analysis also showed that the Id2-GFP+CD45RA− population (pop. 4) of DCs was Sirp-α+ while the Id2-GFP+CD45RAint population (pop. 5) was predominantly Sirp-α− and these populations expressed distinct levels of CD24 consistent with the previously described in vitro phenotype of CD8α− DCs and CD8α+ DCs (Figure 4C; Naik et al, 2005). Figure 4.In vitro cross-presentation in Flt3L-stimulated cultures is limited to CD103-expressing Id2-GFPhigh DCs. (A–C) Flt3L-derived DCs from Id2gfp/gfp BM were analysed on day 5 of culture. Six different DC populations were discriminated based on their expression of CD11c, CD45RA and CD103. Right panels: CD11c+CD45RA+Id2-GFP− cells expressed markers of pDCs. Histograms show expression of Bst2 (upper right panel) and Siglec-H (lower right panel) of total CD45RAint cells (grey shading), CD45RAintId2-GFP− immature pDCs (black line). The expression of markers for CD103−CD45RAhigh (mature) pDC is indicated in red. (B) Populations 4, 5 and 6 could be discriminated based on their expression of Sirp-α or CD103. Profiles are representative of at least 10 independent experiments with similar results. (C) Id2-GFP DC subsets express distinct levels of Sirp-α and CD24. (D) In vitro generated Id2gfp/gfp DCs were flow cytometrically sorted 5 days after initiation of cell culture according to their expression of CD103, CD45RA, Sirp-α and Id2-GFP and analysed for their ability to cross-present cell-associated OVA to CFSE-labelled OVA-specific CD8+ T cells (upper panels). The ability of these subsets of present exogenous antigen to CFSE-labelled OVA-specific CD4+ T cells was evaluated as a control (lower panels). Data are representative of four independent experiments. T-cell proliferation was analysed in 1–3 replicates for each DC subset/responder population for each experiment. (E) Ly5.1+CFSE-labelled CD8+ OVA-specific T cells were adoptively transferred into H-2Kbm-1, B6 or Itgae−/− mice 1 day before transfer of 2 × 107 OVA-coated H-2bm-1 splenocytes. Proliferation of Ly5.1+Vα2+CD8+ T cells in spleen was analysed by flow cytometry after 60 h. Data are representative of two independent experiments with seven individuals analysed in each group. (F) The expression level of surface CD103 was monitored by flow cytometry 18 h after exposure to TLR ligands LPS or CpG. Data are representative of at least five independent experiments and show MFI expression levels. Download figure Download PowerPoint Differentiation of in vitro generated DC subsets To determine the relationship between different populations of DCs observed in vitro, DC subsets from day 5 cultures were purified into the six fractions described in Figure 4 and re-cultured in Flt3L-conditioned medium for further 3 days (Supplementary Figure S3). We hypothesized that Id2-GFP−CD45RA− DCs (pop. 1) contained multipotent DC precursors. Concordant with this notion, this subset gave rise to all identified in vitro subsets of DCs. Id2-GFP−CD45RAhi (pop. 3) generated only pDCs while Id2-GFP−CD45RAint DCs (pop. 2) predominantly gave rise to Id2-GFP−CD45RAhi cells, suggesting that they contain the major immature population of pDCs. CD103−Id2-GFP+CD45RA−Sirp-α+ DCs (pop. 4) maintained their phenotype while CD103−Id2-GFP+CD45RAintSirp-α− DCs (pop. 5) generated Sirp-α− DCs that expressed varying levels of CD103 and CD103−Sirp-α+ DCs. In contrast, CD103+ DCs (pop. 6) almost exclusively gave rise to CD103+ DCs, suggesting that these cells are terminally differentiated. Thus, it appears that some in vitro subsets represent end-state DC populations (e.g., mature pDCs and CD103+ DCs) while other subsets retain differentiation potential. Similarly, Id2-GFP−CD45RAint DCs appear to be immature pDCs. This was further supported by the failure of Id2-GFP−CD45RAint DCs to upregulate CD80 and MHC class II in response to TLR ligands such as LPS or poly I:C and the induction of these activation markers following stimulation with CpG motifs (Supplementary Figure S4). Thus, the in vitro culture contains a combination of early developing and differentiated DCs that may represent the counterparts of blood-derived lymphoid tissue-resident and tissue-derived DCs. Characteristics of CD103+ DCs in vitro One property that varies extensively among DC subsets is the ability to take up exogenous antigens and divert these antigens into the MHC class I pathway—a process known as cross-presentation and is thought to be of major importance for the recognition of viral or bacterial antigens when DCs are not directly infected (Carbone and Bevan, 1990). In mice, CD8α+ DCs, and more recently CD103+ DCs, have been identified as the major cross-presenting populations in vivo. Similarly, the CD8α+ DC counterpart in humans, BDCA-3 DCs, also exhibit more efficient cross-presenting ability in vit
Referência(s)