Novel mouse models based on intersectional genetics to identify and characterize plasmacytoid dendritic cells

The pDC-Tom mice allow specific pDC detection by flow cytometry

We generated mice knocked in for Cre expression from Siglech, which is highly expressed by mouse pDCs3. We crossed SiglechiCre and Rosa26LoxP-STOP-LoxP(LSL)-RFP mice16 to generate S-RFP mice for fate-mapping Siglech-targeted cells (Fig. 1a). Over 95% of splenic pDCs were red fluorescent protein positive (RFP+) (Fig. 1b and Extended Data Fig. 1a,b). Variable proportions of myeloid and lymphoid lineages expressed RFP (Fig. 1b and Extended Data Fig. 1a,b), consistent with Siglech expression10,17. We reasoned that enhanced specificity could be achieved by harnessing intersectional genetics, driving expression of a reporter under the control of two genes coexpressed only in pDCs. We aimed for activation by Siglech-driven Cre of a conditional fluorescent reporter cassette knocked in a gene exclusively expressed by pDCs within Siglech fate-mapped cells. We selected Pacsin1, expressed exclusively in pDCs within hematopoietic cells18 and promoting their IFN-I production19. We generated Pacsin1LoxP-STOP-LoxP-tdTomato (Pacsin1LSL-tdT) mice, knocked in with a floxed cassette for tdTomato (tdT) conditional expression. We crossed them with SiglechiCre mice, to generate pDC-Tom mice (Fig. 1c). In splenocytes from pDC-Tom mice, tdT was exclusively expressed in pDCs (Fig. 1d and Extended Data Fig. 1a,c). The tdT+ cells expressed neither lineage markers nor CD11b (Extended Data Fig. 1d). The CD45+ tdT+ cells isolated from different organs were CD11cint and BST2high (Fig. 1e), as expected for pDCs20. CD45+tdT+ cells coexpressed Ly6D, B220, SiglecH and CCR9 (Fig. 1f), a combination specific to pDCs. Thus, tdT expression in pDC-Tom mice is sufficient to specifically and unambiguously identify most pDCs.

Fig. 1: The pDC-Tom mice allow specific and unambiguous identification of pDCs in different organs.figure 1

a, Scheme illustrating the strategy followed to generate S-RFP mice. LoxP is the sequence recognized by Cre recombinase. ‘Stop’ corresponds to a transcriptional stop sequence. b, Splenocytes isolated from S-RFP mice were stained with fluorescently labeled antibodies to identify the indicated myeloid and lymphoid cell populations and analyzed for RFP expression by flow cytometry. The data shown (mean ± s.e.m.) are pooled from two independent experiments (n = 8). c, Scheme illustrating the strategy followed to generate pDC-Tom mice. d, Splenocytes isolated from pDC-Tom mice stained as in b to analyze tdT expression by flow cytometry. The data shown (mean ± s.e.m.) are pooled from two independent experiments (n = 6). e, Single-cell suspensions of indicated organs isolated from pDC-Tom mice stained with indicated fluorescent antibodies and analyzed by flow cytometry. f, Splenocytes from e analyzed for the expression of indicated markers on CD45+tdT+ cells. Gray histograms correspond to negative controls (fluorescence − 1). Black histograms correspond to the signal obtained on staining with the indicated antibody. For e and f, the data shown are from one mouse representing seven animals for the spleen and five animals for the peripheral lymph nodes (LNs), liver and small intestine. g,h, The HyperFinder plugin of the FlowJo software was applied to define an unsupervised gating strategy to identify pDCs from uninfected (g) or 36-h MCMV-infected (h) pDC-Tom mice. i, SiglecH expression (black histograms) shown on the pDCs as defined by the automated gating strategies computed for uninfected animals (g) or 36-h MCMV-infected mice (h). The negative controls (fluorescence − 1) are shown as gray histograms.

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The pDC-Tom mice allow refining pDC gating strategies

Defining pDCs as coexpressing CD11c, BST2 and SiglecH can lead to contamination by conventional DCs (cDCs), pDC-like cells4 or tDCs5,6,21. Moreover, on inflammation, such as during mouse cytomegalovirus (MCMV) infection, the expression of these markers is altered, causing a phenotypic convergence of pDCs and cDCs7. Hence, we harnessed pDC-Tom mice to define a gating strategy allowing unequivocal pDC identification both at steady state and during infection. We defined pDCs as tdT+ cells and used HyperFinder for unsupervised computational generation of a gating strategy to identify them, based on surface markers without using tdT. We included Ly6D, which is selectively expressed on pDCs and B cells, discriminating them from cDCs and tDCs4,5. At steady state, splenic pDCs were identified as Bst2highLy6D+B220+CD19−CCR9+SiglecH+ cells (Fig. 1g). During MCMV infection, they were identified as Ly6D+CX3CR1low/intCD19−CCR9highB220highBST2high cells (Fig. 1h). Hence, current identification of pDCs as lin−CD11b−CD11clow-to-intBST2high cells20 can be improved by addition of positivity for Ly6D or CCR9 and eventual exclusion of CX3CR1high cells. SiglecH is not a good marker postinfection (p.i.), because it is downregulated (Fig. 1i), especially on IFN-I-producing pDCs7. We thus propose identifying pDCs as Ly6DhighBST2highCD19−B220+CD11b−CD11c+ cells.

In pDC-Tom mice, tdT soars in pDCs’ immediate precursors

We analyzed bone marrow cells to investigate tdT expression along the myeloid17,22,23,24,25 and lymphoid4,5 ontogeny paths proposed for pDCs (Fig. 2a). Within differentiated cells, tdT was expressed exclusively in pDCs (Fig. 2b). The tdT was also detected, at a lower mean fluorescence intensity (MFI), in pDCs’ immediate precursors, the CD11c+ pre-pDCs (Fig. 2c and Extended Data Fig. 2a).

Fig. 2: Expression of tdT is detectable in late bone marrow precursors selectively committed to the pDC lineage.figure 2

a, Scheme of the previously proposed ontogenic paths for pDC differentiation along the myeloid (top, magenta) or lymphoid (bottom, cyan) lineages. Cells of these lineages diverging from the pDC main differentiation path are shown in gray. CD11c+ pre-pDCs and terminally differentiated pDCs, which are common to both paths, are shown in red. bg, Bone marrow cells isolated from pDC-Tom animals, stained with fluorescently labeled antibodies and analyzed by flow cytometry. The expression of tdT (orange histograms) was evaluated in bone marrow pDCs and cDCs (b), CD11c+ pre-pDCs (c) and different progenitors along the myeloid (d, pre-DC and e, early progenitors) or lymphoid (f, Ly6D− progenitors, and g, Ly6D+ progenitors) ontogenic paths. C57BL/6 mice were used as negative controls (black histograms). WT, wild-type. The fluorescence histograms shown (left) are from one mouse representing five pDC-Tom animals from two independent experiments. The bar graphs (right) correspond to the results of all five animals, with data shown as mean ± s.e.m. Statistical analysis was by two-sided, unpaired Student’s t-test: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Geom., Geometric.

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Upstream along the myeloid path, very low tdT levels were detected in SiglecH+ pre-DCs, but none in SiglecH− pre-DCs, irrespective of Ly6C expression (Fig. 2d and Extended Data Fig. 2a). This is consistent with SiglecH+Ly6C+/− pre-DCs giving rise to cDCs and pDCs, whereas SiglecH−Ly6C+ and SiglecH−Ly6C− pre-DCs generate mostly cDC2s or cDC1s, respectively17. The common DC progenitor (CDP), monocyte and DC progenitor (MDP) and common myeloid progenitor (CMP) were tdT− (Fig. 2e and Extended Data Fig. 2a).

Upstream along the lymphoid path, low tdT levels were detected in CD127+SiglecH+Ly6D+ progenitors (Fig. 2g and Extended Data Fig. 2b), consistent with these cells giving rise to pDCs4. Very low tdT levels were detected in the Ly6D+SiglecH− progenitor and none upstream (Fig. 2f–g and Extended Data Fig. 2b).

Thus, in pDC-Tom mice, tdT expression is exclusively induced in late bone marrow precursors committed to the pDC lineage, with a strong increase in CD11c+ pre-pDCs and maximal level in differentiated pDCs.

ZeST mice distinguish pDCs, pDC-like cells and tDCs

Refined, flow cytometry phenotypic keys can discriminate pDCs from pDC-like cells and tDCs at steady state6. This remains challenging in inflammation and in tissues by immunohistofluorescence. Within hematopoietic cells, Zbtb46 is specifically expressed in the cDC lineage including in pre-cDCs18, in pDC-like cells, as confirmed in Zbtb46GFP mice4,26, and in tDCs6. Therefore, to rigorously identify pDC-like cells and tDCs, we generated Zbtb46GFP;SiglechiCre;Pacsin1LSL-tdT (ZeST) mice (Fig. 3a).

Fig. 3: ZeST mice allow unambiguous discrimination of pDCs from tDCs and pDC-like cells.figure 3

a, Strategy for generation of ZeST mice. b,c, Splenocytes from ZeST mice stained with fluorescently labeled antibodies and analyzed by flow cytometry. b, Gating strategy followed to identify cDC1s, cDC2s, CD11chigh tDCs, pDC-like cells, pDCs, Zbtb46+Ly6D+ cells and tdT− pDCs. The first dot plot showing CD11c versus SiglecH expression was gated on singlets, live (LiveDead−), nonautofluorescent, Lineage(CD19,CD3,Ly6G,NK1.1)− cells. c, Expression of indicated fluorescent proteins or cell-surface markers on each of the cell populations gated as in b, from splenocyte suspensions from uninfected versus 36-h or 48-h MCMV-infected pDC-Tom mice. d, Projection of the cell types identified in b, according to the color key shown on the upper right of the panel, on the t-SNE space calculated for all cells expressing high levels of CD11c or positive for SiglecH. The data shown are from one ZeST mouse representing at least ten uninfected animals for bd and for seven MCMV-infected animals at 36 h p.i. or eight MCMV-infected animals at 48 h p.i. for c. e, Quantitative and unbiased assessment of the cellular morphology of cDC2s, tDCs, pDC-like cells and pDCs sorted from the spleen of uninfected ZeST mice according to the gating strategy shown in b. One representative confocal microscopy image of each DC type is shown on the left. The distribution of the circularity indices for individual cells across DC types is shown as dots on the right, with the overlaid color bars showing the mean circularity indices of each DC type. The data shown are from two independent experiments, each performed with one mouse, with 37–44 individual cells analyzed for each DC type, as shown below the graph. nb cells, number of indiviudal cells analyzed. The Kruskal–Wallis test was used for the statistical analysis: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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In ZeST mice, most of the lin−, SiglecH+ or CD11chigh cells expressed GFP or tdT in an almost mutually exclusive manner (Fig. 3b). Within tdT+ or GFP+ cells, we identified type 1 cDCs (cDC1s) as XCR1+ and type 2 cDCs (cDC2s) as CD11b+ (Fig. 3b). Within the XCR1−CD11b−BST2highSiglecH+ gate, we identified pDCs as Ly6D+GFP− and pDC-like cells as GFP+ according to their original definition4 but considering only the major Ly6D− fraction. The small fraction coexpressing Ly6D and GFP (Zbtb46+Ly6D+ cells) was studied separately to determine whether they encompassed pDCs. The tDCs were originally characterized as Lin−CD11b−XCR1−SiglecH−/highCD11clow-to-highCX3CR1+ and split into two fractions: CD11clowLy6C+ cells, harboring higher levels of SiglecH and Tcf4, more similar to pDCs, versus CD11chighLy6C− cells, high for Zbtb46, more similar to cDC2s6. Comparing phenotypic markers and genes between CD11clowLy6C+ tDCs6 and pDC-like cells4 suggested that they were the same population. Thus, to avoid overlap between the gates for pDC-like cells and tDCs, we focused on the SiglecH−/low tDCs, identified similarly to their original definition6 as CD11b−, XCR1−, SiglecH−/low, BST2−/lowCX3CR1+ cells, within singlet, live, nonautofluorescent, Lin−, SiglecH+ or CD11chigh, tdT+ or GFP+ cells (Fig. 3b). The SiglecH−/low tDCs were all Ly6D− (Fig. 3b–c) and expressed higher levels of CD11c than pDCs and pDC-like cells (Fig. 3c); hence we called them CD11chigh tDCs. Only very few of the Lin−, CD11chigh or SiglecH+ cells expressed neither GFP nor tdT, a fraction of which were Ly6D+SiglecHhigh and thus probably tdT− pDCs (Fig. 3b).

To validate the identity of the DC types gated manually, we characterized their phenotype further (Fig. 3c). As expected, beyond being Ly6D+SiglecH+, both tdT− and tdT+ pDCs were CCR9highCD11cint. A fraction of Zbtb46+ Ly6D+ cells expressed lower levels of tdT and CCR9, and higher levels of CD11c, compared with tdT+ pDCs. CD11chigh tDCs were GFPhightdT−. The pDC-like cells were GFP+tdT−CCR9−/low. The surface phenotype of these populations was not modified during MCMV infection (Fig. 3c and Extended Data Fig. 3). Hence, tdT was expressed only in cells harboring a phenotype of bona fide pDCs, whereas GFP was mainly expressed in cDC1s, cDC2s, pDC-like cells and CD11chigh tDCs.

Next, we performed an unsupervised analysis of the phenotypic relationships for all the Lin−, CD11chigh or SiglecH+ cells. Onto a t-distributed stochastic neighbor embedding (t-SNE) representation of the data, we projected the populations identified through manual gating as defined in Fig. 3b. This analysis highlighted three main cell clusters, corresponding to cDC2s, cDC1s and pDCs (Fig. 3d). The other DC types formed a continuum between pDCs and cDC2s, with tdT− pDCs and Zbtb46+Ly6D+ cells close to pDCs, versus pDC-like cells and CD11chigh tDCs close to cDC2s, consistent with previous observations6.

We sorted cDC2s, CD11chigh tDCs, pDC-like cells and pDCs from steady-state mouse spleens to examine their morphology (Fig. 3e). The cDC2s harbored many pseudopods or dendrites, translating into a low circularity index. Most pDC-like cells and pDCs harbored a round morphology, translating into a high circularity index. The CD11chigh tDC population was morphologically heterogeneous, with a bimodal distribution of circularity indices, half of the cells being dendritic, like cDC2s, and the other half round, like pDCs. Overall, quantitative and unbiased analysis of cellular morphology supported success in high-degree purification of the DC types.

Finally, to better discriminate the tdT signal from autofluorescence, and analyze more cell-surface markers in ZeST mice, we harnessed spectral flow cytometry (Extended Data Figs. 4 and 5). Unsupervised cell clustering based on all surface markers (Extended Data Fig. 4a,b), without considering tdT and GFP, showed that most GFP+ cells were cDC2s or cDC1s (Extended Data Fig. 4c). They also encompassed lymphoid cells and a cluster of myeloid cells, but with a low MFI (Extended Data Fig. 4d). The pDCs represented 81.5 ± 6% of tdT+ splenocytes (Extended Data Fig. 4e). The individual contribution of other phenotypic cell clusters to the tdT+ gate was very small and their tdT MFI below that of pDCs, barely above background (Extended Data Fig. 4f).

Complementary analysis by supervised identification of cell types via manual gating allowed study of both tDC populations: the Ly6C− versus Ly6C+ fractions of Lin−CD11b−XCR1−, CD11c+ or BST2+, CX3CR1+CD26+ cells (Extended Data Fig. 5a–d). The populations phenotypically defined as pDC-like cells4 or Ly6C+ tDCs6 largely overlapped, as was the case for CD11chigh tDCs and Ly6C− tDCs (Extended Data Fig. 5b–e). Most Lin−CD11b−XCR1−, CD11c+ or BST2+, Ly6D−CX3CR1− cells were CD11c+CD26+GFP+CD64− (Extended Data Fig. 5f), indicating DC lineage. They encompassed major histocompatibility complex II (MHC-II)−/low and MHC-IIhigh cells putatively corresponding to pre-DCs versus differentiated DCs, respectively. A decrease in the absolute numbers of most of DC types was observed in the spleen at 48 h p.i. (Supplementary Table). This analysis confirmed the high specificity and penetrance of GFP expression in cDC1s and cDC2s, and both tDC populations, as well as the high specificity and penetrance of tdT expression in pDCs (Extended Data Fig. 5g).

ScRNA-seq confirms DC-type identification in ZeST mice

We harnessed ZeST mice to perform single-cell RNA sequencing (scRNA-seq) for the five DC types, on index sorting from the spleen of animals either infected or not infected with MCMV, using the gating strategy shown in Fig. 3b and the FB5P-seq (FACS-based 5′-end scRNA-seq) protocol27,28.

We first analyzed 343 splenocytes isolated from noninfected (NI) mice. They were clustered and annotated for cell types (Supplementary Table) by Seurat, based on gene expression profiles (Extended Data Fig. 6a), and by Rphenograph, based on surface marker expression (Extended Data Fig. 6b,c). DC-type assignment to individual cells was rather consistent between these two strategies, but suggested heterogeneity of Seurat clusters II and III (Extended Data Fig. 6d). Therefore, to unambiguously and reliably assign a DC type to individual cells in an unbiased manner, we used a combinatorial strategy: to be selected, a cell had to belong to the expected intersection between the Rphenograph and Seurat clusters (colored cells in Extended Data Fig. 6d) and to be enriched for the corresponding DC-type-specific transcriptomic signatures4,29 as tested with single-cell connectivity Map (sgCMap; Extended Data Fig. 6e). A final cell type was assigned to 205 cells: 103 pDCs, 26 pDC-like cells, 19 CD11chigh tDCs, 23 cDC2s and 34 cDC1s (Extended Data Fig. 6e,f and Supplementary Table).

Our next objective was to assign a DC type to the 951 cells from the whole dataset, from both NI and MCMV-infected mice (Extended Data Fig. 7a and Supplementary Table). We aimed at achieving a robust DC-type assignment, irrespective of cell states and infection conditions, by combining transcriptomic and phenotypic analyses. Based on the intersection of the clustering with Seurat (Extended Data Fig. 7b) versus Rphenograph (Extended Data Fig. 7c,d), a final DC type was assigned to 851 cells (colored cells in Extended Data Fig. 7e): 310 pDCs, 170 pDC-like cells, 146 CD11chigh tDCs, 103 cDC2s and 122 cDC1s, with 100 cells left unannotated (Fig. 4a). We confirmed DC-type assignment by a complementary method: we generated cell type-specific transcriptomic signatures from the dataset focused on cells from NI mice (Supplementary Table) and used them for sgCMap analysis of the whole dataset (Extended Data Fig. 7f). All the cells sorted as pDCs, and most of the tdT− pDCs, were computationally assigned to pDCs (Extended Data Fig. 7e,f). The assignment to cDC1s was also consistent between cell sorting and deductive re-annotation. Cell clustering on sgCMap scores tended to confirm the distinction between cDC2s and CD11chigh tDCs, although many cells had a null score for the ‘tDC_vs_cDC2’ sgCMap signature, emphasizing the proximity between these two DC types (Extended Data Fig. 7f). As expected, Zbtb46+Ly6D+ cells were mostly assigned to pDC-like cells. Some cells sorted as pDC-like cells were in time assigned to CD11chigh tDCs (Extended Data Fig. 7e,f). Not only CD11chigh tDCs but also pDC-like cells were CX3CR1+/high (Fig. 4b). Akin to cDCs, CD11chigh tDCs were GFPhigh, whereas pDC-like cells expressed SiglecH, BST2, Ly6D and CCR9 to levels intermediate between those of pDCs (high) and cDCs (low). The pDCs and pDC-like cells shared high expression of Siglech (Fig. 4c,d), Tcf4 and Runx2 (Fig. 4c). CD11chigh tDCs and pDC-like cells shared high expression of Crip1, Lgals3 and Vim (Fig. 4c), previously reported to discriminate pDC-like cells from pDCs4. The pDC-like cells and CD11chigh tDCs shared with cDCs higher expression of Zbtb46, Spi1, Slamf7 and S100a11, compared with pDCs (Fig. 4c). Contrary to cDC2 cells, a fraction of pDC-like cells and CD11chigh tDCs expressed Cd8a (Fig. 4c,d), as reported for tDCs6,21,29. The pDC-like cells, CD11chigh tDCs and cDC2s specifically expressed Ms4a4c (Fig. 4c,d) and Ms4a6c (Fig. 4c). CD11chigh tDCs and cDC2s selectively shared expression of Ms4a6b (Fig. 4d) and S100a4 (Fig. 4c). CD11chigh tDCs expressed higher levels of certain cDC genes than pDCs and pDC-like cells, including Batf3, Rogdi and Cyria (Fig. 4c). The pDC-like cells expressed very high levels of Ly6c2 (Fig. 4c,d). Hence, the pDC-like cells characterized in the present report were confirmed to align with both the originally described pDC-like cells4 and the CD11clowLy6C+ tDCs6.

Fig. 4: ScRNA-seq confirmed proper identification of pDCs, pDC-like cells and tDCs in ZeST mice.figure 4

a, UMAP dimensionality reduction for DC types isolated from the spleens of eight ZeST mice (three uninfected, three MCMV infected for 36 h and two infected for 48 h; Extended Data Fig. 7a). Cells were index sorted into the five DC types studied (Fig. 3b) and used for scRNA-seq. As indicated by the color code, 851 individual cells were reassigned by deduction to a DC-type identity (cDC1s, cDC2s, pDCs, pDC-like cells or CD11chigh tDCs), based on combined analysis of their phenotypic and transcriptomic characteristics, as assessed, respectively, by Rphenograph clustering (Extended Data Fig. 7c) and Seurat clustering (numbers on the UMAP; Extended Data Fig. 7b), with confirmation via a single-cell enrichment analysis for DC-type-specific signatures generated from prior analysis of the cells from uninfected mice only (Extended Data Figs. 6 and 7); 100 cells were left nonannotated (NA). b, Violin plots showing expression of phenotypic markers across DC types. c, Heatmap showing messenger RNA expression levels of selected genes (rows) with hierarchical clustering using Euclidean distance, across all 951 cells (columns) annotated for (1) cell type final annotation as shown in a, (2) sorting phenotype, (3) time point after MCMV infection, (4) belonging to Rphenograph clusters and (5) belonging to Seurat clusters. Six gene groups are shown: (1) genes specifically expressed at high levels in pDCs, (2) genes with shared selective expression in pDCs and pDC-like cells, (3) cDC1-specific genes, (4) genes previously reported to be expressed at higher levels in pDC-like cells over pDCs, (5) cDC2-specific genes and (6) genes expressed selectively at higher levels in CD11chigh tDCs and cDC2 or cDC1 or pDC-like cells. d, Violin plots showing mRNA expression levels of selected genes across DC types. e, Violin plots showing tdT expression across DC types.

All cDC1s expressed the XCR1 protein (Fig. 4b). However, a fraction was low/negative for Xcr1 and other genes specific of steady-state cDC1s (Gpr141b, Tlr3, Cadm1 and Naaa; Fig. 4c), consistent with DC-type activation decreasing the expression of

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