Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Jan 15.
Published in final edited form as: J Immunol. 2024 Apr 15;212(8):1357–1365. doi: 10.4049/jimmunol.2300431

Single-cell Analysis Reveals a Subset of High IL-12p40-Secreting Dendritic Cells within Mouse Bone Marrow-Derived Macrophages Differentiated with M-CSF

Kate Bridges *,, Gabriela A Pizzurro *,, Mihir Khunte *, Meibin Chen *, Erick Salvador Rocha ‡, Amanda F Alexander *, Victor Bass †, Laura N Kellman †, Janani Baskaran *, Kathryn Miller-Jensen *,†
PMCID: PMC12801409  NIHMSID: NIHMS1966433  PMID: 38416039

Abstract

Macrophages and dendritic cells (DCs), while ontogenetically distinct, have overlapping functions and exhibit substantial cell-to-cell heterogeneity that can complicate their identification and obscure innate immune function. Here we report that M-CSF-differentiated murine bone marrow-derived macrophages (BMDMs) exhibit extreme heterogeneity in the production of IL-12, a key pro-inflammatory cytokine linking innate and adaptive immunity. A microwell secretion assay revealed that a small fraction of BMDMs stimulated with lipopolysaccharide (LPS) secrete a majority of IL-12p40, and we confirmed this is due to extremely high expression of Il12b, the gene encoding IL-12p40, in a subset of cells. Using an Il12b-YFP reporter mouse, we isolated cells with high LPS-induced Il12b expression and found that this subset was enriched for genes associated with the DC lineage. Single-cell RNA-sequencing data confirmed a DC-like subset that differentiates within BMDM cultures that is transcriptionally distinct but could not be isolated by surface marker expression. While not readily apparent in the resting state, upon LPS stimulation, this subset exhibited a typical DC-associated activation program that is distinct from LPS-induced stochastic BMDM cell-to-cell heterogeneity. Overall, our findings underscore the difficulty in distinguishing macrophages and DCs even in widely used in vitro murine BMDM cultures and could affect the interpretation of some studies that use BMDMs to explore acute inflammatory responses.

Introduction

Immune cells exhibit multiple layers of heterogeneity to enable robust immune responses in a wide range of contexts (1). Sources of heterogeneity include differentiation into distinct immune cell subsets, with variations in phenotype and functional responses within those subsets. A key example is macrophages and dendritic cells (DCs), innate mononuclear phagocytes which primarily derive from common hematopoietic progenitors and share roles in antigen presentation and orchestrating adaptive immune responses (2, 3). Interestingly, macrophages and DCs exhibit stochastic heterogeneity in their response to inflammatory stimuli: namely a small fraction of cells exhibiting heightened functional activity (4–8). Both differences in ontogeny and inflammatory response heterogeneity are important for the regulation of immune function (9), and understanding the underlying sources of heterogeneity is critical for optimal therapeutic targeting and control.

Interleukin-12 (IL-12) is a pro-inflammatory cytokine made by monocytes, macrophages, and DCs in response to pathogens, and it is an emerging target to treat inflammatory autoimmune diseases and cancer (10). Although monocytes and macrophages were originally reported to be the main producers of IL-12 (11), DCs are the first producers of IL-12 during pathogenic infections (12, 13). IL-12 provides a critical link between the innate and adaptive immune responses in both humans and mice by inducing interferon-γ (IFN-γ) production by T cells and promoting their differentiation to T helper 1 (TH1) cells (12). IL-12 is a heterodimer comprising p35 and p40 subunits. While p35 is expressed in many cell types, the expression of the p40 subunit is limited to macrophages and dendritic cells (14). The engagement of TLRs by microbial products results in a massive induction of transcription and secretion of the p40 protein (15). Although much is known about the immunobiology of IL-12p40, fundamental questions remain about which in vivo cellular sources are linked to specific immunological processes (14).

Many studies have explored mechanisms of IL-12p40 production and regulation using murine bone marrow-derived macrophages (BMDMs) as a mononuclear phagocyte source (e.g., (16–19). BMDMs can be generated in high yields from murine bone marrow precursors by differentiating in the presence of macrophage colony stimulating factor (M-CSF or CSF1) and can be stored by freezing (20). BMDMs are widely used in macrophage research; for example, as a reference to define the nomenclature macrophage polarization (21, 22) and to define principles of inflammatory activation via pathogen-associated molecular pattern molecules (PAMPs) (18, 23). Thus, the behavior of this in vitro-generated macrophage model has influenced our general understanding of macrophage biology, including the regulation of IL-12.

Here we combine multiple single-cell measurements to study the regulation and heterogeneity of IL-12 production in murine BMDMs following activation of TLR4 with the bacterial endotoxin lipopolysaccharide (LPS). Using a single-cell secretion assay and single-cell RNA sequencing, we discovered a previously unreported subpopulation within BMDMs that preferentially produces and secretes IL-12p40 upon LPS stimulation. We show that this subpopulation is consistent with a DC phenotype, supported by previous reports of M-CSF as an alternate pathway for DC differentiation (24). The DC subset is difficult to identify prior to activation, however these cells contribute substantially to LPS-stimulated IL-12p40 secretion in the BMDM population. Our findings should be considered when using BMDMs to study inflammatory activation and IL-12p40 regulation, and when distinguishing between macrophages and DCs in cultures and tissues.

Materials and Methods

Mice and cell culture

Wild type C57BL/6J and B6.129-Il12btm1.1Lky/J (Il12b-IRES-eYFP) mice were purchased from Jackson Laboratories. All mice were housed in the Yale Animal Resources Center in specific pathogen-free conditions. All animal experiments were performed according to the approved protocols of the Yale University Institutional Animal Care and Use Committee.

Bone marrow-derived macrophages were differentiated with 20 ng/ml macrophage-colony stimulating factor (M-CSF; Peprotech) as previously described (25, 26). Bone marrow-derived dendritic cells and macrophages were differentiated with 20 ng/ml GMCSF according to the same timeline. Loosely adherent cells (comprising GM-DC and GM-Mac) were collected by gentle pipetting and adhered cells (GM-Mac-Adherent) were detached with PBS+EDTA as described.

6 days after plating, cells were harvested in PBS + 5 mM EDTA with gentle scraping. BMDMs were plated and stimulated in BMDM media + 10 ng/ml M-CSF. Cells were cultured in non-TC treated plates at a density of 100,000 cells per cm2 (or microwell devices as described below) and allowed to adhere overnight. Cells were stimulated at the indicated doses and times using LPS (Invivogen), IFN-γ (Peprotech), PAM3CSK4 (Invivogen), and/or IL-4 (Peprotech). When indicated, cells were fixed, mounted, and analyzed for IL12-YFP expression with a fluorescent microscope (Zeiss Axio Observer, US).

ELISA

Cells were plated and treated as described. Supernatants were collected at the indicated time points. IL-12p40 secretion was analyzed with the OptEIA assay kit (BD #555165) according to the manufacturer’s instructions.

Single-cell secretion data analysis

Single-cell secretion profiling data was reanalyzed from experiments previously described (26).

Single molecule RNA fluorescent in situ hybridization (smFISH) and analysis

The probe sets targeting Il12b and Tnf were designed using the Stellaris® RNA FISH Probe Designer (Biosearch Technologies, Inc., Petaluma, CA). Stellaris RNA FISH Probes were labeled with Quasar 670 (Biosearch Technologies, Inc.) and mRNAs were hybridized following the manufacturer’s instructions as previously described (27). Cells were imaged on an Axio Observer Zi inverted microscope (Zeiss) with an Orca Flash 4.0 V2 digital CMOS camera (Hamamatsu) and a 100x APO oil objective (NA 1.4, Zeiss). smFISH images were analyzed using FISH-Quant (28) as previously described (27).

Fluorescence activated cell sorting of Il12b-YFP cell populations

BMDMs were gated on Live+CD11b+F4/80+ prior to sorting based on Il12b-YFP expression. GM-CSF-derived cells were gated as previously described (29). Additional antibodies used (clone, catalog#): F4/80 PerCP (BM8, 123126), CSF1R BV605 (AFS98, 135517), CD40 PE-Cy5 (3/23, 124618), CD64 BV711 (X54–5/7.1, 139311) from BioLegend. For additional antibody details, see below in Surface protein staining section. Samples were analyzed on a LSRFortessa and cell sorting was performed in a FACSAria (BD Biosciences). Flow cytometry data was analyzed using FlowJo software (TreeStar Inc.).

Surface protein and intracellular cytokine staining

Single-cell suspensions were incubated with FcBlock CD16/32 (93, 16–0161-82, eBiosciences) 1:200, washed and stained for extracellular markers in PBS+2% FBS. BMDM staining panels included (clone, catalog#): CD11b BV421 (M1/70, 101236), F4/80 AF700 (BM8, 123130), CD24 BV605 (M1/69, 101827), Ly6G BV650 (1A8, 127641), CD11c PE-Cy7 (N418, 117318), Ly6C BV785 (HK1.4, 128041), CD172a FITC (P84, 144006), XCR1 APC (ZET, 148206), CCR7 PE (4B12, 120105), CD64 PerCP-Cy5.5 (X54–5/7.1, 139308), CD86 PE-Dazzle594 (GL-1, 105042), MHCII APC-Cy7 (M5/114.15.2, 107628) from BioLegend Live/Dead eFluor506 (65–0866-18) from Thermo Fisher. For intracellular staining (ICS), cells were incubated with 5ug/ml Brefeldin A (420601, BioLegend) in RPMI complete media, in 6-well plates at 37C for the indicated time and then processed with CytoFix/CytoPerm and Perm/Wash Buffer kit (BD #554714) according to manufacturer’s instructions prior to staining with TNF APC (TN3–19.12, 506108) from BioLegend and IL12/IL23 p40 AF488 (C17.8, 53–7123-82) from Thermo Fisher.

RT-qPCR

RNA was extracted using the RNEasy Mini Kit (Qiagen). Genomic DNA was removed on-column with RNase-free DNase (Qiagen), and complementary DNA (cDNA) was synthesized using a dT oligo primer and Superscript III RT (Invitrogen). After dilution in nuclease-free water, cDNA was quantified using SYBR-green for quantitative reverse transcription polymerase chain reaction on a CFX Connect Real-Time System (Bio-Rad) with the following amplification scheme: 95°C denaturation for 1.5 minutes followed by 40 cycles of 95°C denaturation for 10 secs, 65°C annealing for 10 secs, and 72°C elongation for 45 secs with a fluorescence read at the end of the elongation step. All samples were normalized to ubiquitin (Ubc). Primers are reported in Table 1.

Table 1.

List of primers used for qPCR.

Target Forward Primer (5’ to 3’) Reverse Primer (5’ to 3’)
Ccr7 AGAGGCTCAAGACCATGACGGA TCCAGGACTTGGCTTCGCTGTA
Fcgr1 ACCTGAGTCACAGCGGCATCTA TGACACGGATGCTCTCAGCACT
H2-Ab1 GTGTGCAGACACAACTACGAGG CTGTCACTGAGCAGACCAGAGT
Il6 TCCTCTCTGCAAGAGACTTCC TTGTGAAGTAGGGAAGGCCG
Tnf CCCTCACACTCAGATCATCTTCT GCTACGACGTGGGCTACAG
Ubc ACCACCAAGAAGGTCAAACAGG TAAGACACCTCCCCCATCAC
Open in a new tab

Single-cell RNA-sequencing analysis

The sequencing data was preprocessed to remove doublets and dead cells, and counts were normalized using the scran package in R as described (25) but with some critical modifications. Previously, the minimum number of expressed genes was set to 2,000+, which intended to retain only a homogeneous population of transcriptionally active BMDMs. Minimum counts per single cell were further originally set to 10,000 (see: [https://github.com/miller-jensen-lab/munoz-rojas_NatCommunications2020/blob/main/ 00_LoadFiles_QC.py]). When these thresholds were dropped to 1,300+ and 6,000, respectively, a substantial fraction of the DC-like cells were recovered, because these cells are less transcriptionally active than macrophages regardless of stimulation. Lower filtering thresholds are more typically used for scRNA-seq datasets expected to capture heterogeneous immune populations at various levels of transcriptional activity (e.g., in tissues). The same pre-processing conditions were applied to the analysis of GSE117176.

Dimensionality reduction and visualization with Uniform Manifold Approximation and Projection (UMAP) were performed with the scanpy package in Python (30). Cells were clustered with the Leiden algorithm as implemented in scanpy (31). Differentially expressed genes (DEGs) were identified using the rank_genes_groups function in scanpy. Genes with log2FC > 1.5 and adjusted p-value < 0.05 were considered significantly upregulated in each cellular partition of interest. We then performed enrichment analysis on the top 100 DEGs for each group using g:Profiler (32). Gene Ontology (GO) biological processes, Reactome (REAC), KEGG, and WikiPathways (WP) were used as reference databases. Enrichment p-values were adjusted for false discovery using the Benjamini-Hochberg procedure. Code to reproduce processing and analysis of publicly available scRNA-seq data presented in this study is available in the following GitHub repository: [https://github.com/khbridges/khunte-bmdm].

Hierarchical clustering and visualization of the log-transformed transcriptional profiles of the Leiden clusters with DC and macrophage signatures obtained from the Mononuclear Phagocytes Project (33) were completed using the clustermap function from the seaborn module in Python. To compare bulk reference profiles to single-cell transcription, all data was first converted to measurements of “average mRNA per single cell,” where transcripts counts were averaged either over cells in a Leiden cluster (scRNA-seq) or over total cells in the population-level measurement (33).

Results

A small subpopulation of BMDMs produce a majority of IL-12p40 upon TLR4 stimulation

We cultured bone marrow progenitors in 20 ng/ml M-CSF for 7 days to produce a largely homogenous population of F4/80+CD11b+ cells (20) (Supplemental Fig. 1A). BMDMs were treated with 100 ng/ml LPS and secretion in the population was measured by ELISA. BMDMs secreted IL-12p40 in response to LPS stimulation, and secretion was sustained for at least 24 hours (Fig. 1A). When single BMDMs were analyzed by flow cytometry, we confirmed that production of IL-12p40 was bimodal, with 30–40% of the population positive by intracellular cytokine staining (ICS) in the presence of brefeldin A (BFA; Supplemental Fig. 1B) consistent with prior reports (19).

Fig. 1. A majority of IL-12p40 is secreted by a small fraction of BMDMs following LPS stimulation.

Fig. 1.

Open in a new tab

(A) IL-12p40 secreted by BMDMs stimulated with 100 ng/ml LPS for the indicated times. Protein measured by ELISA and data are presented as mean +/− standard deviation (SD) of 2 biological replicates. (B) Violin plots of secretion from individual BMDMs measured in the microwell assay after stimulation for 8 h with the indicated LPS dose. Black bar indicates fluorescent threshold of detection, arbitrary units (a.u.). Data are from one representative experiment of three independent experiments. (C-D) IL-12p40 production by single cells was calculated by converting fluorescence intensities to protein concentrations via recombinant standard curves. Box and whiskers indicate the 10–90 percentiles at each LPS dose (C). Total IL-12p40 production by cells in the top 10% (red) and the remaining cells (black) is indicated in (D). Data are pooled from 3 independent experiments. (E) BMDMs were stimulated in a population with 100 ng/ml LPS and then fixed at the indicated Il12b transcripts were measured by single molecule RNA FISH (smFISH) in BMDMs treated with 100 ng/ml LPS for the indicated time points and Il12b transcripts were labeled by smFISH. Individual counts per cell are plotted for a representative experiment of 2 biological replicates.

We previously showed that measuring single-cell secretion in a microwell assay in the absence of BFA revealed more secretion variability than was observed by ICS in the presence of BFA (34). Therefore, we cultured BMDMs overnight in microwells and then stimulated with LPS for 8 hours at various doses. Surprisingly, we found that secretion of IL-12p40 by individual BMDMs was extremely skewed (Fig. 1B). At the highest LPS dose, only 16% of cells were secreting IL-12p40 above background, however some of those cells were secreting it at much higher levels than average. This distribution was significantly more skewed than what was observed for TNF and IL-6 (Supplemental Fig. 1C). We used recombinant protein standard curves to convert fluorescence intensities to protein concentrations (Fig. 1C) and found that the top 10% of IL-12p40 producers accounted for approximately 60% of all IL-12p40 measured in the microwell device at both 100 and 1000 ng/ml LPS (Fig. 1D).

To distinguish between IL-12p40 protein measurements made by ICS with BFA versus those made in the microwell assay, we assessed the distribution at the transcript level. We cultured BMDMs together in a plate, treated them with LPS for 8 hours, and then fixed them and quantified mRNA transcripts by single molecule RNA fluorescence in situ hybridization (smFISH; Fig. 1E). By 8 hours, we observed a highly skewed distribution of Il12b transcripts (the gene that encodes for IL-12p40) that resembled secretion in the microwell device. The Il12b transcript distribution was significantly more skewed than the LPS-stimulated distribution of Tnf transcripts as measured by smFISH (Supplemental Fig. 1C–D; p = 0.0005). Interestingly, we observed that the addition of BFA decreased the skewness of both Tnf and Il12b transcript distributions, suggesting that BFA perturbs cytokine production at the transcript level and could partly account for the differences in measurements between ICS and the microwell assay. Overall, we conclude that the variability in the production of IL-12p40 by BMDMs is significant, with a small subset of cells accounting for a majority of the production.

High IL-12p40 secretion is not correlated with high inflammatory protein secretion

We had previously used the microwell assay to simultaneously measure multiple cytokines and chemokines (C/Cs) secreted by BMDMs upon LPS stimulation (26). To visualize the relationship between IL-12p40 production and the other C/Cs following TLR4 stimulation, we projected the 10-dimensional data onto two dimensions using Uniform Manifold Approximation and Projection (UMAP; (35)). BMDMs secreting high levels of IL-12p40 separated in UMAP space and did not follow the same pattern of LPS-induced activation observed for TNF, IL-6, and the chemokines CCL5, CXCL1, and CCL3 (Fig. 2A). We calculated the pairwise correlation coefficients between the prototypical proinflammatory cytokine TNF and IL-12p40 and found that TNF and IL-12p40 displayed very low correlation with each other (Fig. 2B; R = 0.096). This contrasted with the much stronger correlation observed between TNF and CCL5 (R = 0.553). This suggests that BMDMs secreting high levels of IL-12p40 are regulated differently than those secreting high levels of other proinflammatory cytokines and chemokines following LPS activation.

Fig. 2. High-dimensional single-cell secretion analysis of LPS-stimulated BMDMs reveals a distinct inflammatory program for high IL12p40-secreting cells.

Fig. 2.

Open in a new tab

(A) BMDMs were cultured in the microwell following LPS stimulation at various doses (0, 10, 100, 1000 ng/mL) and single-cell secretion was assessed at 8 hours. 10-dimensional secretion data is visualized in 2D with UMAP. Points are colored by relative intensity of the indicated cytokine for each cell. Data are pooled from 3 independent experiments. (B) Density-colored scatter plots of single-cell secretion in response to 100 ng/ml LPS for IL-12p40 and CCL5 versus TNF. Black lines indicate calculated threshold of detection. a.u., arbitrary units. Data are reanalyzed from ref. 26.

BMDMs producing high amounts of IL-12p40 are enriched for DC-associated transcripts

To isolate the high IL-12p40-producing cells following LPS stimulation, we took advantage of the C57BL/6 Il12b-IRES-eYFP reporter mouse (36). We differentiated BMDMs from the bone marrow of this mouse as previously described and treated them with 100 ng/ml LPS. The skewed distribution of the Il12b-YFP signal was evident by microscopy (Fig. 3A), and quantification recapitulated the transcript distributions observed using smFISH (Fig. 3B vs. Fig. 1E), demonstrating that the reporter reproduced our observations in WT BMDMs.

Fig. 3. Il12b-IRES-eYFP reporter BMDMs expressing the highest levels of YFP following LPS stimulation are enriched for DC marker genes.

Fig. 3.

Open in a new tab

(A) Microscopy image and quantification of Il12b-YFP in BMDMs following 8 hours of stimulation with 100 ng/ml LPS. (B) Flow cytometry histograms of the Il12b-YFP negative, low, and high gates for control and 100 ng/ml LPS treatment. (C-D) RT-qPCR of Tnf and Il6 (C) and DC-associated markers Ccr7 and H2-Ab1 and macrophage-associated marker Fcgr1 (D) for cells sorted from the YFP negative, low, and high gates. One sample was collected and analyzed.

We sorted BMDMs into three Il12b-YFP levels following 100 ng/ml LPS stimulation: YFP-high (top 3.4%), YFP-low, and YFP-negative (Fig. 3B). We measured transcript levels of selected phenotypic markers in each group by RT-qPCR relative to an unstimulated BMDM (M0) control. We found that the average Tnf transcript level in YFP-high cells was similar to YFP-neg cells, while the Il6 transcript level was lower (Fig. 3C), confirming a change in LPS-induced activity.

We considered the possibility that YFP-high cells result from heterogeneity in differentiation of the hematopoietic precursors. Such heterogeneity has been observed for differentiation with GM-CSF, in which the resulting population is a mixture of bone marrow-derived dendritic cells (BMDCs) and BMDMs (29). The receptor for M-CSF, CSF1R/CD115, is expressed by the macrophage and DC progenitor (MDP) and the common DC progenitor (CDP) (37). Considering that M-CSF supports the development of bona fide DCs from bone marrow progenitors in vitro (24, 38), , and DCs are high IL-12 producers (12), we hypothesized that these cells might exhibit characteristics of DCs. In line with this hypothesis, we found that Il12b-YFP-high cells were enriched for the DC-associated markers Ccr7 (encoding CCR7) and H2-Ab1 (encoding part of the MHCII protein complex), with lower abundance of the macrophage-associated marker Fcgr1 (encoding CD64) as compared to the Il12b-YFP-low and -neg populations (Fig. 3D). Repeating the same experiment following stimulation of TLR2 (with 100ng/ml PAM3CSK) produced similar results (Supplemental Fig. 2), demonstrating that the activation of a distinct IL-12-high subpopulation is not unique to LPS. Overall, these data suggest that BMDMs producing the highest levels of Il12b have a more DC-like phenotype with a distinct inflammatory profile.

We next compared our DC-like BMDMs with GM-CSF-derived BMDCs and BMDMs, which we identified via surface markers (29). We differentiated bone marrow progenitors from the C57BL/6 Il12b-IRES-eYFP reporter mouse with GM-CSF and treated them with 100 ng/ml LPS. We sorted cells based on the expression of markers MHCIIhiCD11chiCD11bint-high (in both adherent and non-adherent cells; Supplemental Fig. 3A) to obtain three populations: GM-DCs, GM-Macs and GM-Macs (adherent), which we then compared with BMDMs for their Il12b-YFP expression level (Supplemental Fig. 3B).

As expected, GM-DCs had significantly more Il12b-YFP than macrophage populations. We then compared macrophage- and DC-associated surface markers between the BMDM-Il12b-YFP subpopulations, GM-DCs and GM-Macs, as well as a BMDM untreated M0 control (Supplemental Fig. 3C). The BMDM-Il12b-YFP-high population showed a slight enrichment for the DC-associated MHCII expression, and reduced expression of macrophage-associated CSF1R after both LPS and PAM3CSK4 stimulation (Supplemental Fig. 3D). However, visualizing BMDMs using UMAP based on the relative intensity of 10 surface markers (not YFP), we observed two areas of YFP+MHCIIhiCSF1Rlo cells that did not separate from the overall population and were F4/80+ (Supplemental Fig. 3E). Therefore, we conclude that the subset of cells with Il12b expression and a DC-like phenotype cannot be readily identified by surface marker expression.

scRNA-seq reveals a distinct cell cluster with high Il12b transcription and with characteristics of dendritic cells

Although these DC-like cells could not be readily identified by surface markers, we hypothesized that we could identify them in scRNA-seq data. To explore this possibility, we reanalyzed our previously published data set for BMDMs that were untreated or stimulated for 6 hours with 10 ng/ml LPS+10 U/ml IFN-γ or with 100 ng/ml IL-4 (25). We identified clusters using Leiden clustering and visualized the clusters using UMAP (Fig. 4A). Although the treatments clustered separately overall, “Cluster 5” was located between the treatment clusters and included cells from all three treatments. Cells in Cluster 5 that had been treated with LPS+IFN-γ were enriched for Il12b expression (Fig. 4B), confirming their identify. Importantly, we observed that Cluster 5 expressed genes associated with the DC lineage, including Ccr7 and Flt3, as well as H2-Aa (associated with MHCII expression; Supplemental Fig. 4A). Even though the number of cells in Cluster 5 was small, bootstrapped error bars indicated that these genes were significantly enriched over the other clusters.

Fig. 4. scRNA-seq of BMDMs reveals a cluster of DC-like cells with enhanced Il12b expression following IFN-γ+LPS stimulation.

Fig. 4.

Open in a new tab

(A-B) UMAP of BMDM scRNA-seq data colored by treatment (left) and by Leiden cluster (right) (A) and by expression level of Il12b. Data are reanalyzed from ref. 25. (C) Hierarchical clustering of BMDM Leiden clusters from (A) according to their expression of macrophage and DC signature genes. (D) Hierarchical clustering of BMDM Leing clusters with signatures of DCs from ImmGen tissue database.

We assembled a list of genes that are associated with the macrophage versus DC lineage, based on signatures from reference studies (29, 39). When we quantified relative differential expression of these gene signatures across the clusters, we found that Cluster 5 was strongly enriched for the DC signature, including Flt3, Ccr7, Itgax (encoding for CD11c) and Zbtb46. All the other clusters were enriched for the macrophage signature, including Cd14, Csf1r (encoding for CD115), Adgre1 (encoding for F4/80), and Mertk (Fig. 4C). To determine if Cluster 5 resembled DCs from tissues, we compared its average scRNA-seq signature to RNA-seq signatures from DCs isolated from tissues that are available in ImmGen (33). We found that Cluster 5 clustered with the tissue DCs, while Clusters 0–4 clustered separately (Fig. 4D).

DCs are further subdivided into conventional DCs (with subsets cDC1, cDC2, and cDC3) and monocyte-derived DCs (moDCs) (3). We noted that several of the genes enriched in Cluster 5 are specific for conventional DCs (e.g., Flt3, and Zbtb46) and others are further associated with cDC1s (Ly75 and Cd24a). This is consistent with the observation that IL-12 production has been predominantly attributed to the cDC1 subset (40). However, staining BMDMs for CD24 and XCR1 could not identify this population at the protein level (Supplemental Fig. 4B). Thus, while the gene expression profile of Cluster 5 exhibits characteristics of cDC1s, their surface markers cannot be distinguished from BMDMs.

To confirm that these cells are present in other in vitro preparations of BMDMs, we analyzed a published data set in which cells were differentiated in the presence of L-929 cell media for 7 days (41). L-cell media contains M-CSF, in addition to other factors, and is a common alternative approach for generating BMDMs in vitro (20). Following differentiation, cells were left unstimulated, or stimulated with IFN-γ+LPS, or with IL-4+IL-13 for 24 hours (vs. 6 hours in our experiments), and scRNA-seq data was collected for each treatment. We projected these data into UMAP space and again found that a small cluster of cells (Cluster 4) were situated between the three treatments, although all cells included in this cluster were from the IFN-γ+LPS treatment (Supplemental Fig. 4C). Cluster 4 had increased expression of Il12b, as well as Ccr7 and H2-Dmb2 (Supplemental Fig. 4D), and it was enriched for the DC-like gene signature, while the remaining clusters were enriched for the macrophage signature (Supplemental Fig. 4E). Overall, we conclude that a small fraction of cells differentiated into BMDCs in the presence of M-CSF, and that these cells express the highest level of Il12b transcript upon treatment with LPS ± IFN-γ.

The DC cluster has a distinct response to LPS that could confound interpretation of LPS-treated BMDMs

We used the scRNA-seq data to evaluate how the inflammatory response in the DC cluster differed from the rest of the BMDM population. The total number of BMDCs identified following LPS+IFN-γ comprised almost 5% of all cells in this condition, as compared to less than 1% of cells in the untreated and IL-4-treated condition (Fig. 5A), suggesting that the distinct state of these cells is more apparent following inflammatory activation.

Fig. 5. LPS+IFN-γ stimulates a distinct transcriptional program in BM-DCs as compared to BMDMs.

Fig. 5.

Open in a new tab

(A) Fraction of cells in each treatment that are included in the DC cluster (cluster 5). Total number of cells is indicated above the bar. (B) UMAP plots of the scRNA-seq data across the conditions introduced in Fig. 4 with cells colored by expression intensity of the indicated genes. (C) Average expression for the DC cluster (cluster 5) vs. control BMDMs (clusters 0 and 4), IL-4-treated BMDMs (cluster 1) and LPS/I-treated BMDMs (clusters 2 and 3). Error bars indicate the 95% confidence intervals calculated by bootstrapping. (D) Average expression for BM-DCs for the indicated targets in each treatment. Error bars indicate the 95% confidence intervals calculated by bootstrapping. (E) Pathway analysis on the DEGs in for BMDMs and the DC-like cluster.

To evaluate the response, we compared the entire DC cluster to BMDM cluster(s) from each other treatment (i.e. BMDM control, BMDM IL-4, and BMDM LPS/I). Average Il12b expression was more than 3-fold greater in the DC cluster as compared to BMDMs treated with LPS+IFNγ, while Tnf expression was reduced approximately 5-fold and Ccl5 expression was similar (Fig. 5B–C). This is consistent with the observations by single-cell secretion (Fig. 2). In addition, Ccl22 expression was significantly increased in the DC cluster, as was Ccl17 and Socs2. Interestingly, when DCs were evaluated by treatment condition, we observed that Ccl17 increased following IL-4 treatment, while Ccl22 was increased across every condition, although the sample size was small (Fig. 5D).

Finally, we performed pathway analysis on the LPS-stimulated macrophages and the DC cluster. The DC cluster was enriched for positive regulation of T-cells and antigen presentation, while macrophages exhibited upregulation in TNF production, the LPS response, and positive regulation of the MAP kinase cascade (Fig. 5E). Overall, we conclude that the DC cluster exhibits a distinct response to LPS as compared to BMDMs that is consistent with the distinct functionality of DCs in vivo.

Discussion

M-CSF-derived BMDMs have been used as a model to study macrophage biology in countless studies. Although it has been reported that M-CSF supports the development of DCs from bone marrow progenitors in vitro (24, 38), the prevailing assumption has been that the CD11b+ cells obtained via M-CSF differentiation constitute pure macrophage populations. Here, we demonstrate that the CD11b+F4/80+fraction of BMDMs contains a distinct subset of cells that exhibit a DC phenotype. Upon exposure to LPS, the DC subset displays distinct functional properties, most notably a significantly increased capacity to secrete IL-12p40. This subset is distinct from the “first responder” macrophages that produce high levels of TNF and other inflammatory cytokines and chemokines (5, 26). Thus, M-CSF-derived BMDM cultures exhibit multiple layers of heterogeneity, both phenotypic and functional, that affect interpretation of studies exploring acute inflammatory responses.

Differentiation of murine bone marrow precursors with M-CSF is the most standardized method to generate murine macrophages in vitro (20, 21). Macrophages can also be generated from bone marrow precursors via differentiation with GM-CSF, but although macrophages are enriched in the adherent fraction (42), it still contains a population of BMDCs (29). This is consistent with the observation that GM-CSF can expand some populations of cDCs in vivo (43), and thus is not typically used for macrophage differentiation. In contrast, the combinations of growth factors and ligands used for in vitro generation of DCs from the bone marrow is more varied. GM-CSF is commonly used (42), but this produces a heterogenous population of cells with distinct ontogenies, including bona fide macrophage (GM-Mac) and dendritic cell (GM-DC) populations as discussed previously (29). The addition of IL-4 to GM-CSF-differentiated bone marrow cultures promotes a more DC-specific transcriptional program in monocytes (44). Flt3-L, the ligand that binds to the FMS-like tyrosine kinase 3 (Flt3) receptor expressed on the common dendritic cell progenitor (CDP) (45), is increasingly used to generate a more homogeneous in vitro population of conventional DCs from total murine bone marrow. By using different combinations of these ligands (GM-CSF, IL-4, and Flt3-L) it is possible to tune the types of DCs generated in vitro (44).

Based on literature evidence and the totality of our data, we propose that the high IL-12p40-producing cells represent bona fide classical DCs. Helft et al studied the ontogeny of BMDCs obtained with GM-CSF and showed that CD11c+MHCII+ population contains cells derived from both the CDP and the common monocyte progenitor (cMoP) (46). DCs derived from the CDP are in the minority, but Helft et al noted that they could be distinguished by their expression of CD135/Flt3 (and lack of expression of CD115/CSF1R). They labeled these CD11c+MHCIIhiCSF1R–Flt3+ cells GM-DCs because they constitute bona fide DCs by ontogenetic criteria. Notably, the DC cluster in BMDMs expresses Flt3 and Zbtb46, bona fide DC markers, and exhibit reduced expression Csf1r (which we also observed to some extent at the protein level; Supp. Fig. 3C–E). It has been shown that M-CSF can compensate for Flt3-L in generating DCs from CDPs, which express CSF1R (the receptor for M-CSF) (24). Although Flt3−/− progenitors are more responsive to this pathway than WT progenitors, Durai et al. showed that M-CSF could support the development of cDCs from WT bone marrow in vitro (24). We note, however, that our finding is distinct from Durai et al because we identified DCs in the adherent fraction of the M-CSF-treated BM culture, while they isolated DCs from the non-adherent fraction.

An alternate possibility to direct differentiation via M-CSF is that BMDMs in the culture secrete DC growth factors that indirectly promote the development of DCs. However, based on the scRNA-seq data, there is little to no expression of transcripts for common DC growth factors including Csf2 (GM-CSF), Flt3l (Flt3L), and Il4 (IL-4), which suggests that such an indirect pathway is unlikely. Indeed, there are many examples of a role for M-CSF in DC differentiation and proliferation in vivo (47–49). This raises the possibility that M-CSF provides an alternate means of generating DCs in environments in which Flt3-L is scarce.

The fraction of DCs we identified by scRNA-seq was <1% in our untreated BMDM scRNA-seq data, but LPS stimulation significantly increased the DC signature, suggesting that activation and maturation expose underlying differences in lineage that are not obvious in the unstimulated state. This has important implications for proper identification of cells using scRNA-seq data from tissues. For example, we recently explored scRNA-seq data of myeloid cells in the melanoma tumor microenvironment with and without stimulation with CD40 agonist + CSF1R inhibitor + anti-PD-1 for 24 hours (50). While most myeloid cells were classified as macrophages in the untreated condition, a substantial fraction were classified as DCs in the treated condition with an inflammatory signature very similar to the one observed in this data set. Thus, it is possible that scRNA-seq data is unable to fully disentangle macrophages and DCs in the basal state, but that their differential function is exposed upon stimulation.

Supplementary Material

1

Key points.

  • A small subset of BMDMs secretes a majority of IL-12p40 upon LPS stimulation.

  • Phenotypic and sequencing analysis shows that this subset contains dendritic cells.

  • Dendritic cells are consistently present in M-CSF-differentiated BMDMs.

References

  • 1.Satija R, and Shalek AK. 2014. Heterogeneity in immune responses: from populations to single cells. Trends in immunology 35: 219–229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Guilliams M, Ginhoux F, Jakubzick C, Naik SH, Onai N, Schraml BU, Segura E, Tussiwand R, and Yona S. 2014. Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nature reviews. Immunology 14: 571–578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Cabeza-Cabrerizo M, Cardoso A, Minutti CM, Pereira da Costa M, and Reis e Sousa C. 2021. Dendritic Cells Revisited. Annu Rev Immunol 39: 131–166. [DOI] [PubMed] [Google Scholar]
  • 4.Patil S, Fribourg M, Ge Y, Batish M, Tyagi S, Hayot F, and Sealfon SC. 2015. Single-cell analysis shows that paracrine signaling by first responder cells shapes the interferon-beta response to viral infection. Science signaling 8: ra16. [DOI] [PubMed] [Google Scholar]
  • 5.Xue Q, Lu Y, Eisele MR, Sulistijo ES, Khan N, Fan R, and Miller-Jensen K. 2015. Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation. Science signaling 8: ra59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, Chen P, Gertner RS, Gaublomme JT, Yosef N, Schwartz S, Fowler B, Weaver S, Wang J, Wang X, Ding R, Raychowdhury R, Friedman N, Hacohen N, Park H, May AP, and Regev A. 2014. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 509: 363–369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Wimmers F, Subedi N, van Buuringen N, Heister D, Vivie J, Beeren-Reinieren I, Woestenenk R, Dolstra H, Piruska A, Jacobs JFM, van Oudenaarden A, Figdor CG, Huck WTS, de Vries IJM, and Tel J. 2018. Single-cell analysis reveals that stochasticity and paracrine signaling control interferon-alpha production by plasmacytoid dendritic cells. Nature communications 9: 3317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Deak P, Studnitzer B, Ung T, Steinhardt R, Swartz M, and Esser-Kahn A. 2022. Isolating and targeting a highly active, stochastic dendritic cell subpopulation for improved immune responses. Cell Rep 41: 111563. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Antonioli L, Blandizzi C, Pacher P, Guilliams M, and Hasko G. 2019. Rethinking Communication in the Immune System: The Quorum Sensing Concept. Trends in immunology 40: 88–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Teng MW, Bowman EP, McElwee JJ, Smyth MJ, Casanova JL, Cooper AM, and Cua DJ. 2015. IL-12 and IL-23 cytokines: from discovery to targeted therapies for immune-mediated inflammatory diseases. Nat Med 21: 719–729. [DOI] [PubMed] [Google Scholar]
  • 11.D’Andrea A, Rengaraju M, Valiante NM, Chehimi J, Kubin M, Aste M, Chan SH, Kobayashi M, Young D, Nickbarg E, and et al. 1992. Production of natural killer cell stimulatory factor (interleukin 12) by peripheral blood mononuclear cells. J Exp Med 176: 1387–1398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Trinchieri G 2003. Interleukin-12 and the regulation of innate resistance and adaptive immunity. Nature reviews. Immunology 3: 133–146. [DOI] [PubMed] [Google Scholar]
  • 13.Macatonia SE, Hosken NA, Litton M, Vieira P, Hsieh CS, Culpepper JA, Wysocka M, Trinchieri G, Murphy KM, and O’Garra A. 1995. Dendritic cells produce IL-12 and direct the development of Th1 cells from naive CD4+ T cells. J Immunol 154: 5071–5079. [PubMed] [Google Scholar]
  • 14.Tait Wojno ED, Hunter CA, and Stumhofer JS. 2019. The Immunobiology of the Interleukin-12 Family: Room for Discovery. Immunity 50: 851–870. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Abdi K, and Singh NJ. 2015. Making many from few: IL-12p40 as a model for the combinatorial assembly of heterodimeric cytokines. Cytokine 76: 53–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Grazia Cappiello M, Sutterwala FS, Trinchieri G, Mosser DM, and Ma X. 2001. Suppression of Il-12 transcription in macrophages following Fc gamma receptor ligation. J Immunol 166: 4498–4506. [DOI] [PubMed] [Google Scholar]
  • 17.Kobayashi T, Matsuoka K, Sheikh SZ, Elloumi HZ, Kamada N, Hisamatsu T, Hansen JJ, Doty KR, Pope SD, Smale ST, Hibi T, Rothman PB, Kashiwada M, and Plevy SE. 2011. NFIL3 is a regulator of IL-12 p40 in macrophages and mucosal immunity. J Immunol 186: 4649–4655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Tong AJ, Liu X, Thomas BJ, Lissner MM, Baker MR, Senagolage MD, Allred AL, Barish GD, and Smale ST. 2016. A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation. Cell 165: 165–179. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Allen NC, Philip NH, Hui L, Zhou X, Franklin RA, Kong Y, and Medzhitov R. 2019. Desynchronization of the molecular clock contributes to the heterogeneity of the inflammatory response. Science signaling 12. [DOI] [PubMed] [Google Scholar]
  • 20.Assouvie A, Daley-Bauer LP, and Rousselet G. 2018. Growing Murine Bone Marrow-Derived Macrophages. Methods Mol Biol 1784: 29–33. [DOI] [PubMed] [Google Scholar]
  • 21.Murray PJ, Allen JE, Biswas SK, Fisher EA, Gilroy DW, Goerdt S, Gordon S, Hamilton JA, Ivashkiv LB, Lawrence T, Locati M, Mantovani A, Martinez FO, Mege JL, Mosser DM, Natoli G, Saeij JP, Schultze JL, Shirey KA, Sica A, Suttles J, Udalova I, van Ginderachter JA, Vogel SN, and Wynn TA. 2014. Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41: 14–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Piccolo V, Curina A, Genua M, Ghisletti S, Simonatto M, Sabo A, Amati B, Ostuni R, and Natoli G. 2017. Opposing macrophage polarization programs show extensive epigenomic and transcriptional cross-talk. Nat Immunol 18: 530–540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Ramirez-Carrozzi VR, Braas D, Bhatt DM, Cheng CS, Hong C, Doty KR, Black JC, Hoffmann A, Carey M, and Smale ST. 2009. A unifying model for the selective regulation of inducible transcription by CpG islands and nucleosome remodeling. Cell 138: 114–128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Durai V, Bagadia P, Briseno CG, Theisen DJ, Iwata A, Davidson J. T. t., Gargaro M, Fremont DH, Murphy TL, and Murphy KM. 2018. Altered compensatory cytokine signaling underlies the discrepancy between Flt3(−/−) and Flt3l(−/−) mice. J Exp Med 215: 1417–1435. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Munoz-Rojas AR, Kelsey I, Pappalardo JL, Chen M, and Miller-Jensen K. 2021. Co-stimulation with opposing macrophage polarization cues leads to orthogonal secretion programs in individual cells. Nature communications 12: 301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Alexander AF, Kelsey I, Forbes H, and Miller-Jensen K. 2021. Single-cell secretion analysis reveals a dual role for IL-10 in restraining and resolving the TLR4-induced inflammatory response. Cell Rep 36: 109728. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Bass VL, Wong VC, Bullock ME, Gaudet S, and Miller-Jensen K. 2021. TNF primarily modulates transcriptional burst size of NF-kB-regulated genes. Molecular systems biology 17: e10127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Mueller F, Senecal A, Tantale K, Marie-Nelly H, Ly N, Collin O, Basyuk E, Bertrand E, Darzacq X, and Zimmer C. 2013. FISH-quant: automatic counting of transcripts in 3D FISH images. Nat Methods 10: 277–278. [DOI] [PubMed] [Google Scholar]
  • 29.Helft J, Bottcher J, Chakravarty P, Zelenay S, Huotari J, Schraml BU, Goubau D, and Reis e Sousa C. 2015. GM-CSF Mouse Bone Marrow Cultures Comprise a Heterogeneous Population of CD11c(+)MHCII(+) Macrophages and Dendritic Cells. Immunity 42: 1197–1211. [DOI] [PubMed] [Google Scholar]
  • 30.Wolf FA, Angerer P, and Theis FJ. 2018. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19: 15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Traag VA, Waltman L, and van Eck NJ. 2019. From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports 9: 5233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, and Vilo J. 2019. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res 47: W191–W198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.ImmGen C 2016. Open-source ImmGen: mononuclear phagocytes. Nat Immunol 17: 741. [DOI] [PubMed] [Google Scholar]
  • 34.Lu Y, Xue Q, Eisele MR, Sulistijo ES, Brower K, Han L, Amir el AD, Pe’er D, Miller-Jensen K, and Fan R. 2015. Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands. Proc Natl Acad Sci U S A 112: E607–615. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Becht E, McInnes L, Healy J, Dutertre CA, Kwok IWH, Ng LG, Ginhoux F, and Newell EW. 2018. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. [DOI] [PubMed] [Google Scholar]
  • 36.Reinhardt RL, Hong S, Kang SJ, Wang ZE, and Locksley RM. 2006. Visualization of IL-12/23p40 in vivo reveals immunostimulatory dendritic cell migrants that promote Th1 differentiation. J Immunol 177: 1618–1627. [DOI] [PubMed] [Google Scholar]
  • 37.Liu K, Victora GD, Schwickert TA, Guermonprez P, Meredith MM, Yao K, Chu FF, Randolph GJ, Rudensky AY, and Nussenzweig M. 2009. In vivo analysis of dendritic cell development and homeostasis. Science 324: 392–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Fancke B, Suter M, Hochrein H, and O’Keeffe M. 2008. M-CSF: a novel plasmacytoid and conventional dendritic cell poietin. Blood 111: 150–159. [DOI] [PubMed] [Google Scholar]
  • 39.Miller JC, Brown BD, Shay T, Gautier EL, Jojic V, Cohain A, Pandey G, Leboeuf M, Elpek KG, Helft J, Hashimoto D, Chow A, Price J, Greter M, Bogunovic M, Bellemare-Pelletier A, Frenette PS, Randolph GJ, Turley SJ, Merad M, and Immunological Genome C. 2012. Deciphering the transcriptional network of the dendritic cell lineage. Nat Immunol 13: 888–899. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Ashour D, Arampatzi P, Pavlovic V, Forstner KU, Kaisho T, Beilhack A, Erhard F, and Lutz MB. 2020. IL-12 from endogenous cDC1, and not vaccine DC, is required for Th1 induction. JCI Insight 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Li C, Menoret A, Farragher C, Ouyang Z, Bonin C, Holvoet P, Vella AT, and Zhou B. 2019. Single cell transcriptomics based-MacSpectrum reveals novel macrophage activation signatures in diseases. JCI Insight 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Inaba K, Inaba M, Romani N, Aya H, Deguchi M, Ikehara S, Muramatsu S, and Steinman RM. 1992. Generation of large numbers of dendritic cells from mouse bone marrow cultures supplemented with granulocyte/macrophage colony-stimulating factor. J Exp Med 176: 1693–1702. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Ryu SH, Shin HS, Eum HH, Park JS, Choi W, Na HY, In H, Kim TG, Park S, Hwang S, Sohn M, Kim ED, Seo KY, Lee HO, Lee MG, Chu MK, and Park CG. 2021. Granulocyte Macrophage-Colony Stimulating Factor Produces a Splenic Subset of Monocyte-Derived Dendritic Cells That Efficiently Polarize T Helper Type 2 Cells in Response to Blood-Borne Antigen. Front Immunol 12: 767037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Gerber-Ferder Y, Bourdely P, Vetillard M, Guermonprez P, and Helft J. 2023. In Vitro Generation of Murine Bone Marrow-Derived Dendritic Cells. Methods Mol Biol 2618: 83–92. [DOI] [PubMed] [Google Scholar]
  • 45.Naik SH, Sathe P, Park HY, Metcalf D, Proietto AI, Dakic A, Carotta S, O’Keeffe M, Bahlo M, Papenfuss A, Kwak JY, Wu L, and Shortman K. 2007. Development of plasmacytoid and conventional dendritic cell subtypes from single precursor cells derived in vitro and in vivo. Nat Immunol 8: 1217–1226. [DOI] [PubMed] [Google Scholar]
  • 46.Hettinger J, Richards DM, Hansson J, Barra MM, Joschko AC, Krijgsveld J, and Feuerer M. 2013. Origin of monocytes and macrophages in a committed progenitor. Nat Immunol 14: 821–830. [DOI] [PubMed] [Google Scholar]
  • 47.Tagliani E, Shi C, Nancy P, Tay CS, Pamer EG, and Erlebacher A. 2011. Coordinate regulation of tissue macrophage and dendritic cell population dynamics by CSF-1. J Exp Med 208: 1901–1916. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Percin GI, Eitler J, Kranz A, Fu J, Pollard JW, Naumann R, and Waskow C. 2018. CSF1R regulates the dendritic cell pool size in adult mice via embryo-derived tissue-resident macrophages. Nature communications 9: 5279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.MacDonald KP, Rowe V, Bofinger HM, Thomas R, Sasmono T, Hume DA, and Hill GR. 2005. The colony-stimulating factor 1 receptor is expressed on dendritic cells during differentiation and regulates their expansion. J Immunol 175: 1399–1405. [DOI] [PubMed] [Google Scholar]
  • 50.Krykbaeva I, Bridges K, Damsky W, Pizzurro GA, Alexander AF, McGeary MK, Park K, Muthusamy V, Eyles J, Luheshi N, Turner N, Weiss SA, Olino K, Kaech SM, Kluger HM, Miller-Jensen K, and Bosenberg M. 2023. Combinatorial Immunotherapy with Agonistic CD40 Activates Dendritic Cells to Express IL12 and Overcomes PD-1 Resistance. Cancer Immunol Res 11: 1332–1350. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1966433-supplement-1.pdf (7.1MB, pdf)

RESOURCES