Research Article

Chronic TLR7 and TLR9 signaling drives anemia via differentiation of specialized hemophagocytes

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Science  11 Jan 2019:
Vol. 363, Issue 6423, eaao5213
DOI: 10.1126/science.aao5213

Unmasking an agent of inflammatory anemia

Infectious and autoimmune diseases are associated with anemia and thrombocytopenia. A severe form of inflammatory cytopenia called macrophage activation syndrome (MAS) may occur during rheumatological disorders and viral infections. Akilesh et al. show that monocyte recognition of self- or pathogen-derived nucleic acids via Toll-like receptors 7 and 9 (TLR7 and TLR9) drives MAS-like disease in mice. TLR7 or TLR9 signaling in monocytes causes these cells to differentiate into inflammatory hematophagocytes (iHPCs), which are similar to but distinct from red pulp macrophages. Preventing iHPC differentiation by depleting monocytes relieves MAS-like symptoms. When mice were subjected to a model of malarial anemia, MyD88- and endosomal TLR-dependent iHPC differentiation also occurred. Thus, iHPCs may play a role in both MAS-driven and malarial anemia, as well as thrombocytopenia.

Science, this issue p. eaao5213

Structured Abstract


Inflammatory disorders and infections are associated with cytopenias, including anemia and thrombocytopenia. Common to these conditions is activation of the innate immune system, which includes the monocyte/macrophage lineage, through receptors that recognize pathogen-derived molecules. Toll-like receptors (TLRs) are one family of pathogen sensors that recognize bacterial and viral ligands, including pathogen-derived nucleic acids through TLR7 and TLR9. TLRs not only recognize pathogens, leading to clearance of infection, they are also implicated in inflammatory and autoimmune disease. How signaling through TLRs in monocytes and/or macrophages may participate in inflammation- and infection-associated cytopenias is not completely understood.


The phagocytosis of red blood cells (RBCs), platelets, and leukocytes can be a major contributor to acute cytopenias. Thus, we reasoned that specialized phagocytes may develop in inflammatory conditions in response to the signaling of pattern-recognition receptors, such as TLRs. In vitro, TLR signaling can directly induce macrophage development. However, whether TLR-induced differentiation specifies a particular macrophage fate that is distinct from homeostatic macrophage differentiation is not clear. To address this question, we undertook in vitro and in vivo studies to investigate TLR-induced macrophage differentiation and the role of this process in inflammatory cytopenias.


Transcriptional profiling of macrophages differentiated through TLR7 signaling in vitro showed that these cells have a gene signature similar to red pulp macrophages (RPMs), the steady-state hemophagocytes of the spleen. Using a mouse model of TLR7-driven inflammation (the TLR7.1 mouse), we found a population of hemophagocytes that were distinct from RPMs by cell-surface phenotype and that were not found in uninflamed wild-type mice. Therefore, we have termed these cells “inflammatory hemophagocytes,” or iHPCs. iHPCs shared expression of the transcription factor Spi-C with RPMs but showed higher phagocytic uptake of RBCs. Thus, iHPCs, although similar to RPMs, are a distinct population of hemophagocytes.

iHPCs required cell-intrinsic TLR7 signaling for their development and differentiated from inflammatory Ly6Chi monocytes by way of IRF5. Signaling in these monocytes through TLR7 or TLR9—but not through TLR4, TLR3, interleukin-1β, or interferon-γ—induced the iHPC phenotype, and chronic depletion of monocytes caused a severe reduction in iHPC numbers. TLR7.1 mice showed progressive severe anemia and thrombocytopenia with age, and blocking iHPC differentiation through monocyte depletion rescued these inflammatory cytopenias. We next asked whether infection-driven anemia and thrombocytopenia also involved iHPCs. Infection of mice with RBC stage Plasmodium yoelii 17XNL, a model of malarial anemia, showed MyD88 and endosomal TLR-dependent iHPC differentiation. Thus, iHPCs differentiate in situations of both sterile and infectious cytopenias.


We identified a previously unknown TLR7/9-driven monocyte differentiation pathway associated with inflammatory cytopenias. We propose that macrophage activation syndrome (MAS), a life-threatening complication of rheumatological diseases or viral infection associated with acute cytopenias, may be caused by iHPCs and that these cells also drive severe malarial anemia. Our studies suggest unexplored avenues to treat MAS, severe malarial anemia, and “anemia of inflammation.”

iHPCs differentiate in response to TLR7 and TLR9 signals and participate in inflammation-induced anemia.

(A) Before release into the circulation, Ly6Chi monocytes develop in the bone marrow from hematopoietic stem cells (HSCs) and common myeloid progenitors (CMPs). During inflammation, including TLR7 overexpression and Plasmodium infection, Ly6Chi monocytes differentiate into hemophagocytes in response to signaling from the endosomal nucleic acid–sensing receptors TLR7 and TLR9 by means of the IRF5 transcription factor. These splenic iHPCs phagocytose RBCs and express the transcription factor Spi-C and cell-surface proteins CD31 and DR3. (B) iHPCs drive inflammatory anemia and thrombocytopenia, such as that seen in MAS and severe malarial anemia.


Cytopenias are an important clinical problem associated with inflammatory disease and infection. We show that specialized phagocytes that internalize red blood cells develop in Toll-like receptor 7 (TLR7)–driven inflammation. TLR7 signaling caused the development of inflammatory hemophagocytes (iHPCs), which resemble splenic red pulp macrophages but are a distinct population derived from Ly6Chi monocytes. iHPCs were responsible for anemia and thrombocytopenia in TLR7-overexpressing mice, which have a macrophage activation syndrome (MAS)–like disease. Interferon regulatory factor 5 (IRF5), associated with MAS, participated in TLR7-driven iHPC differentiation. We also found iHPCs during experimental malarial anemia, in which they required endosomal TLR and MyD88 signaling for differentiation. Our findings uncover a mechanism by which TLR7 and TLR9 specify monocyte fate and identify a specialized population of phagocytes responsible for anemia and thrombocytopenia associated with inflammation and infection.

Inflammatory disorders and infections are associated with cytopenias, including anemia and thrombocytopenia. However, the mechanisms underlying these phenomena are poorly understood. A particularly acute and life-threatening form of inflammatory cytopenia is seen in macrophage activation syndrome (MAS), in which activated macrophages containing red blood cells (RBCs) and leukocytes are found in the bone marrow, spleen, and liver (1, 2). MAS is a severe complication of some rheumatological diseases, most commonly in systemic juvenile idiopathic arthritis (sJIA) and pediatric lupus, or MAS can develop after viral infections, such as with Epstein–Barr virus (1, 3, 4). Severe cytopenias, principally anemia and thrombocytopenia, also occur during acute malaria infection, particularly in young children, in whom it can cause mortality (57). Thus, an understanding of the mechanisms underlying cytopenias that accompany inflammatory disease and infection is important in order to identify points of therapeutic intervention for these conditions.

The phagocytosis of RBCs, platelets, and leukocytes can be a major contributor to acute cytopenias. Thus, we reasoned that specialized phagocytes may develop in inflammatory conditions in response to the signaling of pattern-recognition receptors, such as Toll-like receptors (TLRs). TLRs are well known to trigger cytokine production from mature myeloid cells, such as macrophages. However, little is known about the role of TLRs in specifying myeloid cell development. TLRs are highly expressed on hematopoietic stem and progenitor cells (HSPCs), beginning with hematopoietic stem cells (HSCs) through to more committed myeloid progenitor cells, such as common myeloid progenitors (CMPs). The treatment of HSPCs with TLR agonists in vitro can induce macrophage differentiation in the absence of the homeostatic macrophage differentiation factor M-CSF (macrophage colony-stimulating factor) (810). However, it is unclear whether this occurs in vivo. Viral or bacterial infection or injection of mice with TLR agonists leads to characteristic changes in HSPCs, which correlate with the increased production of neutrophils and monocytes in a process termed “emergency myelopoiesis” or “demand-adapted hematopoiesis” (11). However, many of these effects depend on the TLR-induced production of inflammatory cytokines—including interleukin-3 (IL-3), IL-6, interferon-γ (IFNγ), and type I IFN—from mature myeloid cells or nonhematopoietic cells that promote myelopoiesis (10, 12). Thus, in contrast to its potent effects in vitro, the cell-intrinsic role of TLR signaling in directing monocyte/macrophage differentiation in vivo remains an open question.

TLR7 promotes hemophagocyte development in vitro and in vivo

We hypothesized that TLR signaling may drive a specialized macrophage phenotype. To test this hypothesis, we used an in vitro culture system in which bone marrow CMPs were cultured with the TLR7 agonist R848. This approach efficiently induced the differentiation of CD11b+F4/80+ macrophages after 4 days (Fig. 1A) (9). We compared the transcriptional profiles of macrophages differentiated from CMPs with R848 with those differentiated with the homeostatic macrophage-differentiating growth factor M-CSF and found 813 up-regulated and 1020 down-regulated transcripts [greater than or equal to twofold, false discovery rate (FDR) ≤ 0.05] in macrophages from R848 compared with M-CSF cultures (Fig. 1B). The gene encoding the transcription factor Spi-C (Spic), which governs splenic red pulp macrophage (RPM) development (13) was significantly up-regulated, suggesting that TLR7 signaling in CMPs may preferentially promote differentiation of RPM-like cells (Fig. 1B). These R848-differentiated macrophages most strongly resembled RPMs in comparison with microglia, peritoneal macrophages, and alveolar macrophages (Fig. 1C). Furthermore, they were enriched for a core set of genes that distinguish RPMs from these other tissue macrophage populations (Fig. 1D) (14). The hallmark function of RPMs is the phagocytosis of RBCs (“hemophagocytosis”) (15). R848-differentiated macrophages efficiently phagocytosed RBCs (Fig. 1E). Thus, TLR7 signaling in CMPs dictates the development of hemophagocytic RPM-like macrophages in vitro.

Fig. 1 TLR7 promotes RPM-like hemophagocyte development in vitro.

(A) Representative flow cytometric staining of CMPs cultured with SCF or SCF+R848. (B to D) RNA-seq analysis of CD11b+F4/80+ macrophages sorted from CMPs differentiated in R848 or M-CSF. (B) Of the 22,707 total protein coding genes, 813 were up-regulated and 1020 were down-regulated in R848-differentiated macrophages with to M-CSF–differentiated macrophages (greater than or equal to twofold, FDR ≥ 0.05). Three independent biological replicates were sequenced for each condition. (C) Red bars indicate the percent of genes in a tissue macrophage core transcriptional signature (14) that were significantly increased in R848-differentiated compared with M-CSF–differentiated macrophages. Black line indicates –log P value calculated by using exact hypergeometric probability with a normal approximation. (D) Heat map of increased genes (greater than or equal to twofold, FDR ≥ 0.05) in R848-differentiated compared with M-CSF–differentiated macrophages in RPM core signature. (E) R848-differentiated macrophages were treated with or without cytochalasin D (CytoD) then allowed to phagocytose CFSE-labeled RBC for 15 min at indicated ratios. Percent of CD11b+F4/80+ macrophages that had phagocytosed RBC is shown. Data are representative of four experiments, n = 3 technical replicates per condition/experiment. (E) Mean values + SD are shown.

To examine whether TLR7 signaling increased hemophagocyte development in vivo, we used TLR7.1 mice (16), which overexpress TLR7 approximately 10-fold under its own regulatory elements, including in HSPCs and mature myeloid cells (12). Among CD45+ leukocytes that had internalized RBCs (as determined with intracellular anti-Ter-119 staining), we identified a small number of hemophagocytic leukocytes in the spleens of wild-type (WT) mice, which exhibited cell-surface staining CD11bint/loF4/80hi consistent with RPMs (Fig. 2, A to C). Significantly higher numbers of hemophagocytes were found in the spleen and bone marrow of TLR7.1 mice (Fig. 2, A and B, and fig. S1). These cells had increased levels of intracellular anti-Ter-119 staining, suggesting that hemophagocytes in TLR7.1 mice were more phagocytic than in WT mice. Furthermore, although a small population of hemophagocytes in TLR7.1 mice resembled RPMs through F4/80 and CD11b staining, the majority were CD11bint/hiF4/80lo (Fig. 2C). These hemophagocytes lacked the high vascular cell adhesion molecule (VCAM) and CD64 expression associated with RPMs and expressed higher levels of CD31 and CD55. They also expressed similar levels of SIRPα (signal regulatory protein α) and TREML4 (triggering receptor expressed on myeloid cells like 4) compared with RPMs (Fig. 2D). Thus, most hemophagocytes in TLR7.1 mice appeared to represent a population of hemophagocytes distinct from RPMs. Hemophagocytes with the identical phenotype were found in the spleen after daily injection with the TLR7 agonist R848 (fig. S2). Because these CD11bint/hiF4/80lo hemophagocytes did not exist in untreated or non-inflamed WT mice, we have termed them “inflammatory hemophagocytes,” or iHPCs.

Fig. 2 TLR7 signaling drives formation of hemophagocytes distinct from RPMs in vivo.

(A to D) Splenocytes from WT and TLR7.1 mice were surface-stained for CD11b, CD45.2, F4/80, Ly6G, and Siglec-F and then intracellularly stained with monoclonal antibody to Ter-119 to detect leukocytes that had phagocytosed RBCs. (A) Representative flow cytometry pre-gated as live singlets, CD45.2+ cells. Before intracellular staining with fluorescently labeled antibody to Ter-119, some samples were blocked with unconjugated Ter-119 (control). Other samples were not blocked before staining (Ter-119). (B) Frequency and number of CD45.2+Ly6GSiglec-FTer-119+ cells and mean fluorescence intensity (MFI) of Ter-119 staining in CD45.2+Ter-119+ cells were then quantified. Data are representative of four experiments. (C) CD11b and F4/80 expression on CD45.2+Ly6GSiglec-FTer-119+ splenocytes. iHPCs are in blue, and RPMs are in red. Data are representative of four experiments. (D) RPMs were gated as CD45.2+Ly6GSiglec-F-Ter-119+ cells that were CD11bint/loF4/80hi, and iHPCs were gated as CD45.2+Ter-119+ cells that were CD11bint/hiF4/80lo. Histograms of indicated surface staining are shown. Data are representative of four experiments. (E) Percentage of RPMs or iHPCs that were Ter-119+ from WT and TLR7.1 mice quantified by means of flow cytometry. Data are representative of four experiments, n = 5 mice per group. (F and G) RPMs and iHPCs were fluorescence-activated cell–sorted and stained with H&E. Intracellular RBCs were quantitated by means of microscopy. (G) Phagocytic index (number of intracellular RBCs per 100 cells) (left) and percentage of cells with at least one RBC (right) were calculated. Data are representative of two experiments, n = 3 to 4 mice per group. In (B), mean ± SEM; in (F) and (G), mean + SEM; and in (B), each symbol represents an individual mouse. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, two-tailed, unpaired Student’s t test (B). One-way analysis of variance (ANOVA) with Tukey’s post test (E).

Gating iHPCs and RPMs by using only cell-surface markers (fig. S3) showed that TLR7.1 iHPCs were approximately two- to threefold more phagocytic than RPMs from either WT or TLR7.1 mice as measured with intracellular anti-Ter-119 staining (Fig. 2E). Sorting of iHPCs and RPMs followed by hematoxylin and eosin (H&E) staining confirmed that the anti-Ter-119 staining corresponded to internalized RBCs and showed that more iHPCs contained multiple RBCs, confirming that these cells were more phagocytic than RPMs (Fig. 2, F and G). Thus, iHPCs, although similar to RPMs, are a distinct population of hemophagocytes.

iHPCs differentiate in response to cell-intrinsic TLR7 signals and do not require Spi-C

We next investigated the developmental pathway of iHPCs. To determine whether iHPCs require cell-intrinsic TLR7 signaling to develop or whether the inflammation present in TLR7.1 mice is sufficient for this process, we used mixed bone marrow chimeras. Whereas splenic B cells and monocytes reconstituted at the 1:1 ratio of the input bone marrow, iHPCs were almost solely derived from TLR7.1 bone marrow with an ~100:1 ratio of TLR7.1:WT iHPCs (Fig. 3A and fig. S4, A to C). Thus, iHPCs specifically develop in response to cell-intrinsic chronic TLR7 signaling.

Fig. 3 iHPCs differentiate in response to cell-intrinsic TLR7 signals.

(A) The ratio of TLR7.1 to WT BM-derived cells in mixed bone marrow chimeras of indicated populations after reconstitution. Data are representative of two experiments with n = 8 to 10 mice per experiment. (B) The ratio of WT to Tlr7−/− BM-derived cells in mixed bone marrow chimeras injected with the TLR7 agonist R848 (right) or PBS (left) for 13 days. Data are representative of two experiments, with n = 3 to 5 mice per group per experiment. In (A) and (B), mean ± SEM; in (A) and (B), each symbol represents an individual mouse. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA with Dunnett’s post test [(A) and (B)].

We used the R848 injection model to determine whether TLR7 signaling is required for iHPC development. After R848 injection in mixed WT:Tlr7−/− bone marrow chimeras, monocytes were found at the 1:1 WT:Tlr7−/− ratio of the input bone marrow. However, iHPCs were heavily skewed toward WT cells at a ratio of ~100:1 (Fig. 3B and fig. S5, A and B). Thus, cell-intrinsic TLR7 signaling promotes and is required for iHPC development in vivo. Therefore TLR7 signaling plays a critical role in the induction of a specific macrophage phenotype induced during TLR7-driven inflammation.

The transcription factor Spi-C is required for RPM development (13) and is also highly expressed in macrophages generated by TLR7 signaling in vitro (Fig. 1, B and D). Splenic iHPCs sorted directly ex vivo from TLR7.1 mice also expressed high levels of Spic mRNA comparable with RPMs, and in contrast to splenic Ly6Chi monocytes (fig. S6A). Because of the functional similarities between RPMs and iHPCs and our observation that both express high levels of Spi-C, we hypothesized this transcription factor would be required for iHPC differentiation. Therefore, we generated TLR7.1/Spic−/− mice. As expected, both Spic−/− and TLR7.1/Spic−/− mice had few splenic RPMs, and Spic−/− mice showed a significant reduction in total hemophagocytes in comparison with WT mice (fig. S6, B to D) because most of these cells are Spic-dependent RPMs. Surprisingly, TLR7.1/Spic−/− mice had similar numbers of splenic hemophagocytes as TLR7.1/Spic+/+ and TLR7.1/Spic+/− mice (fig. S6C). When the total hemophagocyte population was separated into RPMs and iHPCs (fig. S6, D and E), there was no difference in iHPC frequency or number in TLR7.1 mice regardless of Spic expression. Similarly, in our in vitro differentiation system, there was no difference in R848-induced macrophage differentiation from Spic+/− and Spic−/− CMPs (fig. S6F). Thus, Spi-C is not required for iHPC development in vivo or in vitro, demonstrating that iHPCs develop through a program distinct from RPMs.

iHPCs differentiate from Ly6Chi monocytes

In the steady state, many tissue macrophages, including RPMs, are derived from embryonic yolk sac– or fetal liver–derived progenitors that locally self-renew. However, monocytes can replenish some but not all of these populations both in the steady state or during inflammation or other perturbations (1719). For example, RPMs can be replaced by “classical” or “inflammatory” Ly6Chi monocyte–derived cells after RPM death because of heme-mediated toxicity (20). Thus, we asked whether TLR7-induced iHPCs are derived from Ly6Chi inflammatory monocytes. iHPCs did not express the defining inflammatory monocyte markers CCR2 or Ly6C and had low expression of the tissue macrophage marker CD64 similar to Ly6Chi monocytes (Fig. 4A). Ly6Chi monocytes also expressed low levels of the iHPC marker CD31. Culture of Ly6Chi monocytes with TLR7 ligands induced phenotypic changes associated with iHPCs, including the induction of Spic and Pecam1 (encoding CD31) and the reduced expression of Ccr2 and Ly6c1 (Fig. 4B). Thus, although Ly6Chi monocytes had a distinct cell-surface phenotype from iHPCs, TLR7 signaling in Ly6Chi monocytes caused transcriptional changes associated with the iHPC phenotype, suggesting that iHPCs differentiate from Ly6Chi monocytes in response to TLR7 signals.

Fig. 4 iHPCs are derived from Ly6Chi monocytes.

(A) Splenic monocytes (live singlets, CD11b+F4/80Ly6GLy6Chi or CCR2+ cells) (black) and iHPCs (live singlets, F4/80loLy6GTer-119+VCAM1lo or CD31hi cells) (blue) were assessed for the expression of the cell-surface proteins indicated (solid lines) compared with fluorescence minus one (FMO) control stains (dashed lines). Data are representative of three experiments. (B) Bone marrow Ly6Chi monocytes were sorted from WT B6 mice and cultured for 21 hours with media alone (–) or with R848. Spic, Pecam1, Ccr2, and Ly6c1 transcripts were quantified by means of quantitative polymerase chain reaction (PCR). Data are representative from five experiments, with n = 3 mice per experiment. (C and D) Ccr2-DTR, Ccr2-DTR+, TLR7.1/Ccr2-DTR, and TLR7.1/Ccr2-DTR+ mice (n = 5 to 7 mice per group) were injected with DT every other day for 17 days. (C) Representative flow cytometry of Ter-119+ hemophagocytes pre-gated on live singlets, CD45.2+Ly6GSiglec-F cells from the spleens of TLR7.1/Ccr2-DTR and TLR7.1/Ccr2-DTR+ mice determined by means of flow cytometry. (D) Frequency and number of the indicated cell populations were quantitated from the spleens of Ccr2-DTR, Ccr2-DTR+, TLR7.1/Ccr2-DTR, and TLR7.1/Ccr2-DTR+ mice by means of flow cytometry. Data are combined from three experiments. (E) Bone marrow Ly6Chi monocytes were sorted from WT B6 mice and cultured for 21 hours with media alone (–), R848, LPS, or CpG. Spic, Pecam1, Ccr2, and Ly6c1 transcripts were quantified by means of quantitative PCR. Data are representative from two experiments. (F and G) RNA-seq analysis of RPMs and Ly6Chi monocytes sorted from spleens of WT B6 mice and TLR7.1 mice and iHPCs from spleens of TLR7.1 mice. n = 5 mice (TLR7.1 iHPC), n = 4 mice (WT and TLR7.1 RPM), and n = 6 mice (WT and TLR7.1 Mono). (F) Principal components analysis of indicated populations. (G) Heat map of differentially expressed genes between the three populations (RPMs, Ly6Chi monocytes, and iHPCs) sorted from TLR7.1 mice. Mean values + SEM (D), ±SEM [(B) and (E)]. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, two-tailed, unpaired Student’s t test (B) and Mann-Whitney U test (D).

To directly assess whether iHPCs derive from Ly6Chi monocytes, we crossed TLR7.1 mice to Ccr2-DTR mice, in which injection of diphtheria toxin (DT) results in the depletion of Ly6Chi monocytes within 24 hours and which can be maintained over time with subsequent DT injections (2123). Ly6Chi monocyte depletion over 2.5 weeks (fig. S7, A and B) caused a significant reduction in total splenic hemophagocytes and iHPCs in TLR7.1/Ccr2-DTR mice, in comparison with TLR7.1 mice not expressing the Ccr2-DTR transgene (Fig. 4, C and D). Consistent with the fact that iHPCs do not express CCR2 (Fig. 4A), a single DT injection into TLR7.1/Ccr2-DTR mice depleted Ly6Chi monocytes but not iHPCs after 24 hours (fig. S7, B and C). Thus, iHPCs were not directly depleted by DT injections. Two and a half weeks of DT treatment also significantly reduced RPM numbers in TLR7.1/Ccr2-DTR mice (fig. S7E), suggesting that during chronic TLR7-driven inflammation, not only are iHPCs derived from Ly6Chi monocytes but RPMs are also replaced by monocyte-derived cells.

The transcriptional changes in Ly6Chi monocytes associated with the iHPC phenotype were not specific to TLR7 signaling. Signaling via TLR9 through CpG DNA also induced Spic and Pecam1 and reduced Ccr2 and Ly6c1 in Ly6Chi monocytes (Fig. 4E). Signaling via TLR4 only caused some of the iHPC transcriptional changes; lipopolysaccharide (LPS) induced Spic and reduced Ccr2 but did not induce Pecam1 or reduce Ly6c1 expression (Fig. 4E). We also assessed IL-1β, which, similar to TLRs, signals by means of MyD88. IL-1β signaling was similar to LPS in that it induced Spic but not Pecam1 (fig. S8A). We also tested signaling with polyinosinic:polycytidylic acid [poly(I:C)] through TLR3, which uses TRIF exclusively and is expressed at low levels on Ly6Chi monocytes (14). TLR3 signaling did not significantly induce Spic and Pecam1 or reduce Ly6c1 expression. However TLR3 signaling did significantly reduce Ccr2 expression to a lesser extent than other TLR agonists tested (fig. S8B). Last, IFNγ, a classic monocyte activator, did not induce any of the transcriptional changes associated with iHPC differentiation in Ly6Chi monocytes (fig. S8A). Thus, TLR7 and TLR9 signaling alone drive the iHPC phenotype in Ly6Chi monocytes.

To further assess how iHPCs are related to Ly6Chi monocytes and RPMs, we performed RNA-sequencing (RNA-seq) analysis of these populations from naïve WT and TLR7.1 mice. Principal component analysis of these data revealed that TLR7.1 iHPCs cluster separately from both Ly6Chi monocytes and RPMs, whether they were derived from WT or TLR7.1 mice (Fig. 4F), reinforcing their particular iHPC identity. Unsupervised hierarchical clustering of iHPCs, Ly6Chi monocytes, and RPMs from TLR7.1 mice by using significantly differentially expressed genes [fold-change (FC) > 1.5, FDR < 0.05] between these three populations also highlighted these differences and demonstrated a closer relationship between iHPCs and Ly6Chi monocytes than between iHPCs and RPMs. We also used this dataset to identify distinct surface markers of iHPCs to better distinguish them from Ly6Chi monocytes and RPMs by means of flow cytometry (fig. S9A). Of those tested, DR3, encoded by Tnfrsf25, was best at identifying iHPCs because it is expressed in neither Ly6Chi monocytes nor RPMs. DR3 used in conjunction with CD31 reliably identified TLR7.1 splenic iHPCs that were uniformly expressing Spi-C and enriched for hemophagocytes (fig. S9, B to D). Thus, transcriptional profiling supports our contention that iHPCs are a distinct population of Ly6Chi monocyte-derived cells.

Monocyte-derived iHPCs drive TLR7 and TLR9-induced MAS-like disease

The presence of iHPCs in TLR7.1 mice was associated with anemia characterized by reduced RBC count that typically developed by 3 months of age (Fig. 5A) (16). The percent and number of splenic iHPCs was inversely correlated with the RBC count in a cohort of TLR7.1 mice (Fig. 5B). The lack of RPMs, but not iHPCs, in TLR7.1/Spic−/− mice allowed us to assess the contribution of RPMs versus iHPCs in anemia. Similar to published results, we found no difference in RBC count between Spic+/+, Spic+/−, and Spic−/− mice, suggesting that in the steady state, Spi-C–dependent RPMs are not major contributors to RBC homeostasis (13). TLR7.1/Spic−/− mice developed anemia similarly to TLR7.1/Spic+/+ and TLR7.1/Spic+/− mice (Fig. 5C), showing that RPMs do not contribute to TLR7-driven anemia and suggesting that iHPCs are sufficient to cause this outcome.

Fig. 5 Monocyte-derived iHPCs drive anemia.

(A) RBC count, hemoglobin levels, and hematocrit from 3-month-old WT and TLR7.1 mice. Each symbol represents an individual mouse, n = 8 to 12 mice per group. (B) Correlation between RBC count and number (left) and frequency (right) of splenic Ter-119+ iHPCs in TLR7.1 mice. (C) RBC count of TLR7.1 WT, TLR7.1 Spic+/−, TLR7.1 Spic−/−, and control mice that were bled before 8 weeks and between 9 and 13 weeks of age. n = 7 to 14 mice per group. (D) TLR7.1/Ccr2-DTR and TLR7.1/Ccr2-DTR+ mice were treated with DT every other day for 17 days beginning when RBC count was below 8. RBC count was measured at indicated times. n = 5 to 7 mice per group. (E) Ccr2-DTR and Ccr2-DTR+ mice were treated with DT every day for 6 days and CpG daily starting 1 day after beginning DT treatment. RBC count was measured before and at the end of treatment. Data are representative of two experiments, n = 3 (No Tx) and n = 7 (CpG) mice per group. (F) Platelet counts in TLR7.1/Ccr2-DTR and TLR7.1/Ccr2-DTR+ mice treated as in (D). Mean values ± SEM [(A) and (C) to (F)] are shown. In (A) and (B), each symbol represents an individual mouse.*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns, not significant; Mann-Whitney (A), Wilcoxon paired t test of days −1 and +17 for TLR7.1 experiment and −1 and +5 for CpG injection [(D) to (F)].

The lack of iHPCs in DT-injected TLR7.1/Ccr2-DTR mice allowed us to ask whether iHPCs drive anemia in the TLR7.1 model by beginning depletions once anemia was detected (fig. S7A). TLR7.1 mice not expressing the Ccr2-DTR transgene became progressively more anemic during the course of DT treatment, whereas anemia was completely reversed in the DT-treated TLR7.1/Ccr2-DTR mice (Fig. 5D). Taken together with the sustained anemia in TLR7.1/Spic−/− mice that lack RPMs, we conclude that hemophagoyctosis by iHPCs is required for TLR7-driven anemia. We also investigated a model of anemia caused by chronic TLR9 signaling induced with repetitive CpG DNA injection in Ccr2-DTR mice (21). Similar effects of monocyte and iHPC depletion were observed in this TLR9-dependent model (Fig. 5E), indicating that hemophagocytosis by iHPCs may be a common mechanism of anemia associated with TLR7- and/or TLR9-dependent inflammation.

The anemia in TLR7.1 mice is reminiscent of the spectrum of diseases defined as MAS, in which activated macrophages cause severe cytopenias by phagocytosing RBCs as well as leukocytes and platelets (1, 2). We confirmed that TLR7.1 mice have very low platelet counts (16), even when the RBC count is still close to the range of wild-type mice (Fig. 5F). Similar to RBC counts, platelet counts were completely restored after 2.5 weeks of Ly6Chi monocyte depletion in TLR7.1/Ccr2-DTR mice (Fig. 5F). Thus, iHPCs contribute to both anemia and thrombocytopenia and likely to other aspects of the MAS-like disease in TLR7.1 mice.

This led us to ask which receptors might allow iHPCs to phagocytose RBC and, potentially, platelets and other cells. Analysis of receptors, bridging molecules, and transcription factors that have been implicated in phagocytosis of self cells in our RNA-seq dataset showed that there is a subset of these molecules expressed more highly in iHPCs than monocytes and RPMs, including genes encoding the αv integrin chain, CD300f, and the β2 integrin chain (22) (fig. S10). Additionally, genes for hemophagocytosis may be shared with RPMs, indicating possible roles for C1q, Mer (encoded by Mertk), and LXRα (encoded by Nr1h3), which are all more highly expressed in iHPCs and RPMs than monocytes.

IRF5 participates in iHPC differentiation

We propose that cytopenias in MAS can be caused by direct chronic endosomal TLR signaling in monocytes or myeloid progenitor cells. Whether because of infection, genetic perturbations in TLR signaling, and/or the increased availability of nucleic acid endosomal TLR ligands, this may directly lead to the differentiation of pathogenic iHPCs. Some forms of MAS are associated with variants in the gene encoding the IRF5, a transcription factor activated downstream of TLR signaling in monocytes and macrophages (23, 24). The MAS-associated SNPs in IRF5 are proposed to increase TLR signals (2527). Accordingly, we investigated whether IRF5 is involved in TLR7-induced iHPC differentiation. Induction of Spic and Pecam1 was significantly reduced in IRF5-deficient Ly6Chi monocytes compared with WT monocytes, whereas down-regulation of Ccr2 and Ly6c1 did not depend on IRF5 (Fig. 6A). The in vivo induction of iHPCs after R848 injection was significantly reduced in Irf5−/− mice compared with WT mice (Fig. 6, B and C). Thus, IRF5 is required for optimal iHPC differentiation, and increased IRF5 signaling is genetically associated with MAS.

Fig. 6 iHPC differentiation depends on IRF5.

(A) Bone marrow Ly6Chi monocytes were sorted from WT and Irf5−/− mice and cultured for 21 hours with media alone (–) or with R848. Spic, Pecam1, Ccr2, and Ly6c1 transcripts were quantified by means of quantitative PCR. Data are representative from two experiments with n = 2 to 4 mice per group per experiment. (B and C) WT and Irf5−/− mice were injected with R848 intraperitoneally daily for 2 days. Splenocytes were analyzed by means of flow cytometry. (B) Representative flow plots of WT and Irf5−/− CD11b+CD31+ iHPCs (gated on live singlets, CD45.2+F4/80Ly6GSiglec-F cells). (C) Frequency (left) and number (right) of iHPCs in WT and Irf5−/− spleens. Data are representative from two experiments with n = 4 mice per group per experiment. Mean values±SEM [(A) and (C)] are shown. In (A) and (C)], each symbol represents an individual mouse. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, two-tailed, unpaired Student’s t test [(A) and (C)].

iHPCs differentiate in response to endosomal TLR signaling in a preclinical model of severe malarial anemia

In addition to MAS, severe cytopenias accompany malaria caused by infection with Plasmodium falciparum and Plasmodium vivax, particularly the anemia and thrombocytopenia seen in severe malarial anemia (57). Reasoning that iHPCs may also develop during malaria, we infected mice with Plasmodium yoelii 17XNL–infected RBCs, a preclinical, nonlethal model of blood stage malaria that causes severe anemia and thrombocytopenia (Fig. 7A). RBC-stage P. yoelii infection induced hemophagocytosis (Fig. 7, B and C) (7). iHPCs were seen as early as day 5 after infection, and iHPC number peaked at the time of most severe anemia and correlated inversely with RBC count (Fig. 7, D and E). We also found iHPC differentiation during mouse cytomegalovirus (MCMV) infection of young Balb/c mice in a model of virally induced MAS (fig. S11) (28). Thus, iHPCs also differentiate during infection.

Fig. 7 iHPC development during malaria infection is dependent on Myd88 and endosomal TLRs.

(A to E) B6 mice were injected with 1 × 106 P. yoelii 17XNL-infected RBCs (solid squares) or PBS (open circles) and analyzed at indicated days [(A), (B), and (D)] or day 12 of infection (C). (A) Parasitemia as measured by means of flow cytometry of RFP-expressing P. yoelii 17XNL, and RBC and platelet count during the course of infection. (B) Percent (left) and number (right) of intracellular Ter-119+ cells of total CD45+ splenocytes. (C) Gated CD31+CD45.2+Ly6GSiglec-FTer-119+ iHPCs (blue gate) and RPMs (red gate) on day 12 of infection. (D) iHPC frequency (left) and number (right) during the course of infection. (E) Correlation of RBC count and iHPC number on all days. Data are representative of two experiments, n = 3 (PBS) and 5 to 6 (P. yoelii 17XNL) mice per group. (F and G) WT B6 and Myd88−/− mice were infected with 1 × 106 P. yoelii 17XNL-infected RBCs and analyzed at day 12 of infection (F) or the indicated days (G). (F) Gated CD11b+CD31+ iHPCs (Gated on live singlets, CD45.2+ F4/80Ly6G Siglec-F) on day 12 of infection. (G) iHPC frequency and number per spleen at day 12 of infection (left); RBC count and parasitemia at the indicated days (right). Data are representative of two experiments, n = 5 (WT) and n = 4 to 5 (Myd88−/−) mice per group. (H and I) The ratio of WT to Unc93b1−/− (H) or WT to Myd88−/−Trif−/− (I) BM-derived cells in mixed bone marrow chimeras of indicated populations before (pre) and on day 8 after (post) infection with 1 × 106 P. yoelii 17XNL-infected RBCs. Ly6Chi monocytes preinfection are from blood (open circles). Ly6Chi monocytes postinfection (black circles) and iHPCs postinfection (blue circles) are from spleen. Data are representative of two experiments. Mean values ± SEM [(A), (B), (D), (G), (H), and (I)] are shown. In (E), (G) left, (H), and (I), Each symbol represents an individual mouse. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, two-tailed, unpaired Student’s t test [(A), (B), and (G)], linear regression (E), one-way ANOVA with Tukey’s post test [(H) and (I)].

We next investigated whether TLR signals are required for Plasmodium-induced iHPC differentiation. P. yoelii–infected Myd88−/− mice, which lack most TLR signaling as well as IL-1R and IL-18R signaling, showed significantly reduced iHPC differentiation and anemia compared with that of WT mice (Fig. 7, F and G). Myd88−/− mice showed reduced parasitemia compared with that of WT mice, which may reflect the increased RBC count in Myd88−/− mice or a role for iHPCs in the clearance or sequestration of infected RBC in tissues. Mixed bone marrow chimeras showed a cell-intrinsic requirement for the TLR signaling adapters MyD88 and TRIF and for the endosomal TLR chaperone UNC93B1 in iHPC differentiation during RBC stage P. yoelii 17XNL infection (Fig. 7, H and I). Thus, cell-intrinsic endosomal TLR signaling, likely via TLR7 and/or TLR9, also drives iHPC differentiation during experimental malarial anemia.


TLR signaling has previously been shown to cause macrophage differentiation in vitro. However, in vivo evidence for a cell-intrinsic role of TLRs in this process and in defining macrophage fate has been lacking. Our work reveals a distinct developmental pathway by which myeloid progenitors and Ly6Chi monocytes respond directly to chronic TLR7 and TLR9 signaling in vitro and in vivo by inducing hemophagocytes similar to, yet distinct from, RPMs. We identified iHPCs not only in a transgenic model of TLR7 overexpression resulting in a MAS-like disease but also during RBC-stage P. yoelii 17XNL infection and during infection with MCMV. Thus, iHPCs differentiate in a broad array of situations that have systemic TLR7 and/or TLR9 activation in common (2937). Not only do these models share innate sensors, they also share anemia and thrombocytopenia during the course of infection or disease.

The iHPC program is specific to TLR7 and TLR9 signaling. In vivo, both chronic TLR7 and TLR9 signaling drive anemia, and we have precisely assessed the contribution of TLR7 to iHPC differentiation in the TLR7.1 model. During P. yoelii 17XNL infection, both MyD88 and UNC93B1-dependent endosomal TLRs promote iHPC differentiation, and MyD88 participates in the anemia seen in this infection. In vitro, TLR4, TLR7, and TLR9 agonists and IL-1β can all induce the iHPC- and RPM-expressed transcription factor Spic in bone marrow Ly6Chi monocytes, suggesting that MyD88 signaling is sufficient for Spi-C expression. This is a distinct pathway leading to Spi-C induction; previously, myeloid Spi-C expression was only linked developmentally to RPMs and a subset of bone marrow macrophages or to heme-induced signals in monocytes (13, 20, 38). Although Spi-C is critical for RPM differentiation and can repress inflammation in intestinal Cx3CR1+ macrophages (38), we found no role for Spi-C in iHPC differentiation or in TLR7-mediated MAS-like disease, although it remains possible that Spi-C subtly affects iHPC function in a manner not yet determined.

Distinct from Spi-C expression, only TLR7 and TLR9 signaling induced Ly6Chi monocyte Pecam1 transcripts that encode CD31, which is a robust marker for iHPCs in all in vivo settings we examined. Whether TLR3—an endosomal TLR that signals via TRIF—can induce the iHPC program was not tested in vivo. However, Ly6Chi monocytes did not induce Spic or Pecam1 after treatment with poly(I:C) in vitro, suggesting that TLR3/TRIF may be unable to signal for iHPC differentiation. Alternatively, the low expression of TLR3 on Ly6Chi monocytes may be insufficient. This leaves us to ask why only TLR7 and TLR9 signaling can cause iHPC differentiation. One possibility is that IRF5, which we show contributes to iHPC differentiation, couples more strongly to these endosomal TLRs than to cell-surface TLRs. Although IRF5 is activated downstream of TLR4, perhaps the balance of nuclear factor κB (NF-κB) and IRF5 activation differs downstream of surface-expressed TLR4 and endosome-expressed TLR7 and TLR9, leading to differential gene transcription. Alternatively, Ly6Chi monocytes may not use IRF5 for TLR4 signaling, unlike bone marrow–derived macrophages and other cell types, in which most of the work on IRF5 in LPS responses has been performed (23, 39). Polymorphisms in IRF5 are linked to increased susceptibility to systemic lupus erythematosus (SLE), a disease associated with innate responses to nucleic acids and in which IRF5 is constitutively activated in human CD14+ classical monocytes (4044), the corresponding population to mouse Ly6Chi monocytes. Further studies are required to determine the mechanisms by which IRF5 mediates transcriptional responses for iHPC differentiation. Particularly intriguing is the potential interplay between IRF5, Spi-C, and NF-κB p65 (38). Additionally, specific signaling components downstream of TLR7 and TLR9 in Ly6Chi monocytes may be involved in iHPC differentiation.

iHPCs are required to cause anemia and thrombocytopenia in TLR7.1 mice, which have a mild lupus-like disease, which we propose here is a model of MAS, a complication of SLE and more frequently sJIA. Although sJIA has an autoinflammatory component and can be successfully treated with IL-1–pathway blockers, sJIA patients can develop MAS on these therapies, in which MAS can be associated with infection (45). MAS, also called secondary hemophagocytic lymphohistiocytosis (HLH), can also be caused by viral infection. IRF5 polymorphisms have also been associated with increased risk of these hemophagocytic diseases (25, 26), similar to SLE. Primary or familial HLH—caused by defects in cell-mediated cytotoxicity, including mutations in PRF1 encoding perforin—may be caused by lack of viral clearance by natural killer cells and CD8+ T cells, resulting in chronic viral infection (46). Thus, a common thread among MAS or HLH may be chronic or excessive TLR7 and/or TLR9 activation, leading to iHPC differentiation.

iHPCs correlate with anemia in a malaria model, suggesting a similarity in mechanisms between MAS and severe malarial anemia. When numbers of Plasmodium-induced iHPCs are very low because of MyD88-deficiency, not only was anemia reduced but also parasitemia, suggesting that iHPCs may be exploited by Plasmodium to promote infection. Additionally, “anemia of inflammation,” in which individuals with infections develop mild to moderate anemia, may be a mild form of MAS caused by sustained TLR7 or TLR9 signaling during infection (47). This TLR-driven anemia may have protective roles against secondary bacterial infections after viral infection by reducing the amount of iron available from RBC hemolysis. Our studies not only define a distinct monocyte/macrophage induced through TLR7 and TLR9 signaling but also suggest unexplored avenues by which to treat MAS, severe malarial anemia, and “anemia of inflammation” by interfering with iHPC generation and function or by their selective depletion.

Materials and methods

Mice, BM chimeras, and in vivo treatments

TLR7.1 mice were obtained from S. Bolland (NIH) (16), Spic−/− (Spictm1Kmm) Myd88−/−(Myd88tm1.1Defr/J), and SpiciGFP/+ (Spictm2.1Kmm) mice from Jackson Labs (13, 20, 48), Ccr2-DTR mice from T. Hohl (MSKCC) (49), and BALB/c, C57BL/6, and B6.SJL mice from Jackson Labs. Irf5−/− mice were used on both C57BL/6 and BALB/c backgrounds (23). Bones from Tlr7−/−, MyD88/Trif−/−, and Unc93b1−/− mice were obtained from G. Barton (UC Berkeley). All experiments were performed under approved protocols from the Benaroya Research Institute or Feinstein Institute Institutional Animal Care and Use Committee.

Mixed bone marrow chimeras were generated by lethally irradiating (1,000 rad) recipient C57BL/6×B6.SJL F1 mice and reconstituting with a 1:1 ratio of 5×106 B6.SJL (CD45.1+) and 5 × 106 of either C57BL/6, Tlr7−/−, TLR7.1, or MyD88/Trif−/− (CD45.2+) bone marrow cells. For Unc93b1−/−: WT mixed bone marrow chimeras and controls, B6.SJL (CD45.1+) recipient mice were lethally irradiated (1,000 rad) and reconstituted with a 1:1 ratio of 5×106 C57BL/6×B6.SJL F1(CD45.1+CD45.2+) and 5 × 106 Unc93b1−/− or C57BL/6 (CD45.2) bone marrow cells. For experiments with TLR7.1/Ccr2-DTR mice, mice were injected intraperitoneally with 10 ng DT/g of body weight (List Biological Laboratories) in phosphate-buffered saline every other day for 17 days. In experiments with Tlr7−/− and B6.SJL mixed bone marrow chimeras, mice were injected intraperitoneally daily with 100 μg of R848 (Enzo Life Sciences) for 13 days. In experiments with Irf5−/−, mice were injected daily for 2 days with 100 μg of R848 (Invivogen). In CpG injection experiments with Ccr2-DTR mice, mice were injected intraperitoneally with 40 μg daily of CpG-B (ODN1826) for 5 days (Integrated DNA Technologies). To assess anemia and thrombocytopenia, mice were bled retro-orbitally with heparinized capillary tubes. Blood was run on a Hemavet Hematology Analyzer (Drew Scientific).

In malaria infection experiments, P. yoelii 17XNL expressing RFP, provided by S. Kappe and A. Vaughn (50), was passaged through a donor mouse by infection i.p. with 2 × 106 frozen infected RBCs. From day 2 of infection, the donor mouse was monitored for parasitemia by tail vein prick and flow cytometric analysis of blood. When parasitemia reached ~1%, the donor mouse was sacrificed and blood harvested. Recipient mice were each injected i.p. with 1 × 106 infected RBCs.

MCMV (Smith strain) salivary gland viral stocks were provided by J. Sun (MSKCC) (51). Five-week-old BALB/c mice were infected with 8 × 103 plaque-forming units (PFU) MCMV i.p. and monitored daily for weight loss. On day 5, mice were sacrificed. Splenocytes were then stained for iHPCs and analyzed by flow cytometry.

Cell isolation, flow cytometry, and cell sorting

CMPs were isolated as described (9). RPMs and iHPCs were isolated from spleen by digestion in a cocktail of Liberase TL (Sigma) at 0.17 mg/ml and DNase1 (Sigma) at 40 μg/ml in complete RPMI (Hyclone). Bone marrow cells were isolated by centrifugation. Splenocytes and bone marrow cells were blocked with polyclonal rat IgG (65 μg/ml, Sigma) and purified anti-mouse Ter-119 (Ter-119, 71.4 μg/ml, Biolegend) prior to cell surface staining with fluorescently labeled antibodies as indicated in Supplementary Materials and Methods. Cells were then washed and incubated in Fixable Viability Dye eF780 (eBioscience) or Live/Dead Fixable Blue Dead Cell Stain (Invitrogen). Cells were washed and prepared for intracellular staining with Fixation and Permeabilization buffer (BD Biosciences), washed in Perm/Wash buffer (BD Biosciences) and then stained with fluorescently labeled anti-Ter-119 to detect cells that had phagocytosed RBCs. To accurately assess phagocytosis, some samples were blocked intracellularly with purified anti-mouse Ter-119 (25 μg/ml) prior to intracellular staining with fluorescently labeled anti-Ter-119. To assess spleen and bone marrow cells without Ter-119 stain, cells were blocked with polyclonal rat IgG and polyclonal mouse IgG (65 μg/ml, Sigma), stained with appropriate antibodies, and then fixed with 2% paraformaldehyde. Data were acquired on an LSRII or FACSCanto (BD Biosciences) and analyzed using FlowJo (Tree Star).

For isolation of iHPCs, RPMs, and monocytes for quantitative real-time PCR and microscopic analysis, splenocytes isolated as above were stained with APC-conjugated rat anti-mouse SIRPα (P84, 1 μg/ml), incubated with anti-APC beads (Miltenyi), and positively selected on LS columns (Miltenyi). Following isolation, cells were then stained as indicated in Supplemental Materials and Methods and sorted on a FACSAria (BD Biosciences). For experiments requiring only monocytes, bone marrow was depleted using biotinylated antibodies to hamster anti-mouse CD3ε (eBio500A2, eBioscience), rat anti-mouse CD19 (6D5, Biolegend), rat anti-mouse Ly6G (1A8, Biolegend), and mouse anti-mouse NK1.1 (PK136, eBioscience) (all at 5 μg/ml), anti-biotin beads (Miltenyi), and LS columns (Miltenyi). Negatively selected bone marrow was then stained with rat anti-mouse Ly6C (HK1.4), rat anti-mouse Siglec-F (E50-2440), rat anti-mouse Ly6G (1A8), rat anti-mouse/human CD11b (M1/70), rat anti-mouse MHCII (M5/114.15.2), and hamster anti-mouse CD11c (N418). Cells were then sorted on a FACSAria (BD Biosciences) as in fig. S3.

In vitro cell culture

Sorted bone marrow CMPs were plated as previously described (9). CMPs (2500–20,000) were plated per well in 96-well plates in complete serum-free StemPro-34 media (Life Technologies) with 20 ng/ml of stem cell factor (Peprotech) for all experiments. Unless otherwise noted, 1 μg/ml of R848 (Invivogen) and 20 ng/ml of M-CSF (Peprotech) were used. For flow cytometric quantification of CD11b+ F4/80+ cells, adherent cells were isolated using cell dissociation buffer (Life Technologies) and stained with antibodies to CD11b and F4/80. Cell yield was quantified using polystyrene microspheres (Polysciences) and flow cytometry as the number of CD11b+F4/80+ events per well divided by the number of polystyrene bead events per well multiplied by the total number of polystyrene beads per well.

For gene expression analysis, sorted monocytes were plated in either RPMI alone, 100 ng/ml of LPS (List Biologicals), 3 μM CpG-C ODN2395 (Integrated DNA Technologies), 10 μg/ml of R848 (Invivogen), 40 ng/ml of MCSF (Peprotech), 100 ng/ml of IFNγ (Peprotech), 100 ng/ml of IL-1β (Miltenyi), or 25–50 μg/ml of Poly(I:C) (Invivogen).

Hemophagocytosis assay

CMPs were sorted as above and then placed in culture at 10,000 cells/well in either 10 μg/ml of R848 or 40 ng/ml of M-CSF. On day 4, cells were harvested from wells with cell dissociation buffer (Gibco), washed in Dulbecco’s Modified Eagle Medium (Gibco) supplemented with 10% fetal bovine serum (Sigma-Aldrich), plated at 50,000 cells per well in non-tissue culture treated flat bottom 96-well plates, and rested overnight. On day 5, heparinized blood was harvested from a C57BL/6 mouse, and 40 μl of whole blood (or approximately 4 × 108 RBCs) were then washed in PBS and resuspended at 2 × 107/ml in 20 ml of PBS containing 5 μM carboxyfluorescein diacetate succinimidyl ester (CFSE) (Sigma-Aldrich) and incubated at 37°C for 10 min while shaking to obtain CFSE-labeled RBCs. Following incubation, the reaction was stopped with DMEM with 10% FBS for 10 min on ice, and then washed three times. R848-differentiated macrophages were pretreated with 2 μM cytochalasin D (Calbiochem) or DMSO (Fisher) vehicle for 30 min and 10 μg/ml of purified anti-SIRPα antibody (P84) for 15 min, prior to the addition of CFSE-labeled RBCs. Following a 15-min incubation with RBCs, assay wells were washed with cold PBS and extracellular RBCs were lysed with cold ACK lysis buffer (Lonza) for 5 min on ice. Cells were then washed with cold DMEM with 10% FBS, followed by cold PBS. Macrophages were then harvested from assay plates with cell dissociation buffer (Gibco, ThermoFisher) at 37°C on a shaker for 10 min. Cells were blocked for Fc receptor binding with polyclonal rat IgG and polyclonal mouse IgG (65 μg/ml, Sigma) and stained for CD11b and F4/80 for 20 min. Samples were then washed, fixed with 2% paraformaldehyde, and analyzed on a FACSCanto (BD Biosciences) and using FlowJo software (Tree Star).


RPMs and iHPCs were sorted from spleens of TLR7.1 and WT mice, cytospun onto slides (Cytospin 4, Thermo Scientific), and stained by hematoxylin and eosin. At least two fields per sample were quantified for phagocytic index using a Leica DM2500 microscope with SPOT Software 5.1 and SPOT Insight Wide-field 4 Mp Monochrome FireWire Digital Camera. A total of 43–409 cells per sample were counted. The phagocytic index was calculated by using the following formula: PI = (% phagocytic cells containing ≥ 1 RBC) × (mean number of RBC/phagocytic cell containing RBCs).

Quantitative RT-PCR

RNA was generated using RNeasy Plus Mini Kit and RNeasy MinElute Cleanup kit (Qiagen). cDNA was synthesized using Primescript (Takara) and Invitrogen reagents with random hexamers and OligoDT primers. qPCR was performed using SYBR green reagents (Takara) on a 7500 Fast Real-Time PCR System (Applied Biosystems). Arbitrary units were calculated using the ΔΔCT method normalized to HPRT. The values were then normalized again by setting either media alone (–) or monocyte values to 1.

RNA-seq and bioinformatic analysis

CMP+R848 versus CMP+M-CSF RNA-Seq

Samples were generated by sorting CMPs and plating 10,000 cells per well of a 96-well plate in complete serum-free StemPro 34 (Gibco) media with 20 ng/ml Stem Cell Factor (Peprotech) for 4 days with 1 μg/ml of R848 (Invivogen) or 20 ng/ml of M-CSF (Peprotech). At day 4, cells were washed with Dulbecco’s Modified Eagle Medium (Gibco) supplemented with 10% fetal bovine serum (Sigma-Aldrich), rested for 24 hours, and isolated using cell dissociation buffer. Samples were sorted as propidium iodide CD11b+F4/80+ cells directly into RLT plus lysis buffer (Qiagen). RNA was generated using RNeasy kit and MinElute cleanup kit (Qiagen). RNA from three independent sorts for each M-CSF and R848-diferentiated macrophages were used for RNA sequencing.

RNA-Seq libraries were constructed from 100 ng of RNA using the TruSeq RNA Sample Preparation V2 kit (Illumina). Libraries were clustered on a flowcell using the TruSeq SR Cluster Kit, v3 using a cBot (Illumina), followed by single read sequencing on a HiSeq2500 (Illumina) for 100 cycles. FASTQ files were downloaded from

Libraries were processed via Galaxy on a local computer cluster. Libraries were aligned via TopHat (v1.4.1) to Ensembl’s Mus musculus GRCm38.78 gtf ( The –single-paired flag was set to “single,” whereas all other TopHat parameters were set to defaults. HTSeq-count (52) was used to generate gene counts with mode as “Intersection (nonempty)” and Minimum alignment quality set to 0; all others were set to default parameters.

Analysis of the 37,991 Ensembl ID count data was performed using the edgeR package (53) in the R software environment (R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. For each gene, a negative binomial general linear model (54) appropriate for count data was used for the two-group comparisons of R848 versus M-CSF. The Ensembl IDs were filtered to those that had a TMM normalized count of at least one in at least one library, which resulted in 13,690 Ensembl IDs used in the general linear model. The two-group comparison had an 18% biological coefficient of variation and 1833 protein coding Ensembl IDs had a false discovery rate less than 0.05 and fold change greater than 2 (in either direction) (Shilin Zhao, Yan Guo, Quanhu Sheng and Yu Shyr (2015). heatmap3: An Improved Heatmap Package. R package version 1.1.1.

Tissue macrophage gene signatures were identified in Gautier et al. 2012 (14). Analysis of tissue macrophage signature overlap was conducted by comparing the number of genes significantly upregulated (>2-fold) in R848-derived macrophages versus M-CSF–derived macrophages to the number of significantly enriched genes in each tissue macrophage signature (14) using an online tool (

iHPC, RPM, and Ly6Chi monocyte RNA-seq

Five hundred cells were sorted into lysis buffer from the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara). Reverse transcription was performed followed by PCR amplification to generate full-length amplified cDNA. Sequencing libraries were constructed using the NexteraXT DNA sample preparation kit (Illumina) to generate Illumina-compatible barcoded libraries. Libraries were pooled and quantified using a Qubit Fluorometer (Life Technologies). Dual-index, single-read sequencing of pooled libraries was carried out on a HiSeq2500 sequencer (Illumina) with 58-base reads, using HiSeq v4 Cluster and SBS kits (Illumina) with a target depth of 5 × 106 reads per sample. Basecalls were processed to FASTQs on BaseSpace (Illumina), and a base call quality trimming step was applied to remove low-confidence base calls from the ends of reads.

Libraries were processed via Galaxy as above. Analysis of the 37,991 Ensembl ID count data was performed using voom from the limma package updated for RNA-sequencing experiments (55) in the R software environment. The Ensembl IDs were filtered to those that encoded for protein coding genes, and had a TMM normalized count of at least one count per million in at least 10% of the libraries, which resulted in 12,856 Ensembl IDs used in the general linear model. Samples were removed from analysis if the number of aligned reads was less than 500,000. Two-group comparisons were filtered for a false discovery rate of 0.05 after multiple testing correction, and a fold change of 1.5 or greater. Heatmaps were constructed using the heatmap3 package (54).

RNA-seq data are available in GEO SuperSeries GSE117718 containing CMP dataset (GSE70520) and iHPC dataset (GSE117711).

Supplementary Materials

Materials and Methods

Figs. S1 to S11

References and Notes

Acknowledgments: The authors thank R. Doty and the Hamerman laboratory members for helpful discussions, D. Campbell and S. Ziegler for review of the manuscript, T. Hohl for Ccr2-DTR mice, J. Sun for MCMV, G. Barton for bones from MyD88/Trif−/− and Unc93b1−/− mice, A. Vaughn and S. Kappe for RFP-expressing P. yoelii 17XNL, S. Bolland for TLR7.1 mice, and J. Abkowitz for Hemavet use. We also thank the Benaroya Research Institute Flow Cytometry Core Lab and Genomics Core for technical support and the Vivarium staff for support. We also acknowledge technical support from BioRender with the print page summary figure. Funding: This work was supported by NIH T32 AR007108 and an AAI Fellowship (H.M.A.); NSF Graduate Research Fellowship DGE-0718124 (M.B.B.); NIH T32 AI007044-39 (W.O.H.); NIH T32 AI106677 (J.M.D.); NIH R21 CA195256; DOD BCRP W81XWH-08-1-0570; Lupus Research Alliance (B.J.B.); NIH R01 DK09369 (A.L-H.); NIH R01 AI118803 (M.P.); NIH R01 AI081948, NIH R01 AI113325, and NIH R21 AI138067 (J.A.H.); and NIH R21 ES024437 (K.B.E.). Author contributions: H.M.A, M.B.B and J.A.H. conceived and designed the study. H.M.A, M.B.B, J.M.D, W.O.H, X.S., G.G., B.M., and J.A.H performed experiments. S.R.P., E.W., and M.M. performed RNA-seq analysis. K.B.E, A.L-H., B.J.B., and M.P. provided key reagents. H.M.A., M.B.B., W.O.H., K.B.E., A.L.-H., M.P., B.J.B., and J.A.H wrote the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: RNA-seq data are deposited in the NCBI Gene Expression Omnibus under SuperSeries GSE117718 containing CMP dataset (GSE70520) and iHPC dataset (GSE117711). The TLR7.1 mouse strain used in this study was obtained under a materials transfer agreement (MTA) with the National Institute of Allergy and Infectious Diseases. The P. yoelii 17XNL parasite (S1-Red) used in this study was obtained via a MTA with the Center for Infectious Disease Research, Seattle, Washington. All other data needed to evaluate the conclusions in this paper are present either in the main text or the supplementary materials.

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