Modulation of macrophage subtypes by IRF5 determines osteoclastogenic potential

Yang, Jihyun; Park, Ok‐Jin; Kim, Jiseon; Kwon, Yeongkag; Yun, Cheol‐Heui

doi:10.1002/jcp.28863

Cited by 26 publications

(26 citation statements)

References 34 publications

(64 reference statements)

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“…M1 and M2 is a subclassification of macrophages wherein M1 macrophages are classically activated and pro‐inflammatory, whereas M2 macrophages are alternatively activated and anti‐inflammatory. ( 46 ) Recent evidence demonstrates that M2 macrophages are more efficient at osteoclastogenesis compared with M1 macrophages, ( 47 ) which is consistent with our previous report, ( 10 ) and we validated herein (Figs. 4 and 5) that OM form more osteoclasts than BM Mφ.…”

Section: Discussionsupporting

confidence: 93%

Neonatal Osteomacs and Bone Marrow Macrophages Differ in Phenotypic Marker Expression and Function

Mohamad

Gunawan

Blosser

et al. 2020

Journal of Bone and Mineral Research

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Osteomacs (OM) are specialized bone‐resident macrophages that are a component of the hematopoietic niche and support bone formation. Also located in the niche are a second subset of macrophages, namely bone marrow–derived macrophages (BM Mφ). We previously reported that a subpopulation of OM co‐express both CD166 and CSF1R, the receptor for macrophage colony‐stimulating factor (MCSF), and that OM form more bone‐resorbing osteoclasts than BM Mφ. Reported here are single‐cell quantitative RT‐PCR (qRT‐PCR), mass cytometry (CyTOF), and marker‐specific functional studies that further identify differences between OM and BM Mφ from neonatal C57Bl/6 mice. Although OM express higher levels of CSF1R and MCSF, they do not respond to MCSF‐induced proliferation, in contrast to BM Mφ. Moreover, receptor activator of NF‐κB ligand (RANKL), without the addition of MCSF, was sufficient to induce osteoclast formation in OM but not BM Mφ cultures. OM express higher levels of CD166 than BM Mφ, and we found that osteoclast formation by CD166−/− OM was reduced compared with wild‐type (WT) OM, whereas CD166−/− BM Mφ showed enhanced osteoclast formation. CD110/c‐Mpl, the receptor for thrombopoietin (TPO), was also higher in OM, but TPO did not alter OM‐derived osteoclast formation, whereas TPO stimulated BM Mφ osteoclast formation. CyTOF analyses demonstrated OM uniquely co‐express CD86 and CD206, markers of M1 and M2 polarized macrophages, respectively. OM performed equivalent phagocytosis in response to LPS or IL‐4/IL‐10, which induce polarization to M1 and M2 subtypes, respectively, whereas BM Mφ were less competent at phagocytosis when polarized to the M2 subtype. Moreover, in contrast to BM Mφ, LPS treatment of OM led to the upregulation of CD80, an M1 marker, as well as IL‐10 and IL‐6, known anti‐inflammatory cytokines. Overall, these data reveal that OM and BM Mφ are distinct subgroups of macrophages, whose phenotypic and functional differences in proliferation, phagocytosis, and osteoclast formation may contribute physiological specificity during health and disease. © 2021 American Society for Bone and Mineral Research (ASBMR).

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Section: Discussionsupporting

confidence: 93%

Neonatal Osteomacs and Bone Marrow Macrophages Differ in Phenotypic Marker Expression and Function

Mohamad

Gunawan

Blosser

et al. 2020

Journal of Bone and Mineral Research

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“…Our SVM model predicted that IRF5 may function as a repressor of osteoclast differentiation through the activation of IRF8. Consistent with this prediction, Yang et al(2019) [23] reported that silencing IRF5 increased osteoclast differentiation. However, in this study, NFATc1 expression leads to suppression of IRF5 expression.…”

Section: Resultsmentioning

confidence: 66%

“…The training is done using the class labels, OCU and OCD, as summarized in Table 5. In addition, total 213 ChIP-seq identified putative IRF8 target genes obtained from mouse GC B cell lines [23] and 6,812 ChIP-seq identified NFATc1 target genes from Harmonizome [43] have been fed into the learned models.…”

Section: Choosing Key Genes and Incorporating Chip-seq Identified Targetsmentioning

confidence: 99%

Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP

et al. 2022

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Background Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context. Method We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple “functional groups” of marker genes pertaining to the concerned biological process. It uses two notions, Gene-Present Sufficiently (GP) and Gene-Absent Insufficiently (GA), in addition to log2 fold changes of differentially expressed genes for the prediction. Target prediction is made by applying multiple machine-learning models, which learn the patterns of GP and GA from log2 fold changes and four types of Z scores from the normalized cohort’s gene expression data. The learned patterns are then associated with the putative transcription factor targets to identify genes that consistently exhibit Up/Down gene regulation patterns within the cohort. We applied this method to 11 publicly available GEO data sets related to osteoclastgenesis. Result Our experiment identified a small number of Up/Down IRF8 and NFATc1 target genes as relevant to osteoclast differentiation. The machine learning models using GP and GA produced NFATc1 and IRF8 target genes different than simply using a log2 fold change alone. Our literature survey revealed that all predicted target genes have known roles in bone remodeling, specifically related to the immune system and osteoclast formation and functions, suggesting confidence and validity in our method. Conclusion cTAP was motivated by recognizing that biologists tend to use Z score values present in data sets for the analysis. However, using cTAP effectively presupposes assembling a sizable cohort of gene expression data sets within a comparable context. As public gene expression data repositories grow, the need to use cohort-based analysis method like cTAP will become increasingly important.

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“…A previous report showed that peritoneal macrophages from adiponectin-deficient mice express M1 markers (30). It was recently reported that M1 macrophages have inefficient osteoclastogenic potential compared to M2 macrophages (31, 32). Thus, we examined the immunological and osteoclastogenic properties of CD11b-positive osteoclast precursors from various sources including PBMCs, peritoneal cells, and bone marrow cells.…”

Section: Resultsmentioning

confidence: 99%

“…When osteoclastogenic potential and macrophage phenotypes were examined using peritoneal macrophages, lower numbers of TRAP + MNCs with higher IL-6 and lower IL-10 induction were also observed in adiponectin-deficient peritoneal macrophages compared to wild-type (Figures 5D,E), implying that adiponectin-deficient macrophages have attenuated osteoclastogenic potential with M1-like properties. We recently reported that M2 macrophages have higher osteoclastogenic potential than M1 macrophages (32). Since adiponectin-deficient osteoclast precursors had M1-like properties in the current study, we hypothesized that adiponectin-exposed osteoclast precursors could polarize into M2-like macrophages, thereby possessing high osteoclastogenic potential.…”

Section: Resultsmentioning

confidence: 99%

Adiponectin Deficiency Triggers Bone Loss by Up-Regulation of Osteoclastogenesis and Down-Regulation of Osteoblastogenesis

et al. 2019

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Osteoporosis and bone disorders related to the metabolic syndrome are often associated with adipokines secreted by adipocytes in bone. Adiponectin, a type of adipokine, is a regulator of immune responses and metabolic processes, but its role in bone biology remains uncertain. We investigated the role of adiponectin in bone metabolism using adiponectin-deficient mice in vivo and in vitro. Adiponectin-deficient mice exhibited reduced bone mass and increased adiposity. Adiponectin-deficient calvarial cells were prone to differentiate into adipocytes rather than osteoblasts. Although bone marrow macrophages (BMMs) from adiponectin-deficient mice had low osteoclastogenic potential as osteoclast precursors with increasing interferon regulatory factor 5 expression, under co-culture conditions of calvarial cells and BMMs, the enhanced receptor activator of nuclear factor κB ligand/osteoprotegerin (RANKL/OPG) ratio of adiponectin-deficient mesenchymal progenitor cells facilitated osteoclast differentiation. In addition, increased RANKL/OPG ratio was observed in the bone marrow extracellular fluid of adiponectin-deficient mice compared to that of wild-type mice. Notably, recombinant adiponectin treatment enhanced RANKL-induced osteoclast differentiation from BMMs but up-regulated OPG production in recombinant adiponectin-exposed calvarial cells, which inhibited osteoclast differentiation. Taken together, these results suggest that adiponectin plays an inhibitory role in bone metabolism through cross talk between precursor cells of both osteoclasts and osteoblasts by regulating RANKL/OPG ratio in the bone marrow microenvironment.

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Modulation of macrophage subtypes by IRF5 determines osteoclastogenic potential

Cited by 26 publications

References 34 publications

Neonatal Osteomacs and Bone Marrow Macrophages Differ in Phenotypic Marker Expression and Function

Neonatal Osteomacs and Bone Marrow Macrophages Differ in Phenotypic Marker Expression and Function

Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP

Adiponectin Deficiency Triggers Bone Loss by Up-Regulation of Osteoclastogenesis and Down-Regulation of Osteoblastogenesis

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