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ne w s and vie w s at given sites may enable selective manipulation of the methylation states of the DMR to assess their effects on CD4 expression. Likewise, it will be interesting to explore the mechanisms of S4and E4P-mediated modulation of the DMR. Published studies have revealed key roles for lineage-specification factors not only in the establishment of lineage identity in differentiated cells but also in its maintenance. Such findings provide a rationale for the hypothesis that epigenetic modifications of specialized cis-regulatory elements may preserve cellular lineage identity and the differentiated state in the presence of fluctuating intracellular and extracellular cues. In particular, during cell division, epigenetic ‘bookmarks’ at some of these sites would ensure the inheritance of transcriptional states of key genes that define a given differentiated cell type1,9. That notion is supported by the observation that proper histone acetylation controlled by the histone deacetylases HDAC1 and HDAC2 is needed to maintain stability of the CD4+ T cell lineage by repressing the cytotoxic T cell program, including expression of CD8 and Runx3 (ref. 10). In addition, trimethylation of histone H3 at Lys27 by Ezh2, a component of the polycomb repressive complex PRC2, seems to help maintain the identity of activated regulatory T cells, a sublineage of helper CD4+ T cells11. The study by Sellars et al. makes substantial contributions to this body of work by demonstrating that the maintenance of DNA methylation or directed active demethylation may have essential roles in solidifying cytotoxic or helper T cell lineages by repressing or stabilizing CD4 expression3. It is conceivable that dynamic regulation of DNA methylation has a broader effect on the transcriptional regulation of lineage-related
genes other than Cd4. Nonetheless, the distinct roles of HDACs, Ezh2 and DNA methyltransferases indicate that permissive and repressive histone modifications, as well as DNA methylation, are used to sustain lineage-specific gene expression in different cellular and biological contexts. More studies will be needed in the future to demonstrate in a cell type–, stage-, locus- and context-specific manner how various epigenetic marks are used to maintain a stable cellular identity. Cell division has a critical part in cell fate determination12. Along with several other reports10,11,13, the observations by Sellars at al. point to cell division as a critical variable that influences lineage stability3. Although asymmetric cell division can lead to heterogeneity of the daughter cells, along with stochastic dilution of limiting transcription factors or epigenetic marks, how cell division affects T cell lineage stability remains largely unknown12–15. Examination of the effect of cell cycle on the distribution of factors that participate in transcriptional regulation and cell-lineage specification, as well as the inheritance of epigenetic modifications, will provide valuable insights into the mechanisms of the determination and maintenance of the T cell lineages. Compromised stability of heritable CD4 expression in E4P-deficient CD4+ T cells, or loss of repression of Cd4 in the absence of the silencer S4 or DNA methyltransferases in CD8+ T cells3, together with the reported role of a cis-regulatory element in sustaining regulatory T cell identity13, suggest that a distinct set of cis-regulatory elements is dedicated to the maintenance of differentiated cellular states. Unlike traditional enhancers that act together with promoters to initiate
and establish transcription upon induction, these cis elements may be dispensable for the induction of gene expression but instead are essential for the maintenance of stable gene expression in particular biological contexts that promote alternative cell fate or cell division. It seems reasonable to assume that the emergence of such dedicated cis elements owes to the increasing complexity of transcriptional regulation in multicellular organisms with a more complex body plan. The identification and characterization of additional such elements and the common molecular logic underlying their function will help to better elucidate cell-fate maintenance and offer unique tools with which to probe cellular behaviors. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Holmberg, J. & Perlmann, T. Nat. Rev. Genet. 13, 429–439 (2012). 2. Taniuchi, I. & Ellmeier, W. Adv. Immunol. 110, 71–110 (2011). 3. Sellars, M. et al. Nat. Immunol. 16, 746–754 (2015). 4. Smith, Z.D. & Meissner, A. Nat. Rev. Genet. 14, 204–220 (2013). 5. Chen, T., Ueda, Y., Dodge, J.E., Wang, Z. & Li, E. Mol. Cell. Biol. 23, 5594–5605 (2003). 6. Wu, H. & Zhang, Y. Cell 156, 45–68 (2014). 7. Rountree, M.R., Bachman, K.E. & Baylin, S.B. Nat. Genet. 25, 269–277 (2000). 8. Lee, P.P. et al. Immunity 15, 763–774 (2001). 9. Ragunathan, K., Jih, G. & Moazed, D. Science 348, 1258699 (2014). 10. Boucheron, N. et al. Nat. Immunol. 15, 439–448 (2014). 11. DuPage, M. et al. Immunity 42, 227–238 (2015). 12. Mullen, A.C. et al. Curr. Biol. 11, 1695–1699 (2001). 13. Feng, Y. et al. Cell 158, 749–763 (2014). 14. Chang, J.T. et al. Science 315, 1687–1691 (2007). 15. Kueh, H.Y., Champhekar, A., Nutt, S.L., Elowitz, M.B. & Rothenberg, E.V. Science 341, 670–673 (2013).
DCs are ready to commit Deborah R Winter & Ido Amit Dendritic cell progenitors commit to a specific conventional dendritic cell fate earlier than previously thought, by initiating transcription-factor regulatory circuits unique to their subtype.
D
endritic cells (DCs) are a critical compartment of innate immunity and perform several specialized immunological functions1. In this issue of Nature Immunology, two studies critically contribute to the understanding of Deborah R. Winter and Ido Amit are in the Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. e-mail: [email protected] or [email protected]
DC origins by demonstrating how progenitor cells commit to the various DC subtypes in mice through distinct intermediate stages. Schlitzer et al. use single-cell mRNA sequencing to analyze the heterogeneity of progenitor DC populations and find, among individual cells, varying levels of commitment to develop into specific conventional DCs (cDCs)2. Grajales-Reyes et al. use mice with expression of green fluorescent protein (GFP) from the locus encoding the transcription factor Zbtb46,
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selectively expressed by cDCs (Zbtb46GFP), and a defined sorting scheme to identify progenitors of cDC subtypes. Through the use of chromatin profiling, they identify the transcription factor IRF8 as a critical factor in the early regulatory circuits that lock cDC fate3. DCs were first observed in 1973 (ref. 4), but their location among the myeloid and lymphoid branches of the hematopoietic tree has yet to be agreed upon5. Although understanding of how the DC lineage develops 683
ne w s and vie w s Bone marrow Grajales-Reyes et al. model IRF8
Classical model
Schlitzer et al. model
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Marina Corral Spence/Nature Publishing Group
Irf8
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PrecDC1
PrecDC2
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Peripheral tissues cDC1
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Figure 1 Proposed models for DC development. The classical pathway for DC development (middle) describes the differentiation of DCs from the MDP stage, with monocyte and macrophage potential, through the CDP stage, with pDC potential, to the pre-DC stage, with only cDC potential. Pre-DCs (lineage-negative (Lin–) CD135+MHCII–CD11c+) migrate through the blood to infiltrate tissues and differentiate into both cDC subtypes9. In the regulatory circuit necessary for cDC1 commitment as described by Grajales-Reyes et al. (left), IRF8 binds together with Batf3 at a downstream enhancer in the Irf8 locus to activate its own expression3. In this model, the pre-DC compartment includes clonogenic precursors of the cDC1 subset (bottom left; Lin–CD135+CD11c+CD117intMHCIIint Zbtb46-GFP+) and cDC2 subset (bottom right; Lin–CD135+CD11c+CD117–CD115+). In the model of Schlitzer et al. (right), the pre-DC compartment is divided into four subsets: uncommitted pre-DC stage 1 (top; Siglec-H+Ly6C–); uncommitted pre-DC stage 2 (middle; Siglec-H+Ly6C+); committed pre-cDC1 (bottom left; Siglec-H–Ly6C–); and committed pre-cDC2 (bottom right; Siglec-H–Ly6C+)2. The first two stages are restricted to the bone marrow.
from the hematopoietic stem cell is still preliminary, a progenitor cell with the potential to develop into DCs, monocytes and macrophages (the MDP) has been identified in mouse bone marrow6. The MDP can give rise to a common DC progenitor (the CDP) with the capacity to differentiate into all DC subtypes7,8. According to the classical model, CDPs give rise to pre-DCs in the bone marrow, which migrate into the blood and enter the peripheral tissues to become cDCs9 (Fig. 1). DC subsets in tissues include plasmacytoid DCs (pDCs), which are distinguished by their prominent production of type I interferon, and the two major classes of cDCs, which for simplicity are referred to here as ‘cDC1’ (identified as XCR1+CD24+CD8α+ DCs), and ‘cDC2’ (identified as CD11b+CD172α+CD4+ DCs)1. The generation of these cDC subsets depends on members of the IRF family of transcription factors; specifically, IRF8 is required for the cDC1 subset, while IRF4 is crucial for the cDC2 subset10. The timing and regulatory circuits that control the commitment of DC progenitors to the cDC1 or cDC2 subtype remain elusive. Although the MDP, CDP and pre-DC populations have been characterized, little is known about the steps that lead to irreversible commitment to a DC subtype–in other words, what drives the transition between steps and 684
at what point cells commit to their specific cDC fate. In the study by Schlitzer et al., the authors analyze the transcriptome of single cells from MDP, CDP and pre-DC populations in bone marrow on the basis of conventional markers2. They find that individual cells in the DC progenitor populations are highly variable in terms of their degree of differentiation toward mature cDCs. Across the populations analyzed, a number of cells have expression profiles similar to those of either the cDC1 subset or the cDC2 subset, which suggests that these are examples of committed cells. By identifying surface markers (Siglec-H and Ly6C) among the products of genes differentially expressed by sets of single cells, the authors confirm that certain pre-DC subpopulations (Fig. 1) are already functionally committed in the bone marrow to generate predominantly either cDC1 cells or cDC2 cells, in in vitro and in vivo functional assays. These results indicate that DC specialization occurs earlier than previously appreciated. Grajales-Reyes et al. further investigate DC commitment by demonstrating that IRF8 is crucial for the development of cDC1 cells but not for that of cDC2 cells3. The authors first find that the originally defined pre-DC does not develop into cDC1 cells but rather develops only into cDC2 cells
and pDCs9. To identify the source of cDC2 cells, they use the Zbtb46GFP reporter mouse along with a carefully selected set of markers (CD117intMHCIIintCD11c+CD115–) and identify a previously unknown progenitor population that is excluded from traditional sorting schemes. The authors show that this population can differentiate selectively toward the cDC1 subset but not toward the cDC2 or pDC subset; this newly identified clonogenic cDC1 progenitor is absent in IRF8-deficient mice. Using chromatin profiling to characterize the epigenetic state surrounding the Irf8 locus, Grajales-Reyes et al. show that the transcription factor Batf3 binds at a cDC1specific enhancer (located downstream of Irf8), together with IRF8, to initiate an autoactivation loop that locks the cDC1 fate3 (Fig. 1). Interestingly, the authors show that progenitors of cDC1 cells require IRF8 but not Batf3 for early specification. This work provides a precedent for the power of combining genomic approaches with classical immunological methods to characterize key cell populations. The authors perform a comparative analysis of a single, critical locus in mature cells and defer investigation of the role of possibly unknown factors to follow-up studies. In the future, genome-wide profiling of the chromatin state in progenitor cells as well as differentiated cells will provide a global view of differentiation and the regulatory networks that drive specification11. It can be difficult to distinguish between factors involved in commitment to a specific cell fate and those involved in the maintenance of that cell fate. The observation that the activity of Batf3, in conjunction with IRF8, is critical in directing progenitors toward the cDC1 fate rather than the cDC2 fate3 explains why Batf3deficient mice produce only a small population of irregular cDC1 cells. It is possible that as the cells mature through the known phases from MDP to CDP to pre-DC, some subset will pass a certain threshold for IRF8 expression that leads them irrevocably down the cDC1 pathway. If Batf3 is not present to secure IRF8 expression, the majority of cells revert to developing into cDC2 cells, perhaps by stochastic expression of yet-to-be-identified cDC2-enforcing factors. Additional investigation is needed to determine whether the resulting cells are true cDC2 cells or are simply cDC1 cells that have lost some of their distinguishing features. It seems likely that in addition to arising from uncommitted cDC1 cells, cDC2 cells have their own positively enforcing regulatory circuits. Several transcription factors proposed to regulate differentiation into the cDC2 subset, particularly IRF4 (ref. 12), are expressed in the committed pre-cDC2 cells defined
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ne w s and vie w s in these two studies2,3. Still, the role of these factors in the process of cDC commitment remains to be demonstrated. In addition, since cDCs differ depending on the tissue in which they reside, studying bone marrow progenitors will reveal only the central programming of DC identity. For elucidation of the peripheral programing of various DC subsets, comparative studies of the regulatory networks of DC populations across tissues will be required. Presumably a number of the MDPs and CDPs analyzed by Schlitzer et al.2 are predisposed toward the pDC fate, although this is not explored in these two studies. Both studies find some evidence of pDC potential among the general pre-DC populations. Published studies have indicated the importance of IRF8 in pDC development10, which adds further complexity to the underlying regulation. Genomic analyses of chromatin and transcription-factor binding in various DC progenitors and differentiated cells may help to identify additional factors and interactions that put into perspective the combinatorial roles of IRF8 and IRF4 in the DC regulatory networks. Together these two studies use complementary genomic techniques to shed light on the stages through which a cell progresses while differentiating into specific DC subtypes2,3. They also raise the question of why some cells in the progenitor populations seem to commit at much earlier stages than others do. However, much of the present understanding is necessarily based on the average state of populations of cells. It remains unclear
when an individual cell passes the threshold of commitment to a specific fate and how to gauge the reversibility of this ‘decision’13. Studies based on single-cell analyses may hold the key to understanding cell-type heterogeneity and how individual ‘decisions’ lead to population dynamics. While powerful, these approaches can be compromised by classical definitions based solely on cell-surface markers that may not have clear links to a specific cell function or regulatory module14. Circular logic should be avoided, whereby observations such as the heterogeneous nature of a population are the direct result of a particular sorting strategy and do not necessarily reflect the underlying biology. Indeed, these two studies identify the precursor population of the cDC1 and cDC2 subsets by using different sorting strategies and cell-surface markers. It is not yet clear if these markers define the same cells and, if they do, whether these progenitors represent a homogeneous population2,3. Future studies would benefit from the use of unbiased, ‘bottom-up’ approaches to redefine populations in a biologically meaningful way. As the throughput and quality of single-cell data and analysis improve, so will the ability to study DC development and heterogeneity. An exciting time is on the horizon as the genomic revolution affects immunology, and many more integrated studies like these can be expected in the future. When handling such rich, high-throughput data, researchers will have to be extra cautious to avoid fitting the data to their assumptions and to follow up hypothesis-generating genome-wide
analyses with functional assays. As communal proficiency with newly developed genome engineering tools (such as the genomeediting approach CRISPR-Cas9) improves, researchers will be better equipped to test their findings with perturbations of regulatory networks in the immune system. Understanding the underlying regulatory networks is vital for determining the role of DCs in disease and, hence, the development of therapeutic approaches. Detailed characterization of the commitment and maintenance processes in the DC lineage will allow the development of informed therapies that target specific subsets and pathways. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Merad, M., Sathe, P., Helft, J., Miller, J. & Mortha, A. Annu. Rev. Immunol. 31, 563–604 (2013). 2. Schlitzer, A. et al. Nat. Immunol. 16, 718–728 (2015). 3. Grajales-Reyes, G.E. et al. Nat. Immunol. 16, 708–717 (2015). 4. Steinman, R.M. & Cohn, Z.A. J. Exp. Med. 137, 1142–1162 (1973). 5. Naik, S. et al. Nature 496, 229–232 (2013). 6. Fogg, D.K. et al. Science 311, 83–87 (2006). 7. Naik, S.H. et al. Nat. Immunol. 8, 1217–1226 (2007). 8. Onai, N. et al. Nat. Immunol. 8, 1207–1216 (2007). 9. Liu, K. et al. Science 324, 392–397 (2009). 10. Tamura, T. et al. J. Immunol. 174, 2573–2581 (2005). 11. Winter, D.R. & Amit, I. Immunol. Rev. 261, 9–22 (2014). 12. Vander Lugt, B. et al. Nat. Immunol. 15, 161–167 (2014). 13. Etzrodt, M., Endele, M. & Schroeder, T. Cell Stem Cell 15, 546–558 (2014). 14. Jaitin, D. et al. Science 343, 776–779 (2014).
How many memories does it take to make an SLE flare? David M Tarlinton & Kenneth G C Smith Deep-sequencing analyses of immunoglobulin variable-segment genes from antibody-secreting cells have allowed comparisons of conventional immunization responses to disease flares experienced by patients with systemic lupus erythematosus. Such analyses provide insight into B cell recruitment and differentiation processes yielding expanded clones that contribute to this complex autoimmune disease.
S
ystemic lupus erythematosus (SLE) is characterized by the presence of autoreactive antibodies, with individual patients often demonstrating a range of antigenic specificities David M. Tarlinton is with The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia. Kenneth G.C. Smith is in the Department of Medicine and Cambridge Institute of Medical Research, University of Cambridge School of Clinical Medicine, Cambridge, UK. e-mail: [email protected]
representative of the more than 180 different autoantibodies associated with the disease1. These autoantibodies, although continuously present in SLE, increase in amount in patients suffering a relapse, or ‘flare’, in disease. Whether there is a specific population of B cells carrying these autoreactivities from one flare to the next, as well as what factors trigger their activation and differentiation into plasmablasts, generating the immunocomplexes and inflammation that contribute to the debilitating symptoms of lupus, has been uncertain. A published study
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has correlated increases in autoantibodies bearing the 9G4 idiotype with flares2, which would suggest that a memory or recall response contributes to the repeated targeting of self antigens. In this issue of Nature Immunology, Tipton et al. provide a quantum advance in the understanding of the origin of the autoreactive B cells whose autoantibody output often correlates with disease activity in SLE3. Identifying autoreactive B cells and the mechanisms of their persistence and (re)activation has been considered crucial to developing 685
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ne w s and vie w s at given sites may enable selective manipulation of the methylation states of the DMR to assess their effects on CD4 expression. Likewise, it will be interesting to explore the mechanisms of S4and E4P-mediated modulation of the DMR. Published studies have revealed key roles for lineage-specification factors not only in the establishment of lineage identity in differentiated cells but also in its maintenance. Such findings provide a rationale for the hypothesis that epigenetic modifications of specialized cis-regulatory elements may preserve cellular lineage identity and the differentiated state in the presence of fluctuating intracellular and extracellular cues. In particular, during cell division, epigenetic ‘bookmarks’ at some of these sites would ensure the inheritance of transcriptional states of key genes that define a given differentiated cell type1,9. That notion is supported by the observation that proper histone acetylation controlled by the histone deacetylases HDAC1 and HDAC2 is needed to maintain stability of the CD4+ T cell lineage by repressing the cytotoxic T cell program, including expression of CD8 and Runx3 (ref. 10). In addition, trimethylation of histone H3 at Lys27 by Ezh2, a component of the polycomb repressive complex PRC2, seems to help maintain the identity of activated regulatory T cells, a sublineage of helper CD4+ T cells11. The study by Sellars et al. makes substantial contributions to this body of work by demonstrating that the maintenance of DNA methylation or directed active demethylation may have essential roles in solidifying cytotoxic or helper T cell lineages by repressing or stabilizing CD4 expression3. It is conceivable that dynamic regulation of DNA methylation has a broader effect on the transcriptional regulation of lineage-related
genes other than Cd4. Nonetheless, the distinct roles of HDACs, Ezh2 and DNA methyltransferases indicate that permissive and repressive histone modifications, as well as DNA methylation, are used to sustain lineage-specific gene expression in different cellular and biological contexts. More studies will be needed in the future to demonstrate in a cell type–, stage-, locus- and context-specific manner how various epigenetic marks are used to maintain a stable cellular identity. Cell division has a critical part in cell fate determination12. Along with several other reports10,11,13, the observations by Sellars at al. point to cell division as a critical variable that influences lineage stability3. Although asymmetric cell division can lead to heterogeneity of the daughter cells, along with stochastic dilution of limiting transcription factors or epigenetic marks, how cell division affects T cell lineage stability remains largely unknown12–15. Examination of the effect of cell cycle on the distribution of factors that participate in transcriptional regulation and cell-lineage specification, as well as the inheritance of epigenetic modifications, will provide valuable insights into the mechanisms of the determination and maintenance of the T cell lineages. Compromised stability of heritable CD4 expression in E4P-deficient CD4+ T cells, or loss of repression of Cd4 in the absence of the silencer S4 or DNA methyltransferases in CD8+ T cells3, together with the reported role of a cis-regulatory element in sustaining regulatory T cell identity13, suggest that a distinct set of cis-regulatory elements is dedicated to the maintenance of differentiated cellular states. Unlike traditional enhancers that act together with promoters to initiate
and establish transcription upon induction, these cis elements may be dispensable for the induction of gene expression but instead are essential for the maintenance of stable gene expression in particular biological contexts that promote alternative cell fate or cell division. It seems reasonable to assume that the emergence of such dedicated cis elements owes to the increasing complexity of transcriptional regulation in multicellular organisms with a more complex body plan. The identification and characterization of additional such elements and the common molecular logic underlying their function will help to better elucidate cell-fate maintenance and offer unique tools with which to probe cellular behaviors. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Holmberg, J. & Perlmann, T. Nat. Rev. Genet. 13, 429–439 (2012). 2. Taniuchi, I. & Ellmeier, W. Adv. Immunol. 110, 71–110 (2011). 3. Sellars, M. et al. Nat. Immunol. 16, 746–754 (2015). 4. Smith, Z.D. & Meissner, A. Nat. Rev. Genet. 14, 204–220 (2013). 5. Chen, T., Ueda, Y., Dodge, J.E., Wang, Z. & Li, E. Mol. Cell. Biol. 23, 5594–5605 (2003). 6. Wu, H. & Zhang, Y. Cell 156, 45–68 (2014). 7. Rountree, M.R., Bachman, K.E. & Baylin, S.B. Nat. Genet. 25, 269–277 (2000). 8. Lee, P.P. et al. Immunity 15, 763–774 (2001). 9. Ragunathan, K., Jih, G. & Moazed, D. Science 348, 1258699 (2014). 10. Boucheron, N. et al. Nat. Immunol. 15, 439–448 (2014). 11. DuPage, M. et al. Immunity 42, 227–238 (2015). 12. Mullen, A.C. et al. Curr. Biol. 11, 1695–1699 (2001). 13. Feng, Y. et al. Cell 158, 749–763 (2014). 14. Chang, J.T. et al. Science 315, 1687–1691 (2007). 15. Kueh, H.Y., Champhekar, A., Nutt, S.L., Elowitz, M.B. & Rothenberg, E.V. Science 341, 670–673 (2013).
DCs are ready to commit Deborah R Winter & Ido Amit Dendritic cell progenitors commit to a specific conventional dendritic cell fate earlier than previously thought, by initiating transcription-factor regulatory circuits unique to their subtype.
D
endritic cells (DCs) are a critical compartment of innate immunity and perform several specialized immunological functions1. In this issue of Nature Immunology, two studies critically contribute to the understanding of Deborah R. Winter and Ido Amit are in the Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. e-mail: [email protected] or [email protected]
DC origins by demonstrating how progenitor cells commit to the various DC subtypes in mice through distinct intermediate stages. Schlitzer et al. use single-cell mRNA sequencing to analyze the heterogeneity of progenitor DC populations and find, among individual cells, varying levels of commitment to develop into specific conventional DCs (cDCs)2. Grajales-Reyes et al. use mice with expression of green fluorescent protein (GFP) from the locus encoding the transcription factor Zbtb46,
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selectively expressed by cDCs (Zbtb46GFP), and a defined sorting scheme to identify progenitors of cDC subtypes. Through the use of chromatin profiling, they identify the transcription factor IRF8 as a critical factor in the early regulatory circuits that lock cDC fate3. DCs were first observed in 1973 (ref. 4), but their location among the myeloid and lymphoid branches of the hematopoietic tree has yet to be agreed upon5. Although understanding of how the DC lineage develops 683
ne w s and vie w s Bone marrow Grajales-Reyes et al. model IRF8
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Marina Corral Spence/Nature Publishing Group
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Peripheral tissues cDC1
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Figure 1 Proposed models for DC development. The classical pathway for DC development (middle) describes the differentiation of DCs from the MDP stage, with monocyte and macrophage potential, through the CDP stage, with pDC potential, to the pre-DC stage, with only cDC potential. Pre-DCs (lineage-negative (Lin–) CD135+MHCII–CD11c+) migrate through the blood to infiltrate tissues and differentiate into both cDC subtypes9. In the regulatory circuit necessary for cDC1 commitment as described by Grajales-Reyes et al. (left), IRF8 binds together with Batf3 at a downstream enhancer in the Irf8 locus to activate its own expression3. In this model, the pre-DC compartment includes clonogenic precursors of the cDC1 subset (bottom left; Lin–CD135+CD11c+CD117intMHCIIint Zbtb46-GFP+) and cDC2 subset (bottom right; Lin–CD135+CD11c+CD117–CD115+). In the model of Schlitzer et al. (right), the pre-DC compartment is divided into four subsets: uncommitted pre-DC stage 1 (top; Siglec-H+Ly6C–); uncommitted pre-DC stage 2 (middle; Siglec-H+Ly6C+); committed pre-cDC1 (bottom left; Siglec-H–Ly6C–); and committed pre-cDC2 (bottom right; Siglec-H–Ly6C+)2. The first two stages are restricted to the bone marrow.
from the hematopoietic stem cell is still preliminary, a progenitor cell with the potential to develop into DCs, monocytes and macrophages (the MDP) has been identified in mouse bone marrow6. The MDP can give rise to a common DC progenitor (the CDP) with the capacity to differentiate into all DC subtypes7,8. According to the classical model, CDPs give rise to pre-DCs in the bone marrow, which migrate into the blood and enter the peripheral tissues to become cDCs9 (Fig. 1). DC subsets in tissues include plasmacytoid DCs (pDCs), which are distinguished by their prominent production of type I interferon, and the two major classes of cDCs, which for simplicity are referred to here as ‘cDC1’ (identified as XCR1+CD24+CD8α+ DCs), and ‘cDC2’ (identified as CD11b+CD172α+CD4+ DCs)1. The generation of these cDC subsets depends on members of the IRF family of transcription factors; specifically, IRF8 is required for the cDC1 subset, while IRF4 is crucial for the cDC2 subset10. The timing and regulatory circuits that control the commitment of DC progenitors to the cDC1 or cDC2 subtype remain elusive. Although the MDP, CDP and pre-DC populations have been characterized, little is known about the steps that lead to irreversible commitment to a DC subtype–in other words, what drives the transition between steps and 684
at what point cells commit to their specific cDC fate. In the study by Schlitzer et al., the authors analyze the transcriptome of single cells from MDP, CDP and pre-DC populations in bone marrow on the basis of conventional markers2. They find that individual cells in the DC progenitor populations are highly variable in terms of their degree of differentiation toward mature cDCs. Across the populations analyzed, a number of cells have expression profiles similar to those of either the cDC1 subset or the cDC2 subset, which suggests that these are examples of committed cells. By identifying surface markers (Siglec-H and Ly6C) among the products of genes differentially expressed by sets of single cells, the authors confirm that certain pre-DC subpopulations (Fig. 1) are already functionally committed in the bone marrow to generate predominantly either cDC1 cells or cDC2 cells, in in vitro and in vivo functional assays. These results indicate that DC specialization occurs earlier than previously appreciated. Grajales-Reyes et al. further investigate DC commitment by demonstrating that IRF8 is crucial for the development of cDC1 cells but not for that of cDC2 cells3. The authors first find that the originally defined pre-DC does not develop into cDC1 cells but rather develops only into cDC2 cells
and pDCs9. To identify the source of cDC2 cells, they use the Zbtb46GFP reporter mouse along with a carefully selected set of markers (CD117intMHCIIintCD11c+CD115–) and identify a previously unknown progenitor population that is excluded from traditional sorting schemes. The authors show that this population can differentiate selectively toward the cDC1 subset but not toward the cDC2 or pDC subset; this newly identified clonogenic cDC1 progenitor is absent in IRF8-deficient mice. Using chromatin profiling to characterize the epigenetic state surrounding the Irf8 locus, Grajales-Reyes et al. show that the transcription factor Batf3 binds at a cDC1specific enhancer (located downstream of Irf8), together with IRF8, to initiate an autoactivation loop that locks the cDC1 fate3 (Fig. 1). Interestingly, the authors show that progenitors of cDC1 cells require IRF8 but not Batf3 for early specification. This work provides a precedent for the power of combining genomic approaches with classical immunological methods to characterize key cell populations. The authors perform a comparative analysis of a single, critical locus in mature cells and defer investigation of the role of possibly unknown factors to follow-up studies. In the future, genome-wide profiling of the chromatin state in progenitor cells as well as differentiated cells will provide a global view of differentiation and the regulatory networks that drive specification11. It can be difficult to distinguish between factors involved in commitment to a specific cell fate and those involved in the maintenance of that cell fate. The observation that the activity of Batf3, in conjunction with IRF8, is critical in directing progenitors toward the cDC1 fate rather than the cDC2 fate3 explains why Batf3deficient mice produce only a small population of irregular cDC1 cells. It is possible that as the cells mature through the known phases from MDP to CDP to pre-DC, some subset will pass a certain threshold for IRF8 expression that leads them irrevocably down the cDC1 pathway. If Batf3 is not present to secure IRF8 expression, the majority of cells revert to developing into cDC2 cells, perhaps by stochastic expression of yet-to-be-identified cDC2-enforcing factors. Additional investigation is needed to determine whether the resulting cells are true cDC2 cells or are simply cDC1 cells that have lost some of their distinguishing features. It seems likely that in addition to arising from uncommitted cDC1 cells, cDC2 cells have their own positively enforcing regulatory circuits. Several transcription factors proposed to regulate differentiation into the cDC2 subset, particularly IRF4 (ref. 12), are expressed in the committed pre-cDC2 cells defined
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ne w s and vie w s in these two studies2,3. Still, the role of these factors in the process of cDC commitment remains to be demonstrated. In addition, since cDCs differ depending on the tissue in which they reside, studying bone marrow progenitors will reveal only the central programming of DC identity. For elucidation of the peripheral programing of various DC subsets, comparative studies of the regulatory networks of DC populations across tissues will be required. Presumably a number of the MDPs and CDPs analyzed by Schlitzer et al.2 are predisposed toward the pDC fate, although this is not explored in these two studies. Both studies find some evidence of pDC potential among the general pre-DC populations. Published studies have indicated the importance of IRF8 in pDC development10, which adds further complexity to the underlying regulation. Genomic analyses of chromatin and transcription-factor binding in various DC progenitors and differentiated cells may help to identify additional factors and interactions that put into perspective the combinatorial roles of IRF8 and IRF4 in the DC regulatory networks. Together these two studies use complementary genomic techniques to shed light on the stages through which a cell progresses while differentiating into specific DC subtypes2,3. They also raise the question of why some cells in the progenitor populations seem to commit at much earlier stages than others do. However, much of the present understanding is necessarily based on the average state of populations of cells. It remains unclear
when an individual cell passes the threshold of commitment to a specific fate and how to gauge the reversibility of this ‘decision’13. Studies based on single-cell analyses may hold the key to understanding cell-type heterogeneity and how individual ‘decisions’ lead to population dynamics. While powerful, these approaches can be compromised by classical definitions based solely on cell-surface markers that may not have clear links to a specific cell function or regulatory module14. Circular logic should be avoided, whereby observations such as the heterogeneous nature of a population are the direct result of a particular sorting strategy and do not necessarily reflect the underlying biology. Indeed, these two studies identify the precursor population of the cDC1 and cDC2 subsets by using different sorting strategies and cell-surface markers. It is not yet clear if these markers define the same cells and, if they do, whether these progenitors represent a homogeneous population2,3. Future studies would benefit from the use of unbiased, ‘bottom-up’ approaches to redefine populations in a biologically meaningful way. As the throughput and quality of single-cell data and analysis improve, so will the ability to study DC development and heterogeneity. An exciting time is on the horizon as the genomic revolution affects immunology, and many more integrated studies like these can be expected in the future. When handling such rich, high-throughput data, researchers will have to be extra cautious to avoid fitting the data to their assumptions and to follow up hypothesis-generating genome-wide
analyses with functional assays. As communal proficiency with newly developed genome engineering tools (such as the genomeediting approach CRISPR-Cas9) improves, researchers will be better equipped to test their findings with perturbations of regulatory networks in the immune system. Understanding the underlying regulatory networks is vital for determining the role of DCs in disease and, hence, the development of therapeutic approaches. Detailed characterization of the commitment and maintenance processes in the DC lineage will allow the development of informed therapies that target specific subsets and pathways. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Merad, M., Sathe, P., Helft, J., Miller, J. & Mortha, A. Annu. Rev. Immunol. 31, 563–604 (2013). 2. Schlitzer, A. et al. Nat. Immunol. 16, 718–728 (2015). 3. Grajales-Reyes, G.E. et al. Nat. Immunol. 16, 708–717 (2015). 4. Steinman, R.M. & Cohn, Z.A. J. Exp. Med. 137, 1142–1162 (1973). 5. Naik, S. et al. Nature 496, 229–232 (2013). 6. Fogg, D.K. et al. Science 311, 83–87 (2006). 7. Naik, S.H. et al. Nat. Immunol. 8, 1217–1226 (2007). 8. Onai, N. et al. Nat. Immunol. 8, 1207–1216 (2007). 9. Liu, K. et al. Science 324, 392–397 (2009). 10. Tamura, T. et al. J. Immunol. 174, 2573–2581 (2005). 11. Winter, D.R. & Amit, I. Immunol. Rev. 261, 9–22 (2014). 12. Vander Lugt, B. et al. Nat. Immunol. 15, 161–167 (2014). 13. Etzrodt, M., Endele, M. & Schroeder, T. Cell Stem Cell 15, 546–558 (2014). 14. Jaitin, D. et al. Science 343, 776–779 (2014).
How many memories does it take to make an SLE flare? David M Tarlinton & Kenneth G C Smith Deep-sequencing analyses of immunoglobulin variable-segment genes from antibody-secreting cells have allowed comparisons of conventional immunization responses to disease flares experienced by patients with systemic lupus erythematosus. Such analyses provide insight into B cell recruitment and differentiation processes yielding expanded clones that contribute to this complex autoimmune disease.
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ystemic lupus erythematosus (SLE) is characterized by the presence of autoreactive antibodies, with individual patients often demonstrating a range of antigenic specificities David M. Tarlinton is with The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia. Kenneth G.C. Smith is in the Department of Medicine and Cambridge Institute of Medical Research, University of Cambridge School of Clinical Medicine, Cambridge, UK. e-mail: [email protected]
representative of the more than 180 different autoantibodies associated with the disease1. These autoantibodies, although continuously present in SLE, increase in amount in patients suffering a relapse, or ‘flare’, in disease. Whether there is a specific population of B cells carrying these autoreactivities from one flare to the next, as well as what factors trigger their activation and differentiation into plasmablasts, generating the immunocomplexes and inflammation that contribute to the debilitating symptoms of lupus, has been uncertain. A published study
nature immunology volume 16 number 7 july 2015
has correlated increases in autoantibodies bearing the 9G4 idiotype with flares2, which would suggest that a memory or recall response contributes to the repeated targeting of self antigens. In this issue of Nature Immunology, Tipton et al. provide a quantum advance in the understanding of the origin of the autoreactive B cells whose autoantibody output often correlates with disease activity in SLE3. Identifying autoreactive B cells and the mechanisms of their persistence and (re)activation has been considered crucial to developing 685
