The quest for faithful in vitro models of human dendritic cells types Xin-Long Luo, Marc Dalod

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Xin-Long Luo, Marc Dalod. The quest for faithful in vitro models of human dendritic cells types. Molecular Immunology, Elsevier, 2020, 123, pp.40-59. ￿10.1016/j.molimm.2020.04.018￿. ￿hal-02981716￿

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Luo XL, Dalod M.

Mol Immunol. 2020 Jul;123:40‐59. doi: 10.1016/j.molimm.2020.04.018. Epub 2020 May 13.

PMID: 32413788. https://www.sciencedirect.com/science/article/abs/pii/S0161589019309174 The quest for faithful in vitro models of human dendritic cells types

Xin-Long Luo1 and Marc Dalod1*

1Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Marseille, France

*Corresponding author at: Centre d’Immunologie de Marseille-Luminy (CIML), Parc scientifique et technnologique de Luminy, case 906, 163 avenue de Luminy, F-13288 Marseille Cedex 09, France. E-mail address: [email protected] (M. Dalod).

Abstract Dendritic cells (DCs) are mononuclear phagocytes that are specialized in the induction and functional polarization of effector lymphocytes, thus orchestrating immune defenses against infections and cancer. The population of DC encompasses distinct cell types that vary in their efficacy for complementary functions and are thus likely involved in defending the body against different threats. Plasmacytoid DCs specialize in the production of high levels of the antiviral type I interferons. Type 1 conventional DCs (cDC1s) excel in the activation of cytotoxic CD8+ T cells (CTLs) which are critical for defense against cancer and infections by intracellular pathogens. Type 2 conventional DCs (cDC2s) prime helper CD4+ T cells for the production of type 2 cytokines underpinning immune defenses against worms or of IL-17 promoting control of infections by extracellular bacteria or fungi. Hence, clinically manipulating the development and functions of DC types could have a major impact for improving treatments against many diseases. However, the rarity and fragility of human DC types is impeding advancement towards this goal. To overcome this roadblock, major efforts are ongoing to generate in vitro large numbers of distinct human DC types. We review here the current state of this research field, emphasizing recent breakthrough and proposing future priorities. We also pinpoint the necessity to develop a consensus nomenclature and rigorous methodologies to ensure proper identification and characterization of human DC types. Finally, we elaborate on how faithful in vitro models of human DC types can accelerate our understanding of the biology of these cells and the engineering of next generation vaccines or immunotherapies against viral infections or cancer.

Keywords: type 1 conventional dendritic cells; plasmacytoid dendritic cells; hematopoiesis; cancer; viral infection  We review the current state of the art regarding in vitro generation and characterization of human DC types.  We emphasize recent breakthroughs and highlight possible future priorities.  We provide a guideline proposal for proper identification and characterization of in vitro derived human DC types.  We discuss how in vitro models of human DC types can accelerate our understanding of the biology of these cells and the engineering of next generation vaccines or immunotherapies against viral infections or cancer. Abbreviations: AhR, aryl hydrocarbon ; ASDCs, AXL+ SIGLEC6+ dendritic cells; cDC1s, type 1 conventional dendritic cells; cDC2s, type 2 conventional dendritic cells; CDP, common DC progenitor; cGMP, current good manufacturing practices; cMoP, classical monocyte progenitor; cMos, classical monocytes; CMP, common myeloid progenitors; CTLs, cytotoxic CD8+ T cells; GMDP, granulocyte- monocyte-DC progenitor; HSCs, hematopoietic stem cells; IFN-I, type I interferons; iPSCs, induced pulripotent stem cells.; LCs, Langerhans cells; LMMPs, Lymphoid-primed multipotent progenitors; MDP, and progenitor; MHC-I, class I major histocompatibility complex; MLPs, Multi-lymphoid progenitors; MoDCs, monocyte-derived dendritic cells; MoMacs, monocyte- derived ; pDCs, plasmacytoid dendritic cells; pre-cDC, cDC precurosor; Pre-cDC1, cDC1 precursor; pre-cDC2, cDC2 precursor; pro-cDC, classical DC progenitor; pro-pDC, pDC progenitor; tDCs, transitional DCs; Th, helper CD4+ T cells. 1. Introduction Vertebrate are equipped with a complex immune system that can discriminate pathological from normal self, enabling recognition and elimination/control of cancer or infections by intracellular pathogens. This process largely relies on effector cytotoxic immune cell types including natural killer cells and CD8+ T lymphocytes (CTLs), whose activation requires signals from accessory immune cells, in particular dendritic cells (DCs). DCs are uniquely able to deliver to naïve T cells all the signals necessary for their initial activation upon the first encounter with their cognate antigen, a process called T cell priming (Vu Manh et al., 2015). DCs can detect a variety of danger signals and translate their combinatorial sensing into delivery of a matched array of output signals instructing the functional polarization of T lymphocytes towards the function that should be the best suited to fight the threat that the organism is facing (Vu Manh et al., 2015). Hence, DC functions are highly plastic, locally shaped by the tissue microenvironment where they reside, which contributes to establish a beneficial balance between host defense mechanisms and avoidance of autoimmunity or immunopathology. An additional layer ensuring the plasticity of DC functions, and the adaptability of the immune system to different types of threats, is the existence within the DC family of distinct cell types. DC types differ in the arrays of innate immune sensors that they express, in link with the combination of activation or inhibitory signals that they can deliver to T cells. This functional specialization of DC types more broadly relates to differences in their ontogeny and expression profiles (Vu Manh et al., 2015). Beyond their different functional specialization in health, distinct DC types also present different susceptibilities to infection by intracellular pathogens or to hijacking of their immunoregulatory activities by microbes or tumor cells for their own benefits and at the expense of the host (Bakdash et al., 2016; Fries and Dalod, 2016; Silvin et al., 2017). Thus, when harnessing DCs for vaccination or immunotherapy purposes, it is essential to ensure targeting the right DC type for the proper function, through a strategy preventing their repurposing in the lesion microenvironment in a manner that would favor disease development instead of benefiting the patient. To this aim, we must gain a precise knowledge of the identity of human DC types, their function and their molecular regulation. However, the rarity and frailness of primary human DC types isolated ex vivo is impeding progress towards this aim. Surrogate strategies are thus needed to overcome this roadblock. This unmet need constitutes one of the major incent driving the quest for faithful in vitro models of human DC types. A critical prerequisite to achieve this aim is to first develop a consensus nomenclature and rigorous methodologies to ensure proper identification and characterization of human DC types across biological and experimental settings and between laboratories (Vu Manh et al., 2015).

A simplified nomenclature classifies DCs in five main cell types (Guilliams et al., 2014; Guilliams et al., 2010; Vu Manh et al., 2015). The establishment of transcriptomic homologies between mouse and human DC types was a key contribution to initially establish this simplified nomenclature (Crozat et al., 2010b; Guilliams et al., 2010; Robbins et al., 2008) that was further refined largely based on ontogeny studies in mice (Guilliams et al., 2014). It is thus important to underscore the usefulness of the work performed in mice, where studies on the phenotypic and functional characterization of DC types, as well as on their ontogeny requirements including through the development of in vitro differentiation models, and the underlying mechanistic studies, have paved the way for translation to human, and still do. Some striking differences do exist between the two species (Crozat et al., 2010b; Vu Manh et al., 2015). However, one might rather want to look at the glass as half-full rather than half-empty, appreciating the translatability of the mouse model for understanding human immunology, provided that a rational approach is followed to help focusing on conserved biological processes and molecular functions (Crozat et al., 2010a; Crozat et al., 2010b; Dutertre et al., 2014; Reynolds and Haniffa, 2015; Vu Manh et al., 2015). Plasmacytoid DCs (pDCs) are specialized in rapid and high-level production of type I interferons (IFN-I) during many viral infections. These innate cytokines mediate both direct antiviral effects and immunoregulatory functions (Tomasello et al., 2014). They are at the very center of the orchestration of vertebrate antiviral immunity. Type 1 conventional DCs (cDC1s) are most efficient for CTL priming, in particular through uptake and processing of cell-associated exogenous antigens for their presentation in association with class I major histocompatibility complex (MHC-I) molecules, a process called cross-presentation (Vu Manh et al., 2015). Type 2 conventional DCs (cDC2s) are most efficient for CD4+ helper T cell (Th) priming, in particular, their polarization toward Th2 or Th17, and for the promotion of humoral immunity. They are proposed to play a critical role in immune defenses against extracellular pathogens (Vu Manh et al., 2015). Langerhans cells (LCs) are mostly found in the epidermis. They are proposed to contribute to skin homeostatic and repair as well as to promote local induction of CTL responses against intracellular pathogens or tumors (Kashem et al., 2017). Monocyte-derived DCs (MoDCs) constitute one of the multiple differentiation fates of CD14+ classical monocytes (cMos) upon activation develop during inflammation, along with inflammatory monocyte-derived macrophages (MoMacs) and myeloid-derived suppressor cells (Guilliams et al., 2014; Segura et al., 2013). For a long time, the only available model of in vitro-derived DCs was the differentiation of cMos in the presence of GM-CSF and IL-4. Studying these in vitro derived MoDCs has therefore been instrumental in advancing our understanding of the biology of DCs and has led to many key discoveries on the functions of those cells and their molecular regulation (Segura and Amigorena, 2015; Trombetta and Mellman, 2005).

Recently, the CD123+ BDCA2+ gate commonly used to identify human blood pDCs was shown to encompass a newly identified population of AXL+ SIGLEC6+ DCs (ASDCs) that failed to produce IFN-I (See et al., 2017; Villani et al., 2017). Similarly, in the mouse, a population of cells bearing mixed features of pDCs and cDCs was recently characterized (Dress et al., 2019; Rodrigues et al., 2018), and called pDC-like cells in one study (Rodrigues et al., 2018). These cells were then shown to align across species and proposed to be called transitional DC (tDCs) (Leylek et al., 2019). It has been hypothesized that tDCs account for all of the T cell activating functions previously attributed to pDCs (Dress et al., 2019; Leylek et al., 2019; Rodrigues et al., 2018; See et al., 2017; Villani et al., 2017). Certain ontogeny studies suggested that mouse pDC share a proximal common progenitor with B lymphocytes rather than with cDC (Dress et al., 2019; Rodrigues et al., 2018). Based both these functional and ontogenetic studies, it was proposed that pDCs do not belong to the DC family but rather to the innate lymphoid cell family (Dress et al., 2019). However, there is clearly still an active controversy on the exact nature of pDCs, including whether or not they share ontogenic and functional properties with cDCs. Indeed, some studies showed that cDC1 commitment occurred early in the hematopoietic tree, independently of the segregation between the lymphoid and myeloid lineages(Naik et al., 2013)(Helft et al., 2017; Lee et al., 2017), with a sizeable fraction of cDC1 sharing a common progenitor with pDCs, lymphocytes and eventually cDC2s, rather than with monocytes and granulocytes (Lee et al., 2017; Naik et al., 2013). Moreover, recent studies combining the use of modern methods to purify bona fide human pDC with proper stimulation of these cells did confirm that activated human pDC populations could efficiently activate T cells (Alcantara-Hernandez et al., 2017; Alculumbre et al., 2018). Thus, the exact nature of pDCs remains an open question. In any case, it is important to use proper criteria to discriminate bona fide pDCs from tDCs, including in the validation of protocols aiming at differentiating these cells in vitro from human hematopoietic progenitors.

Each DC type can exist in an immature state and in different mature states. Immature DCs express low levels of co-stimulation molecules and are poorly efficient at activating T cells. In contrast, mature DCs show improved efficacy for establishing cognate interactions with T cells and driving their functional polarization, at least in part due to their increased expression of MHC and co-stimulation molecules as well as to their production of various cytokines (Dalod et al., 2014). Depending on the array of co-stimulation molecules that they express, on the cytokines that they produce, and on their metabolism, mature DCs can also be generally classified as immunogenic or activating versus tolerogenic or regulatory (Ardouin et al., 2016; Marin et al., 2019). CCR7 expression can be induced on any DC type during its maturation. Under steady state conditions in vivo, it selectively marks the tolerogenic DCs that have received maturation signals in non-lymphoid tissues and consecutively migrated into the draining lymph nodes (CCR7+ ‘migratory’ DCs), distinguishing them from the immature lymph-node resident CCR7- DCs. During an immune response, CCR7+ ‘migratory’ DCs can receive signals to become immunogenic, and resident DC can upregulate CCR7 during their maturation. Thus, depending on the pathophysiological context, CCR7+ DCs can encompass a variety of DC types and activation states. Hence, DCs are very plastic cells that can be polarized towards different activation states associated to distinct functional profiles, depending on the array of signals that they received, contributing to the high heterogeneity of the DC family on top of its inclusion of different cell types (Vu Manh et al., 2015).

Mouse DC heterogeneity has been discovered almost 30 years ago (Vremec et al., 1992) and ever since the subject of intense research as reviewed elsewhere (Durai and Murphy, 2016; Shortman and Heath, 2010). Whereas human blood cDC heterogeneity was reported in 2000 with the identification of what are now referred to as pDCs, cDC1s and cDC2s (Dzionek et al., 2000), in the following decade studies of human blood DCs mostly focused on pDCs. This could be explained by three main reasons (Crozat et al., 2010b). First, the unique ability of pDCs to produce high levels of IFN-I has important potential therapeutic applications (Furie et al., 2019; Pham et al., 2019; Smith et al., 2017; Tomasello et al., 2014). Second, shortly after their discovery in humans, pDCs were shown to be strongly conserved in mice (Asselin-Paturel et al., 2001; Bjorck, 2001; Nakano et al., 2001). Finally, yet importantly, the ability to derive human pDCs in vitro from hematopoietic stem cells (HSCs) enabled the molecular dissection of the mechanisms regulating their ontogeny and functions (Spits et al., 2000) (cited 222 times). From this point of view, it is also revealing that human LCs have been studied as extensively as pDCs, with steadily increasing numbers of reports after 1992, consecutive to the demonstration that in vitro equivalents to these cells can be derived from cultures of HSCs in the presence of GM-CSF and TNF (Caux et al., 1992) (cited 1401 times). In contrast, the community struggled accepting that human cDC1s and cDC2s are truly distinct cell types. It is only after the demonstration of their strong homologies with mouse DC types (Bachem et al., 2010; Crozat et al., 2010a; Jongbloed et al., 2010; Poulin et al., 2010; Robbins et al., 2008; Villadangos and Shortman, 2010) that a much greater interest arose in studying their precise identity, functional specialization and molecular regulation. The study of human cDC1s and cDC2s has also been hindered by the difficulty to perform ex vivo functional studies on these cell types due to their rarity and frailness, and due to the lack of any documented culture system enabling the generation of in vitro equivalents to these cell types (Crozat et al., 2010b). However, in the last years, basic and clinical evidences have accumulated of a higher efficacy of human cDC1s for the cross-presentation of cell-associated antigens (Vu Manh et al., 2015) and the promotion of protective antiviral (Silvin et al., 2017) and anti-tumor (Cancel et al., 2019) CTL responses. This has led to a further increase in the number of teams now working on characterizing human DC types, in particular on aiming at generating and/or harnessing cDC1s or cells harboring cDC1-like properties for treating cancer or infections by intracellular pathogens. Recently, therapeutic vaccines using in vitro derived MoDCs pulsed with antigens derived from autologous viral quasi-species did increase the antiviral CTL responses of HIV-1-infected patients and improved their control of viral replication after antiretroviral therapy interruption (Brezar et al., 2015; Garcia et al., 2013; Levy et al., 2014; Surenaud et al., 2019; Thiebaut et al., 2019). However, for many years, the use of MoDCs for immunotherapy or vaccination against viral infections or tumors did not yield any strong benefit for the patients. This relative inefficacy of MoDCs in adoptive cell therapy clinical trials might have resulted from their poor recirculation to lymphoid organs and from other additional differences with cDC1s or cDC2s. Indeed, by using gene expression profiling, we contributed to show that human MoDCs differ strikingly from pDCs, cDC1s and cDC2s and share more similarity to monocytes and macrophages (Robbins et al., 2008), which additional gene expression profiling and functional studies confirmed (Alcantara-Hernandez et al., 2017; Balan et al., 2014). In addition, MoDCs or cDC2s might be more plastic than cDC1s for functional reprogramming by their microenvironment, presenting an increase risk of hijacking by pathogens or tumors for their own benefit to favor their dissemination or enhance immunosuppression (Bakdash et al., 2016; Di Blasio et al., 2019; Fries and Dalod, 2016). These different issues must be carefully considered when designing strategies to harness DCs for treating diseases, for example to boost anti-tumor responses in cancer patients (Bakdash et al., 2016) or to prevent graft rejection upon organ transplantation (Marin et al., 2019; Marin et al., 2018; Thomson and Ezzelarab, 2018). Thus, it will be critical to compare DC types side-by-side for the precise nature and stability of their functional responses to candidate drugs or vaccines. This could be most efficiently achieved by engineering and deeply characterizing cell culture systems enabling the simultaneous differentiation of distinct human DC types from the same progenitors in the same dish. Moreover, once the best suited combinations of DC type and activation state has been identified to treat a given disease, the ability to generate high yields of these cells in vitro under current good manufacturing practices (cGMP) could enable using them clinically in adoptive cell transfer-based treatments. Hence, we review here the current state of studies aiming at recapitulating in vitro the differentiation of human DC types in a dish. We emphasize recent breakthroughs, pinpoint key issues and potential pitfalls, and propose future priorities. We also discuss how faithful in vitro models of human DC types could both advance our basic understanding of the biology of these cells and accelerate the engineering of next generation vaccines or immunotherapies against viral infections or cancer. 2. Strategies used to generate human DC types in vitro. The first reports of successful in vitro differentiation of human DCs date back to almost 30 years ago, with the pioneering demonstration that the combination of the cytokines GM-CSF with TNF or IL-4 respectively drove the differentiation of human CD34+ HSCs into LCs (Caux et al., 1992) and of human circulating blood cMo into cells bearing morphological, phenotypic and functional key characteristics of DCs (Sallusto and Lanzavecchia, 1994) now classically referred to as MoDCs. As illustrated by the high number of citations collected by the original papers (over 1,400 and 4,000 citations, respectivey), these two protocols have been extremely heavily used over the years, both for basic study of the functions of human DCs and their molecular regulation (Segura and Amigorena, 2015; Trombetta and Mellman, 2005), and as a source of DCs for adoptive cell therapy in clinical trials for treating cancer or viral infections (Wimmers et al., 2014). They also paved the way for the development of alternate protocols aiming at deriving other DC types from the same progenitors, with a different functional specialization, including pDCs to study the molecular mechanism regulating their ontogeny and IFN-I production, and cells sharing with cDC1s a high efficacy for the induction of anti-tumor or anti-viral CTLs including through cross-presentation. More recently, other strategies were implemented to achieve the same aims, including DC differentiation from iPSCs, trans-differentiation of fibroblasts into cDC1s upon ectopic expression of key transcription factors, or immortalization of ex vivo isolated human blood DCs. Selected key studies illustrating these different strategies are summarized in Table 1 and commented upon in the following paragraphs.

2.1 In vitro differentiation of human LCs and CD14+ DDCs from HSCs. To the best of our knowledge, the first report of in vitro generation of human DC was published by Christophe Caux, Jacques Banchereau and colleagues in a landmark Nature paper (Caux et al., 1992) (Table 1). In this study, the authors designed the now classical protocol for differentiation of CD1a+ LCs and CD14+ DDCs from CD34+ HSCs upon culture for 5 days and up to 21 days with the cytokines GM- CSF and TNF. This recipe for in vitro differentiation of human LC from HSCs was further improved by addition of exogenous TGF-β and of the growth factor FLT3-L (Klechevsky et al., 2008; Strobl et al., 1997; Strobl et al., 1996). Already in their original report and in a series of other studies that followed up over the following 15 years (Caux et al., 1992; Caux et al., 1997; Caux et al., 1996; Klechevsky et al., 2008), Jacques Banchereau and his colleagues thoroughly characterized the in vitro generated LCs and CD14+ DDCs. They studied them side-by-side, phenotypically and functionally, and in comparison with their natural counterparts isolated ex vivo from human skin, demonstrating their equivalency (Table 1). Moreover, they used the in vitro derived cells to guide the functional characterization of human LCs and CD14+ DDCs and the identification of some of the underpinning molecular mechanisms. 2.2 In vitro differentiation of human MoDCs and MoMacs from peripheral blood cMo. In a pioneering work published By Frederica Sallusto and Antonio Lanzavecchia in 1994 (Sallusto and Lanzavecchia, 1994), the adherent fraction of PBMCs, or the low-density PBMC fraction further depleted of T/B cells, was shown to differentiate in vitro as rapidly as in 7 days into cells bearing morphological, phenotypic and functional key characteristics of DCs (Table 1), including a high efficacy for allogeneic T cell activation and for the processing and presentation of a soluble Ag to a CD4+ T cell clone or to polyclonal T cell lines. This study is at the origin of the now classical protocol for human MoDC generation from peripheral blood cMo. Recent adaptations of this protocol have allowed the simultaneous in vitro generation in the same CD14+ Mo cultures of MoDCs and MoMacs (Table 1), respectively resembling closely tumor ascites inflammatory MoDCs and Macs based on gene expression profiling and functional characterization (Goudot et al., 2017).

2.3 High yield differentiation of human MoDCs from HSCs. Getting enough MoDCs from in vitro differentiation of blood cMo for adoptive cell immunotherapy requires harvesting many cells from the patient because hardly any proliferation occurs during this differentiation process. Therefore, alternate protocols have been developed starting form HSCs (Table 1), to increase MoDC yields by taking advance by the enormous expansion potential of these multipotent progenitors (Balan et al., 2009, 2010). This protocol thus consist in a first 7d phase of HSC expansion with FLT3-L, SCF, IL-3 and IL-6, followed by a 12-14d differentiation phase under the instruction of FLT3-L, SCF, GM-CSF and IL-4. This can yield near to 200 MoDCs per HSCs, as compared to less than one MoDC per cMo.

2.4 Simultaneous in vitro differentiation of human cDC1s and MoDCs from HSCs. Based on the knowledge gained in the mouse on the network of cytokines/growth factors and transcription factors instructing the differentiation of mouse cDC1s and pDCs versus MoDCs (Gilliet et al., 2002; Naik et al., 2005; Xu et al., 2007), and on observations of the simultaneous differentiation of pDCs and CD11c+ TLR3+ cells in HSCs cultured with FLT3-L (Chen et al., 2004), it was proposed that human HSCs might be induced to differentiate into cDC1s under the instruction of FLT3-L combined with low dose of GM-CSF (Crozat et al., 2010b). Indeed, a landmark study was published in 2010 by the team of Caetano Reis e Sousa (Poulin et al., 2010) reporting a two-phase culture system enabling human cDC1 differentiation from HSCs (Table 1). The in vitro differentiated cDC1s represented up to ~3% of live cells. Likewise to their blood counterparts, they were characterized as CD141(BDCA3)hi CLEC9A+ CD11c+ HLA-DR+ CD11b- CLEC4C(BDCA2)- CD123(IL-3RA)- /low, cross-presented long peptides at least as efficiently as MoDCs, and were able to produce IL- 12p70 upon proper stimulation. This protocol was further optimized to increase the cDC1 yields (Balan et al., 2014). The other cell types generated in the same culture were also more deeply characterized, showing that a high proportion of them corresponds to MoDCs (Balan et al., 2014) consistent with the presence of cMo in the cultures that also encompassed putative cDC2s (Helft et al., 2017).

2.5 In vitro differentiation of human pDCs from HSCs. To the best of our knowledge, the first two report of in vitro generation of human pDCs from HSCs were published almost 20 years ago by the groups of Hergen Spits (Spits et al., 2000) and Yong-Jun Liu (Blom et al., 2000) (Table 1). The former method was based upon short-term (5d) culture on S17 feeder cells. The rationale was that this system was previously reported to enable human B lymphocyte differentiation from HSCs (Rawlings et al., 1997), and that pDCs wre thought to belong to the lymphoid branch of the hematopoietic tree. Indeed, pDC share expression of many with B or T cells and harbor rearrangements of the B cell receptor locus (Corcoran et al., 2003; Rissoan et al., 2002). The latter method consisted in long-term (20d to 60d) culture with FLT3-L. In both experimental settings, in vitro derived pDCs were shown to strongly resemble their blood counterparts based on several readouts, including their morphology (Chen et al., 2004), their phenotype (Blom et al., 2000; Chen et al., 2004; Spits et al., 2000), their high-level production of IFN-I upon stimulation with HSV-1 (Blom et al., 2000; Chen et al., 2004; Spits et al., 2000), and their differentiation into mature functional DCs able to activate allogeneic T cells (Chen et al., 2004; Spits et al., 2000). Interestingly, under conditions of HSC differentiation into pDCs upon instruction by FLT3-L and TPO (Chen et al., 2004), the differentiation of CD11c+ TLR3+ cells was also observed that might have corresponded to in vitro derived cDC1s. Modified protocols were developed (Dontje et al., 2006; Nagasawa et al., 2008; Schotte et al., 2004), combining the use of FLT3-L and IL-7 with feeder cells known to enable lymphoid development from HSCs (Haddad et al., 2004; La Motte-Mohs et al., 2005). Finally, it was recently reported that pDCs differentiated in vitro according to (Thordardottir et al., 2014) could be induced to further resemble their peripheral blood counterparts upon deprivation of the growth factors Flt3-L and TPO and stimulation with IFN-γ or IFN-β for three days. This final differentiation/maturation step enhanced in the in vitro differentiated pDCs both the expression levels of signature genes including HLA-DR, CD4, CD303 and CD304 and the ability to produce type I interferon after stimulation with synthetic TLR ligands (Laustsen et al., 2018).

2.6 Simultaneous in vitro differentiation of human cDC1s, cDC2s and pDCs from HSCs. The studies that enable in vitro differentiation of either cDC1s or pDCs from HSCs have been inspiring for further optimization of these protocols to achieve simultaneous differentiation of human pDCs, cDC1s and cDC2s in vitro in the same culture. This aim was first reported to be met in 2012 by the team of Li Wu (Proietto et al., 2012). They cultured HSCs for 21d in Yssel's medium supplemented with 10% AB serum, in the presence of FLT3-L and TPO, i.e; using a protocol very similar to that used 8 years before by the team of Yong-Jun Liu to generate pDCs and CD11c+ TLR3+ DCs (Chen et al., 2004). Under these conditions (Proietto et al., 2012), the authors identified distinct cell types bearing phenotypes and expressing key genes resembling those of cDC1s (CD14- CD11cint CLEC9A+ HLA-DR+ SIRP1a-/low CD11b- cells expressing higher levels of the IRF8 and TLR3 genes than cDC2s and cMos), cDC2s (CD14- CD11c+ CD1c+ HLA-DR+ SIRP1ahi CD11b+ cells expressing higher levels of the IRF4 gene than cDC1s and cMos), pDCs (CD14- CD11c- CD123+ HLA-DR+ SIRP1a+ CD11b-/low cells expressing high levels of IRF8 and TLR7 and specifically TLR9) or cMos (CD14+ cells). In vitro differentiated pDCs were shown to produce some IFN-α upon CpG stimulation but did not express NRP1 (alias BDCA4 or CD304) contrary to blood pDCs and were not assessed for CLEC4C expression. In vitro derived cDC1s did not express CD141 contrary to blood cDC1s. The cells classified as cDC2s harbored a phenotype overlapping with that of MoDCs such that further phenotypic and gene expression profiling characterization would be required to ensure of their precise identity. The yields were relatively low (Table 1). Another study reported the simultaneous in vitro generation of cDC1s, cDC2s and pDCs from HSCs using a similar protocol with the exception of the addition of IL-6, SCF and StemRegenin 1 (SR1), a small molecule inhibitor of aryl hydrocarbon receptor (AhR) (Thordardottir et al., 2014). The use of SR1 was shown to be critical for reaching higher cell yields for all three DC types with this protocol (Table 1), especially for cDC1s and cDC2s. cDC1s were phenotypically defined as CD14- CD123low CD141+ CD1c- HLA-DR+ and not all of them expressed CLEC9A. cDC2s were defined as CD14- CD123low CD141- CD1c+ HLA-DR+, a phenotype overlapping with that of MoDCs, and not all these cells expressed CD11c. These issues emphasize the necessity to develop a consensus nomenclature and rigorous methodologies to ensure proper identification and characterization of in vitro derived human DC types and to assess the extent of their resemblance to their blood counterparts. Finally, other protocols were developed combining the use of cytokines and feeder cells. Some of these protocols were optimized to enable recapitulating in vitro the differentiation of most immune cell lineages rather than for high yields of DC types, in order to study the ontogeny of these cells in terms of precursor-product relationships and of the underlying transcription factor networks, (Breton et al., 2015a; Breton et al., 2015b; Lee et al., 2015a; Lee et al., 2015b; Lee et al., 2017). Other protocols were tuned to increase the functionality and/or yields of cDC1s and pDCs, to facilitate studying the functions of these cells and their molecular regulation (Balan et al., 2018; Kirkling et al., 2018), and potentially with the aim to adapt them for compatibility with clinical use for adoptive cell immunotherapy in cancer patients. In these studies, in vitro derived DCs were characterized by gene expression profiling on sorted bulk populations in a pangenomic manner (Lee et al., 2015a) or by focusing on over 600 immune-related genes (Kirkling et al., 2018), or even by single cell RNA sequencing (Balan et al., 2018), demonstrating their close proximity to their blood counterparts. The study of cDC1 differentiation in vitro from HSCs led to the identification of their immediate, proliferative, precursor lacking XCR1 expression (Balan et al., 2018).

2.7 In vitro differentiation from cMo of cells sharing some features with blood cDC1s. Because they are much more accessible and numerous than HSCs, several teams attempted to derive cDC1s from blood cMos. At least three independent teams did report the in vitro differentiation of blood cMos into cells sharing some features with blood cDC1s, including the co-expression of CD11c, CD141 and CCR7, and eventually improved migratory, cross-presentation and co-stimulation capacities (Findlay et al., 2019; Kim et al., 2019; Tomita et al., 2019) (Table 1). The CD141+ DCs derived from cMo did express higher levels of CLEC9A, XCR1 and TLR3 than the other MoDCs to which they were compared, but only slightly, and not always reaching statistical significance. Moreover, in at least one study, these cells expressed high levels of CD11b and CD209 (Kim et al., 2019), unlike any other type of bona fide cDC1 reported to date, but like CD141+ MoDCs (Balan et al., 2014; Goudot et al., 2017). Thus, further investigations must be carried out before definite conclusions can be reached regarding the precise nature of these CD141+ DCs.

2.8 In vitro differentiation from iPSCs. Because they are amenable to gene editing more easily than HSCs to decipher the molecular mechanisms regulating their differentiation into distinct human cell types, and because of their potential for clinical use, iPSCs have also been used recently as progenitors for in vitro differentiation of human DC types. At least two different groups derived iPSC lines from human dermal fibroblasts or blood KIT+ cells and used them for in vitro differentiation in a two-step culture system (Table 1). The first step consisted in cultivating the iPSCs for several weeks with a cocktail previously reported to instruct their proliferation and their differentiation into hematopoietic progenitors. After, these cells were shifted into other culture conditions for a few days, favoring their further differentiation into DCs. One group used GM-CSF and IL-4 for the differentiation of iPSC-derived HSCs into DCs. They were able to differentiate cells co-expressing HLA-DR, CD11c and CD141 likewise to blood cDC1s (Sachamitr et al., 2017; Silk et al., 2012). However, these in vitro differentiated CD141+ DCs also expressed CD11b, CD14 and a fraction was CD209+ (Sachamitr et al., 2017; Silk et al., 2012). This phenotype more akin to MoDCs (Balan et al., 2014; Goudot et al., 2017) raises questions on the precise nature of these CD141+ DCs. In any case, at an immature state, these CD141+ DCs exerted tolerogenic functions that could be further reinforced by treatment with Vitamin D3, leading to an increase in the induction of regulatory FOXP3+ or IL-10+ CD4+ T cells. Another group differentiated the CD43+ HSCs derived from iPSCs with FLT3L, SCF, GM-CSF ± IL-4, on irradiated OP9 feeder cells (Sontag et al., 2017). In this experimental set-up, they were able to generated a variety of cell types bearing phenotypes and expressing key genes resembling those of distinct immune cell types (Table 1), including cDC1s (CD141+ CLEC9A+ CD11c+ HLA-DR+), cDC2s (CD14- CD1c+ CD11c+ HLA-DR+), pDCs (CLEC4C+ NRP1+ CD123+ HLA-DR+), cMo (CD14+ CD1c-), granulocytes (CD66b+) and mast cells (FCER1+ KIT+). However, the pDCs generated in vitro expressed CD11c contrary to blood pDCs and were not tested for IFN-α production upon TLR7 or TLR9 triggering. The phenotypic definition used for cDC2s overlapped with that of MoDCs. Thus, definite conclusions cannot be drawn yet regarding the precise nature of these putative in vitro derived cDC2s and pDCs.

2.9 Trans-differentiation from fibroblasts. An alternative method that was recently used to differentiate in vitro cells sharing typical features of blood cDC1s was the transdifferentiation from fibroblasts under the combined instruction of PU.1, IRF8 and BATF3 (Rosa et al., 2018). This was achieved in parallel with mouse cells, and the cDC1-like cells obtained through this method were deeply characterized including by gene expression profiling. The characterization of the human fibroblast-derived cDC1 was much less profound, such that further studies will be required to determine the extent of their similarity to blood cDC1s.

2.10 Immortalization of primary DC types. Once fully differentiated, in vitro derived DCs remain relatively resistant to lentiviral transduction (Silvin et al., 2017) and do not survive long. Thus, availability of immortalized cell lines that would tightly mirror the molecular make-up and immune activities of primary human DC types would considerably ease the dissection of the molecular bases underlying their functional specialization, including by enabling use of the CRISPR/Cas9 technology to generate cell lines knocked out for one or even several candidate genes. However, publicly available myeloid cell lines do not align well with either primary MoDCs or ex vivo DCs, failing to recapitulate their most critical biological and immunological features (Lundberg et al., 2013; van Helden et al., 2008). This is even the case for widely used tumor pDC lines, which for example produce much less IFN-I than their primary counterparts and under a different molecular control that paradoxically required IRF5 but not IRF7 (Pelka and Latz, 2013; Steinhagen et al., 2013; Steinhagen et al., 2016) contrary to primary pDC (Ciancanelli et al., 2015). Recently, transduction of the TAX from HTLV-2 into MoDCs or blood DCs was shown to lead to their survival for many months in a fraction of samples, or even to immortalization for blood DC, in a manner preserving or even improving their ability to prime CTL through direct antigen presentation (Wu et al., 2018) (Table 1). The Tax-DCs obtained were CD3- CD14- CD19- CD11c+ CD205+ TLR3+ TLR4- cells harboring a constitutive activation of the NF-κB pathway associated to high-level expression of positive co-stimulation molecules (CD70+ CD80+ CD83+ CD86+), spontaneous production of several cytokines, and a strongly enhanced T cell priming ability. These DC lines express CD141 and high levels of TLR3 and DEC205 but not CD14 and TLR4, likewise to primary cDC1s. However, they also express high levels of TLR7 and TLR9 contrary to primary cDC1s. They were neither tested for the expression of the cDC1-specific markers CLEC9A, XCR1 or CADM1, nor examined for cytokine responses to TLR3 triggering or characterized by global gene expression profiling. Hence, the precise identity and functions of these cell lines, and their molecular regulation, remain to be established. Moreover, it will be important to pursue the characterization of how their immortalization by TAX may have altered their molecular makeup and functions, and hence to which extent, for which functions, they could represent a good surrogate model of primary DC types. In any case, these Tax-DC lines could be genetically modified to express tumor-associated Ags to prime antitumor CTLs, for enhanced expression of positive co-stimulation signals and for knockout of endogenous negative immune checkpoint engagers. This further enhanced their ability to activate anti-tumor CTLs and NK cells, which were then are able to suppress metastasis of human lung cancer cells transplanted in NSG mice. Thus, this study pointed out a novel and promising method for human DC immortalization with potential therapeutic applications against viral infections or cancer.

3. Proposed guidelines to ensure of the identity of the DC types generated. As discussed in the previous section, the precise identity of some of DC types generated in vitro was not always clear in some studies, due to use of ambiguous phenotypic keys, lack of deep enough transcriptional profiling, insufficient functional characterization and/or absence of side-by-side comparison with appropriate reference populations. For example, in several studies, in vitro derived DCs were assumed to be cDC1s mostly based on their high CD141 expression, which is inappropriate since this cell surface marker is promiscuously expressed on other DC types in several conditions. Indeed, in vitro derived bone fide MoDCs can express high levels of CD141 (Balan et al., 2014; Goudot et al., 2017), which was also observed for the MoDCs isolated from tumor ascites (Segura et al., 2013) as well as for a fraction of blood cDC2s from healthy individuals (Haniffa et al., 2012) and all of the cDC2s isolated from the blood of patients deficient for IRF8 (Kong et al., 2018). Conversely, in one study, in vitro derived CLEC9A+ cDC1s were reported not to express CD141 (Proietto et al., 2012). Similarly, CD1c is not a reliable markers of cDC2s since it can also be expressed on MoDCs (Goudot et al., 2017) and in vitro derived cDC1s (Balan et al., 2018; Balan et al., 2014; Kirkling et al., 2018; Poulin et al., 2010), as well as on the circulating cDC1s arising upon in vivo injection of FLT3-L (Breton et al., 2015b). Hence, for future studies, it is important to attempt defining consensus guidelines on how to ensure of the identity of the DC types generated. To move towards this aim, we propose a concise list of phenotypic keys, transcriptomic signatures, archetypic functions and eventually few other characteristics that should help rigorously discriminating different DC types from one another (Table 2), as a working base to be examined, discussed and edited by other experts in the field. An important issue remains the choice of antibody used, and the necessity to perform fluorescence minus one controls to ensure specificity of the signal. For example, in several studies, XCR1 expression by in vitro derived DCs was not reliably assessed due to use of an Ab of insufficient specificity and avidity (Proietto et al., 2012; Sachamitr et al., 2017; Silk et al., 2012), or because of a very low signal-to-background ratio with lack of side-by-side comparison with blood cDC1s (Kim et al., 2019; Sontag et al., 2017). In fact, all of the characteristics proposed to help identifying DC types are relative, such that result interpretation will always require side-by-side comparison with their blood or tissue counterparts as well as with other reference populations such as classical MoDCs and MoMacs. Ultimately, each time a novel in vitro differentiation protocol is designed to generate DC types, ideally the identities of the corresponding cells should be established by single cell RNA sequencing in side-by-side comparison with blood mononuclear phagocytes, classical MoDCs and classical MoMacs. As now possible with the Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) technology, it is even anticipated that combining single cell RNA sequencing with a panel of cell-surface antibodies tagged with oligonucleotide barcodes should enable in the very near future to refine invariant phenotypic keys enabling rigorous identification of human DC types in a conserved manner between cells derived in vitro and cells directly isolated ex vivo from various tissues.

Of note, the heterogeneity of human cDC2s and its alignment with that of mouse cDC2s is still the object of intense research and debate. Several studies established heterogeneity in human cDC2 circulating in blood (Bakdash et al., 2016; Villani et al., 2017; Yin et al., 2017), which has since been confirmed and refined by other studies (Alcantara-Hernandez et al., 2017; Cytlak et al., 2019; Dutertre et al., 2019). In brief, co-expression of CLEC10A and FCER1 and lack of expression of CD88 and CD89 appeared to be one of the most reliable criteria to identify human blood cDC2s within Lineage- HLA- DR+ CD11c+ cells (Dutertre et al., 2019; Heger et al., 2018). Within that population, BTLA expression most robustly discriminated the two cDC2 populations described, namely BTLA+ CD5high CD14- CD163- cells (sometimes coined DC2), versus BTLA- CD5low/- CD14+/- CD163+/- cells (sometimes coined DC3) (Cytlak et al., 2019; Dutertre et al., 2019). Importantly, the paper by Cytlak et al. established that the development of two types of human blood CLEC10A+ FCER1+ cDC2s differed in their requirement for IRF8, which is only required for the BTLA+ CD5+/- blood cDC2 subset but not for the BTLA- CD5- CD14+ subset (Cytlak et al., 2019). However, the Rudensky group reported two distinct populations in human spleen (Brown et al., 2019), which they reported to align well with mouse spleen cDC2 subsets but apparently not with the BTLA+ and BTLA- human blood cDC2 subsets. These results thus illustrate the complexity of the rigorous identification of cDC2s and their heterogeneity in both humans and mice, and show that this line of research still needs to be further developed in order to try to resolve current controversies and reach a consensual definition of cDC2s subpopulations.

4. Roles of feeder cells, cytokines, growth factors and transcription factors. 4.1 Feeder cells. Feeder cells promote the differentiation of specific immune cell lineages, especially lymphocytes but also pDC, that otherwise do not develop or do not reach their terminal differentiation state (Table 1). Combinations of different types of feeder cells have been shown to be optimal to promote multi- lineage HSC differentiation (Lee et al., 2017). In addition, feeder cells can contribute strongly increasing cell yields. However, to the best of our knowledge, the underpinning mechanisms have not been clearly identified yet. This line of investigation is important to pursue, both to advance our basic understanding of the molecular mechanisms regulating human DC ontogeny and also to be able to replace feeder cells by synthetic components. Indeed, clinical applications will require developing in vitro differentiation protocols of human HSCs that combine robust and high yield generation of well- identified DC types with compliance to cGMP and being as simple and cheap as possible.

4.2 Cytokines and growth factors. 4.2.1 The combination of SCF, FLT3-L and TPO promotes HSC expansion before their differentiation into DCs. The combination of SCF, FLT3-L and TPO promotes optimal expansion of HSCs (Murray et al., 1999), as is achieved in some of the protocols for one week prior to shifting the cell into the culture conditions instructing their differentiation into DCs (Table 1).

4.2.2 TGF-β is critical for the differentiation of LCs. Exogenous addition of TGF-β allows higher yield LC differentiation from HSCs, even in the absence of serum, as well as an increase in the frequency of these cells harboring Birbeck granules (Strobl et al., 1996). Moreover, the endogenous TGF-β present in the serum was shown to be critical for LC differentiation in the absence of exogenous addition of this cytokine (Caux et al., 1999). The molecular regulation of LC differentiation, including the specific effects of TGF-β, has been thoroughly reviewed in a recent publication (Strobl et al., 2019).

4.2.3 FLT3-L is the most critical cytokine for the differentiation of pDCs and cDCs from HSCs and synergizes with other cytokines in particular TPO and eventually IL-7. FLT3-L alone can support the expansion of HSCs (Piacibello et al., 1997). Culturing human HSCs with FLT3-L alone was sufficient to enable their differentiation into pDCs (Blom et al., 2000) (Table 1). Individual addition to FLT3-L of SCF, IL-3, IL-7, GM-CSF or G-CSF under these experimental settings did not improve pDC differentiation (Blom et al., 2000). On the contrary, strikingly, IL-3 was shown to inhibit pDC differentiation from HSCs in this culture system (Blom et al., 2000), even though this cytokine promotes the survival of already differentiated human pDCs (Grouard et al., 1997). HSCs mobilized into the peripheral blood by G-CSF administration were reported to undergo apoptosis when cultured with FLT3-L alone, which could be counteracted by the addition of TPO and SCF (Murray et al., 1999). Indeed, it was later shown that addition of TPO synergized with FLT3-L leading to an improved protocol yielding higher numbers of pDCs (Chen et al., 2004) (Table1). Not only pDCs, but also CD11c+ TLR3+ DCs (likely cDC1s) and cMo were produced upon culture of human HSCs with FLT3- L alone and their yields were significantly increased by TPO addition (Chen et al., 2004), emphasizing the key role of these growth factors in driving the development of both human pDCs and cDCs. Addition of IL-7 to FLT3-L and TPO could further promote both total cell expansion and the differentiation of pDCs and cDC1s (Balan et al., 2018). FLT3-L was shown to be indispensable for the in vitro production of cDC1s both in the absence (Poulin et al., 2010) or presence (Balan et al., 2018) of feeder cells. FLT3-L also cooperates with TGF-β to promote LC differentiation (Strobl et al., 1997). Consistent with these observations, DC numbers are increased by FLT3-L injection in mice, monkeys and humans (Breton et al., 2015b; Coates et al., 2003; Drakes et al., 1997; Maraskovsky et al., 1996; Pulendran et al., 2000) and CD135, the receptor of FLT3-L, is expressed on the entire DC development pathway, from BM precursors to terminally differentiated DCs (Chicha et al., 2004; Doulatov et al., 2010; Fogg et al., 2006; Lee et al., 2015b; Naik et al., 2007; Waskow et al., 2008).

4.2.4 GM-CSF and IL-4 can promote cDC1 differentiation. GM-CSF was shown to be critical together with FLT3-L, SCF and IL-4 for cDC1 generation from HSCs in the absence of feeder layer cells (Poulin et al., 2010). In a protocol using OP9-DL1 cells as feeder, low dose addition of GM-CSF to the FLT3-L, TPO and IL-7 cytokine differentiation cocktail boosted the generation of both pDCs and cDC1s from non-mobilized adult blood HSCs, and promoted the terminal differentiation of the cells including their expression of XCR1, which is particularly relevant for therapeutic applications (Balan et al., 2018).

4.2.5 Different factors might tip the balance of HSC differentiation towards the monocytic lineage at the expanse of pDCs and cDCs. Although GM-CSF and IL-4 can promote cDC1 differentiation as discussed above, they are classically used to drive cMo differentiation into MoDCs (Sallusto and Lanzavecchia, 1994; Sander et al., 2017). Moreover, GM-CSF impairs human HSC and mouse bone marrow progenitor differentiation into pDCs in FLT3-L cultures (Blom et al., 2000; Gilliet et al., 2002), consistent with signaling by GM-CSF through STAT5 which can inhibit STAT3 signaling downstream of FLT3-L (Crozat et al., 2010b). Thus, caution should be used regarding the time and dose of GM-CSF and IL-4 addition to HSC cultures aiming at generating pDCs and cDCs. Adding it too early or too concentrated may shift differentiation towards the monocyte/macrophage lineage. It is not known how pharmacological inhibition of AhR by SR1 promotes high yield differentiation of HSCs into pDCs, cDC1s and cDC2s upon culture with FLT3-L, TPO, SCF and IL-6 (Thordardottir et al., 2014). It might in part have occurred by enhancing the expansion and preserving the pluripotency of HSCs (Boitano et al., 2010). However, AhR was also recently shown to promote cMo differentiation into MoDC at the expense of MoMac, through the induction of BLIMP1 and by synergizing with IL-4 or TNF to induced IRF4 expression (Goudot et al., 2017). Thus, it is possible that AhR signaling also biases HSCs differentiation towards the monocytic/MoDC lineage at the expense pDCs and cDCs. Indeed, IRF4 and IRF8 appear to be oppositely regulated in immune cells, with high ratio of IRF8/IRF4 characterizing hematopoietic progenitors primed for differentiation into pDCs or cDC1s (Lee et al., 2017; Ma et al., 2019). Moreover, IRF8 is indispensable for the differentiation of human HSCs not only into pDCs and cDC1s but also into the BTLA+ fraction of cDC2s, whereas loss-of- function mutations of IRF8 do not impede the differentiation of cMo and BTLA- cDC2s (Cytlak et al., 2019).

4.3 Transcription factors. 4.3.1 The transcription factor network underpinning pDC identity. The ability to differentiate in vitro human HSCs into pDCs under conditions amenable to genetic manipulation was instrumental in dissecting the transcription factor network underpinning the identity of this cell type. PU.1 was shown to be required for HSC differentiation into pDCs but also into pro-B cells and CD14+ CD11c+ cells (Spits et al., 2000). ID2 and ID3 inhibit whereas TCF4 instructs and SPIB favors human HSC differentiation into pDCs (Nagasawa et al., 2008; Schotte et al., 2004; Spits et al., 2000), mirroring the molecular requirements for mouse pDC differentiation in vivo as identified by studying mutant animals (Reizis, 2019). The critical role of TCF4 in instructing human pDC differentiation was independently established upon the description of a significant decrease and impaired functionality of these cells in Pitt-Hopkins syndrome patients bearing a mono-allelic loss-of- function mutation of this gene (Cisse et al., 2008). Importantly, TCF4 overexpression increased pDC differentiation and could even overcome its inhibition by ectopically expressed ID2, consist with a model whereby E2-2 promotes pDC over cDC1 differentiation at least in part by sequestering ID2 (Reizis, 2019). NOTCH signaling was demonstrated to promote HSC differentiation into T cells (Dontje et al., 2006) or cDC1s (Balan et al., 2018) over pDCs. Pharmacological inhibition of IKAROS also promoted HSC differentiation into cDC1s over pDCs, consistent with decreased pDC numbers and expanded cDC1s in patients with heterozygous IKZF1 mutations (Cytlak et al., 2018), and mirroring the situation previously described in mice homozygous for a hypomorphic mutation of this transcription factor (Allman et al., 2006). HSCs from patients deficient for IRF8 were compromised for their differentiation into pDCs, cDC1s and BTLA+ cDC2s but not into cMo or BTLA- cDC2s (Cytlak et al., 2019; Kirkling et al., 2018). By generating and characterizing IRF8-/- human iPSCs and ES cells, using RNA guided CRISPR/Cas9n genome editing, other authors confirmed that IRF8 is dispensable for hematopoietic progenitor differentiation from iPS or ES cells, whereas IRF8 deficiency biased differentiation toward granulocytes over cMo and strongly reduced cDC1 and pDC but not cDC2 development (Sontag et al., 2017).

4.3.2 The transcription factor network underpinning cDC1 identity. As discussed above, IRF8 was shown to be indispensable for ES cells, iPSC or HSC differentiation into cDC1s in vitro (Cytlak et al., 2019; Kirkling et al., 2018; Sontag et al., 2017), consistent with the lack of pDCs and cDC1s in patients deficient for IRF8 (Kong et al., 2018). BATF3 was indispensable for HSC differentiation into cDC1s in vitro but not in vivo in humanized mice (Poulin et al., 2010), consistent with the context-dependent requirement of this transcription factor for mouse cDC1 development in vivo due to compensation by BATF or BATF2 under certain inflammatory conditions (Tussiwand et al., 2012). In the cDC1 lineage, enforced ID2 expression is proposed to sequester TCF4 and prevent auto- amplification of its expression, thus preventing pDC differentiation (Reizis, 2019). In mice, cDC1 development heavily depends on an NFIL3–ZEB2–ID2 transcription-factor regulatory circuit instructing usage of a specific enhancer of the IRF8 gene (Bagadia et al., 2019; Durai et al., 2019).

4.3.3 The transcription factor network underpinning cDC2 identity. The role of transcription factor networks in defining cDC2 identity and functions has been reviewed thoroughly in a recent review (Bosteels and Scott, 2020). Most work on this topic has been performed in the mouse, with still many questions open and the necessity to extend studies to humans. Here, we will summarize key findings on IRF4, IRF8, NOTCH and T-BET. In both humans and mice, IRF4 is preferentially expressed by cDC2s (Guilliams et al., 2016), and a lower IRF8/IRF4 ratio correlates with pre-cDC commitment to cDC2s (Grajales-Reyes et al., 2015; Ma et al., 2019; Schlitzer et al., 2015). In mice, IRF4 contributes to controlling cDC2 development, survival, maturation and ability to present antigens to CD4+ T cells (Bosteels and Scott, 2020). However, its inactivation does not result in the complete loss of that population. Human patients with a heterozygous dominant-negative mutation of IRF8 harbored not only a complete loss of pDCs and cDC1s but also of BTLA+ cDC2s whereas the BTLA- cDC2 subset was expanded (Cytlak et al., 2019). The dependency of human BTLA+ cDC2 development on IRF8 was recapitulated in vitro upon differentiation of HSCs (Cytlak et al., 2019). IRF8 inactivation abrogates cDC1 development and alters pDC phenotype and functions in mice, whereas it appears to largely spare cDC2s at least at steady state (Sichien et al., 2016). However, Irf8−/− cDC2s were reported to be impaired in their maturation and ability to activate CD4+ T cells (Aliberti et al., 2003; Mattei et al., 2006). In mice, Notch2 signaling is specifically required for the development of ESAMhigh cDC2 subset (Bosteels and Scott, 2020). Moreover, its inactivation compromises the steady state development of intestinal IL-17-producing CD4+ T cells as well as the induction of IL-17 responses to certain bacterial infections, likely because of loss of IL-23 production by cDC2s. Notch2 signaling in cDC2s may also promote their ability to induce T follicular helper CD4+ T cells that promote antibody production (Bosteels and Scott, 2020). In human culture of hematopoietic precursors, NOTCH activation through DL1 does promote cDC2 development although muck less strikingly that for cDC1s (Balan et al., 2018; Kirkling et al., 2018). Although typically thought of as a TF associated with and innate lymphoid cell (ILC) subsets, recently, T-bet expression was reported to delineate two subsets of cDC2s in mice (Brown et al., 2019). The phenotype and gene expression pattern of T-bet+ cDC2 overlapped to some extent although not perfectly with those of ESAMhigh, Notch2-dependent cDC2s. However, T-bet+ cDC2s were reported to be more anti-inflammatory, at least at steady state(Brown et al., 2019), which appears contradictory with the functions assigned to ESAMhigh cDC2s and their regulation by Notch2 signaling (Bosteels and Scott, 2020). Moreover, although two equivalent human cDC2 subsets were identified in the human spleen, whereas the CLEC10A+ CLEC4A- cDC2s equivalent of the mouse T-bet- cDCs were reported in all human anatomical compartments examined, the CLEC10A- CLEC4A+ cDC2s equivalent to the mouse T-bet+ cDC2s were present in the spleen and in tumors but absent from peripheral blood (Brown et al., 2019). Hence; further studies will be necessary to better understand the transcription factor networks controlling cDC2 ontogeny and functions in mice and to investigate to which extent these mechanisms are conserved in humans (Bosteels and Scott, 2020).

4.3.4 The transcription factor network controlling MoDC versus MoMac differentiation. cMo differentiation towards MoDC versus MoMac differentiation had been previously reported to be instructed by a balance between the transcription factors PU.1 and MAFB (Bakri et al., 2005). Our understanding of the molecular regulation of this bifurcation in cMo lineage commitment has recently been further advanced by harnessing a novel differentiation protocol enabling simultaneous generation of MoMac and MoDC in the same cMo culture, confirming that MAFB is essential for MoMac differentiation and newly identifying IRF4 and AHR-to-BLIMP1 signaling as critical for MoDC differentiation (Goudot et al., 2017). Finally, in an independent sudy, nuclear receptor co-repressor 2 (NCOR2) was identified as another transcription factor key for the promotion of MoDC differentiation downstream of IL-4 signaling (Sander et al., 2017). 5. How in vitro-derived DCs can facilitate basic research on DC biology. 5.1 Ontogeny. Our understanding of the ontogeny of mouse DC types advanced tremendously in the last decade, benefiting from the use of a combination of methods, including the study of mutant mice deficient for growth factors or cytokines and the development of clonal in vitro differentiation cultures (Mildner and Jung, 2014). This led to the discovery of hematopoietic progenitors with restricted potential for the monocytic and/or DC lineages. The macrophage and dendritic cell progenitor (MDP) gives rise exclusively to the monocytic and dendritic cell lineages including pDCs (Auffray et al., 2009; Fogg et al., 2006). The common DC progenitor (CDP) gives rise to cDCs and pDCs (Naik et al., 2007; Onai et al., 2007). However, new technical advances, including the engineering and characterization of reporter mice enabling fate mapping of specific immune lineages, and the ex vivo characterization of the gene expression program and epigenetic landscaped of single cells, provided strong evidence that these progenitor population are heterogeneous. They encompass distinct populations each endowed with a more stringent commitment, namely the monocyte progenitor (cMoP) (Hettinger et al., 2013; Liu et al., 2019), the pDC progenitor (pro-pDC) (Dress et al., 2019; Onai et al., 2013; Rodrigues et al., 2018), the classical DC progenitor (pro-cDC)(Meredith et al., 2012; Sathe et al., 2014; Satpathy et al., 2012; Schraml et al., 2013), and the pre-terminal stages of cDC differentiation (pre-cDC, pre-cDC1 and pre- cDC2) (Schlitzer et al., 2015). Moreover, the possibility to genetically tag in vitro hundreds of HSCs with unique lentivector-based barcodes allowed to follow in vivo the clonal output of single HSCs to probe the existing models of the hematopoietic tree. Some of these studies provided strong support to a novel view of hematopoiesis, whereby lineage commitment in vivo in mice occurs at much earlier stages than previously thought, in particular with an early segregation of the DC lineage from pre- committed multipotent progenitors independent of the segregation between the lymphoid and myeloid lineages (Naik et al., 2013; Paul et al., 2015). Yet, recent papers claim that mouse pDCs exclusively derive from lymphoid progenitors (Dress et al., 2019; Rodrigues et al., 2018). Hence, even in the mouse, active controversies persist pertaining to the ontogeny relationship between monocytes/macrophages, cDCs and pDCs. The picture can only be more blurry for the ontogeny of human DC types, since many of the experimental strategies used in mice are not achievable in the human system. Nevertheless, remarkable progresses have been made in the last few years in a large part by using the in vitro differentiation models described in the previous sections. Although some of these studies were designed in a supervised manner based on the knowledge previously acquired in the mouse model, the data obtained are quite clear and their interpretation further supported by unbiased single analysis of progenitor cells in clonal differentiation assays and by gene expression profiling. Overall, the picture emerging seems quite similar to what has been discovered in mice. Specifically, downstream of the HSC to multipotent progenitors (MPP) to common myeloid progenitors (CMP) differentiation trajectory, use of the multi-lineage differentiation model of human HSCs on MS5 feeder cells with FLT3- L, SCF and GM-CSF led to the identification of a series of hematopoietic progenitors with progressively more restricted commitment for DC differentiation (Figure 1), well matching the model proposed in mice, namely the granulocyte-monocyte-DC progenitor (GMDP), the MDP, the CDP (Lee et al., 2015a; Lee et al., 2015b) and the immediate precursors for cDCs (pre-DC) (Breton et al., 2015b; Breton et al., 2016). The pre-cDC was further resolved into distinct subpopulations based on their expression levels of CD172a and on their preferential commitment to differentiation into cDC1s or cDC2s, as instructed by their expression of specific transcription factors and assessed in clonogenic differentiation assays, namely CD172aint uncommitted pre-cDCs, BATF3 hi IRF8 hi CD172a- pre-cDC1s and IRF4 + CD172a+ pre- cDC2s. These pre-cDC1s and pre-cDC2s could be detected not only in BM but also in peripheral blood, consistent with the knowledge that mouse pre-cDCs can migrate from BM to lymphoid and non- lymphoid tissue. A parallel, independent, study confirmed the existence of pre-cDC1s and pre-cDC2s circulating in human blood, based on characterization of the CD123+ CD33+ CD45RA+ pre-cDC population by a combination of high content mass cytometry and single cell RNA sequencing. This led to the phenotypic definition of pre-cDC1s as CADM1+CD1c- and of pre-cDC2s as CADM1-CD1c+, with functional confirmation of their differentiation commitment in clonogenic differentiation assays on MS5 feeder cells (See et al., 2017). In another study, based on single cell RNA sequencing, a circulating population of CD45RA+ HLA-DR+ CD11c- CD123- CD100hi CD34int cells was identified in human blood and shown to differentiate into cDC1s and cDC2s but not pDCs in vitro on MS5 feeder cells, thus functionally corresponding to pre-cDC (Villani et al., 2017). To which extent the populations of pre- cDCs defined by distinct phenotypes in these different studies overlap remains to be established, but CD100 might be a useful marker to distinguish pre-cDCs from CDP and pre-pDCs. In any case, as proposed in the mouse, other recent studies demonstrated that the majority of mature blood cells are produced from lineage-specified, long-term progenitor cells that proliferate and transmit their lineage bias to their progeny (Lee et al., 2017). In particular, cDC1 commitment was shown to occur early in the hematopoietic tree independently of the segregation between the lymphoid and myeloid lineages, already in lymphoid-primed multipotent progenitors (LMMPs) or multi-lymphoid progenitors (MLPs), instructed by high IRF8 expression in some of these progenitors (Helft et al., 2017; Lee et al., 2017) (Figure 1). In any case, there is little doubt that further use of well-defined in vitro differentiation models of human DC types will continue accelerating our understanding of the molecular mechanisms underpinning their ontogeny, including by enabling high through screening of cytokines, transcription factors or noncoding regulatory RNA.

5.2 Functional specialization. In vitro differentiation models of human DC types already enabled confirming the functional specialization of human DC types. LCs were demonstrated to excel in naïve CTL activation, including through cross-presentation, whereas CD14+ DDCs promoted humoral immunity through Tfh induction and direct B cell stimulation (Klechevsky et al., 2008). In vitro derived pDCs were confirmed to produce high levels of IFN-I/III upon stimulation by virus-type stimuli (Balan et al., 2018; Chen et al., 2004; Dontje et al., 2006; Schotte et al., 2004; Spits et al., 2000), and to diffrentiate into mature DCs able to activate allogeneic T cells under adequate stimulation conditions (Chen et al., 2004; Spits et al., 2000). In vitro derived cDC1s harbored a high efficacy for the cross-presentation of cell-associated antigens, at least in comparison with MoDCs from the same culture (Balan et al., 2014). In vitro derived DC types were demonstrated to differ in their responses to various adjuvants, with confirmation of the unique ability of cDC1s to produce high levels of IFN-III upon TLR3 triggering and of IL-12p70 upon TLR8 triggering (Balan et al., 2018; Balan et al., 2014). cDC1s were also demonstrated to be resistant to viral infections, depending at least in part on their high selective expression of RAB15 (Silvin et al., 2017). MoDCs were shown to selectively produce IL-23 and induce a Th17 polarization of CD4+ T cells (Goudot et al., 2017). Further studies using well-defined in vitro differentiation models of human DC types will undoubtedly continue accelerating our understanding of the functional specialization of these cells and its molecular regulation, including by enabling high through screening to test adjuvant or vaccine candidates to improve the care of patients suffering from chronic viral infections or cancer.

6. Clinical applications of in vitro derived DCs. 6.1 Vaccination or treatment against Cancer. Many clinical trials have been performed over the last 25 years to attempt harnessing DC functions for treating cancer patients (Tacken et al., 2007; Wimmers et al., 2014). Up to now, the results have been disappointingly far below expectations. These failures occurred at least in part because of the almost exclusive use of MoDCs for adoptive cell therapy in cancer patients. Indeed, as discussed in the previous sections, for a very long time MoDCs were the only DC type that could be produced in vitro in high numbers and under cGMP. Moreover, it is only in the last decade that definite advances were made regarding the precise nature and the functional specialization of other DC types. This progress in the identification of human DC types and in our basic understanding of their heterogeneity and functional plasticity led to many evidences converging on the hypothesis that the DCs naturally orchestrating immune responses in our body should be better suited for boosting protective antitumor CTL responses in cancer patients (Bol et al., 2019). Hence, novel clinical trials have starting using ex vivo antigen loading, activation and reinfusion of autologous blood pDCs or cDC2s for treating cancer patients, since the frequency of these cells in circulation is sufficiently high for this purpose (Wimmers et al., 2014). Encouraging results were obtained (Schreibelt et al., 2016; Tel et al., 2013). However, evidences are accumulating that cDC2s are highly plastic and can be reprogrammed in the tumor microenvironment towards immunosuppressive functions deleterious for the patients (Bakdash et al., 2016; Di Blasio et al., 2019). In parallel, preclinical studies in mice and correlative analysis in humans are consistently pointing towards cDC1s as naturally associated with better tumor control including during checkpoint blockade administration (Cancel et al., 2019). Moreover, a preclinical proof-of- principle study was recently published supporting the therapeutic efficacy of cancer immunotherapy with syngeneic dead tumor cell antigen-loaded mouse cDC1s (Wculek et al., 2019). However, their very low frequency in peripheral blood and their frailness after ex vivo isolation constitute a major roadblock for using human blood cDC1s in adoptive transfer settings. This issue could be circumvented by further modifying the protocols for high yield in vitro generation of human cDC1s discussed in the previous sections, to replace the mouse feeder layers with clinical grade synthetic components, simplify the process as much as possible, and make it cGMP compliant.

6.2 Vaccination or treatment against HIV infection. A recent report reviewed twelve vaccination trials against HIV-1 based on adoptive cell transfer of autologous MoDCs exposed to different forms of antigens including mRNA, short peptides from either a consensus sequence virus or autologous viruses, long lipopeptides encompassing both MHC-I- and MHC-II-restricted epitopes, inactivated autologous virus, or infected apoptotic cells (Coelho et al., 2016). The clinical results were variable, generally much below expectations. The use of MoDCs presenting antigens derived from autologous viral quasi-species did increase the antiviral CTL responses of HIV-1-infected patients and improved their control of viral replication after antiretroviral therapy interruption (Brezar et al., 2015; Garcia et al., 2013; Levy et al., 2014; Surenaud et al., 2019). A recent analysis seeking for correlates of enhanced viral control in patients who received the vaccine consisting in autologous MoDCs loaded with HIV-1 lipopeptides showed a positive correlation with anti-HIV-1 polyfunctional T cell responses and a negative correlation with the levels of HIV-1-specific CD134+ CD25+ CD39+ FoxP3+ regulatory CD4+ T cells and the duration of vaccine-induced inflammatory responses (Thiebaut et al., 2019). These observations not only identified potential mechanisms explaining the differences in individual responses to the vaccination but also may provide a way to predict for each patient the outcome of vaccination by profiling his early transcriptomic response before deciding whether or not to proceed with antiretroviral therapy interruption. In any case, vaccines need to be further improved to increase the proportion of responders whose immune system is successfully reprogrammed for autonomous, efficient and sustained, virus control after antiretroviral therapy interruption. Different strategies have been proposed to reach this aim, including optimizing the format of the antigen and the types of adjuvants used to boost the immunogenic activity of the MoDCs, or even targeting the antigens to endogenous DCs in vivo by coupling with an anti-DEC205 antibody (Garcia, Plana et al. 2013). To the best of our knowledge, no studies have been conducted or even proposed based on using other types of DCs with a higher efficacy for the induction of CTL responses and a lower susceptibility to hijacking by the virus for its dissemination or to cause immunosuppression, as compared to MoDCs. cDC1s could represent a target of choice for this type of strategy (Silvin et al., 2017).

6.3 Induction of graft tolerance. In solid organ transplantation, there is a critical need to identify novel treatments able to prevent allograft rejection by inducing a sustained, donor-specific immune tolerance, enabling to reduce the dose and duration of treatment with broadly immunosuppressive drugs that have severe side effects including causing an enhanced susceptibility to infections and cancer. DCs represent an attractive target for this purpose, since they are thought to play a key role in tilting the balance between immune tolerance versus immune activation depending on the context (Marin et al., 2018; Thomson and Ezzelarab, 2018). Hence, several teams are working on protocols to generate in vitro regulatory DCs able to suppress anti-donor T cell responses and prolong transplant survival in preclinical animal models, from cMos (Marin et al., 2019) of from iPSCs (Sachamitr et al., 2017; Silk et al., 2012). The goal is to identify the best DC type and functional polarization procedure for the cGMP-compliant manufacturing of tolerogenic DCs. This should be greatly facilitated by the ability to differentiate different types of DCs in vitro, to genetically manipulate them, to test their functionality, including the steadiness of their polarization for tolerance induction even under conditions of exposure to immune activating signals, and to decipher the underlying mechanisms.

7. Concluding remarks. The ability to generate in vitro in the same culture different types of human DCs is a major breakthrough that has already accelerated the pace of discoveries on the ontogeny and functional specialization of these cells. In the few coming years, these in vitro model systems will likely be confirmed to be critical to allow us answering key questions regarding the biology of human DC types. For example, they may enable performing high throughput screening to decipher the molecular mechanisms regulating antigen cross-presentation by different types of human DCs. This was recently achieved for mouse cDC1s derived in vitro in FLT3-L cultures of bone marrow progenitors isolated from Cas9 transgenic mice and transduced with retroviruses expressing various sgRNAs (Theisen et al., 2018). Similar strategies could be used to understand the molecular basis of the differential susceptibility of human DC types to viral infections (Silvin et al., 2017). These models will undoubtedly also continue helping us understand the ontogeny of human DC types. They have already allowed confirming that, as in mice, several pairs of opposing transcription factors including E2-2/TCF4 and IKAROS/NOTCH appear to modulate the function of IRF8 to balance HSC differentiation towards pDCs versus cDC1s. These results advocate for the existence of a common precursor to pDCs and cDC1s in both species, in line with results from clonal analysis of hematopoietic progenitor differentiation in vitro and in vivo in mice (Naik et al., 2013; Naik et al., 2007; Onai et al., 2007) and in vitro in humans (Lee et al., 2017). This contrasts with the recent claim that pDC exclusively derive from lymphoid progenitors in mice (Dress et al., 2019; Rodrigues et al., 2018). A recent and original method enabling to image, track, analyze and model the dynamics of single progenitor developmental trajectories in a dish showed that mouse cDC and pDC lineages are largely separated already at the HSC stage (Lin et al., 2018). Applying this methodology to the in vitro development of human DCs from HSCs should be revealing. Finally, these models also represent interesting platforms to screen potential vaccine or immunotherapeutic treatments aiming at irreversibly polarizing DCs towards specific states of immunogenicity or tolerance to treat patients suffering from infections or cancer versus allograft recipients or individuals with autoimmune or inflammatory diseases, respectively. However, to achieve these goals, major efforts are required one the one hand to develop a consensus nomenclature and rigorous methodologies to ensure proper identification and characterization of human DC types, and on the other hand to adapt existing protocols to make them compatible with clinical use for adoptive cell therapy. Authorship XL and MD wrote the manuscript.

Declaration of Competing Interest The authors declare no conflicts of interest.

Acknowledgements This work was supported by CNRS, INSERM, Agence Nationale de Recherches sur le SIDA et les Hépatites Virales (ANRS, project ECTZ25472, to M.D.) and SIDACTION. X.L. is a fellow of SIDACTION. We apologize to the authors of relevant studies that could not be cited in this review due to space constraints. Table 1. Selected studies reporting in vitro generation and characterization of human DC types.

Cell types generated Culture protocol Name Phenotypic characterization1 Yields2 Precursor M: Medium References Additional characterization or % used7 C: Cytokines F: feeder In vitro differentiation of human LCs and CD14+ DDCs from HSCs (Caux et al., LC HLA-DR+ CD11chi CD11b+ CD1a+ CD14+/- CD207+ E-Cad+ ND  Morphology3,4,5. HSCs 5d to 21d differentiation. 1992; Caux CD14+ DDC HLA-DR+ CD11c+ CD11bhi CD1a- CD14hi CD207- E-Cad-  Activation of allogeneic CD4+ and CD8+ T (Gm) M: RPMI 1640, 10% FCS; or Yssel's, 5% autologous serum. et al., 1999; cells. C: GM-CSF, TNF, ± FLT3-L; endogenous TGF-β is required for LC Caux et al.,  Activation of syngeneic naïve CD4+ T cells differentiation. 1997; Caux with super-Ag. et al., 1996;  FITC dextran and HRP uptake. Klechevsky  Naïve B cell differentiation into IgM- et al., 2008) secreting cells upon CD40 triggering.  CD4+ T cell priming towards Th2 or Tfh.  Priming of naïve CD8+ T cells (allogeneic versus autologous Ag-specific).  Cross-presentation of a soluble Ag.  Ag-specific reactivation of memory CD8+ T cells. (Strobl et al., LC CD45+ HLA-DR+ CD1a+ CD33+ CD4+ CD40+ 3x104  Morphology. HSCs 7 to 10d differentiation. 1996)  T cell proliferation. (CB) M: serum-free X-VIVO 15 C: GM-CSF, TNF, SCF, TGF-β1 (Strobl et al., LC HLA-DR+ CD1a+ CD11clow/- CD40+ CD68+ CD32+ 3x105  expression assessed by microscopy HSC 10d differentiation. 1997) immunofluorescence. (CB) M: serum-free X-VIVO 15.  Microscopic evaluation of clonal expansion. C: GM-CSF,TGF-β1, TNF, SCF, FLT3-L.  Quantitation of cloning efficiency of HSCs.  allogeneic T cell activation. In vitro differentiation of human MoDCs and MoMacs from peripheral blood cMo. (Sallusto and MoDC CD3- CD19- HLA-DRhi CD11c+ CD11b+ CD1c+ CD14-/low 104  Morphology3. cMo8 7d up to 3m differentiation. Lanzavecchia  Activation of allogeneic T cells. M: RPMI 1640, 10% FCS, suppl. , 1994)  Processing and presentation of a soluble Ag C: GM-CSF, IL-4. to a CD4+ T cell clone or polyclonal T cell lines. (Goudot et MoDC CD1a+ CD16- CD206+ CD163-/low CD11bhi CD172ahi  Morphology6. cMo 5d differentiation al., 2017) MoMac CD16+ CD1a- CD206+ CD163+ CD11bhi CD172ahi  Gene expression profiling: pangenomic (Blood) M: RPMI, 10% FCS, suppl. microarrays on sorted populations as C: M-CSF, IL-4, TNF ± SR1 or M-CSF alone. compared to inflammatory MoDC and Mac isolated from tumor ascites from cancer patients and to blood cDC2.  Cytokine production upon CD40 triggering (MoDC produce both IL-23 and IL-6, MoMac IL-6).  Activation of allogeneic naïve CD4+ T cells. High yield differentiation of human MoDCs from HSCs (Balan et al., MoDC HLA-DR+ CD11c+ CD1a- 1.8x106  Morphology3,6. HSCs 1) 21d amplification. 2009, 2010)  FITC-dextran/Lucifer yellow endocytosis (CB) M: IMDM, 5% auto. serum. assay. C: FLT3-L, SCF, TPO.  Phenotypic maturation and cytokine 2) Mo enrichment, by plastic adherence or flow cytometry production (IL-12, IL-10) upon TNF + LPS + sorting of CD14+ cells. CD40L stimulation. 3) 7d differentiation.  Activation of allogeneic T cells by mature M: IMDM, 5% auto. serum. DC. C: GM-CSF, IL-4 for 3d, then GM-CSF, TNF for 4d.  Chemotactic assay towards CCL19 of mature DC. Simultaneous in vitro differentiation of human cDC1s and Mo or MoDCs from HSCs. (Helft et al., cDC1 CD141hi CLEC9A+ CD11c+ HLA-DR+ CD11b- 7x105  Morphology6. HSCs 1) 7d amplification. 2017; Poulin Mo CLEC9A- CD14+ CD1a- 9x105  Gene expression profiling: qRT-PCR for a CMP, M: StemSpan (serum free). et al., 2010) cDC2?9 CLEC9A- CD14- CD1a+ CD11chi HLA-DRhi 2x105 few selected genes on bulk sorted cDC1 GMP, MLP C: FLT3-L, SCF, IL-3, IL-6. /GMP10 derived from HSCs as compared to cDC1 or (CB) 2) 12-14d differentiation. pDC sorted from humanized mice; M: RPMI 1640, 10% FCS, suppl. microarray pangenomic profiling of CMP- C: FLT3-L, SCF, GM-CSF, IL-4. and MLP-derived cDC1.  Cytokine production upon stimulation with Poly(I:C) or R848.  Uptake of dead cell debris.  Long peptide cross-presentation to a T cell clone.  Comparison of the efficacy of sorted CMP, GMP and MLP to differentiate into cDC1. (Balan and cDC1 CD11c+ CD141hi CLEC9A+ XCR1+ CD206-CD209- 2x105  Morphology6. HSCs 1) 7d amplification. Dalod, 2016; MoDC CD11chi CD141+ CLEC9A- XCR1- CD206+ CD209+ 7x105  Gene expression profiling: microarrays on (CB or BM M: StemSpan. Balan et al., sorted populations at steady state and upon or Gm) C: FLT3-L, SCF, IL-3, TPO. 2014) activation by synthetic TLR ligands. 2) 11d differentiation.  Responses to TLR ligands [LPS, Poly(I:C), M: RPMI 1640, 10% FCS, suppl. R848]. C: FLT3-L, SCF, GM-CSF, IL-4.  Stimulation of allogeneic CD4+ T cells.  Cross-presentation of a cell-associated Ag. In vitro differentiation of human pDCs from HSCs. (Spits et al., pDC CD123+ CD45RA+ CD4+ CD11c- <3x103  IFN-α production upon stimulation with HSCs 2d differentiation. 2000) HSV-1. (FL) M: Yssel’s, 5% FCS.  Phenotypic maturation and activation of F: S17 allogeneic naïve CD4+ T cells upon culture with IL-3 and simulation through CD40.

(Blom et al., pDC HLA-DR+ CD123hi CD45RA+ CD4+ CD11c- 5-10%  IFN-α production upon stimulation with HSCs 20d to 60d differentiation. 2000) HSV-1. (FL or CB) M: Yssel’s, 2% HS. C: FLT3-L (Dontje et pDC CD123hi CLEC4C+ 103  IFN-α production in bulk cultures upon HSCs 7d differentiation. al., 2006; Mo CD14+ CD11c+/- 2.5x103 stimulation with HSV-1 or CpG. (FL or pnT) M: Yssel’s, 8% FCS; or MEMα, 20% FCS. Schotte et Pro-B cells CD10+ CD19+ 7x102 C: FLT3-L, IL-7. al., 2004) F: OP9 or OP9-DLL1 or -Jag1. (Chen et al., pDC Lin- HLA-DR+ CD123hi CD11c- CD4+ CD45RA+ 6x104  Morphology4,5. HSCs 20d differentiation. 2004) cDC? Lin- HLA-DR+ CD123-/low CD11c+ 2x105  IFN-α production upon stimulation with (FL or Gm) M: Yssel's. Mo CD14+ 3x106 HSV-1. C: FLT3-L, TPO. HSC CD34+ 4x104  Phenotypic maturation and activation of allogeneic T cells upon CpG or CD40L stimulation.  Gene expression profiling: RT-PCR for TLR1, TLR9 and TLR3 on bulk sorted pDC versus CD11c+ DC. Simultaneous in vitro differentiation of human cDC1s, cDC2s and pDCs from HSCs. (Proietto et cDC1 CD14- CD11cint CLEC9A+ HLA-DR+ SIRP1a-/low CD11b- 2x104  Morphology6. HSCs 21d differentiation. al., 2012) cDC2?9 CD14- CD11c+ CD1c+ HLA-DR+ SIRP1ahi CD11b+ 3x104  Gene expression profiling: qRT-PCR for a (Gm) M: Yssel's, 10% AB serum pDC CD14- CD11c- CD123+ HLA-DR+ SIRP1a+ CD11b-/low 3x104 few selected genes on bulk sorted cell C: FLT3-L, TPO. Mo CD14+ 7x105 populations.  Cytokine production upon stimulation with CD40L, IFN-γ, GM-CSF, IL-4, and CpG for pDC leading to IFN-α production, Poly(I:C) for cDC2 or LPS for Mo.  Activation of allogeneic CD4+ T cells.  Cross-presentation of a soluble Ag. (Thordardott cDC1 CD14- CD123low CD141+ CD1c- HLA-DR+ 1x105  Gene expression profiling: qRT-PCR for TLR HSCs 21d differentiation. ir et al., cDC2?9 CD14- CD123low CD141- CD1c+ HLA-DR+ 5x105 genes on bulk sorted cell populations. (CB) M: Yssel's, 10% AB serum, with StemRegenin 1 (SR1), a small 2014; pDC CD14- CD123hi CLEC4C+ HLA-DR+ CD11c- 4x105  Responses to stimulation with molecule inhibitor of aryl hydrocarbon receptor (AhR). Thordardotti [Poly(I:C)+R848] for CD141+ DC and CD1c+ C: FLT3-L, TPO, SCF, IL-6. r et al., DC, and to CpG for pDC. 2017)  Activation of allogeneic CD4+ and CD8+ T cells.  Activation of Ag-specific CD8+ T cells. (Breton et cDC1 CD141+ CLEC9A+ CD11c+ HLA-DR+ ~6x104  Gene expression profiling: RNAseq on HSCs 14d differentiation. al., 2015a; cDC2?9 CLEC9A- CD1chi CX3CR1+ SIRPahi CD11chi HLA-DRhi ~3x106 sorted populations as compared to their (CB or BM M: α-MEM, 10% FCS. Lee et al., pDC HLA-DR+ CD11c- CD123hi CD45RA+ CLEC4C+ CD1c- ~2x105 blood counterparts. or Gm) C: FLT3-L, SCF, GM-CSF. 2015a; Lee Mo CD14+ CD16- CLEC9A- CD66b- CD1c- ~106  Cytokine production upon stimulation with F: MS5 ± OP9 cells (mitomycin C-pretreated). et al., 2015b; Gran. CD66b+ ~3x105 to Poly(I:C) or CpG. Lee et al., B cells CD19+ ~3x104 2017) NK cells CD56+ ~8x103 HSC CD34+ ~8x103 (Balan et al., cDC1 CD11c+ CD141+ CLEC9A+ CADM1+ XCR1+ CD1c+ CD1a+ 3x105  Gene expression profiling by scRNAseq as HSCs 1) 7d amplification. 2018) cDC2 Lin- HLA-DR+ [CLEC10A+ CX3CR1+ CD1A+]10 ~5x105 compared to their blood counterparts. (CB, BM or M: α-MEM, 10% FCS. pDC CD123+ CLEC4C+ LILRA4+ BTLA+ CLEC9A- CADM1- XCR1- 106  Cytokine production upon stimulation with Gm) C: FLT3-L, SCF, IL-7, TPO. ASDC Lin- HLA-DR+ CD123+ CLEC4C+ AXL+ SIGLEC6+ ~104 Poly(I:C), R848 or CpG. 2) 14-21d differentiation. Mo CD14+ ~105 M: α-MEM, 10% FCS, suppl. CLP? [identification based on scRNAseq analysis] ND C: FLT3-L, IL-7, TPO ± GM-CSF. MEP? [identification based on scRNAseq analysis] ND F: OP9 and/or OP9-DL1 cells. HSC [identification based on scRNAseq analysis] ND (Kirkling et cDC1 Lin- HLA-DR+ CD14- CD141+ CLEC9A+ ~5x104  Gene expression profiling: NanoString for HSCs 14-21d differentiation. al., 2018) cDC2 Lin- HLA-DR+ CD14- CD141+/- CLEC9A- CD1c+ CD11c+ ~2x104 614 selected genes on sorted populations. (BM) M: α-MEM, 10% FCS. pDC Lin- HLA-DR+ CD14- CD11c- CD123hi (CLEC4C/NRP1)+ ~2x103  Cytokine production upon stimulation with C: FLT3-L, SCF, GM-CSF. Mo Lin- HLA-DR+ CD14+ ~8x103 a cocktail of Poly(I:C), LPS, CL075, CpG. F: OP9, OP9-DL1 or OP9-DL4 cells.  Activation of allogeneic CD4+ and CD8+ T cells. In vitro differentiation from cMo of cells sharing some features with blood cDC1s. (Kim et al., Att. MoDC CD11b+ CD11c+ CD1a+ CD1c+ CD209+ CD141+ 20%  Comparison of the DC attached, semi- cMo 8d differentiation. 2019) Sa. MoDC CD11b+ CD11c+ CD1a+ CD1c+ CD209+ CD141int 12% attached or in suspension. No comparison (Blood) M: RPMI 1640, 10% FBS. Sus. MoDC CD11b+ CD11c+ CD1a+ CD1c+ CD209+ CD141int 68% with blood cDC1. C: GM-CSF, IL-4.  Morphology6.  Dead cell uptake.  Cytokine production in response to Poly(I:C) stimulation.  Activation and functional polarization of allogeneic CD4+ T cells and CTLs. (Findlay et CD141+ DC HLA-DR+ CD11c+ CD141+  Gene expression profiling: qRT-PCR analysis cMo8 7d differentiation. al., 2019) of the expression of THBD, IRF8 . M: RPMI, suppl.  Chemotaxis to CCL19, CCL21 or XCL1. C: GM-CSF, IL-4 ± LL-37.  IL-12p70 production and presentation of EBV antigens for activation of autologous CTL, upon stimulation with Poly(I:C). (Tomita et CD141+ DC CD11c+ CD1b+ CD1a+ CD141+ 20-50%  Comparison of the steady state MoDC with cMo 6d differentiation. al., 2019) those activated for 2 hrs with (Blood) M: RPMI 1640, 10% FCS, suppl. Mycobacterium‑derived mycolic acid and C: GM-CSF, IL-4. lipoarabinomannan.  Cross-priming of CTLs against dying tumor cells.  IL-12 and IL-10 production.  Activation of allogeneic CD4+ T cells. In vitro differentiation from iPSCs. (Sachamitr CD141+ ipDC HLA-DR+ CD11c+ CD141+ CD14+ CD11b+ CD209+/-  Morphology3. iPSCs iPS cell line differentiation from human dermal fibroblasts. et al., 2017;  2d maturation with TNF, PGE2, IL-1b, IFN-γ. 24d-28d differentiation. Silk et al.,  FITC-bead capture and Ag (DQ-OVA) M: XVIVO-15, suppl. 2012) processing. C: GM-CSF (always), BMP4 (until d5), VEGF (until d14), SCF  Chemotaxis to CCL19 or XCL1, compared to (until d19), IL-4 (from d13) MoDC. 2d-4d replating.  IL-12 production upon combined triggering M: XVIVO-15, suppl. of TLR3,4, 8 and CD40. C: GM-CSF, IL-4.  Ag-specific priming of naïve CTLs.  Soluble Ag cross-presentation to a CTL clone.  Activation and functional polarization of allogeneic naïve T cells. (Sontag et cDC1 CD141+ CLEC9A+ CD11c+ HLA-DR+ 10%  Morphology3. iPSCs iPS cell line differentiation from BM KIT+ progenitor al., 2017) cDC2?9 CD14- CD1c+ CD11c+ HLA-DR+ 2-10%  Activation upon 6 hr stimulation with LPS or reprogramming with OCT4, SOX2, c-MYC, and KLF4 Sendai pDC? CLEC4C+ NRP1+ CD123+ HLA-DR+ CD11c+ 20% CpG and IL-3, and qRT-PCR analysis of the virus vectors. Mo CD14+ CD1c- 5-20% expression of selected genes (IL6, IL12, TNF, 8d-42d differentiation of iPSCs into hematopoietic progenitors Gran. CD66b+ 20-60% CD80, CCR7, HLA-DR). and immune lineages. Mats cells FCER1+ KIT+ 0.5-7% M: StemPro34, suppl. C: BMP4, bFGF, VEGF, hyper-IL-6, SCF, IGF1, IL-3, TPO, FLT3L. 4-8d differentiation from d8 iPSC-derived CD43+ cells. M: RPMI, 10% FCS, suppl. C: FLT3L, SCF, GM-CSF ± IL-4. F: OP9 (irradiated). Trans-differentiation from fibroblasts. (Rosa et al., cDC1 CD45+ HLA-DR+ CD141+ CLEC9A+ 0.6%  Morphology. Fibroblasts 7-9d differentiation of fibroblasts after transduction with 2018)  Ability to engulf beads, OVA and dead cells. lentivectors encoding PU.1, IRF8 and BATF3. Immortalization of primary DC types. (Wu et al., Tax-MoDC CD4+ ND  Morphology3. MoDC Transduction with the HTLV-2 Tax oncogene. 2018) Tax-bDC HLA-DR+ CD11c+ CD141+ CLEC4C- CD11b- CD1c- CD209- ND  TLR expression profiling by intracellular Blood DC staining and western blot.  Spontaneous cytokine production.  Transduction with a tumor-associated Ag for priming of anti-tumor CTLs. 1Sub-selection of the positive and negative markers studied, proposed here to be the most informative about cell type identity. 2from 104 precursors. 3Phase contrast microscopy. 4Transmission electron micrographs. 5May Grünwald Giemsa stainings of DCs alone or in co-cultures with CD4+ T cells. 6Haematoxylin/eosin- or Wright Giemsa- or May Grünwald Giemsa-stained cytospins. 7The origin of precurors is indicated in brackets. Gm, G-CSF mobilized peripheral blood; Blood, peripheral blood of untreated healthy adult donors; CB, cord blood; FL, fetal liver; pnT, postnatal thymus; BM, bone marrow; 8Adherent fraction of the PBMCs, or low-density fraction of the PBMCs further depleted of T/B cells. 9Yields for differentiation from GMPs. Yields from CMPs or MLPs can be retrieved from the original publication. 10The nature of the cells classified as cDC2s is not entirely clear since they were not deeply characterized and have a phenotype overlapping with that of MoDCs. 11The precise phenotype of cDC2s was not determined in this study but scRNAseq analyses characterized them as selectively expressing the genes CLEC10A, CD1A and CX3CR1 and lacking expression of CLEC9A and XCR1. Table 2. Proposed guidelines to ensure of the identity of the DC types generated.

Cell type1 Proposed phenotypic identity2 Proposed transcriptomic signature3 Proposed archetypic functions Additional characteristics References cDC1s HLA-DR+ CD11c+ CD141+ CLEC9A+ CADM1+ XCR1+ CD11b-/low BATF3, BTLA, CADM1, CLEC9A, CLNK,  IFN-III production upon TLR3 stimulation.  BATF3- and IRF8- (Balan et al., 2018; CPNE3, ENPP1, FLT3, GCET2, HLA-DOB,  IL-12p70 production upon TLR8 dependent Balan et al., 2014; IDO1, IDO2, IRF8, SEPT3, SNX22, TLR3, stimulation. differentiation. Carpentier et al., XCR1  High efficacy for cross-presentation of cell- 2016; Robbins et associated Ag. al., 2008; See et al., 2017; Villani et al., 2017) pDCs HLA-DR+ CD11c- CD123+ CLEC4C+ NRP1+ LILRA4+ CLEC4C, EPHB1, GZMB, IRF7, LILRA4,  IFN-I/III production upon TLR7 or TLR9  Plasmacytoid (Balan et al., 2018; NLRP7, PACSIN1, PTPRS, RUNX2, SPIB, stimulation. morphology. Robbins et al., TCF4, TLR7, TLR9  TCF4-dependent 2008; See et al., differentiation. 2017; Villani et al., 2017) BTLA+ cDC2s HLA-DR+ CD11c+ CD1c+ FCER1A+ CLEC10A+ CD2+ CD11b+ CD206-CD209- BTLA, CXCL9, FLT3, HLA-DOB, IRF4,  IL-23 production?  IRF8-dependent (Cytlak et al., BTLA+ CD5+ CD14- CD163- LAMP3, ZEB1  Functional polarization of CD4+ T cells differentiation. 2019; Dutertre et towards Th17 or Th2? al., 2019; Villani et al., 2017) BTLA- cDC2s HLA-DR+ CD11c+ CD1c+ FCER1A+ CLEC10A+ CD2+ CD11b+ CD206-CD209- C1QA, C1QB, CD14, CD209, CLEC4E,  Production of IL-1β and IL-10 in response  IRF8-independent (Cytlak et al., BTLA- CD5- CD14+/- CD163+/- CLEC6A, FCGR2A/C, FCGR2B, to stimulation with a cocktail of CpG, differentiation. 2019; Dutertre et FCGR3A/B, FCN1, IGF2R, IL1B, ITGAM, poly(I:C), CL075 and LPS. al., 2019; Villani et LILRA6, LILRA8, LILRB6, MARCO, MRC1,  Pro-inflammatory; correlated with disease al., 2017) MSR1, S100A12, S100A8, S100A9, TLR4 activity in SLE patients. MoDCs HLA-DR+ CD11chi CD11bhi CD172ahi CD206+ CD209+ CD1a+ CD2- CLEC9A-/low CD1A, CD209, CD226, CD68, CSF1R,  Production of high levels of in response to  IRF4-dependent (Balan et al., 2014; XCR1- CD163-/low CD16- EBI3, FCER1A, FCER2, FCGR2A, TLR4 triggering. differentiation. Goudot et al., FCGR2B, FCGR2C, FCGR3A, IRF4,  IL-23 production upon CD40 triggering. 2017; Robbins et ITGAM, LAMP3, LILRB2, MAF, MAFB,  Functional polarization of CD4+ T cells al., 2008) MMP12, MRC1, SIRPA, TLR2, TLR4 towards Th17 (or Th2?). MoMacs CD11bhi CD172ahi CD16+ CD163+ CD206+ CD1a- ABCA1, APOE, CD163, FCGR3A, FOLR2,  High .  Foam cell morphology. (Goudot et al., GIMAP6, ITGA9, LILRB5, MERTK  Production of high levels of in response to  MAFB-dependent 2017) TLR4 triggering. differentiation. LCs HLA-DR+ CD11chi CD11b+ CD1a+ CD207+ E-Cad+ ABCC4, AXIN2, BMPR1A, CD207,  High efficacy for CD8+ T cell priming.  Birbeck granules. (Carpentier et al., EPCAM, MICAL2, MYO6, TJP1 2016) CD14+ DDCs HLA-DR+ CD11c+ CD11bhi CD1a- CD14hi CD207- E-Cad- C1QC, CD14, CEBPB, MAFB, MSR1,  Functional polarization of CD4+ T cells (Carpentier et al., TLR4 towards Tfh. 2016; Klechevsky  Direct B cell stimulation. et al., 2008) 1For cDC2 heterogeneity, we prefer to use the nomenclature of BTLA+ versus BTLA- cDC2, because differential expression of that cell surface marker appears to be the best way to discriminate the two major subsets of human blood cDC2s. The nomenclature DC2 and DC3 may mislead the reader in thinking that DC3 are an entirely different cell type, which is not the hypothesis currently favored in the field. Moreover, the DC2 and DC3 nomenclature has been used to refer to other types of DCs. In any case, the heterogeneity of human cDC2s and its alignment with that of mouse cDC2s is still the object of intense research and debate as discussed in the main text. 2The proposed phenotypic identity should be conserved between ex vivo isolated and in vitro derived DC types, based on the references cited in the table. The markers that should be the most specific for each DC type irrespective of its origin, within CD45+ Lineage- cells, are indicated in bold. However, none of these markers alone is sufficient to ensure of the identity of the cells; it is critical to use a combination of both positive and negative markers as well as antibodies that have proven specificity and a high signal-to-noise ratio. 3These transcriptomic signatures were selected as a subset of the genes found to be specific to both ex vivo isolated and in vitro derived DC types, based on the references cited in the table. The cDC1, pDC and LC transcriptomic signatures have been established upon comparisons with many other immune cell types (Balan et al., 2018; Balan et al., 2014; Carpentier et al., 2016; Robbins et al., 2008; See et al., 2017; Villani et al., 2017). The transcriptomic signatures of BTLA+ cDC2s and BTLA- pDCs have been established by comparison of these two populations with one another (Cytlak et al., 2019). The MoDC signature (Robbins et al., 2008) was refined from there comparison with cDC1s or MoMacs from the same cultures (Balan et al., 2014; Goudot et al., 2017). The MoMac transcriptomic signature was established in comparison with MoDCs from the same culture (Goudot et al., 2017). The CD14+ DDC signature was established by comparison with cDC1s, cDC2s, pDCs and LCs from various tissues (Carpentier et al., 2016). Fig. 1. Putative model of human DC type ontogeny.

Fig. 1. Putative model of human DC type ontogeny. HSCs give rise to MPPs, which then differentiate into either CMPs or LMPPs. Direct differentiation of CMPs or LMPPs from HSCs without an MPP intermediate state has been proposed but remain to be formally demonstrated. The CMPs contribute to the production of most myeloid lineage cells. They can give rise to GMPs, encompassing GMDPs, MDPs and CDPs (also referred as pro-DC in some studies). CDPs are DC committed progenitors giving rise specifically to pDCs and pre-cDCs, which can then leave the bone marrow and enter into circulation or seed the peripheral tissues for further differentiation and exercise of local functions. Early pre-cDCs differentiate into unipotent pre-cDC1 and pre- cDC2, which are the precursors for circulating cDC1s and cDC2s respectively. Other studies suggested a lymphoid development pathway for all the DC types. LMPPs could give rise to DCs via MLP intermediates or eventually via GMDP differentiation then following the classical myeloid pathway. The exact differentiation trajectory through which MLPs or CLPs can differentiate into DCs is still controversial. In any case, the results from many studies are challenging the classical view of hematopoiesis as a succession of dichotomous fate decisions leading to a progressive restriction of progenitor potentials starting with a split between the lymphoid and myeloid lineages. Rather, evidences are accumulating that progenitor populations classically defined by a few phenotypic markers are heterogeneous and that lineage commitment occurs at a much earlier progenitor state than previously thought. In particular, single cell gene expression profiling and clonogenic differentiation studies have shown that a significant fraction of LMPPs is already primed for cDC1 differentiation, in part due to their high expression of IRF8. Graphical key: white cells represent either cells with multi-lineage potentials or with the potential to differentiate in other lineages than those illustrated here; the other cells are committed to become either cDC1s, cDC2s or pDCs according to the corresponding color code; dashed line, controversial or putative differentiation pathways; red line with blunt ends indicates progenitors that are thought not to interconvert into one another. Abbreviations: CDP, common DC progenitor; CLP, common lymphoid progenitor; CMP, common myeloid progenitor; GMDP, granulocyte- monocyte-DC progenitor; GMP, granulocyte-monocyte progenitor; HSC, hematopoietic stem cell; LMPP, Lymphoid-primed multipotent progenitor; MDP, monocyte-DC progenitor; MLP, multi-lymphoid progenitor; MPP, multipotent progenitor; pre-cDC, precursor of conventional DC. References. Alcantara-Hernandez, M., Leylek, R., Wagar, L.E., Engleman, E.G., Keler, T., Marinkovich, M.P., Davis, M.M., Nolan, G.P., Idoyaga, J., 2017. 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