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Dendritische Zellen (DZ) sind essentiell für die Aktivierung von Immunantworten. Drei Flt3-abhängige DZ Populationen aus dem Blut bestehend aus konventionellen (kDZ) BDCA1+ DZs und BDCA3+ DZs und plasmazytoide DZs wurden bereits beschrieben. Hier wurden zum ersten Mal sich aus Monozyten entwickelnde DZ (moDZ), genauer BDCA1+CD14+ pro-inflammatorische DZ (pro-iDZ) aus periphärem Blut unter homöostatischen Bedingungen identifiziert. Isolierte pro-iDZ sekretierten spontan große Mengen an pro-inflammatorischen Zytokinen, die kDZ reifen ließen und T Zell Proliferation unterstützten. Sie waren BDCA1+CD14- DZ und CD14+CD16- Monozyten in der TH17 Zell Induktion überlegen. Pro-iDZ ähnliche BDCA1+CD14+ Zellen konnten durch imaging cycler microscopy in Geweben von Patienten die an Psoriasis, Dermatomyositis oder entzündetem Halonävus erkrankt waren identifiziert werden. Ihr Fehlen in gesunder Haut deutete eine Rekrutierung von pro-iDZs in entzündetes Gewebe an. Eine Verwandtschaftsanalyse von pro-iDZ zwischen Monozyten, kDZ des Blutes und in vitro generierten moDZ auf genomweiter Ebene wies auf einen monozytären Ursprung hin. Anylse mittels funktioneller Annotation auf differentiell exprimierten Genen zwischen pro-iDZ und Monozyten zeigte eine DZ spezifische Gensignatur auf. Diese Gene waren insgesamt in der gleichen Weise wie in kDZ und moDZ reguliert, das eine Entwicklung von Monozyten nach DZ nahelegte. Dieses Entwicklungskonzept wurde insofern unterstützt, indem unter entzündlichen Bedingungen kultivierte CD14+CD16- Monozyten BDCA1 Expression und DZ Funktion erlangten. Da pro-iDZ sehr ähnlich zu BDCA1+CD14+ Zellen aus entzündeter Haut waren und beide große Konvergenz mit zuvor beschriebenen BDCA1+CD14+ inflammatorischen DZ (infDZ) aus entzündeten Geweben aufwiesen, können pro-iDZ als direkte infDZ Vorläufer angesehen werden. Dadurch und wegen ihrer monozytären Herkunft können pro-iDZ als Beweis für die humane Differenzierung von Monozyten nach DZ in vivo betrachtet werden. / Dendritic cells (DCs) are critical for the activation of immune responses. Three Flt3-dependent blood DC populations including conventional BDCA1+ DCs and BDCA3+ DCs (cDCs) and plasmacytoid DCs were described previously. This work identifies for the first time human peripheral blood monocyte derived BDCA1+CD14+ pro-inflammatory DCs (pro-iDCs) during steady state. Isolated pro-iDCs spontaneously secreted high amounts of pro-inflammatory cytokines, which matured cDCs and promoted T cell proliferation. They were superior in priming TH17 cells when compared to BDCA1+CD14- DCs and CD14+CD16- monocytes. BDCA1+CD14+ cells resembling blood pro-iDCs as identified by imaging cycler microscopy were found in samples from patients suffering from psoriasis, dermatomyositosis and inflamed halo nevus. Their absence in healthy donor’s skin indicated a recruitment of pro-iDCs to sites of inflammation. Analysis of the developmental relationship of pro-iDCs between monocytes, blood cDCs and in vitro generated monocyte derived DCs (moDCs) on whole genome level strongly suggested a monocytic origin. Functional annotation analysis of differentially regulated genes between monocytes and pro-iDCs revealed a DC specific gene signature. In addition, these genes were overall regulated in the same way in blood cDCs and moDCs, indicating an ongoing development of pro-iDCs from monocytes towards DCs. This developmental concept was supported as CD14+CD16- monocytes cultured under inflammatory conditions gained BDCA1 expression and DC function. Since pro-iDCs were highly similar to BDCA1+CD14+ cells found in inflamed skin and as both showed a marked convergence with BDCA1+CD14+ inflammatory DCs (infDCs) present in inflamed tissues described previously, pro-iDCs can be regarded as immediate precursors of infDCs. Thus, in respect of a monocytic origin and a presumably inflammatory DC fate, pro-iDCs may constitute a missing link to prove human moDC differentiation in vivo.

Stem cells differentiate through an organized hierarchy of intermediate cell types to terminally differentiated cell types. This process is largely guided by master transcriptional regulators, but it also depends on the expression of many other types of genes. The discrete cell types in the differentiation hierarchy are often identified based on the expression or non-expression of certain marker genes. Historically, these have often been various cell-surface proteins, which are fairly easy to assay biochemically but are not necessarily causative of the cell type, in the sense of being master transcriptional regulators. This raises important questions about how gene expression across the whole genome controls or reflects cell state, and in particular, differentiation hierarchies. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering and maximization of parsimony can organize the cell types into a tree, but in general this tree is different from the differentiation hierarchy. Using hematopoietic differentiation as an example, we demonstrate how many genes other than marker genes are able to discriminate between different branches of the differentiation tree by proposing two models for detecting genes that are up-regulated or down-regulated in distinct lineages. We then propose a novel approach to solving the following problem: Given the differentiation hierarchy and gene expression data at each node, construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming framework to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a sparse weighted Euclidean metric that uses just 175 genes. These 175 genes are different than the marker genes that were used to identify the 38 cell types, hence offering a novel alternative way of discriminating different branches of the tree. A DAVID functional annotation analysis shows that the 175 genes reflect major processes and pathways active in different parts of the tree. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. Our results show that the 175 genes frequently appear in the random metrics, implicating their significance from an empirical point of view as well. Finally, we show how our linear programming method is able to identify columns that were selected to build minimum spanning trees on the nodes of random variable-size matrices.

La réponse immunitaire est régulée spatialement et temporellement. Les cellules immunitaires font partie d’une plus grande communauté de populations cellulaires interconnectées qui coordonnent leurs actions par la signalisation intercellulaire. Suivant une blessure hépatique, la distribution et la composition du compartiment immunitaire évoluent rapidement au fil du temps. Par conséquent, l’information sur la position des cellules immunitaires dans le tissu hépatique est essentielle à la bonne compréhension de leurs fonctions dans la santé et la maladie. Cependant, l’organisation spatiale des cellules immunitaires en réponse à une atteinte hépatique aiguë, ainsi que les conséquences fonctionnelles de leur distribution topographique spécifique, restent mal comprises. Les macrophages hépatiques sont des cellules effectrices clés pendant l’homéostasie et en réponse à des blessures, et sont impliqués dans la pathogenèse de plusieurs maladies du foie. L’hétérogénéité et plasticité des macrophages dans le foie a été exposée avec l’émergence du séquençage de l’ARN, la cytométrie en flux et la cytométrie de masse. Ces techniques ont sensiblement contribué à la compréhension de l’origine, et fonctions des macrophages dans le foie. Cependant, ces technologies impliquent la destruction du tissu pour la préparation de suspension cellulaires ce qui entraîne une perte d’information spatiale et de contexte tissulaire. Par conséquent, la caractérisation spatiale et temporelle des macrophages dans le tissu hépatique pendant l’homéostasie tissulaire, et en réponse à une blessure, fournit une nouvelle information sur la façon dont les macrophages se rapportent aux cellules voisines et leur comportement pendant les réponses immunitaires. Dans la première partie de cette étude, nous avons conçu une stratégie pour le phénotypage spatial des cellules immunitaires hépatiques dans des échantillons de tissus. Cette stratégie combine techniques d'imagerie et l’alignement numérique des images pour surmonter les limitations actuelles du nombre de marqueurs pouvant être visualisés simultanément. En outre, nous avons généré des protocoles pour la quantification automatisée des cellules d’intérêt dans des sections de tissus pour réduire la subjectivité associée à la quantification par inspection visuelle, et pour augmenter la surface et la vitesse de l’analyse. Par conséquent, un plus grand nombre de populations de cellules immunitaires ont été visualisées, quantifiées et cartographiées, et leurs relations spatiales ont été déterminées. Dans la deuxième partie de l’étude, nous avons déterminé la cinétique et la dynamique spatiale des cellules de Kupffer (KCs) et des macrophages dérivés de monocytes (MoMFs) en réponse à une atteinte hépatique aiguë au CCl4, afin de mieux comprendre leurs rôles fonctionnels, et la répartition du travail entre eux. Nous avons constaté que les KC et les MoMFs présentent des différences au niveau de la distribution tissulaire, la morphologie, et la cinétique. En plus, seulement les KCs ont proliféré pour repeupler la population de macrophages résidents pendant la réparation tissulaire. Finalement, nous avons montré que le degré de colocalization de KCs et des MoMFs avec les cellules stellaires est différent. En plus, cette colocalisation varie avec la progression de la réponse immunitaire. Dans l’ensemble, nous avons montré que les KCs et les MoMFs ont des profils spatiaux et temporels différents en réponse à une atteinte hépatique aiguë. Dans l’ensemble, les observations faites dans cette étude suggèrent que le comportement spatial et temporel d’une sous-population donnée de cellules immunitaires est distinct et sous-tend sa capacité à remplir ses fonctions spécifiques pendant la réponse immunitaire. / The immune response is spatially and temporally regulated. Immune cells are part of a larger community of interconnected immune and non-immune cell populations that coordinate their actions mostly through cell-cell intercellular signaling. In the liver, the distribution pattern, and the composition of the immune compartment evolve during an immune response to injury influencing disease pathology, progression, and response to treatment. Hence, information on the location and interacting partners of immune cells in the hepatic tissue is critical for the proper understanding of their functions in health and disease. However, the spatial organization of hepatic resident and infiltrating immune cells in response to acute injury, and the functional consequences of their specific topographical distribution, remain poorly defined. Hepatic macrophages are key effector cells during homeostasis and in response to injury and are involved in the pathogenesis of several liver diseases. The heterogeneity and plasticity of the macrophage compartment in the liver have only recently started to be appreciated with the emergence of RNA sequencing, flow cytometry, and mass cytometry. Detailed transcriptomic and phenotypic profiling have deeply expanded our understanding of macrophage biology. However, these technologies involve tissue disruption with loss of spatial information and tissue context. Therefore, the spatial and temporal profiling of liver macrophages in tissue samples during the steady state, and in response to injury, provide novel information on how the macrophages relate to neighboring cells and their behavior during immune responses. In the first part of this study, we designed a strategy for the spatial phenotyping of hepatic immune cells in tissue samples. This strategy combined serial and sequential labeling, and digital tissue alignment to overcome current limitations in the number of markers that can be simultaneously visualized. In addition, we generated protocols for automated quantification of cells of interest in whole tissue sections which removed the subjectivity associated with quantification by visual inspection and greatly increased the area and the speed of the analysis. As a result, a larger number of immune cell populations were visualized, quantified, and mapped, and their spatial relations were determined in an unbiased manner. In the second part of this study, we monitored the kinetics, and spatial dynamics of resident Kupffer cells (KCs) and infiltrating monocyte-derived macrophages (MoMFs) in response to acute liver injury with CCl4, to gain insight into their functional roles, and the distribution of labor between them. KCs and MoMFs exhibited different tissue distribution patterns and cell morphology, different kinetics, and occupied neighboring but unique microanatomical tissue locations. KCs and MoMFs displayed a different capacity to replenish the macrophage pool upon acute injury, and were differentially related to hepatic stellate cells. Different kinetics and spatial profiles revealed that KCs and MoMFs have distinct spatial signatures and suggest that they perform distinct functions during the wound-healing response to acute liver injury. In summary, we optimized techniques and put together a strategy for the spatial profiling of hepatic immune cells. Then, we used this methodology to profile resident and infiltrating macrophage subpopulations to gain insight into their biology and distinct contribution to healing in response to acute liver injury. Overall, the observations made in this study suggest that the spatial and temporal behavior of a given subpopulation of immune cells underlie its ability to perform its specific functions during the immune response.