No description available.

No description available.

No description available.

No description available.

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4+ T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

T-cell receptor (TCR) polyclonal mature T cells are surprisingly resistant to oncogenic transformation after retroviral insertion of T-cell oncogenes. In a mouse model, it has been shown that mature T-cell lymphoma/leukemia (MTCLL) is not induced upon transplantation of mature, TCR polyclonal wild-type (WT) T cells, transduced with gammaretroviral vectors encoding potent T-cell oncogenes, into RAG1-deficient recipients. However, further studies demonstrated that quasi-monoclonal T cells treated with the same protocol readily induced MTCLL in the recipient mice. It has been hypothesized that in the TCR polyclonal situation, outgrowth of preleukemic cells and subsequent conversion to overt malignancy is suppressed through regulation of clonal abundances on a per-clone basis due to interactions between TCRs and self-peptide-MHC-complexes (spMHCs), while these mechanisms fail in the quasi-monoclonal situation. To quantitatively study this hypothesis, we applied a mathematical modeling approach. In particular, we developed a novel ordinary differential equation model of T-cell homeostasis, in which T-cell fate depends on spMHC-TCR-interaction-triggered stimulatory signals from antigen-presenting cells (APCs). Based on our mathematical modeling approach, we identified parameter configurations of our model, which consistently explain the observed phenomena. Our results suggest that the preleukemic cells are less competent than healthy competitor cells in acquiring survival stimuli from APCs, but that proliferation of these preleukemic cells is less dependent on survival stimuli from APCs. These predictions now call for experimental validation.

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4+ T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

In einem komplexen tierexperimentellen Ansatz wurde das Potenzial der anti huCD4-Antikörper MAX16H5 und MAX12F6 zur Modulierung zellvermittelter Immun-reaktionen in vivo untersucht. Dafür kam ein mehrfach transgenes Mausmodell zur Anwendung, in dem das humane Zielmolekül und dessen physiologischer Ligand als Transgene exprimiert waren. Als T-Zell vermittelte Immunreaktion wurde eine Kon-taktreaktion (delayed type hypersensitivity, DTH) gegen DNFB etabliert und validiert. An der DTH wurde untersucht, ob und wie die verschiedenen Antikörper die Sen-sibilisierungs- und die Auslösungsphase beeinflussen. Die experimentellen Ergeb-nisse zeigen, dass die Antikörper epitop- und isotypabhängig die beiden Phasen der DTH unterschiedlich beeinflussen. Die Applikation der Antikörper während der Sensi-bilisierung führte zu einer unterschiedlich ausgeprägten Suppression der DTH. Dage-gen hatten sie gegensätzliche Effekte auf die Auslösung. Während nach MAX12F6-Behandlung eine stärkere und prolongierte DTH gemessen wurde, verlief die DTH-Reaktion nach MAX16H5-Applikation deutlich abgeschwächt. Mittels flowzytometri-scher Analysen konnte gezeigt werden, dass die Antikörper unterschiedliche Subpo-pulationen der T-Helferzellen depletieren. Darüber hinaus führte MAX16H5 offen-sichtlich zur Induktion regulatorischer T-Zellen. Die Daten erklären unterschiedliche Erfolge aus ersten klinischen Studien mit verschiedenen anti huCD4 Antikörpern. Auch eignet sich CD4 auch als diagnostisches Target zur in vivo Diagnostik T-Zell vermittelter Entzündungsreaktionen. Mit Antikörperfragmenten von MAX16H5 wurde ein immunszintigraphisches Verfahren entwickelt, das die spezifische Darstellung der mit der DTH einhergehenden Entzündungsreaktion ermöglicht.

Dendritic cells (DC) constitute a heterogeneous leukocyte population having in common a unique capacity to induce primary T cell responses and are therefore most attractive candidates for immunomodulatory strategies. Two populations of blood DC (CD11c+ CD123dim and CD11c– CD123high) have been defined so far. However, their direct isolation for experimental purposes is hampered by their low frequency and by the lack of selective markers allowing large scale purification from blood. Here we describe the monoclonal antibody (mAb) M-DC8, which was generated by immunizing mice with highly enriched blood DC. This mAb specifically reacts with 0.2–1% of blood leukocytes and enables their direct isolation by a one-step immunomagnetic procedure from fresh mononuclear cells. These cells can be differentiated from T cells, B cells, NK cells and monocytes using lineage-specific antibodies. M-DC8+ cells express HLA class II molecules, CD33 and low levels of the costimulatory molecules CD86 and CD40. Upon in vitro culture M-DC8+ cells spontaneously mature into cells with the phenotype of highly stimulatory cells as documented by the upregulation of HLA-DR, CD86 and CD40; in parallel CD80 expression is induced. M-DC8+ cells display an outstanding capacity to present antigen. In particular, they proved to be excellent stimulators of autologous mixed leukocyte reaction and to activate T cells against primary antigens such as keyhole limpet hemocyanin. Furthermore, they induce differentiation of purified allogeneic cytotoxic T cells into alloantigen-specific cytotoxic effector cells. While the phenotypical analysis reveals similarities with the two known blood DC populations, the characteristic expression of Fc=γRIII (CD16) and the M-DC8 antigen clearly defines them as a novel population of blood DC. The mAb M-DC8 might thus be a valuable tool to determine circulating DC for diagnostic purposes and to isolate these cells for studies of antigen-specific T cell priming. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Der systemische Lupus erythematodes (SLE) ist eine Autoimmunerkrankung, bei der eine Vielzahl an Organen betroffen sein kann. Hierbei spielen T-Zellen mit gestörter Zytokinproduktion, insbesondere von IL-2 und IFN-γ, eine besondere Rolle. Mit Fortschreiten der Krankheit sinkt die Anzahl an IL-2-Produzenten und gleichzeitig steigt die Anzahl an IFN-γ-Produzenten. Während die Rolle von IFN-γ in SLE bisher kontrovers diskutiert wird, wirkt sich die verringerte Produktion von IL-2 beispielsweise negativ auf regulatorische T-Zellen aus, was zur Pathogenese der Krankheit beiträgt. In dieser Arbeit erfolgte eine Charakterisierung der Zytokinproduzierenden CD4+ Gedächtnis-T-Zellen in erkrankten NZBxW Mäusen, einem Modell für SLE. Anhand der Produktion von IL-2 und/oder IFN-γ wurde dabei in DN (IFN-γ—IL-2— doppelt negative), IL-2 SP (IFN-γ—IL-2+ einzelpositive), DP (IFN-γ+IL-2+ doppelt positive) und IFN-γ SP (IFN-γ+IL-2— einzelpositive) Zellen unterschieden. Ein mehrstufiges Verfahren der Zellsortierung ermöglichte die Isolierung der vier Zellpopulationen. Genexpressionsanalysen legten offen, dass die während der Krankheit vermehrt vorkommende Population der IFN-γ SP Zellen im Vergleich zu DP Zellen deutliche Unterschiede in ihrem Genexpressionsmuster aufweist. IFN-γ SP Zellen exprimieren u.a. verstärkt Chemokinrezeptoren, co-stimulatorische und co-inhibitorische Moleküle, sowie Apoptose-Marker und zeigen eine verminderte Produktion von Effektorzytokinen. Weiterführende funktionelle Analysen untermauerten die Expressionsdaten und zeigten eine verminderte Proliferationsfähigkeit und verstärkte Apoptose der IFN-γ SP Zellen. Die Daten zeigen, dass der Phänotyp der IFN-γ SP Zellen in erkrankten NZBxW Lupus-Mäusen gestört ist, wodurch die IFN-γ SP Zellen zur Erkrankung beitragen könnten. / Systemic lupus erythematosus (SLE) is an autoimmune disease, which can affect almost every organ system of the body. Thereby altered cytokine production by T cells plays an important role in the pathogenesis of the disease. With disease progression, production of IL-2 decreases and production of IFN-γ increases. It has been shown that IL-2 deficiency affects Treg homeostasis in SLE and thus contributes to its pathogenesis. The role of IFN-γ in SLE is, however, controversial. In this work, a comprehensive characterization of four subpopulations of memory CD4 T cells of diseased NZBxW lupus-prone mice was performed. These cell subsets are DN (IFN-γ—IL-2— double negative), IL-2 SP (IFN-γ—IL-2+ single positive), DP (IFN-γ+IL-2+ double positive) and IFN-γ SP (IFN-γ+IL-2—single positive) cells. A multi-step cell sorting procedure was used to isolate these cell subsets. The data showed that IFN-γ SP cells were characterized by a different gene expression profile than DP cells. In detail, IFN-γ SP cells revealed an enhanced expression of chemokine receptors, co-stimulatory and co-inhibitory molecules as well as apoptosis markers and decreased production of effector cytokines. In addition, functional analyses showed that IFN-γ SP cells were tended to increased apoptosis and decreased proliferation. These data show an altered phenotype of IFN-γ SP cells of diseased NZBxW lupus-prone mice, which might be important for the disease pathogenesis at least in this animal model of SLE.