Number of active transcription factor binding sites is essential for the Hes7 oscillator

BACKGROUND: It is commonly accepted that embryonic segmentation of vertebrates is regulated by a segmentation clock, which is induced by the cycling genes Hes1 and Hes7. Their products form dimers that bind to the regulatory regions and thereby repress the transcription of their own encoding genes. An increase of the half-life of Hes7 protein causes irregular somite formation. This was shown in recent experiments by Hirata et al. In the same work, numerical simulations from a delay differential equations model, originally invented by Lewis, gave additional support. For a longer half-life of the Hes7 protein, these simulations exhibited strongly damped oscillations with, after few periods, severely attenuated the amplitudes. In these simulations, the Hill coefficient, a crucial model parameter, was set to 2 indicating that Hes7 has only one binding site in its promoter. On the other hand, Bessho et al. established three regulatory elements in the promoter region. RESULTS: We show that – with the same half life – the delay system is highly sensitive to changes in the Hill coefficient. A small increase changes the qualitative behaviour of the solutions drastically. There is sustained oscillation and hence the model can no longer explain the disruption of the segmentation clock. On the other hand, the Hill coefficient is correlated with the number of active binding sites, and with the way in which dimers bind to them. In this paper, we adopt response functions in order to estimate Hill coefficients for a variable number of active binding sites. It turns out that three active transcription factor binding sites increase the Hill coefficient by at least 20% as compared to one single active site. CONCLUSION: Our findings lead to the following crucial dichotomy: either Hirata's model is correct for the Hes7 oscillator, in which case at most two binding sites are active in its promoter region; or at least three binding sites are active, in which case Hirata's delay system does not explain the experimental results. Recent experiments by Chen et al. seem to support the former hypothesis, but the discussion is still open

The Nlrp3 inflammasome regulates acute graft-versus-host disease

The success of allogeneic hematopoietic cell transplantation is limited by acute graft-versus-host disease (GvHD), a severe complication accompanied by high mortality rates. Yet, the molecular mechanisms initiating this disease remain poorly defined. In this study, we show that, after conditioning therapy, intestinal commensal bacteria and the damage-associated molecular pattern uric acid contribute to Nlrp3 inflammasome-mediated IL-1β production and that gastrointestinal decontamination and uric acid depletion reduced GvHD severity. Early blockade of IL-1β or genetic deficiency of the IL-1 receptor in dendritic cells (DCs) and T cells improved survival. The Nlrp3 inflammasome components Nlrp3 and Asc, which are required for pro-IL-1β cleavage, were critical for the full manifestation of GvHD. In transplanted mice, IL-1β originated from multiple intestinal cell compartments and exerted its effects on DCs and T cells, the latter being preferentially skewed toward Th17. Compatible with these mouse data, increased levels of active caspase-1 and IL-1β were found in circulating leukocytes and intestinal GvHD lesions of patients. Thus, the identification of a crucial role for the Nlrp3 inflammasome sheds new light on the pathogenesis of GvHD and opens a potential new avenue for the targeted therapy of this severe complication

P2Y2R Signaling Is Involved in the Onset of Glomerulonephritis

Endogenously released adenosine-5’-triphosphate (ATP) is a key regulator of physiological function and inflammatory responses in the kidney. Genetic or pharmacological inhibition of purinergic receptors has been linked to attenuation of inflammatory disorders and hence constitutes promising new avenues for halting and reverting inflammatory renal diseases. However, the involvement of purinergic receptors in glomerulonephritis (GN) has only been incompletely mapped. Here, we demonstrate that induction of GN in an experimental antibody-mediated GN model results in a significant increase of urinary ATP-levels and an upregulation of P2Y2R expression in resident kidney cells as well as infiltrating leukocytes pointing toward a possible role of the ATP/P2Y2R-axis in glomerular disease initiation. In agreement, decreasing extracellular ATP-levels or inhibition of P2R during induction of antibody-mediated GN leads to a reduction in all cardinal features of GN such as proteinuria, glomerulosclerosis, and renal failure. The specific involvement of P2Y2R could be further substantiated by demonstrating the protective effect of the lack of P2Y2R in antibody-mediated GN. To systematically differentiate between the function of P2Y2R on resident renal cells versus infiltrating leukocytes, we performed bone marrow-chimera experiments revealing that P2Y2R on hematopoietic cells is the main driver of the ATP/P2Y2R-mediated disease progression in antibody-mediated GN. Thus, these data unravel an important pro-inflammatory role for P2Y2R in the pathogenesis of GN

From Dynamic Expression Patterns to Boundary Formation in the Presomitic Mesoderm

The segmentation of the vertebrate body is laid down during early embryogenesis. The formation of signaling gradients, the periodic expression of genes of the Notch-, Fgf- and Wnt-pathways and their interplay in the unsegmented presomitic mesoderm (PSM) precedes the rhythmic budding of nascent somites at its anterior end, which later develops into epithelialized structures, the somites. Although many in silico models describing partial aspects of somitogenesis already exist, simulations of a complete causal chain from gene expression in the growth zone via the interaction of multiple cells to segmentation are rare. Here, we present an enhanced gene regulatory network (GRN) for mice in a simulation program that models the growing PSM by many virtual cells and integrates WNT3A and FGF8 gradient formation, periodic gene expression and Delta/Notch signaling. Assuming Hes7 as core of the somitogenesis clock and LFNG as modulator, we postulate a negative feedback of HES7 on Dll1 leading to an oscillating Dll1 expression as seen in vivo. Furthermore, we are able to simulate the experimentally observed wave of activated NOTCH (NICD) as a result of the interactions in the GRN. We esteem our model as robust for a wide range of parameter values with the Hes7 mRNA and protein decays exerting a strong influence on the core oscillator. Moreover, our model predicts interference between Hes1 and HES7 oscillators when their intrinsic frequencies differ. In conclusion, we have built a comprehensive model of somitogenesis with HES7 as core oscillator that is able to reproduce many experimentally observed data in mice

Lack of the purinergic receptor P2X7 results in resistance to contact hypersensitivity

Engagement of P2X7 on mouse dendritic cells, presumably by ATP released in response to contact allergen, is needed for IL-1β production and the sensitization phase of contact hypersensitivity

Ruxolitinib for Glucocorticoid-Refractory Acute Graft-versus-Host Disease

BACKGROUND: Acute graft-versus-host disease (GVHD) remains a major limitation of allogeneic stem-cell transplantation; not all patients have a response to standard glucocorticoid treatment. In a phase 2 trial, ruxolitinib, a selective Janus kinase (JAK1 and JAK2) inhibitor, showed potential efficacy in patients with glucocorticoid-refractory acute GVHD. METHODS: We conducted a multicenter, randomized, open-label, phase 3 trial comparing the efficacy and safety of oral ruxolitinib (10 mg twice daily) with the investigator's choice of therapy from a list of nine commonly used options (control) in patients 12 years of age or older who had glucocorticoid-refractory acute GVHD after allogeneic stem-cell transplantation. The primary end point was overall response (complete response or partial response) at day 28. The key secondary end point was durable overall response at day 56. RESULTS: A total of 309 patients underwent randomization; 154 patients were assigned to the ruxolitinib group and 155 to the control group. Overall response at day 28 was higher in the ruxolitinib group than in the control group (62% [96 patients] vs. 39% [61]; odds ratio, 2.64; 95% confidence interval [CI], 1.65 to 4.22; P<0.001). Durable overall response at day 56 was higher in the ruxolitinib group than in the control group (40% [61 patients] vs. 22% [34]; odds ratio, 2.38; 95% CI, 1.43 to 3.94; P<0.001). The estimated cumulative incidence of loss of response at 6 months was 10% in the ruxolitinib group and 39% in the control group. The median failure-free survival was considerably longer with ruxolitinib than with control (5.0 months vs. 1.0 month; hazard ratio for relapse or progression of hematologic disease, non-relapse-related death, or addition of new systemic therapy for acute GVHD, 0.46; 95% CI, 0.35 to 0.60). The median overall survival was 11.1 months in the ruxolitinib group and 6.5 months in the control group (hazard ratio for death, 0.83; 95% CI, 0.60 to 1.15). The most common adverse events up to day 28 were thrombocytopenia (in 50 of 152 patients [33%] in the ruxolitinib group and 27 of 150 [18%] in the control group), anemia (in 46 [30%] and 42 [28%], respectively), and cytomegalovirus infection (in 39 [26%] and 31 [21%]). CONCLUSIONS: Ruxolitinib therapy led to significant improvements in efficacy outcomes, with a higher incidence of thrombocytopenia, the most frequent toxic effect, than that observed with control therapy

Classical and Hybrid Modeling of Gene Regulatory Networks

We present classical and hybrid modeling approaches for genetic regulatory networks focusing on promoter analysis for negatively and positively autoregulated networks. The main aim of this thesis is to introduce an alternative mathematical approach to model gene regulatory networks based on piecewise deterministic Markov processes (PDMP). During somitogenesis, a process describing the early segmentation in vertebrates, molecular oscillators play a crucial role as part of a segmentation clock. In mice, these oscillators are called Hes1 and Hes7 and are commonly modeled by a system of two delay differential equations including a Hill function, which describes gene repression by their own gene products. The Hill coefficient, which is a measure of nonlinearity of the binding processes in the promoter, is assumed to be equal to two, based on the fact that Hes1 and Hes7 form dimers.However, by standard arguments applied to binding analysis, we show that a higher Hill coefficient is reasonable. This leads to results different from those in literature which requires a more sophisticated model. For the Hes7 oscillator we present a system of ordinary differential equations including a Michaelis-Menten term describing a nonlinear degradation of the proteins by the ubiquitinpathway. As demonstrated by the Hes1 and Hes7 oscillator, promoter behavior can have strong influence on the dynamical behavior of genetic networks. Since purely deterministic systems cannot reveal phenomenons caused by the inherent random fluctuations, we propose a novel approach based on PDMPs. Such models allow to model binding processes of transcription factors to binding sites in a promoter as random processes, where all other processes like synthesis, degradation or dimerization of the gene products are modeled in deterministic manner. We present and discuss a simulation algorithm for PDMPs and apply it to three types of genetic networks: an unregulated gene, a toggle switch, and a positively autoregulated network. The different regulation characteristics are analyzed and compared by numerical means. Furthermore, we determine analytical solutions of the stationary distributions of one negatively, and three positively autoregulated networks. Based on these results, we analyze attenuation of noise in a negative feedback loop, and the question of graded or binary response in autocatalytic networks.Die vorliegende Arbeit behandelt klassische und hybride Modellierungsmethoden für genregulatorische Netzwerke mit Schwerpunkt auf der Analyse von Promotoren von negativen und positiven autoregulativen Netzwerken. Hauptziel ist die Einführung eines alternativen mathematischen Ansatzes basierend auf stückweise deterministischen Markov Prozessen (PDMP). Die Somitogenese bezeichnet einen biologischen Prozess, der die frühe Segmentierung von Wirbeltieren beschreibt. Während dieses Prozesses spielen molekulare Oszillatoren als Teil einer Segementationsuhr eine wichtige Rolle. In Mäusen sind dies die beiden Gene Hes1 und Hes7. In der Literatur werden diese üblicherweise mit Hilfe eines zweidimensionalen Delay-Differentialgleichungssystem modelliert. Die Inhibition der Genexpression durch das eigene Genprodukt wird dabei durch eine Hillfunktion beschrieben. Für den Hillkoeffizienten, welcher ein Maß für die Nichtlinearität der Bindung der Proteine an die Bindestellen ist, wird dabei gewöhnlich ein Wert gleich zwei angenommen. Hierbei beruft man sich auf die Tatsache, dass Hes1 und Hes7 als Dimere an die Bindungsstellen im Promotor binden. Anhand eines Standardmodels für die Bindunganalyse zeigen wir jedoch, dass ein höherer Wert realistischer ist. Dies führt jedoch zu Ergebnissen, die sich von denen aus der Lieratur unterscheiden. Diese Diskrepanz erfordert eine feinere Modellierung der negativen Feedbacks. Für den Hes7 Oszillator wird ein System von gewöhnlichen Differentialgleichungen vorgeschlagen, welches ein Michaelis-Menten Term beinhaltet, der den nichtlinearen Abbau des Hes7 Proteins durch den Ubiquitin-Signalweg beschreibt. Wie die Untersuchungen des Hes1 und Hes7 Oszillators zeigen, kann sich die Promotoraktivität stark auf das dynamische Verhalten eines genregulatorischen Netzwerkes auswirken. Da deterministische Systeme keine Phänomene aufzeigen können, die durch die innewohnenden zufälligen Fluktuationen entstehen, schlagen wir einen neuen Modellierungsansatz vor, der auf PDMPs basiert. Solche Modelle ermöglichen, die Bindung von Transkriptionsfaktoren an die Bindungsstellen im Promotor als zufälligen Prozess zu beschreiben, wohingegen alle anderen Prozesse wie Synthese und Abbau der Genprodukte, oder Dimerization der Proteine als deterministische Prozesse beschrieben werden. Wir präsentieren und diskutieren einen Simulationsalgorithmus, und wenden diesen auf drei verschiedene Netzwerktypen an: ein induzierbares Gen, ein Toggleswitch und ein positiv autoreguliertes Netzwerk. Mittels numerischer Methoden werden die verschiedenen Regulationscharakteristiken analysiert und verglichen. Des Weiteren bestimmen wir die analytischen Lösungen der stationären Verteilungen eines negativ und dreier positiv autoregulierten Netzwerke. Anhand dieser Ergebnisse untersuchen wir die Reduktion von Fluktuationen in einem negativen Feedback, und die Frage einer graduellen oder binären Antwort in autokatalytischen Netzwerken

Autocatalytic genetic networks modeled by piecewise-deterministic Markov processes

International audienc

Hybrid Modeling of Noise Reduction by a Negatively Autoregulated System

International audienc