Biology subjects

Benary, U.

Publications and source records attributed to Benary, U..

4 recordsLinked to original sources

bioRxiv2025

A computational model elucidates the effect of oncogene induced expression alterations on the energy metabolism of neuroblastoma

An altered energy metabolism is recognized as a hallmark of cancer. Experimental evidence shows that oncogenes play a key role in the reprogramming of metabolism. In neuroblastoma the oncogene MYCN, a main risk factor of poor prognosis, has been demonstrated to lead to expression changes in numerous glycolytic enzymes. Since it is not clear whether all these targets are required and how the overall metabolic response is shaped, we here dissect the effect of MYCN targets on the pathway individually and in combination using a computational modeling approach. We develop a first mathematical model of the energy metabolism in neuroblastoma cells based on our published experimental data. The analysis shows that MYCN overexpression overall leads to Warburg-like flux alterations with characteristic changes for the individual MYCN targets highlighting that MYCN targets can have opposing and sometimes unexpected effects. Interestingly, not all described MYCN targets contribute to notable flux alterations, at least in glycolysis. Our model moreover predicts a potential bistability of the cellular metabolism with an occurrence of a low-flux state likely representing quiescence. Overall, our study highlights the importance of analysing perturbations such as expression changes in the context of realistic pathways capturing their specific interactions and complex regulations.

systems biology↗

bioRxiv2020

Quantitative lineage analysis identifies a long-term progenitor niche for the hepato-pancreato-biliary organ system

Single cell-based studies have revealed tremendous cellular heterogeneity in stem cell and progenitor compartments, suggesting continuous differentiation trajectories with intermixing of cells at various states of lineage commitment and notable degree of plasticity during organogenesis1-5. The hepato-pancreato-biliary organ system relies on a small endoderm progenitor compartment that gives rise to a variety of different adult tissues, including liver, pancreas, gallbladder, and extra-hepatic bile ducts6, 7. Experimental manipulation of various developmental signals in the mouse embryo underscored an important cellular plasticity in this embryonic territory6, 8. This is also reflected in the existence of human genetic syndromes as well as congenital or environmentally-caused human malformations featuring multiorgan phenotypes in liver, pancreas and gallbladder6, 8. Nevertheless, the precise lineage hierarchy and succession of events leading to the segregation of an endoderm progenitor compartment into hepatic, biliary, and pancreatic structures are not yet established. Here, we combine computational modelling approaches with genetic lineage tracing to assess the tissue dynamics accompanying the ontogeny of the hepato-pancreato-biliary organ system. We show that a long-term multipotent progenitor domain persists at the border between liver and pancreas, even after pancreatic fate is specified, contributing to the formation of several organ derivatives, including the liver. Moreover, using single-cell RNA sequencing we define a specialized niche that possibly supports such long-term cell fate plasticity.

developmental biology↗

bioRxiv2019

A quantitative modular modeling approach reveals the consequences of different A20 feedback implementations for the NF-kB signaling dynamics

Signaling pathways involve complex molecular interactions and are controlled by non-linear regulatory mechanisms. If details of regulatory mechanisms are not fully elucidated, they can be implemented by different, equally reasonable mathematical representations in computational models. The study presented here focusses on NF-{kappa}B signaling, which is regulated by negative feedbacks via I{kappa}B and A20. A20 inhibits NF-{kappa}B activation indirectly through interference with proteins that transduce the signal from the TNF receptor complex to activate the I{kappa}B kinase (IKK) complex. We focus on the question how different implementations of the A20 feedback impact the dynamics of NF-{kappa}B. To this end, we develop a modular modeling approach that allows combining previously published A20 modules with a common pathway core module. The resulting models are based on a comprehensive experimental data set and therefore show quantitatively comparable NF-{kappa}B dynamics. Based on defined measures for the initial and long-term behavior we analyze the effects of a wide range of changes in the A20 feedback strength, the I{kappa}B feedback strength and the TNF stimulation strength on NF-{kappa}B dynamics. This shows similarities between the models but also model-specific differences. In particular, the A20 feedback strength and the TNF stimulation strength affect initial and long-term NF-{kappa}B concentrations differently in the analyzed models. We validated our model predictions experimentally by varying TNF concentrations applied to HeLa cells. These time course data indicate that only one of the A20 feedback models appropriately describes the impact of A20 on the NF-{kappa}B dynamics.\n\nAuthor summaryModels are abstractions of reality and simplify a complex biological process to its essential components and regulations while preserving its particular spatial-temporal characteristics. Modelling of biological processes is based on assumptions, in part to implement the necessary simplifications but also to cope with missing knowledge and experimental information. In consequence, biological processes have been implemented by different, equally reasonable mathematical representations in computational models. We here focus on the NF-{kappa}B signaling pathway and develop a modular modeling approach to investigate how different implementations of a negative feedback regulation impact the dynamical behavior of a computational model. Our analysis shows similarities of the models with different implementations but also reveals implementation-specific differences. The identified differences are used to design and perform informative experiments that elucidate unknown details of the regulatory feedback mechanism.

systems biology↗

bioRxiv2018

MYCN-induced metabolic rewiring creates novel therapeutic vulnerabilities in neuroblastoma

MYCN is a transcription factor that is aberrantly expressed in many tumor types and is often correlated with poor patient prognosis. Recently, several lines of evidence pointed to the fact that oncogenic activation of MYC family proteins is concomitant with reprogramming of tumor cells to cope with an enhanced need for metabolites during cell growth. These adaptions are driven by the ability of MYC proteins to act as transcriptional amplifiers in a tissue-of-origin specific manner. Here, we describe the effects of MYCN overexpression on metabolic reprogramming in neuroblastoma cells. Ectopic expression of MYCN induced a glycolytic switch that was concomitant with enhanced sensitivity towards 2-deoxyglucose, an inhibitor of glycolysis. Moreover, global metabolic profiling revealed extensive alterations in the cellular metabolome resulting from overexpression of MYCN. Limited supply with either of the two main carbon sources, glucose or glutamine, resulted in distinct shifts in steady-state metabolite levels and significant changes in glutathione metabolism. Interestingly, interference with glutamine-glutamate conversion preferentially blocked proliferation of MYCN overexpressing cells, when glutamine levels were reduced. Thus, our study uncovered MYCN induction and nutrient levels as important metabolic master switches in neuroblastoma cells and identified critical nodes that restrict tumor cell proliferation.

cancer biology↗