Global Self-Organization of the Cellular Metabolic Structure

Background: Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using "metabolic networks models'' are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used "dissipative metabolic networks'' (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings: Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance: This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures.Supported by the Spanish Ministry of Science and Education Grants MTM2005-01504, MTM2004-04665, partly with FEDER funds, and by the Basque Government, Grant IT252-07

The α-ketoglutarate dehydrogenase complex in cancer metabolic plasticity

Deregulated metabolism is a well-established hallmark of cancer. At the hub of various metabolic pathways deeply integrated within mitochondrial functions, the α-ketoglutarate dehydrogenase complex represents a major modulator of electron transport chain activity and tricarboxylic acid cycle (TCA) flux, and is a pivotal enzyme in the metabolic reprogramming following a cancer cell’s change in bioenergetic requirements. By contributing to the control of α-ketoglutarate levels, dynamics, and oxidation state, the α-ketoglutarate dehydrogenase is also essential in modulating the epigenetic landscape of cancer cells. In this review, we will discuss the manifold roles that this TCA enzyme and its substrate play in cancer

European Journal of Nuclear Medicine and Molecular Imaging / Ultra-early response assessment in lymphoma treatment : [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment

Purpose To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [18F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously. Methods Patients with histologically proven HL or NHL were included in this prospective IRB-approved study. Patients underwent [18F]FDG PET/MR before, and then 4872 h after (follow-up 1, FU-1) and 1 week after (FU-2) initiation of the first cycle of their respective standard chemotherapy (for HL) or immunochemotherapy (for NHL). Standardized [18F]FDG uptake values (SUVmax, SUVmean) and apparent diffusion coefficients (ADCmin, ADCmean) based on diffusion-weighted MRI, and metabolic and morphological tumour volumes (MTV, VOL) were assessed at each time-point. Multilevel analyses with an unstructured covariance matrix, and pair-wise post-hoc tests were used to test for significant changes in SUVs, ADCs, MTVs and VOLs between the three time-points. Results A total of 58 patients (11 with HL and 47 with NHL) with 166 lesions were analysed. Lesion-based mean rates of change in SUVmax, SUVmean, ADCmin, ADCmean, MTV and VOL between baseline and FU-1 were 46.8%, 33.3%, +20.3%, +14%, 46% and 12.8%, respectively, and between baseline and FU-2 were 65.1%, 49%, +50.7%, +32.4%, 61.1% and 24.2%, respectively. These changes were statistically significant (P<0.01) except for the change in VOL between baseline and FU-1 (P=0.079). Conclusion In lymphoma patients, [18F]FDG PET/MR can capture treatment-induced changes in glucose metabolism and cell density as early as 4872 h after treatment initiation.(VLID)357846