Action potentials as indicators of metabolic perturbations for temporal proteomic analysis

The single largest cause of compound attrition during drug development is due to inadequate tools capable of predicting and identifying protein interactions. Several tools have been developed to explore how a compound interferes with specific pathways. However, these tools lack the potential to chronically monitor the time dependent temporal changes in complex biochemical networks, thus limiting our ability to identify possible secondary signaling pathways that could lead to potential toxicity. To overcome this, we have developed an in silico neuronal-metabolic model by coupling the membrane electrical activity to intracellular biochemical pathways that would enable us to perform non-invasive temporal proteomics. This model is capable of predicting and correlating the changes in cellular signaling, metabolic networks and action potential responses to metabolic perturbation. The neuronal-metabolic model was experimentally validated by performing biochemical and electrophysiological measurements on NG108-15 cells followed by testing its prediction capabilities for pathway analysis. The model accurately predicted the changes in neuronal action potentials and the changes in intracellular biochemical pathways when exposed to metabolic perturbations. NG108-15 cells showed a large effect upon exposure to 2DG compared to cyanide and malonate as these cells have elevated glycolysis. A combinational treatment of 2DG, cyanide and malonate had a much higher and faster effect on the cells. A time-dependent change in neuronal action potentials occurred based on the inhibited pathway. We conclude that the experimentally validated in silico model accurately predicts the changes in neuronal action potential shapes and proteins activities to perturbations, and would be a powerful tool for performing proteomics facilitating drug discovery by using action potential peak shape analysis to determine pathway perturbation from an administered compound

Metabolic-flux dependent regulation of microbial physiology

According to the most prevalent notion, changes in cellular physiology primarily occur in response to altered environmental conditions. Yet, recent studies have shown that changes in metabolic fluxes can also trigger phenotypic changes even when environmental conditions are unchanged. This suggests that cells have mechanisms in place to assess the magnitude of metabolic fluxes, that is, the rate of metabolic reactions, and use this information to regulate their physiology. In this review, we describe recent evidence for metabolic flux-sensing and flux-dependent regulation. Furthermore, we discuss how such sensing and regulation can be mechanistically achieved and present a set of new candidates for flux-signaling metabolites. Similar to metabolic-flux sensing, we argue that cells can also sense protein translation flux. Finally, we elaborate on the advantages that flux-based regulation can confer to cells

Viral hijacking of cellular metabolism.

This review discusses the current state of the viral metabolism field and gaps in knowledge that will be important for future studies to investigate. We discuss metabolic rewiring caused by viruses, the influence of oncogenic viruses on host cell metabolism, and the use of viruses as guides to identify critical metabolic nodes for cancer anabolism. We also discuss the need for more mechanistic studies identifying viral proteins responsible for metabolic hijacking and for in vivo studies of viral-induced metabolic rewiring. Improved technologies for detailed metabolic measurements and genetic manipulation will lead to important discoveries over the next decade

Divergent Effects of Human Cytomegalovirus and Herpes Simplex Virus-1 on Cellular Metabolism

Viruses rely on the metabolic network of the host cell to provide energy and macromolecular precursors to fuel viral replication. Here we used mass spectrometry to examine the impact of two related herpesviruses, human cytomegalovirus (HCMV) and herpes simplex virus type-1 (HSV-1), on the metabolism of fibroblast and epithelial host cells. Each virus triggered strong metabolic changes that were conserved across different host cell types. The metabolic effects of the two viruses were, however, largely distinct. HCMV but not HSV-1 increased glycolytic flux. HCMV profoundly increased TCA compound levels and flow of two carbon units required for TCA cycle turning and fatty acid synthesis. HSV-1 increased anapleurotic influx to the TCA cycle through pyruvate carboxylase, feeding pyrimidine biosynthesis. Thus, these two related herpesviruses drive diverse host cells to execute distinct, virus-specific metabolic programs. Current drugs target nucleotide metabolism for treatment of both viruses. Although our results confirm that this is a robust target for HSV-1, therapeutic interventions at other points in metabolism might prove more effective for treatment of HCMV

Merkel Cell Polyomavirus Small T Antigen Promotes Pro-Glycolytic Metabolic Perturbations Required for Transformation

An accurate analytic model describing the microscopic mechanism of high-harmonic generation (HHG) in solids is derived. Extensive first-principles simulations within a time-dependent density-functional framework corroborate the conclusions of the model. Our results reveal that (i) the emitted HHG spectra are highly anisotropic and laser-polarization dependent even for cubic crystals; (ii) the harmonic emission is enhanced by the inhomogeneity of the electron-nuclei potential; the yield is increased for heavier atoms; and (iii) the cutoff photon energy is driver-wavelength independent. Moreover, we show that it is possible to predict the laser polarization for optimal HHG in bulk crystals solely from the knowledge of their electronic band structure. Our results pave the way to better control and optimize HHG in solids by engineering their band structure

Constrained Allocation Flux Balance Analysis

New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an "ensemble averaging" procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws.Comment: 21 pages, 6 figures (main) + 33 pages, various figures and tables (supporting); for the supplementary MatLab code, see http://tinyurl.com/h763es