Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer.

BACKGROUND: Metabolic alterations can serve as targets for diagnosis and cancer therapy. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. METHODS: We applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterise metabolic reprogramming in murine liver cancer. RESULTS: We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to assess their maximal velocity values. Model simulations predicted tumour-specific alterations of various components of the CCM, a selected number of which were subsequently verified by in vitro and in vivo experiments. Furthermore, we demonstrate the ability of the kinetic model to identify metabolic pathways whose inhibition results in selective tumour cell killing. CONCLUSIONS: Our systems biology approach establishes that combining cellular experimentation with computer simulations of physiology-based metabolic models enables a comprehensive understanding of deregulated energetics in cancer. We propose that modelling proteomics data from human HCC with our approach will enable an individualised metabolic profiling of tumours and predictions of the efficacy of drug therapies targeting specific metabolic pathways.

HEPATOKIN1 is a biochemistry-based model of liver metabolism for applications in medicine and pharmacology.

The epidemic increase of non-alcoholic fatty liver diseases (NAFLD) requires a deeper understanding of the regulatory circuits controlling the response of liver metabolism to nutritional challenges, medical drugs, and genetic enzyme variants. As in vivo studies of human liver metabolism are encumbered with serious ethical and technical issues, we developed a comprehensive biochemistry-based kinetic model of the central liver metabolism including the regulation of enzyme activities by their reactants, allosteric effectors, and hormone-dependent phosphorylation. The utility of the model for basic research and applications in medicine and pharmacology is illustrated by simulating diurnal variations of the metabolic state of the liver at various perturbations caused by nutritional challenges (alcohol), drugs (valproate), and inherited enzyme disorders (galactosemia). Using proteomics data to scale maximal enzyme activities, the model is used to highlight differences in the metabolic functions of normal hepatocytes and malignant liver cells (adenoma and hepatocellular carcinoma).

Renal oncocytoma characterized by the defective complex I of the respiratory chain boosts the synthesis of the ROS scavenger glutathione.

Renal oncocytomas are rare benign tumors of the kidney and characterized by a deficient complex I (CI) enzyme activity of the oxidative phosphorylation (OXPHOS) system caused by mitochondrial DNA (mtDNA) mutations. Yet, little is known about the underlying molecular mechanisms and alterations of metabolic pathways in this tumor. We compared renal oncocytomas with adjacent matched normal kidney tissues on a global scale by multi-omics approaches, including whole exome sequencing (WES), proteomics, metabolomics, and metabolic pathway simulation. The abundance of proteins localized to mitochondria increased more than 2-fold, the only exception was a strong decrease in the abundance for CI subunits that revealed several pathogenic heteroplasmic mtDNA mutations by WES. We also observed renal oncocytomas to dysregulate main metabolic pathways, shunting away from gluconeogenesis and lipid metabolism. Nevertheless, the abundance of energy carrier molecules such as NAD+, NADH, NADP, ATP, and ADP were significantly higher in renal oncocytomas. Finally, a substantial 5000-fold increase of the reactive oxygen species scavenger glutathione can be regarded as a new hallmark of renal oncocytoma. Our findings demonstrate that renal oncocytomas undergo a metabolic switch to eliminate ATP consuming processes to ensure a sufficient energy supply for the tumor.

Implications of enzyme deficiencies on mitochondrial energy metabolism and reactive oxygen species formation of neurons involved in rotenone-induced Parkinson's disease: a model-based analysis.

Steadily growing experimental evidence suggests that mitochondrial dysfunction plays a key role in the age-dependent impairment of nerve cells underlying several neurodegenerative diseases. In particular, the citric acid cycle enzyme complex α-ketoglutarate dehydrogenase (KGDHC) and respiratory chain complex I of the respiratory chain often show reduced activities in the dopaminergic neurons involved in Parkinson's disease, both giving rise to an impaired mitochondrial energy metabolism as demonstrated in a number of in vitro studies with cell lines as well as isolated mitochondria. To understand the metabolic regulation underlying these experimental findings we used a detailed kinetic model of mitochondrial energy metabolism. First, we investigated the effect of complex I inhibition on energy production and formation of reactive oxygen species (ROS). Next, we applied the model to a situation where both KGDHC and complex I exhibit reduced activities. These calculations reveal synergistic effects with respect to the energy metabolism but antagonistic effects with respect to ROS formation: the drop in the ATP production capacity is more pronounced than at inhibition of either enzyme complex alone. Interestingly, however, the reduction state of the ROS-generating sites of the impaired complex I becomes significantly lowered if additionally the activity of the KGDHC is reduced. We discuss the pathophysiological consequences of these intriguing findings.

Enzymatic features of the glucose metabolism in tumor cells.

Many tumor types exhibit an impaired Pasteur effect, i.e. despite the presence of oxygen, glucose is consumed at an extraordinarily high rate compared with the tissue from which they originate - the so-called 'Warburg effect'. Glucose has to serve as the source for a diverse array of cellular functions, including energy production, synthesis of nucleotides and lipids, membrane synthesis and generation of redox equivalents for antioxidative defense. Tumor cells acquire specific enzyme-regulatory mechanisms to direct the main flux of glucose carbons to those pathways most urgently required under challenging external conditions such as varying substrate availability, presence of anti-cancer drugs or different phases of the cell cycle. In this review we summarize the currently available information on tumor-specific expression, activity and kinetic properties of enzymes involved in the main pathways of glucose metabolism with due regard to the explanation of the regulatory basis and physiological significance of the Warburg effect. We conclude that, besides the expression level of the metabolic enzymes involved in the glucose metabolism of tumor cells, the unique tumor-specific pattern of isozymes and accompanying changes in the metabolic regulation below the translation level enable tumor cells to drain selfishly the blood glucose pool that non-transformed cells use as sparingly as possible.

Characterizing the N-terminal processing motif of MHC class I ligands.

Most peptide ligands presented by MHC class I molecules are the product of an intracellular pathway comprising protein breakdown in the cytosol, transport into the endoplasmic reticulum, and successive N-terminal trimming events. The efficiency of each of these processes depends on the amino acid sequence of the presented ligand and its precursors. Thus, relating the amino acid composition N-terminal of presented ligands to the sequence specificity of processes in the pathway gives insight into the usage of ligand precursors in vivo. Examining the amino acid composition upstream the true N terminus of MHC class I ligands, we demonstrate the existence of a distinct N-terminal processing motif comprising approximately seven residues and matching the known preferences of proteasome and TAP, two key players in ligand processing. Furthermore, we find that some residues, which are preferred by both TAP and the proteasome, are underrepresented at positions immediately preceding the N terminus of MHC class I ligands. Based on experimentally determined aminopeptidase activities, this pattern suggests trimming next to the final N terminus to take place predominantly in the endoplasmic reticulum.

Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors.

We are able to make reliable predictions of the efficiency with which peptides of arbitrary lengths will be transported by TAP. The pressure exerted by TAP on Ag presentation thus can be assessed by checking to what extent MHC class I (MHC-I)-presented epitopes can be discriminated from random peptides on the basis of predicted TAP transport efficiencies alone. Best discriminations were obtained when N-terminally prolonged epitope precursor peptides were included and the contribution of the N-terminal residues to the score were down-weighted in comparison with the contribution of the C terminus. We provide evidence that two factors may account for this N-terminal down-weighting: 1) the uncertainty as to which precursors are used in vivo and 2) the coevolution in the C-terminal sequence specificities of TAP and other agents in the pathway, which may vary among the various MHC-I alleles. Combining predictions of MHC-I binding affinities with predictions of TAP transport efficiency led to an improved identification of epitopes, which was not the case when predictions of MHC-I binding affinities were combined with predictions of C-terminal cleavages made by the proteasome.