Human hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults and the most common cause of death in people with cirrhosis. While previous metabolic studies of HCC have mainly focused on the glucose metabolism (Warburg effect), less attention has been paid to tumor-specific features of the lipid metabolism. Here, we applied a computational approach to analyze major pathways of fatty acid utilization in individual HCC. To this end, we used protein intensity profiles of eleven human HCCs to parameterize tumor-specific kinetic models of cellular lipid metabolism including formation, enlargement, and degradation of lipid droplets (LDs). Our analysis reveals significant inter-tumor differences in the lipid metabolism. The majority of HCCs show a reduced uptake of fatty acids and decreased rate of β-oxidation, however, some HCCs display a completely different metabolic phenotype characterized by high rates of β-oxidation. Despite reduced fatty acid uptake in the majority of HCCs, the content of triacylglycerol is significantly enlarged compared to the tumor-adjacent tissue. This is due to tumor-specific expression profiles of regulatory proteins decorating the surface of LDs and controlling their turnover. Our simulations suggest that HCCs characterized by a very high content of triglycerides comprise regulatory peculiarities that render them susceptible to selective drug targeting without affecting healthy tissue.

The brain is an organ with high metabolic rate. However, little is known about energy utilization during different activity states of neuronal networks. We addressed this issue in area CA3 of hippocampal slice cultures under well-defined recording conditions using a 20% O₂ gas mixture. We combined recordings of local field potential and interstitial partial oxygen pressure (pO₂) during three different activity states, namely fast network oscillations in the gamma-frequency band (30 to 100 Hz), spontaneous network activity and absence of spiking (action potentials). Oxygen consumption rates were determined by pO₂ depth profiles with high spatial resolution and a mathematical model that considers convective transport, diffusion, and activity-dependent consumption of oxygen. We show that: (1) Relative oxygen consumption rate during cholinergic gamma oscillations was 2.2-fold and 5.3-fold higher compared with spontaneous activity and absence of spiking, respectively. (2) Gamma oscillations were associated with a similar large decrease in pO₂ as observed previously with a 95% O₂ gas mixture. (3) Sufficient oxygenation during fast network oscillations in vivo is ensured by the calculated critical radius of 30 to 40 μm around a capillary. We conclude that the structural and biophysical features of brain tissue permit variations in local oxygen consumption by a factor of about five.

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).

Background and Aims: Zone‐dependent differences in expression of metabolic enzymes along the portocentral axis of the acinus are a long‐known feature of liver metabolism. A prominent example is the preferential localization of the enzyme, glutamine synthetase, in pericentral hepatocytes, where it converts potentially toxic ammonia to the valuable amino acid, glutamine. However, with the exception of a few key regulatory enzymes, a comprehensive and quantitative assessment of zonal differences in the abundance of metabolic enzymes and, much more important, an estimation of the associated functional differences between portal and central hepatocytes is missing thus far. Approach and Results: We addressed this problem by establishing a method for the separation of periportal and pericentral hepatocytes that yields sufficiently pure fractions of both cell populations. Quantitative shotgun proteomics identified hundreds of differentially expressed enzymes in the two cell populations. We used zone‐specific proteomics data for scaling of the maximal activities to generate portal and central instantiations of a comprehensive kinetic model of central hepatic metabolism (Hepatokin1). Conclusions: The model simulations revealed significant portal‐to‐central differences in almost all metabolic pathways involving carbohydrates, fatty acids, amino acids, and detoxification.

Imaging of the cellular fluorescence of the reduced form of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) is one of the few metabolic readouts that enable noninvasive and time-resolved monitoring of the functional status of mitochondria in neuronal tissues. Stimulation-induced transient changes in NAD(P)H fluorescence intensity frequently display a biphasic characteristic that is influenced by various molecular processes, e.g., intracellular calcium dynamics, tricarboxylic acid cycle activity, the malate–aspartate shuttle, the glycerol-3-phosphate shuttle, oxygen supply or adenosine triphosphate (ATP) demand. To evaluate the relative impact of these processes, we developed and validated a detailed physiologic mathematical model of the energy metabolism of neuronal cells and used the model to simulate metabolic changes of single cells and tissue slices under different settings of stimulus-induced activity and varying nutritional supply of glucose, pyruvate or lactate. Notably, all experimentally determined NAD(P)H responses could be reproduced with one and the same generic cellular model. Our computations reveal that (1) cells with quite different metabolic status may generate almost identical NAD(P)H responses and (2) cells of the same type may quite differently contribute to aggregate NAD(P)H responses recorded in brain slices, depending on the spatial location within the tissue. Our computational approach reconciles different and sometimes even controversial experimental findings and improves our mechanistic understanding of the metabolic changes underlying live-cell NAD(P)H fluorescence transients.