Summary Cancer cells consume glucose and secrete lactate in culture. It is unknown whether lactate contributes to energy metabolism in living tumors. We previously reported that human non-small cell lung cancers (NSCLC) oxidize glucose in the tricarboxylic acid (TCA) cycle. Here we show that lactate is also a TCA cycle carbon source for NSCLC. In human NSCLC, evidence of lactate utilization was most apparent in tumors with high 18fluorodeoxyglucose uptake and aggressive oncological behavior. Infusing human NSCLC patients with 13C-lactate revealed extensive labeling of TCA cycle metabolites. In mice, deleting monocarboxylate transporter-1 (MCT1) from tumor cells eliminated lactate-dependent metabolite labeling, confirming tumor-cell autonomous lactate uptake. Strikingly, directly comparing lactate and glucose metabolism in vivo indicated that lactate's contribution to the TCA cycle predominates. The data indicate that tumors, including bona fide human NSCLC, can use lactate as a fuel in vivo.

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. 13C tracer analysis, although less information-rich than quantitative 13C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting 13C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.

Understanding in vivo regulation of photoautotrophic metabolism is important for identifying strategies to improve photosynthetic efficiency or re-route carbon fluxes to desirable end products. We have developed an approach to reconstruct comprehensive flux maps of photoautotrophic metabolism by computational analysis of dynamic isotope labeling measurements and have applied it to determine metabolic pathway fluxes in the cyanobacterium Synechocystis sp. PCC6803. Comparison to a theoretically predicted flux map revealed inefficiencies in photosynthesis due to oxidative pentose phosphate pathway and malic enzyme activity, despite negligible photorespiration. This approach has potential to fill important gaps in our understanding of how carbon and energy flows are systemically regulated in cyanobacteria, plants, and algae.

13C flux analysis studies have become an essential component of metabolic engineering research. The scope of these studies has gradually expanded to include both isotopically steady-state and transient labeling experiments, the latter of which are uniquely applicable to photosynthetic organisms and slow-to-label mammalian cell cultures. Isotopomer network compartmental analysis (INCA) is the first publicly available software package that can perform both steady-state metabolic flux analysis and isotopically non-stationary metabolic flux analysis. The software provides a framework for comprehensive analysis of metabolic networks using mass balances and elementary metabolite unit balances. The generation of balance equations and their computational solution is completely automated and can be performed on networks of arbitrary complexity.

Cell metabolism can vary considerably over the course of a typical fed-batch antibody production process. However, the intracellular pathway alterations associated with various phases of growth and antibody production have yet to be fully elucidated using industrially relevant production hosts. Therefore, we performed (13)C labeling experiments and metabolic flux analysis (MFA) to characterize CHO cell metabolism during four separate phases of a fed-batch culture designed to closely represent industrial process conditions. First, we found that peak specific growth rate was associated with high lactate production and minimal TCA cycling. Conversely, we found that lactate metabolism switched from net production to net consumption as the culture transitioned from peak growth to peak antibody production. During the peak antibody production phase, energy was primarily generated through oxidative phosphorylation, which was also associated with elevated oxidative pentose phosphate pathway (oxPPP) activity. Interestingly, as TCA cycling and antibody production reached their peaks, specific growth rate continued to diminish as the culture entered stationary phase. However, TCA cycling and oxPPP activity remained high even as viable cell density began to decline. Overall, we found that a highly oxidative state of metabolism corresponded with peak antibody production, whereas peak cell growth was characterized by a highly glycolytic metabolic state.

The steady rise in Western obesity rates has been closely linked to significant increases in a multitude of accompanying health problems including Non-Alcoholic Fatty Liver Disease (NAFLD). NAFLD severity ranges from simple steatosis to acute steatohepatitis, but the molecular mechanisms controlling progression of this disease are poorly understood. Recent literature suggests that elevated free fatty acids (FFAs), especially saturated FFAs, may play an important role in lipotoxic mechanisms, both in experimental models and in NAFLD patients. This review highlights important cellular pathways involved in hepatic lipotoxicity and how the degree of intrahepatic lipid saturation controls cell fate in response to an elevated FFA load. Relevant cellular processes that have been causally linked to lipid-induced apoptosis, known as lipoapoptosis, include endoplasmic reticulum (ER) stress, oxidative stress, mitochondrial dysfunction, and Jun N-terminal kinase (JNK) signaling. In contrast, increased triglyceride synthesis has been shown to have a protective effect against lipotoxicity, despite being one of the hallmark traits of NAFLD. Developing a more nuanced understanding of the molecular mechanisms underlying NAFLD progression will lead to more targeted and effective therapeutics for this increasingly prevalent disease, which to date has no proven pharmacologic treatment to prevent or reverse its course.

Nonstationary metabolic flux analysis (NMFA) is at present a very computationally intensive exercise, especially for large reaction networks. We applied elementary metabolite unit (EMU) theory to NMFA, dramatically reducing computational difficulty. We also introduced block decoupling, a new method that systematically and comprehensively divides EMU systems of equations into smaller subproblems to further reduce computational difficulty. These improvements led to a 5000-fold reduction in simulation times, enabling an entirely new and more complicated set of problems to be analyzed with NMFA. We simulated a series of nonstationary and stationary GC/MS measurements for a large E. coli network that was then used to estimate parameters and their associated confidence intervals. We found that fluxes could be successfully estimated using only nonstationary labeling data and external flux measurements. Addition of near-stationary and stationary time points increased the precision of most parameters. Contrary to prior reports, the precision of nonstationary estimates proved to be comparable to the precision of estimates based solely on stationary data. Finally, we applied EMU-based NMFA to experimental nonstationary measurements taken from brown adipocytes and successfully estimated fluxes and some metabolite concentrations. By using NFMA instead of traditional MFA, the experiment required only 6 h instead of 50 (the time necessary for most metabolite labeling to reach 99% of isotopic steady state).

Improving plant productivity is an important aim for metabolic engineering. There are few comprehensive methods that quantitatively describe leaf metabolism, although such information would be valuable for increasing photosynthetic capacity, enhancing biomass production, and rerouting carbon flux toward desirable end products. Isotopically nonstationary metabolic flux analysis (INST-MFA) has been previously applied to map carbon fluxes in photoautotrophic bacteria, which involves model-based regression of transient 13 C-labeling patterns of intracellular metabolites. However, experimental and computational difficulties have hindered its application to terrestrial plant systems. We performed in vivo isotopic labeling of Arabidopsis thaliana rosettes with . Approximately 1,400 independent mass isotopomer measurements obtained from analysis of 37 metabolite fragment ions were regressed to estimate 136 total fluxes (54 free fluxes) under each condition. The results provide a comprehensive description of changes in carbon partitioning and overall photosynthetic flux after longterm developmental acclimation of leaves to high light. Despite a doubling in the carboxylation rate, the photorespiratory flux increased from 17 to 28% of net CO 2 assimilation with high-light acclimation (Vc/Vo: 3.5:1 vs. 2.3:1, respectively). This study highlights the potential of 13 C INST-MFA to describe emergent flux phenotypes that respond to environmental conditions or plant physiology and cannot be obtained by other complementary approaches.isotopomer modeling | metabolic flux analysis | photosynthesis | 13 C-labeling | primary metabolism P hotosynthetic organisms assimilate more than 100 billion tons of carbon, ∼15% of the atmospheric total, each year and generate organic compounds for food and renewable chemicals (1). However, photosynthesis is a complex process that responds to heterotrophic tissue demands and environmental stimuli such as drought, temperature, and light intensity (2, 3). The light incident on the plant varies with intensities in the range of 0-2,000 μmol photons·m −2 ·s −1 and can change dramatically because of passing clouds, shading, and the position of the sun. Thus, plants adjust light harvesting and carbon assimilation steps to accommodate many fluctuations, resulting in changes in plant morphology, physiology, and metabolism (4).For 95% of all terrestrial plants (i.e., C3 plants), the reductive pentose phosphate (Calvin-Benson-Bassham, or CBB) cycle directly links light and dark reactions and sustains anabolic activities (5). RuBisCO (ribulose-1,5-bisphosphate carboxylase oxygenase) plays a central role in the cycle by carboxylating ribulose-1,5-bisphosphate (RUBP) with CO 2 to form two 3-phosphoglycerate (3PGA) molecules. The other 10 enzymes in the CBB cycle regenerate the RUBP substrate to repeat this process. RuBisCO has a low turnover rate (∼3/s; ref. 6) and also performs a competitive oxygenation side reaction that limits carboxylation activity. The binding of RuBisCO to oxygen produces 2-phosphoglycolat...