Cancer and Alzheimer's disease: intracellular pH scales the metabolic disorders.

Alzheimer's disease (AD) and cancer have much in common than previously recognized. These pathologies share common risk factors (inflammation and aging), with similar epidemiological and biochemical features such as impaired mitochondria. Metabolic reprogramming occurs during aging and inflammation. We assume that inflammation is directly responsible of the Warburg effect in cancer cells, with a decreased oxidative phosphorylation and a compensatory highthroughput glycolysis (HTG). Similarly, the Warburg effect in cancer is thought to support an alkaline intracellular pH (pHi), a key component of unrelenting cell growth. In the brain, inflammation results in increased secretion of lactate by astrocytes. The increased uptake of lactic acid by neurons results in the inverse Warburg effect, such as seen in AD. The neuronal activity is dampened by a fall of pHi. Pronounced cytosol acidification results in decreased mitochondrial energy yield as well as apoptotic cell death. The link between AD and cancer is reinforced by the fact that treatment aiming at restoring the mitochondrial activity have been experimentally shown to be effective in both diseases. Low carb diet, lipoic acid, and/or methylene blue could then appear promising in both sets of these clinically diverse diseases.

Metabolic therapies inhibit tumor growth in vivo and in silico.

In the recent years, cancer research succeeded with sensitive detection methods, targeted drug delivery systems, and the identification of a large set of genes differently expressed. However, although most therapies are still based on antimitotic agents, which are causing wide secondary effects, there is an increasing interest for metabolic therapies that can minimize side effects. In the early 20th century, Otto Warburg revealed that cancer cells rely on the cytoplasmic fermentation of glucose to lactic acid for energy synthesis (called "Warburg effect"). Our investigations aim to reverse this effect in reprogramming cancer cells' metabolism. In this work, we present a metabolic therapy specifically targeting the activity of specific enzymes of central carbon metabolism, combining the METABLOC bi-therapeutic drugs combination (Alpha Lipoic Acid and Hydroxycitrate) to Metformin and Diclofenac, for treating tumors implanted in mice. Furthermore, a dynamic metabolic model describing central carbon metabolism as well as fluxes targeted by the drugs allowed to simulate tumors progression in both treated and non-treated mice, in addition to draw hypotheses on the effects of the drugs on tumor cells metabolism. Our model predicts metabolic therapies-induced reversed Warburg effect on tumor cells.

Identifying Biomarkers of Wharton's Jelly Mesenchymal Stromal Cells Using a Dynamic Metabolic Model: The Cell Passage Effect.

Because of their unique ability to modulate the immune system, mesenchymal stromal cells (MSCs) are widely studied to develop cell therapies for detrimental immune and inflammatory disorders. However, controlling the final cell phenotype and determining immunosuppressive function following cell amplification in vitro often requires prolonged cell culture assays, all of which contribute to major bottlenecks, limiting the clinical emergence of cell therapies. For instance, the multipotent Wharton's Jelly mesenchymal stem/stromal cells (WJMSC), extracted from human umbilical cord, exhibit immunosuppressive traits under pro-inflammatory conditions, in the presence of interferon-γ (IFNγ), and tumor necrosis factor-α (TNFα). However, WJMSCs require co-culture bioassays with immune cells, which can take days, to confirm their immunomodulatory function. Therefore, the establishment of robust cell therapies would benefit from fast and reliable characterization assays. To this end, we have explored the metabolic behaviour of WJMSCs in in vitro culture, to identify biomarkers that are specific to the cell passage effect and the loss of their immunosuppressive phenotype. We clearly show distinct metabolic behaviours comparing WJMSCs at the fourth (P4) and the late ninth (P9) passages, although both P4 and P9 cells do not exhibit significant differences in their low immunosuppressive capacity. Metabolomics data were analysed using an in silico modelling platform specifically adapted to WJMSCs. Of interest, P4 cells exhibit a glycolytic metabolism compared to late passage (P9) cells, which show a phosphorylation oxidative metabolism, while P4 cells show a doubling time of 29 h representing almost half of that for P9 cells (46 h). We also clearly show that fourth passage WJMSCs still express known immunosuppressive biomarkers, although, this behaviour shows overlapping with a senescence phenotype.

A dynamic metabolic flux analysis of ABE (acetone-butanol-ethanol) fermentation by Clostridium acetobutylicum ATCC 824, with riboflavin as a by-product.

The present study reveals that supplementing sodium acetate (NaAc) strongly stimulates riboflavin production in acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum ATCC 824 with xylose as carbon source. Riboflavin production increased from undetectable concentrations to ∼0.2 g L-1 (0.53 mM) when supplementing 60 mM NaAc. Of interest, solvents production and biomass yield were also promoted with fivefold acetone, 2.6-fold butanol, and 2.4-fold biomass adding NaAc. A kinetic metabolic model, developed to simulate ABE biosystem, with riboflavin production, revealed from a dynamic metabolic flux analysis (dMFA) simultaneous increase of riboflavin (ribA) and GTP (precursor of riboflavin) (PurM) synthesis flux rates under NaAc supplementation. The model includes 23 fluxes, 24 metabolites, and 72 kinetic parameters. It also suggested that NaAc condition has first stimulated the accumulation of intracellular metabolite intermediates during the acidogenic phase, which have then fed the solventogenic phase leading to increased ABE production. In addition, NaAc resulted in higher intracellular levels of NADH during the whole culture. Moreover, lower GTP-to-adenosine phosphates (ATP, ADP, AMP) ratio under NaAc supplemented condition suggests that GTP may have a minor role in the cell energetic metabolism compared to its contribution to riboflavin synthesis.

The Redox Status of Cancer Cells Supports Mechanisms behind the Warburg Effect.

To better understand the energetic status of proliferating cells, we have measured the intracellular pH (pHi) and concentrations of key metabolites, such as adenosine triphosphate (ATP), nicotinamide adenine dinucleotide (NAD), and nicotinamide adenine dinucleotide phosphate (NADP) in normal and cancer cells, extracted from fresh human colon tissues. Cells were sorted by elutriation and segregated in different phases of the cell cycle (G0/G1/S/G2/M) in order to study their redox (NAD, NADP) and bioenergetic (ATP, pHi) status. Our results show that the average ATP concentration over the cell cycle is higher and the pHi is globally more acidic in normal proliferating cells. The NAD+/NADH and NADP+/NADPH redox ratios are, respectively, five times and ten times higher in cancer cells compared to the normal cell population. These energetic differences in normal and cancer cells may explain the well-described mechanisms behind the Warburg effect. Oscillations in ATP concentration, pHi, NAD+/NADH, and NADP+/NADPH ratios over one cell cycle are reported and the hypothesis addressed. We also investigated the mitochondrial membrane potential (MMP) of human and mice normal and cancer cell lines. A drastic decrease of the MMP is reported in cancer cell lines compared to their normal counterparts. Altogether, these results strongly support the high throughput aerobic glycolysis, or Warburg effect, observed in cancer cells.

Cell cycle progression is regulated by intertwined redox oscillators.

The different phases of the eukaryotic cell cycle are exceptionally well-preserved phenomena. DNA decompaction, RNA and protein synthesis (in late G1 phase) followed by DNA replication (in S phase) and lipid synthesis (in G2 phase) occur after resting cells (in G0) are committed to proliferate. The G1 phase of the cell cycle is characterized by an increase in the glycolytic metabolism, sustained by high NAD+/NADH ratio. A transient cytosolic acidification occurs, probably due to lactic acid synthesis or ATP hydrolysis, followed by cytosolic alkalinization. A hyperpolarized transmembrane potential is also observed, as result of sodium/potassium pump (NaK-ATPase) activity. During progression of the cell cycle, the Pentose Phosphate Pathway (PPP) is activated by increased NADP+/NADPH ratio, converting glucose 6-phosphate to nucleotide precursors. Then, nucleic acid synthesis and DNA replication occur in S phase. Along with S phase, unpublished results show a cytosolic acidification, probably the result of glutaminolysis occurring during this phase. In G2 phase there is a decrease in NADPH concentration (used for membrane lipid synthesis) and a cytoplasmic alkalinization occurs. Mitochondria hyperfusion matches the cytosolic acidification at late G1/S transition and then triggers ATP synthesis by oxidative phosphorylation. We hypothesize here that the cytosolic pH may coordinate mitochondrial activity and thus the different redox cycles, which in turn control the cell metabolism.

Elementary flux modes analysis of functional domain networks allows a better metabolic pathway interpretation.

Metabolic network analysis is an important step for the functional understanding of biological systems. In these networks, enzymes are made of one or more functional domains often involved in different catalytic activities. Elementary flux mode (EFM) analysis is a method of choice for the topological studies of these enzymatic networks. In this article, we propose to use an EFM approach on networks that encompass available knowledge on structure-function. We introduce a new method that allows to represent the metabolic networks as functional domain networks and provides an application of the algorithm for computing elementary flux modes to analyse them. Any EFM that can be represented using the classical representation can be represented using our functional domain network representation but the fine-grained feature of functional domain networks allows to highlight new connections in EFMs. This methodology is applied to the tricarboxylic acid cycle (TCA cycle) of Bacillus subtilis, and compared to the classical analyses. This new method of analysis of the functional domain network reveals that a specific inhibition on the second domain of the lipoamide dehydrogenase (pdhD) component of pyruvate dehydrogenase complex leads to the loss of all fluxes. Such conclusion was not predictable in the classical approach.