Mathematical models for explaining the Warburg effect: a review focussed on ATP and biomass production

Metabolic Reprogramming of Astrocytes in Pathological Conditions: Implications for Neurodegenerative Diseases

Astrocytes play a pivotal role in maintaining brain energy homeostasis, supporting neuronal function through glycolysis and lipid metabolism. This review explores the metabolic intricacies of astrocytes in both physiological and pathological conditions, highlighting their adaptive plasticity and diverse functions. Under normal conditions, astrocytes modulate synaptic activity, recycle neurotransmitters, and maintain the blood-brain barrier, ensuring a balanced energy supply and protection against oxidative stress. However, in response to central nervous system pathologies such as neurotrauma, stroke, infections, and neurodegenerative diseases like Alzheimer's and Huntington's disease, astrocytes undergo significant morphological, molecular, and metabolic changes. Reactive astrocytes upregulate glycolysis and fatty acid oxidation to meet increased energy demands, which can be protective in acute settings but may exacerbate chronic inflammation and disease progression. This review emphasizes the need for advanced molecular, genetic, and physiological tools to further understand astrocyte heterogeneity and their metabolic reprogramming in disease states.

Rethinking the role of microglia in obesity

Microglia are the macrophages of the central nervous system (CNS), implying their role in maintaining brain homeostasis. To achieve this, these cells are sensitive to a plethora of endogenous and exogenous signals, such as neuronal activity, cellular debris, hormones, and pathological patterns, among many others. More recent research suggests that microglia are highly responsive to nutrients and dietary variations. In this context, numerous studies have demonstrated their significant role in the development of obesity under calorie surfeit. Because many reviews already exist on this topic, we have chosen to present the state of our reflections on various concepts put forth in the literature, bringing a new perspective whenever possible. Our literature review focuses on studies conducted in the arcuate nucleus of the hypothalamus, a key structure in the control of food intake. Specifically, we present the recent data available on the modifications of microglial energy metabolism following the consumption of an obesogenic diet and their consequences on hypothalamic neuron activity. We also highlight the studies unraveling the mechanisms underlying obesity-related sexual dimorphism. The review concludes with a list of questions that remain to be addressed in the field to achieve a comprehensive understanding of the role of microglia in the regulation of body energy metabolism. This article is part of the Special Issue on "Microglia".

What do stimulated beta cells have in common with cancer cells?

This study investigates the metabolic parallels between stimulated pancreatic beta cells and cancer cells, focusing on glucose and glutamine metabolism. Addressing the significant public health challenges of Type 2 Diabetes (T2D) and cancer, we aim to deepen our understanding of the mechanisms driving insulin secretion and cellular proliferation. Our analysis of anaplerotic cycles and the role of NADPH in biosynthesis elucidates their vital functions in both processes. Additionally, we point out that both cell types share an antioxidative response mediated by the Nrf2 signaling pathway, glutathione synthesis, and UCP2 upregulation. Notably, UCP2 facilitates the transfer of C4 metabolites, enhancing reductive TCA cycle metabolism. Furthermore, we observe that hypoxic responses are transient in beta cells post-stimulation but persistent in cancer cells. By synthesizing these insights, the research may suggest novel therapeutic targets for T2D, highlighting the shared metabolic strategies of stimulated beta cells and cancer cells. This comparative analysis not only illuminates the metabolic complexity of these conditions but also emphasizes the crucial role of metabolic pathways in cell function and survival, offering fresh perspectives for tackling T2D and cancer challenges.

Including glutamine in a resource allocation model of energy metabolism in cancer and yeast cells

Energy metabolism is crucial for all living cells, especially during fast growth or stress scenarios. Many cancer and activated immune cells (Warburg effect) or yeasts (Crabtree effect) mostly rely on aerobic glucose fermentation leading to lactate or ethanol, respectively, to generate ATP. In recent years, several mathematical models have been proposed to explain the Warburg effect on theoretical grounds. Besides glucose, glutamine is a very important substrate for eukaryotic cells-not only for biosynthesis, but also for energy metabolism. Here, we present a minimal constraint-based stoichiometric model for explaining both the classical Warburg effect and the experimentally observed respirofermentation of glutamine (WarburQ effect). We consider glucose and glutamine respiration as well as the respective fermentation pathways. Our resource allocation model calculates the ATP production rate, taking into account enzyme masses and, therefore, pathway costs. While our calculation predicts glucose fermentation to be a superior energy-generating pathway in human cells, different enzyme characteristics in yeasts reduce this advantage, in some cases to such an extent that glucose respiration is preferred. The latter is observed for the fungal pathogen Candida albicans, which is a known Crabtree-negative yeast. Further, optimization results show that glutamine is a valuable energy source and important substrate under glucose limitation, in addition to its role as a carbon and nitrogen source of biomass in eukaryotic cells. In conclusion, our model provides insights that glutamine is an underestimated fuel for eukaryotic cells during fast growth and infection scenarios and explains well the observed parallel respirofermentation of glucose and glutamine in several cell types.

The crosstalk between glucose metabolism and telomerase regulation in cancer

Accumulated alterations in metabolic control provide energy and anabolic demands for enhanced cancer cell proliferation. Exemplified by the Warburg effect, changes in glucose metabolism during cancer progression are widely recognized as a characteristic of metabolic disorders. Since telomerases are a vital factor in maintaining DNA integrity and stability, any damage threatening telomerases could have a severe impact on DNA and, subsequently, whole-cell homeostasis. However, it remains unclear whether the regulation of glucose metabolism in cancer is connected to the regulation of telomerase. In this review, we present the latest insights into the crosstalk between telomerase function and glucose metabolism in cancer cells. However, at this moment this subject is not well investigated that the association is mostly indirectly regulations and few explicit regulating pathways were identified between telomerase and glucose metabolism. Therefore, the information presented in this review can provide a scientific basis for further research on the detail mechanism and the clinical application of cancer therapy, which could be valuable in improving the effectiveness of chemotherapy.

Activation of Cannabinoid Type 2 Receptor in Microglia Reduces Neuroinflammation through Inhibiting Aerobic Glycolysis to Relieve Hypertension

BACKGROUND

Studies have shown that the chronic use of cannabis is associated with a decrease in blood pressure. Our previous studies prove that activating the cannabinoid type 2 (CB2) receptor in the brain can effectively reduce blood pressure in spontaneously hypertensive rats; however, the exact mechanism has not been clarified. The objective of this study is to demonstrate that activation of microglial CB2 receptors can effectively reduce the levels of TNF-α, IL-1β, and IL-6 in the paraventricular nucleus (PVN) through inhibiting aerobic glycolysis, thereby relieving hypertension.

METHODS

AngiotensinII (AngII) was administered to BV2 cells and C57 mice to induce hypertension and the release of proinflammatory cytokines. The mRNA and protein expression of the CB2 receptor, TNF-α, IL-1β, IL-6, and the PFK and LDHa enzymes were detected using RT-qPCR and Western blotting. The Seahorse XF Energy Metabolism Analyzer was used to measure the oxidative phosphorylation and aerobic glycolysis metabolic pathways in BV2 cells. The long-term effects of injecting JWH133, a selective CB2 receptor agonist, intraperitoneally on blood pressure were ascertained. ELISA was used to measure norepinephrine and lactic acid levels while immunofluorescence labeling was used to locate the CB2 receptor and c-Fos. By injecting pAAV-F4/80-GFP-mir30shRNA (AAV2-r-CB2shRNA) into the lateral cerebral ventricle, the CB2 receptor in microglia was specifically knocked down.

RESULTS

Activation of CB2 receptors by the agonist JWH133 suppressed TNF-α, IL-1β, and IL-6 by inhibiting PFK and LDHa enzymes involved in glycolysis, as well as lactic acid accumulation, along with a reduction in glycoPER levels (marks of aerobic glycolysis) in AngII-treated BV2 cells. In AngII-treated mice, the administration of JWH133 specifically activated CB2 receptors on microglia, resulting in decreased expression levels of PFK, LDHa, TNF-α, IL-1β, and IL-6, subsequently leading to a decrease in c-Fos protein expression within PVN neurons as well as reduced norepinephrine levels in plasma, ultimately contributing to blood pressure reduction.

CONCLUSION

The results suggest that activation of the microglia CB2 receptor decreases the neuroinflammation to relieve hypertension; the underlying mechanism is related to inhibiting aerobic glycolysis of microglia.

The Warburg Effect Reinterpreted 100 yr on: A First-Principles Stoichiometric Analysis and Interpretation from the Perspective of ATP Metabolism in Cancer Cells

The Warburg Effect is a longstanding enigma in cancer biology. Despite the passage of 100 yr since its discovery, and the accumulation of a vast body of research on the subject, no convincing biochemical explanation has been given for the original observations of aerobic glycolysis in cancer cell metabolism. Here, we have worked out a first-principles quantitative analysis of the problem from the principles of stoichiometry and available electron balance. The results have been interpreted using Nath's unified theory of energy coupling and adenosine triphosphate (ATP) synthesis, and the original data of Warburg and colleagues have been analyzed from this new perspective. Use of the biomass yield based on ATP per unit substrate consumed, [Formula: see text], or the Nath-Warburg number, NaWa has been shown to excellently model the original data on the Warburg Effect with very small standard deviation values, and without employing additional fitted or adjustable parameters. Based on the results of the quantitative analysis, a novel conservative mechanism of synthesis, utilization, and recycling of ATP and other key metabolites (eg, lactate) is proposed. The mechanism offers fresh insights into metabolic symbiosis and coupling within and/or among proliferating cells. The fundamental understanding gained using our approach should help in catalyzing the development of more efficient metabolism-targeting anticancer drugs.

Long non-coding RNA HANR modulates the glucose metabolism of triple negative breast cancer via stabilizing hexokinase 2

Increasing evidence has demonstrated the oncogenic roles of long non-coding RNA (lncRNA) hepatocellular carcinoma (HCC)-associated long non-coding RNA (HANR) in the development of HCC and lung cancer; however, the involvement of HANR in triple-negative breast cancer (TNBC) remains largely unknown. Our results demonstrated the significant overexpression of HANR in TNBC tissues and cells. Higher HANR levels significantly correlated with the poorer phenotypes in patients with TNBC. HANR down-regulation inhibited the proliferation and cell cycle progression and increased the apoptosis of TNBC cells. Mechanistically, immunoprecipitation-mass spectrometry revealed hexokinase II (HK2) as a direct binding target of HANR. HANR binds to and stabilizes HK2 through the proteasomal pathway. Consistent with the important role of HK2 in cancer cells, HANR depletion represses the glucose absorbance and lactate secretion, thus reprogramming the metabolism of TNBC cells. An in vivo xenograft model also demonstrated that HANR promoted tumor growth and aerobic glycolysis. This study reveals the role of HANR in modulating the glycolysis in TNBC cells by regulating HK2 stability, suggesting that HANR is a potential drug target for TNBC.

KIF22 promotes the proliferation and glycolysis of melanoma by activating EGFR/STAT3 signaling

OBJECTIVES

Melanoma is one of the leading causes of cancer death. Kinesin Family member 22 (KIF22) is essential for the invasion of melanoma cells, but the role and mechanism of KIF22 in the proliferation and glycolysis in melanoma remains unknown.

METHODS

KIF22 expression in melanoma tissues and the relationship between KIF22 high expression and overall survival rate in patients with melanoma were analyzed using the Tnmplot database. KIF22 expression in melanoma cells was examined by western blot. Then, KIF22 was silenced and CCK-8 assay, EDU staining and flow cytometry analysis were adopted for assessing cell proliferation and apoptosis. In addition, the glycolysis metabolism of melanoma cells was reflected by detecting Extracellular Acidification Rates (ECAR) and Oxygen Consumption Rates (OCR). The expression of proteins related to apoptosis, glycolysis and EGFR/STAT3 signaling was tested by western blot. Subsequently, melanoma cells were treated with EGF or Colivelin to further elucidate the regulatory effect of KIF22 on EGFR/STAT3 signaling.

RESULTS

KIF22 expression was notably upregulated in melanoma tissues and cells, and KIF22 high expression was associated with a poor prognosis. Moreover, KIF22 insufficiency suppressed proliferation and accelerated apoptosis of melanoma cells. Additionally, glycolysis was reduced by KIF22 depletion, evidenced by the decreased ECAR and increased OCR, accompanied by the downregulated expression of HK2, PKM2 and LDHA. Importantly, the impacts of KIF22 depletion on the progression of melanoma were partially attenuated after EGF or Colivelin treatment.

CONCLUSION

Collectively, KIF22 knockdown suppressed the proliferation and glycolysis and facilitated the apoptosis of melanoma cells by inactivating EGFR/STAT3 signaling.

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow

IMPORTANCE

Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli.

Long non-coding RNA CCHE1 modulates LDHA-mediated glycolysis and confers chemoresistance to melanoma cells

Melanoma is considered as the most common metastatic skin cancer with increasing incidence and high mortality globally. The vital roles of long non-coding RNAs (lncRNAs) in the tumorigenesis of melanoma are elucidated by emerging evidence. The lncRNA cervical carcinoma high-expressed 1 (CCHE1) was overexpressed and acted as an oncogene in a variety of cancers, while the function of CCHE1 in melanoma remains unclear. Here, we found that CCHE1 was highly expressed in melanoma and correlated with the poorer survival of melanoma patients. Depletion of CCHE1 inhibited the proliferation, induced cell apoptosis and suppressed in vivo tumor growth. To further understand the functional mechanism of CCHE1, the interacting partners of CCHE1 were identified via RNA pull-down assay followed by mass spectrometry. CCHE1 was found to bind lactate dehydrogenase A (LDHA) and acted as a scaffold to enhance the interaction of LDHA with the fibroblast growth factor receptor type 1 (FGFR1), which consequently enhanced LDHA phosphorylation and activity of LDHA. Inhibiting CCHE1 strikingly suppressed the glycolytic flux of melanoma cells and lactate generation in vivo. Further study demonstrated that CCHE1 desensitized melanoma cells to dacarbazine and inhibition of glycolysis reversed CCHE1-induced chemoresistance. These results uncovered the novel function of CCHE1 in melanoma by reprogramming the glucose metabolism via orchestrating the activity of LDHA.

Propofol inhibits neuroinflammation and metabolic reprogramming in microglia in vitro and in vivo

Microglial activation-induced neuroinflammation is closely related to the development of sepsis-associated encephalopathy. Accumulating evidence suggests that changes in the metabolic profile of microglia is crucial for their response to inflammation. Propofol is widely used for sedation in mechanically ventilated patients with sepsis. Here, we investigate the effect of propofol on lipopolysaccharide-induced neuroinflammation, neuronal injuries, microglia metabolic reprogramming as well as the underlying molecular mechanisms. The neuroprotective effects of propofol (80 mg/kg) in vivo were measured in the lipopolysaccharide (2 mg/kg)-induced sepsis in mice through behavioral tests, Western blot analysis and immunofluorescent staining. The anti-inflammatory effects of propofol (50 μM) in microglial cell cultures under lipopolysaccharide (10 ng/ml) challenge were examined with Seahorse XF Glycolysis Stress test, ROS assay, Western blot, and immunofluorescent staining. We showed that propofol treatment reduced microglia activation and neuroinflammation, inhibited neuronal apoptosis and improved lipopolysaccharide-induced cognitive dysfunction. Propofol also attenuated lipopolysaccharide-stimulated increases of inducible nitric oxide synthase, nitric oxide, tumor necrosis factor-α, interlukin-1β and COX-2 in cultured BV-2 cells. Propofol-treated microglia showed a remarkable suppression of lipopolysaccharide-induced HIF-1α, PFKFB3, HK2 expression and along with downregulation of the ROS/PI3K/Akt/mTOR signaling pathway. Moreover, propofol attenuated the enhancement of mitochondrial respiration and glycolysis induced by lipopolysaccharide. Together, our data suggest that propofol attenuated inflammatory response by inhibiting metabolic reprogramming, at least in part, through downregulation of the ROS/PI3K/Akt/mTOR/HIF-1α signaling pathway.

Hybrid computational models of multicellular tumour growth considering glucose metabolism

Cancer cells metabolize glucose through metabolic pathways that differ from those used by healthy and differentiated cells. In particular, tumours have been shown to consume more glucose than their healthy counterparts and to use anaerobic metabolic pathways, even under aerobic conditions. Nevertheless, scientists have still not been able to explain why cancer cells evolved to present an altered metabolism and what evolutionary advantage this might provide them. Experimental and computational models have been increasingly used in recent years to understand some of these biological questions. Multicellular tumour spheroids are effective experimental models as they replicate the initial stages of avascular solid tumour growth. Furthermore, these experiments generate data which can be used to calibrate and validate computational studies that aim to simulate tumour growth. Hybrid models are of particular relevance in this field of research because they model cells as individual agents while also incorporating continuum representations of the substances present in the surrounding microenvironment that may participate in intracellular metabolic networks as concentration or density distributions. Henceforth, in this review, we explore the potential of computational modelling to reveal the role of metabolic reprogramming in tumour growth.

Nonlinear multi-objective flux balance analysis of the Warburg Effect

Due to its implication in cancer treatment, the Warburg Effect has received extensive in silico investigation. Flux Balance Analysis (FBA), based on constrained optimization, was successfully applied in the Warburg Effect modelling. Yet, the assumption that cell types have one invariant cellular objective severely limits the applicability of the previous FBA models. Meanwhile, we note that cell types with different objectives show different extents of the Warburg Effect. To extend the applicability of the previous model and model the disparate cellular pathway preferences in different cell types, we built a Nonlinear Multi-Objective FBA (NLMOFBA) model by including three key objective terms (ATP production rate, lactate generation rate and ATP yield) into one objective function through linear scalarization. By constructing a cellular objective map and iteratively varying the objective weights, we showed disparate cellular pathway preferences manifested by different cell types driven by their unique cellular objectives, and we gained insights about the causal relationship between cellular objectives and the Warburg Effect. In addition, we obtained other biologically consistent results by using our NLMOFBA model. For example, augmented with the constraint associated with inefficient mitochondria function, low oxygen availability, or limited substrate, NLMOFBA predicts cellular pathways supported by the biology literature. Collectively, our NLMOFBA model can help build a complete understanding towards the Warburg Effect in different cell types. Finally, we investigated the impact of glutaminolysis, an important pathway related to glycolysis, on the occurrence of the Warburg Effect by using linear programming.

The role of glial cells in multiple sclerosis disease progression

Despite the development of highly effective treatments for relapsing-remitting multiple sclerosis (MS), limited progress has been made in addressing primary progressive or secondary progressive MS, both of which lead to loss of oligodendrocytes and neurons and axons, and to irreversible accumulation of disability. Neuroinflammation is central to all forms of MS. The current effective therapies for relapsing-remitting MS target the peripheral immune system; these treatments, however, have repeatedly failed in progressive MS. Greater understanding of inflammation driven by CNS-resident cells - including astrocytes and microglia - is, therefore, required to identify novel potential therapeutic opportunities. Advances in imaging, biomarker analysis and genomics suggest that microglia and astrocytes have central roles in the progressive disease process. In this Review, we provide an overview of the involvement of astrocytes and microglia at major sites of pathology in progressive MS. We discuss current and future therapeutic approaches to directly target glial cells, either to inhibit pathogenic functions or to restore homeostatic functions lost during the course of the disease. We also discuss how bidirectional communication between astrocytes and microglia needs to be considered, as therapeutic targeting of one is likely to alter the functions of the other.

Therapeutic Approach of KRAS Mutant Tumours by the Combination of Pharmacologic Ascorbate and Chloroquine

The Warburg effect has been considered a potential therapeutic target to fight against cancer progression. In KRAS mutant cells, PKM2 (pyruvate kinase isozyme M2) is hyper-activated, and it induces GLUT1 expression; therefore, KRAS has been closely involved in the initiation of Warburg metabolism. Although mTOR (mammalian target of rapamycin), a well-known inhibitor of autophagy-dependent survival in physiological conditions, is also activated in KRAS mutants, many recent studies have revealed that autophagy becomes hyper-active in KRAS mutant cancer cells. In the present study, a mathematical model was built containing the main elements of the regulatory network in KRAS mutant cancer cells to explore the further possible therapeutic strategies. Our dynamical analysis suggests that the downregulation of KRAS, mTOR and autophagy are crucial in anti-cancer therapy. PKM2 has been assumed to be the key switch in the stress response mechanism. We predicted that the addition of both pharmacologic ascorbate and chloroquine is able to block both KRAS and mTOR pathways: in this case, no GLUT1 expression is observed, meanwhile autophagy, essential for KRAS mutant cancer cells, is blocked. Corresponding to our system biological analysis, this combined pharmacologic ascorbate and chloroquine treatment in KRAS mutant cancers might be a therapeutic approach in anti-cancer therapies.

Modeling the energy metabolism in immune cells

In this review, we summarize and briefly discuss various approaches to modeling the metabolism in human immune cells, with a focus on energy metabolism. These approaches include metabolic reconstruction, elementary modes, and flux balance analysis, which are often subsumed under constraint-based modeling. Further approaches are evolutionary game theory and kinetic modeling. Many immune cells such as macrophages show the Warburg effect, meaning that glycolysis is upregulated upon activation. We outline a minimal model for explaining that effect using optimization. The effect of a confrontation with pathogen cells on immunometabolism is highlighted. Models describing the differences between M1 and M2 macrophages, ROS production in neutrophils, and tryptophan metabolism are discussed. Obstacles and future prospects are outlined.

Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy

Pseudomonas aeruginosa is a globally-distributed bacterium often found in medical infections. The opportunistic pathogen uses a different, carbon catabolite repression (CCR) strategy than many, model microorganisms. It does not utilize a classic diauxie phenotype, nor does it follow common systems biology assumptions including preferential consumption of glucose with an 'overflow' metabolism. Despite these contradictions, P. aeruginosa is competitive in many, disparate environments underscoring knowledge gaps in microbial ecology and systems biology. Physiological, omics, and in silico analyses were used to quantify the P. aeruginosa CCR strategy known as 'reverse diauxie'. An ecological basis of reverse diauxie was identified using a genome-scale, metabolic model interrogated with in vitro omics data. Reverse diauxie preference for lower energy, nonfermentable carbon sources, such as acetate or succinate over glucose, was predicted using a multidimensional strategy which minimized resource investment into central metabolism while completely oxidizing substrates. Application of a common, in silico optimization criterion, which maximizes growth rate, did not predict the reverse diauxie phenotypes. This study quantifies P. aeruginosa metabolic strategies foundational to its wide distribution and virulence including its potentially, mutualistic interactions with microorganisms found commonly in the environment and in medical infections.

Anti-Warburg Effect of Melatonin: A Proposed Mechanism to Explain its Inhibition of Multiple Diseases

Glucose is an essential nutrient for every cell but its metabolic fate depends on cellular phenotype. Normally, the product of cytosolic glycolysis, pyruvate, is transported into mitochondria and irreversibly converted to acetyl coenzyme A by pyruvate dehydrogenase complex (PDC). In some pathological cells, however, pyruvate transport into the mitochondria is blocked due to the inhibition of PDC by pyruvate dehydrogenase kinase. This altered metabolism is referred to as aerobic glycolysis (Warburg effect) and is common in solid tumors and in other pathological cells. Switching from mitochondrial oxidative phosphorylation to aerobic glycolysis provides diseased cells with advantages because of the rapid production of ATP and the activation of pentose phosphate pathway (PPP) which provides nucleotides required for elevated cellular metabolism. Molecules, called glycolytics, inhibit aerobic glycolysis and convert cells to a healthier phenotype. Glycolytics often function by inhibiting hypoxia-inducible factor-1α leading to PDC disinhibition allowing for intramitochondrial conversion of pyruvate into acetyl coenzyme A. Melatonin is a glycolytic which converts diseased cells to the healthier phenotype. Herein we propose that melatonin's function as a glycolytic explains its actions in inhibiting a variety of diseases. Thus, the common denominator is melatonin's action in switching the metabolic phenotype of cells.

Mitochondria: The Retina's Achilles' Heel in AMD

Strong experimental evidence from studies in human donor retinas and animal models supports the idea that the retinal pathology associated with age-related macular degeneration (AMD) involves mitochondrial dysfunction and consequent altered retinal metabolism. This chapter provides a brief overview of mitochondrial structure and function, summarizes evidence for mitochondrial defects in AMD, and highlights the potential ramifications of these defects on retinal health and function. Discussion of mitochondrial haplogroups and their association with AMD brings to light how mitochondrial genetics can influence disease outcome. As one of the most metabolically active tissues in the human body, there is strong evidence that disruption in key metabolic pathways contributes to AMD pathology. The section on retinal metabolism reviews cell-specific metabolic differences and how the metabolic interdependence of each retinal cell type creates a unique ecosystem that is disrupted in the diseased retina. The final discussion includes strategies for therapeutic interventions that target key mitochondrial pathways as a treatment for AMD.

Microglial metabolic disturbances and neuroinflammation in cerebral infarction

Cerebral ischemia/reperfusion injury activates microglia, resident immune cells in the brain, and allows the infiltration of circulating immune cells into the ischemic lesions. Microglia play both exacerbating and protective roles in pathological processes and are thus often referred to as "double-edged swords." In ischemic brains, blood-borne macrophages play a role that is distinct from that of resident activated microglia. Recently, the metabolic alteration of immune cells in the pathogenesis of inflammatory disorders including cerebral infarction has become a critical target for investigation. We begin this review by describing the multifaceted functions of microglia in cerebral infarction. Next, we focus on the metabolic alterations that occur in microglia during pathological processes. We also discuss morphological changes that take place in the mitochondria, leading to functional disturbances, accompanied by alterations in microglial function. Moreover, we describe the involvement of the reactive oxygen species that are produced during aberrant metabolic activity. Finally, we discuss therapeutic strategies to ameliorate aggravative changes in metabolism.

Biodegradable pH-responsive micelles loaded with 8-hydroxyquinoline glycoconjugates for Warburg effect based tumor targeting

Biodegradable triblock copolymer poly(ethylene glycol)-b-polycarbonate-b-oligo([R]-3-hydroxybutyrate) was prepared via metal-free ring-opening polymerization of ketal protected six-membered cyclic carbonate followed by esterification with bacterial oligo([R]-3-hydroxybutyrate) (oPHB). Amphiphilic triblock copolymer self-organizes into micelles with a diameter of ~25 nm. Acid-triggered hydrolysis of ketal groups to two hydroxyl groups causes an increase in hydrophilicity of the hydrophobic micelle core, resulting in the micelles swell and drug release. oPHB was added as core-forming block to increase the stability of prepared micelles in all pH (7.4, 6.4, 5.5) studied. Doxorubicin and 8-hydroxyquinoline glucose- and galactose conjugates were loaded in the micelles. In vitro drug release profiles in PBS buffers with different pH showed that a small amount of loaded drug was released in PBS at pH 7.4, while the drug was released much faster at pH 5.5. MTT assay showed that the blank micelles were non-toxic to different cell lines, while glycoconjugates-loaded micelles, showed significantly increased ability to inhibit the proliferation of MCF-7 and HCT-116 cells compared to free glycoconjugates. The glycoconjugation of anti-cancer drugs and pH-responsive nanocarriers have separately shown great potential to increase the tumor-targeted drug delivery efficiency. The combination of drug glycoconjugation and the use of pH-responsive nanocarrier opens up new possibilities to develop novel strategies for efficient tumor therapy.

Linkage between Carbon Metabolism, Redox Status and Cellular Physiology in the Yeast Saccharomyces cerevisiae Devoid of SOD1 or SOD2 Gene

Saccharomyces cerevisiae yeast cells may generate energy both by fermentation and aerobic respiration, which are dependent on the type and availability of carbon sources. Cells adapt to changes in nutrient availability, which entails the specific costs and benefits of different types of metabolism but also may cause alteration in redox homeostasis, both by changes in reactive oxygen species (ROS) and in cellular reductant molecules contents. In this study, yeast cells devoid of the SOD1 or SOD2 gene and fermentative or respiratory conditions were used to unravel the connection between the type of metabolism and redox status of cells and also how this affects selected parameters of cellular physiology. The performed analysis provides an argument that the source of ROS depends on the type of metabolism and non-mitochondrial sources are an important pool of ROS in yeast cells, especially under fermentative metabolism. There is a strict interconnection between carbon metabolism and redox status, which in turn has an influence on the physiological efficiency of the cells. Furthermore, pyridine nucleotide cofactors play an important role in these relationships.

Metabolic cell communication within tumour microenvironment: models, methods and perspectives

Environmental cues are essential in defining tumour malignancy, by promoting tumour initiation, progression and metastatic spreading. Stromal cells may metabolically cooperate or compete with cancer cells, playing a mandatory role in defining cancer metabolic plasticity, potentially dictating the final tumour outcome. Assessing shared nutrients between different tumoural or stromal compartments is essential to understand the impact of environmental nutrients on the metabolic plasticity of tumours. Here, we review analytical and computational approaches for studying the tumour metabolic microenvironment, the destiny of nutrients shared among tumour and stromal populations, as well as the molecular modules of these metabolic relationships.

The Warburg Effect, Lactate, and Nearly a Century of Trying to Cure Cancer

Nearly 100 years ago, Otto Warburg undertook a study of tumor metabolism, and discovered increased lactate caused by increased glycolysis in cancer cells. His experiments were conducted in the presence of excess oxygen, but today tumor tissue is known to be a hypoxic environment. However, an increase of glycolysis and lactate production is still a valid observation. Numerous abnormalities and mutations of metabolic enzymes have been found in many cancers. For example, pyruvate kinase M2 has been associated with many cancers and is a major contributor to directing glycolysis into fermentation, forming lactate. Increases in several enzymes, including glucose 6-phosphate dehydrogenase, pyruvate kinase M2, Rad6, or deficiency of other enzymes such as succinate dehydrogenase, all may contribute directly or indirectly to increases in lactate associated with the Warburg effect. In addition, the increased lactate and acid-base changes are modified further by monocarboxylate transporters and carbonic anhydrase, which contribute to alkalinizing tumor cells while acidifying the tumor extracellular environment. This acidification leads to cancer spread. Fully understanding the mechanisms underlying the Warburg effect should provide new approaches to cancer treatment.

Metabolic Reprograming of Microglia in the Regulation of the Innate Inflammatory Response

Microglia sustain normal brain functions continuously monitoring cerebral parenchyma to detect neuronal activities and alteration of homeostatic processes. The metabolic pathways involved in microglia activity adapt at and contribute to cell phenotypes. While the mitochondrial oxidative phosphorylation is highly efficient in ATP production, glycolysis enables microglia with a faster rate of ATP production, with the generation of intermediates for cell growth and cytokine production. In macrophages, pro-inflammatory stimuli induce a metabolic switch from oxidative phosphorylation to glycolysis, a phenomenon similar to the Warburg effect well characterized in tumor cells. Modification of metabolic functions allows macrophages to properly respond to a changing environment and many evidence suggest that, similarly to macrophages, microglial cells are capable of a plastic use of energy substrates. Neuroinflammation is a common condition in many neurodegenerative diseases and the metabolic reprograming of microglia has been reported in neurodegeneration. Here we review the existing data on microglia metabolism and the connections with neuroinflammatory diseases, highlighting how metabolic changes contribute to module the homeostatic functions of microglia.

Clinical features of aflatoxin B1-exposed patients with liver cancer and the molecular mechanism of aflatoxin B1 on liver cancer cells

Aflatoxin B1 (AFB1) induces hepatocellular carcinoma (HCC) through consumption of contaminated food in Southern China. Aldo-keto reductase-7A (AKR7A) functionally plays a potent role in the biodetoxification in the liver. In addition, hepatocellular lipid disorder has found to be closely linked to the development of HCC. This study was, therefore, designed to investigate the potent bioeffect of AKR7A on the lipid metabolism in AFB1-exposed hepatocellular carcinoma cells through assaying human cancerous samples and cell culture. In the baseline data, the HCC patients showed increased contents of AFB1 in sera and cancerous samples. In the clinical parameters, the HCC patients demonstrated changed lipid settings in sera. As revealed by immunostaining and immunoblotting, AFB1-elevated HCC sections showed marked down-regulation of AKR7A expression, accompanied with reduced ApoB expression and increased CD36, S6K1 expressions in the HCC. Studies in the human hepatocarcinoma line HepG2 also showed AFB1-exposure to increase ApoA1, LDL, TC, and TG contents; induce cell proliferation; and reduce hepatocellular AKR7A expression. Furthermore, AKR7A bioactivity was inactivated after treatment with perfluorooctane sulfonate (PFOS), an ApoB activator, in AFB1-dosed HepG2 cells. Collectively, our current findings suggest that hepatocellular AKR7A has a protective role against AFB1-induced cytotoxicity through the regulation of CD36, S6K1 and ApoB expression through the reduction of lipid utilization in malignant liver cells.

Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast

Computational predictions of double gene knockout effects by flux balance analysis (FBA) have been used to characterized genome-wide patterns of epistasis in microorganisms. However, it is unclear how in silico predictions are related to in vivo epistasis, as FBA predicted only a minority of experimentally observed genetic interactions between non-essential metabolic genes in yeast. Here, we perform a detailed comparison of yeast experimental epistasis data to predictions generated with different constraint-based metabolic modeling algorithms. The tested methods comprise standard FBA; a variant of MOMA, which was specifically designed to predict fitness effects of non-essential gene knockouts; and two alternative implementations of FBA with macro-molecular crowding, which account approximately for enzyme kinetics. The number of interactions uniquely predicted by one method is typically larger than its overlap with any alternative method. Only 20% of negative and 10% of positive interactions jointly predicted by all methods are confirmed by the experimental data; almost all unique predictions appear to be false. More than two thirds of epistatic interactions are undetectable by any of the tested methods. The low prediction accuracies indicate that the physiology of yeast double metabolic gene knockouts is dominated by processes not captured by current constraint-based analysis methods.

A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth

Living cells react to changes in growth conditions by re-shaping their proteome. This accounts for different stress-response strategies, both specific (i.e., aimed at increasing the availability of stress-mitigating proteins) and systemic (such as large-scale changes in the use of metabolic pathways aimed at a more efficient exploitation of resources). Proteome re-allocation can, however, imply significant biosynthetic costs. Whether and how such costs impact the growth performance are largely open problems. Focusing on carbon-limited E. coli growth, we integrate genome-scale modeling and proteomic data to address these questions at quantitative level. After deriving a simple formula linking growth rate, carbon intake, and biosynthetic costs, we show that optimal growth results from the tradeoff between yield maximization and protein burden minimization. Empirical data confirm that E. coli growth is indeed close to Pareto-optimal over a broad range of growth rates. Moreover, we establish that, while most of the intaken carbon is diverted into biomass precursors, the efficiency of ATP synthesis is the key driver of the yield-cost tradeoff. These findings provide a quantitative perspective on carbon overflow, the origin of growth laws and the multidimensional optimality of E. coli metabolism.

Less is more or more is less: Implications of glucose metabolism in the regulation of the reproductive potential and total lifespan of the Saccharomyces cerevisiae yeast

Carbohydrates are dietary nutrients that have an influence on cells physiology, cell reproductive capacity and, consequently, the lifespan of organisms. They are used in cellular processes after conversion to glucose, which is the primary source of energy and carbon skeleton for biosynthetic processes. Studies of the influence of glucose on cellular parameters and lifespan of organisms are primarily concerned with the effect of low glucose concentration defined as calorie restriction conditions. However, the effect of high glucose concentration on cell physiology is also very important. Thus, a comparative analysis of the effects of low and high glucose concentration conditions on cell efficiency was proposed with regard to reproductive capacity and total lifespan of the cell. Glucose concentration determines the type of metabolism and biosynthetic capabilities, which in turn, through the regulation on the cell size, may affect the reproductive capacity of cells. This study was conducted on yeast cells of wild-type and mutant strains Δgpa2 and Δgpr1 with glucose signalling pathway impairment. Such an experimental model enabled testing both the role of glucose concentration in the regulation of metabolic changes and the extent to which these changes depend on the extracellular or intracellular glucose concentrations. It has been shown here that calorie/glucose excess connected with changes in cell metabolic fluxes increases biosynthetic capabilities of yeast cells. This leads to an increase in cell dry weight accompanied by the increase in cell size and a simultaneous decrease in the reproductive potential and the overall length of cell life.

Lipopolysaccharide-induced alteration of mitochondrial morphology induces a metabolic shift in microglia modulating the inflammatory response in vitro and in vivo

Accumulating evidence suggests that changes in the metabolic signature of microglia underlie their response to inflammation. We sought to increase our knowledge of how pro-inflammatory stimuli induce metabolic changes. Primary microglia exposed to lipopolysaccharide (LPS)-expressed excessive fission leading to more fragmented mitochondria than tubular mitochondria. LPS-mediated Toll-like receptor 4 (TLR4) activation also resulted in metabolic reprogramming from oxidative phosphorylation to glycolysis. Blockade of mitochondrial fission by Mdivi-1, a putative mitochondrial division inhibitor led to the reversal of the metabolic shift. Mdivi-1 treatment also normalized the changes caused by LPS exposure, namely an increase in mitochondrial reactive oxygen species production and mitochondrial membrane potential as well as accumulation of key metabolic intermediate of TCA cycle succinate. Moreover, Mdivi-1 treatment substantially reduced LPS induced cytokine and chemokine production. Finally, we showed that Mdivi-1 treatment attenuated expression of genes related to cytotoxic, repair, and immunomodulatory microglia phenotypes in an in vivo neuroinflammation paradigm. Collectively, our data show that the activation of microglia to a classically pro-inflammatory state is associated with a switch to glycolysis that is mediated by mitochondrial fission, a process which may be a pharmacological target for immunomodulation.

Modelling overflow metabolism in Escherichia coli with flux balance analysis incorporating differential proteomic efficiencies of energy pathways

Background

The formation of acetate by fast-growing Escherichia coli (E. coli) is a commonly observed phenomenon, often referred to as overflow metabolism. Among various studies that have been carried over decades, a recent work (Basan, M. et al. Nature528, 99–104, 2015) suggested and validated that it is the differential proteomic efficiencies in energy biogenesis between fermentation and respiration that lead to the production of acetate at rapid growth conditions, as the consequence of optimally allocating the limited proteomic resource. In the current work, we attempt to incorporate this newly developed proteome allocation theory into flux balance analysis (FBA) to capture quantitatively the extent of overflow metabolism in different E. coli strains.

Results

A concise constraint was introduced into a FBA-based model with three proteomic cost parameters to represent constrained allocation of proteome over two energy (respiration and fermentation) pathways and biomass synthesis. Linear relationships were shown to exist between the three proteomic cost parameters. Tests with three different strains revealed that the proteomic cost of fermentation was consistently lower than that of respiration. A slow-growing strain appeared to have a higher proteomic cost for biomass synthesis than fast-growing strains. Different assumed levels of carbon flowing into pentose phosphate pathway affected the absolute value of model parameters, but had no qualitative impact on the comparative proteomic costs. For the prediction of biomass yield, significant errors that occurred for one of the tested strains (ML308) were rectified by adjusting the cellular energy demand according to literature data.

Conclusions

With the aid of a concise proteome allocation constraint, our FBA-based model is able to quantitatively predict the onset and extent of the overflow metabolism in various E. coli strains. Such prediction is enabled by three linearly-correlated (as opposed to uniquely determinable) proteomic cost parameters. The linear relationships between these parameters, when determined using data from cell culturing experiments, render biologically meaningful comparative proteomic costs between fermentation and respiration pathways and between the biomass synthesis sectors of slow- and fast-growing species. Simultaneous prediction of acetate production and biomass yield in the overflow region requires the use of reliable cellular energy demand data.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0677-4) contains supplementary material, which is available to authorized users.

Mathematical Modeling of the Function of Warburg Effect in Tumor Microenvironment

Tumor cells are known for their increased glucose uptake rates even in the presence of abundant oxygen. This altered metabolic shift towards aerobic glycolysis is known as the Warburg effect. Despite an enormous number of studies conducted on the causes and consequences of this phenomenon, little is known about how the Warburg effect affects tumor growth and progression. We developed a multi-scale computational model to explore the detailed effects of glucose metabolism of cancer cells on tumorigenesis behavior in a tumor microenvironment. Despite glycolytic tumors, the growth of non-glycolytic tumor is dependent on a congruous morphology without markedly interfering with glucose and acid concentrations of the tumor microenvironment. Upregulated glucose metabolism helped to retain oxygen levels above the hypoxic limit during early tumor growth, and thus obviated the need for neo-vasculature recruitment. Importantly, simulating growth of tumors within a range of glucose uptake rates showed that there exists a spectrum of glucose uptake rates within which the tumor is most aggressive, i.e. it can exert maximal acidic stress on its microenvironment and most efficiently compete for glucose supplies. Moreover, within the same spectrum, the tumor could grow to invasive morphologies while its size did not markedly shrink.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering

BACKGROUND

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing.

RESULTS

We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli.

CONCLUSIONS

We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements.

Competitive resource allocation to metabolic pathways contributes to overflow metabolisms and emergent properties in cross-feeding microbial consortia

Resource scarcity is a common stress in nature and has a major impact on microbial physiology. This review highlights microbial acclimations to resource scarcity, focusing on resource investment strategies for chemoheterotrophs from the molecular level to the pathway level. Competitive resource allocation strategies often lead to a phenotype known as overflow metabolism; the resulting overflow byproducts can stabilize cooperative interactions in microbial communities and can lead to cross-feeding consortia. These consortia can exhibit emergent properties such as enhanced resource usage and biomass productivity. The literature distilled here draws parallels between in silico and laboratory studies and ties them together with ecological theories to better understand microbial stress responses and mutualistic consortia functioning.

Metabo-Devo: A metabolic perspective of development

In the last years, several reports have established the notion that metabolism is not just a housekeeping process, but instead an active effector of physiological changes. The idea that the metabolic status may rule a wide range of phenomena in cell biology is starting to be broadly accepted. Thus, current developmental biology has begun to describe different ways by which the metabolic profile of the cell and developmental programs of the organism can crosstalk. In this review, we discuss mechanisms by which metabolism impacts on processes governing development. We review the growing body of evidence that supports the notion that aerobic glycolysis is required in cells undergoing fast growth and high proliferation, similarly to the Warburg effect described in tumor cells. Glycolytic metabolism explains not only the higher ATP synthesis rate required for cell growth, but also the uncoupling between mitochondrial activity and bioenergetics needed to provide anabolism with sufficient precursors. We also discuss some recent studies, which show that in addition to its role in providing energy and carbon chains, the metabolic status of the cell can also influence epigenetic regulation of developmental processes. Although metabolic aspects of development are just starting to be explored, there is no doubt that ongoing research in this field will shape the future landscape of Developmental Biology.

Linear programming model can explain respiration of fermentation products

Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary ¹³C-metabolic flux analysis (INST ¹³C-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

Resource allocation in living organisms

Quantitative prediction of resource allocation for living systems has been an intensive area of research in the field of biology. Resource allocation was initially investigated in higher organisms by using empirical mathematical models based on mass distribution. A challenge is now to go a step further by reconciling the cellular scale to the individual scale. In the present paper, we review the foundations of modelling of resource allocation, particularly at the cellular scale: from small macro-molecular models to genome-scale cellular models. We enlighten how the combination of omic measurements and computational advances together with systems biology has contributed to dramatic progresses in the current understanding and prediction of cellular resource allocation. Accurate genome-wide predictive methods of resource allocation based on the resource balance analysis (RBA) framework have been developed and ensure a good trade-off between the complexity/tractability and the prediction capability of the model. The RBA framework shows promise for a wide range of applications in metabolic engineering and synthetic biology, and for pursuing investigations of the design principles of cellular and multi-cellular organisms.

MicroRNA-33b inhibits cell proliferation and glycolysis by targeting hypoxia-inducible factor-1α in malignant melanoma

Malignant melanoma (MM) is the most aggressive type of skin cancer. MicroRNA (miR) has been implicated in the development and progression of MM; however, their underlying mechanism of action remains largely unknown. The present study aimed to investigate the role of miR-33b in MM. Reverse transcription-quantitative polymerase chain reaction data indicated that the expression of miR-33b was significantly reduced (P<0.01) in MM cell lines, including WM35, WM451 and SK-MEL-1, when compared with human melanocyte cells. Subsequently, WM451 and SK-MEL-1 cells were transfected with an miR-33b mimic or inhibitor. MTT assay data demonstrated that the viability of MM cells markedly decreased following miR-33b overexpression; however, viability was markedly upregulated following miR-33b knockdown. Additionally, the glycolysis level was examined. Results demonstrated that glucose consumption and lactic acid production were significantly downregulated (P<0.01) after miR-33b upregulation, whereas these levels significantly increased in MM cells transfected with miR-33b inhibitor (P<0.01), suggesting that miR-33b negatively mediates the glycolysis level in MM cells. Bioinformatics indicated that hypoxia-inducible factor (HIF)-1α was a putative target gene of miR-33b, and this was confirmed by a luciferase reporter assay, which demonstrated that miR-33b was able to directly bind to the 3′ untranslated region of HIF-1α mRNA. Furthermore, the expression of HIF-1α was negatively regulated by miR-33b at the post-transcriptional level in MM cells. Overexpression of HIF-1α reversed the inhibitory effect of miR-33b on the proliferation and glycolysis in MM cells. Finally, the results of the present study demonstrated that hexokinase 2 and lactate dehydrogenase-A may be involved in miR-33b/HIF-1α mediated glycolysis in MM cells. In conclusion, these results suggest that miR-33b inhibits cell proliferation and glycolysis by targeting HIF-1α in MM.

Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient reservoir (the blood), aimed at characterizing the role of the microenvironment for aberrant growth. Accounting for cellular metabolic activity, competition for nutrients, spatial diffusion and their feedbacks on aberrant replication and death rates, we obtain a phase portrait where distinct asymptotic whole-tissue states are found upon varying the tissue-blood turnover rate and the level of blood-borne primary nutrient. Over a broad range of parameters, the spreading dynamics is bistable as random fluctuations can impact the final state of the tissue. Such a behaviour turns out to be linked to the re-cycling of overflow products by non-aberrant cells. Quantitative insight on the overall emerging picture is provided by a spatially homogeneous version of the model.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.

Immunometabolism in early and late stages of rheumatoid arthritis

One of the fundamental traits of immune cells in rheumatoid arthritis (RA) is their ability to proliferate, a property shared with the joint-resident cells that form the synovial pannus. The building of biomass imposes high demands for energy and biosynthetic precursors, implicating metabolic control as a basic disease mechanism. During preclinical RA, when autoreactive T cells expand and immunological tolerance is broken, the main sites of disease are the secondary lymphoid tissues. Naive CD4⁺ T cells from patients with RA have a distinct metabolic signature, characterized by dampened glycolysis, low ATP levels and enhanced shunting of glucose into the pentose phosphate pathway. Equipped with high levels of NADPH and depleted of intracellular reactive oxygen species, such T cells hyperproliferate and acquire proinflammatory effector functions. During clinical RA, immune cells coexist with stromal cells in the acidic milieu of the inflamed joint. This microenvironment is rich in metabolic intermediates that are released into the extracellular space to shape cell-cell communication and the functional activity of tissue-resident cells. Increasing awareness of how metabolites regulate signalling pathways, guide post-translational modifications and condition the tissue microenvironment will help to connect environmental factors with the pathogenic behaviour of T cells in RA.

The importance of controlling mRNA turnover during cell proliferation

Microbial gene expression depends not only on specific regulatory mechanisms, but also on cellular growth because important global parameters, such as abundance of mRNAs and ribosomes, could be growth rate dependent. Understanding these global effects is necessary to quantitatively judge gene regulation. In the last few years, transcriptomic works in budding yeast have shown that a large fraction of its genes is coordinately regulated with growth rate. As mRNA levels depend simultaneously on synthesis and degradation rates, those studies were unable to discriminate the respective roles of both arms of the equilibrium process. We recently analyzed 80 different genomic experiments and found a positive and parallel correlation between both RNA polymerase II transcription and mRNA degradation with growth rates. Thus, the total mRNA concentration remains roughly constant. Some gene groups, however, regulate their mRNA concentration by uncoupling mRNA stability from the transcription rate. Ribosome-related genes modulate their transcription rates to increase mRNA levels under fast growth. In contrast, mitochondria-related and stress-induced genes lower mRNA levels by reducing mRNA stability or the transcription rate, respectively. We critically review here these results and analyze them in relation to their possible extrapolation to other organisms and in relation to the new questions they open.