ACSM1 and ACSM3 regulate fatty acid metabolism to support prostate cancer growth and constrain ferroptosis

Solid tumors are highly reliant on lipids for energy, growth, and survival. In prostate cancer, the activity of the androgen receptor (AR) is associated with reprogramming of lipid metabolic processes. Here, we identified acyl-CoA synthetase medium chain family members 1 and 3 (ACSM1 and ACSM3) as AR-regulated mediators of prostate cancer metabolism and growth. ACSM1 and ACSM3 were upregulated in prostate tumors compared to non-malignant tissues and other cancer types. Both enzymes enhanced proliferation and protected prostate cancer cells from death in vitro, while silencing ACSM3 led to reduced tumor growth in an orthotopic xenograft model. ACSM1 and ACSM3 were major regulators of the prostate cancer lipidome and enhanced energy production via fatty acid oxidation. Metabolic dysregulation caused by loss of ACSM1/3 led to mitochondrial oxidative stress, lipid peroxidation and cell death by ferroptosis. Conversely, elevated ACSM1/3 activity enabled prostate cancer cells to survive toxic levels of medium chain fatty acids and promoted resistance to ferroptosis-inducing drugs and AR antagonists. Collectively, this study reveals a tumor-promoting function for medium chain acyl-CoA synthetases and positions ACSM1 and ACSM3 as key players in prostate cancer progression and therapy resistance.

Tumor Biomechanics Alters Metastatic Dissemination of Triple Negative Breast Cancer via Rewiring Fatty Acid Metabolism

In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

Peroxisomal β-oxidation enzyme, DECR2, regulates lipid metabolism and promotes treatment resistance in advanced prostate cancer

BACKGROUND

Peroxisomes are central metabolic organelles that have key roles in fatty acid homoeostasis. As prostate cancer (PCa) is particularly reliant on fatty acid metabolism, we explored the contribution of peroxisomal β-oxidation (perFAO) to PCa viability and therapy response.

METHODS

Bioinformatic analysis was performed on clinical transcriptomic datasets to identify the perFAO enzyme, 2,4-dienoyl CoA reductase 2 (DECR2) as a target gene of interest. Impact of DECR2 and perFAO inhibition via thioridazine was examined in vitro, in vivo, and in clinical prostate tumours cultured ex vivo. Transcriptomic and lipidomic profiling was used to determine the functional consequences of DECR2 inhibition in PCa.

RESULTS

DECR2 is upregulated in clinical PCa, most notably in metastatic castrate-resistant PCa (CRPC). Depletion of DECR2 significantly suppressed proliferation, migration, and 3D growth of a range of CRPC and therapy-resistant PCa cell lines, and inhibited LNCaP tumour growth and proliferation in vivo. DECR2 influences cell cycle progression and lipid metabolism to support tumour cell proliferation. Further, co-targeting of perFAO and standard-of-care androgen receptor inhibition enhanced suppression of PCa cell proliferation.

CONCLUSION

Our findings support a focus on perFAO, specifically DECR2, as a promising therapeutic target for CRPC and as a novel strategy to overcome lethal treatment resistance.

Fatty acid elongation regulates mitochondrial β-oxidation and cell viability in prostate cancer by controlling malonyl-CoA levels

Recently, the fatty acid elongation enzyme ELOVL5 was identified as a critical pro-metastatic factor in prostate cancer, required for cell growth and mitochondrial homeostasis. The fatty acid elongation reaction catalyzed by ELOVL5 utilizes malonyl-CoA as the carbon donor. Here, we demonstrate that ELOVL5 knockdown causes malonyl-CoA accumulation. Malonyl-CoA is a cellular substrate that can inhibit fatty acid β-oxidation in the mitochondria through allosteric inhibition of carnitine palmitoyltransferase 1A (CPT1A), the enzyme that controls the rate-limiting step of the long chain fatty acid β-oxidation cycle. We hypothesized that changes in malonyl-CoA abundance following ELOVL5 knockdown could influence mitochondrial β-oxidation rates in prostate cancer cells, and regulate cell viability. Accordingly, we find that ELOVL5 knockdown is associated with decreased mitochondrial β-oxidation in prostate cancer cells. Combining ELOVL5 knockdown with FASN inhibition to increase malonyl-CoA abundance endogenously enhances the effect of ELOVL5 knockdown on prostate cancer cell viability, while preventing malonyl-CoA production rescues the cells from the effect of ELOVL5 knockdown. Our findings indicate an additional role for fatty acid elongation, in the control of malonyl-CoA homeostasis, alongside its established role in the production of long-chain fatty acid species, to explain the importance of fatty acid elongation for cell viability.

Host-microbiome interactions in nicotinamide mononucleotide (NMN) deamidation

The nicotinamide adenine dinucleotide (NAD+ ) precursor nicotinamide mononucleotide (NMN) is a proposed therapy for age-related disease, whereby it is assumed that NMN is incorporated into NAD+ through the canonical recycling pathway. During oral delivery, NMN is exposed to the gut microbiome, which could modify the NAD+ metabolome through enzyme activities not present in the mammalian host. We show that orally delivered NMN can undergo deamidation and incorporation in mammalian tissue via the de novo pathway, which is reduced in animals treated with antibiotics to ablate the gut microbiome. Antibiotics increased the availability of NAD+ metabolites, suggesting the microbiome could be in competition with the host for dietary NAD+ precursors. These findings highlight new interactions between NMN and the gut microbiome.

Abstract 3687: Disruption of nucleotide homeostasis confers cancer cell susceptibility to oxidative phosphorylation inhibition independently of energy depletion

Cancer metabolism is highly heterogenous and flexible with the Warburg effect or oxidative phosphorylation (OXPHOS) prevailing in a cancer type- and context-dependent manner. Past studies have demonstrated that targeting OXPHOS robustly inhibits glycolysis-deficient cancer cell viability and tumorigenicity. However, the therapeutic potential of OXPHOS inhibition in metabolically flexible glycolysis-competent cancers is unclear. Furthermore, whether the depletion of OXPHOS-derived ATP or the abolition of OXPHOS-supported biosynthesis is the major determinant of cancer cell susceptibility remains obscure. To address these questions, we exposed a panel of metabolically flexible glycolysis-competent cancer cell lines to OXPHOS inhibitors and tested cell survival and proliferation. We monitored metabolic phenotypes and changes in metabolites using seahorse metabolic flux assays and targeted metabolomics, respectively. Stable isotope-tracing was carried out with uniformly labelled [15N]-/[13C]-aspartate. Patient-derived xenograft (PDX) models of colorectal cancer in NSG mice were used for in vivo validation. Here we provide evidence that OXPHOS inhibition potently diminishes metabolically flexible glycolysis-competent cancer cell proliferation and tumorigenicity without causing devastating energy stress. The inhibition of cell proliferation by OXPHOS inhibitors is associated with S-phase cell cycle arrest and the enrichment of the G2/M DNA-damage check point regulation pathway, suggestive of replication stress. Indeed, IACS treatment significantly reduces the purine/pyrimidine nucleotide pools, which is primarily caused by aspartate deficiency resulting from a shortage in the electron acceptor NAD+. The supplementation of exogenous nucleosides, aspartate, or pyruvate that can accept electron generating NAD+, into the culture medium rescues cells from IACS-induced cell cycle arrest. Instructively, inhibition of GOT1, which catalyzes cytosolic aspartate biosynthesis when mitochondrial aspartate production is dampened, renders cancer cells grown in two- and three-dimensional cultures more susceptible to OXPHOS inhibition. Collectively, these results indicate that 1) disruption of nucleotide homeostasis is a major determinant of cancer cell susceptibility to OXPHOS inhibition; 2) OXPHOS inhibition is a promising avenue for the treatment of cancers that are metabolic flexible and glycolysis competent; and 3) GOT1 targeting is potentially a useful approach to improve the therapeutic efficacy of OXPHOS inhibition for cancer treatment.

Citation Format: Xiaohong Zhao, Yuan Yuan Zhang, Liang Xu, Ting La, Yu Chen Feng, Hai Jie Tang, Ran Xu, Vinod K. Narayana, David P. De Souza, Lake-Ee Quek, Jeff Holst, Rick F. Thorne, Mark Baker, Tao Liu, Lei Jin, Xu Dong Zhang. Disruption of nucleotide homeostasis confers cancer cell susceptibility to oxidative phosphorylation inhibition independently of energy depletion. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3687.

Insulin sensitivity is preserved in mice made obese by feeding a high starch diet

Obesity is generally associated with insulin resistance in liver and muscle and increased risk of developing type 2 diabetes, however there is a population of obese people that remain insulin sensitive. Similarly, recent work suggests that mice fed high carbohydrate diets can become obese without apparent glucose intolerance. To investigate this phenomenon further, we fed mice either a high fat (Hi-F) or high starch (Hi-ST) diet and measured adiposity, glucose tolerance, insulin sensitivity and tissue lipids compared to control mice fed a standard laboratory chow. Both Hi-ST and Hi-F mice accumulated a similar amount of fat and tissue triglyceride compared to chow-fed mice. However while Hi-F diet mice developed glucose intolerance as well as liver and muscle insulin resistance (assessed via euglycemic/hyperinsulinemic clamp), obese Hi-ST mice maintained glucose tolerance and insulin action similar to lean, chow-fed controls. This preservation of insulin action despite obesity in Hi-ST mice was associated with differences in de novo lipogenesis and levels of C22:0 ceramide in liver and C18:0 ceramide in muscle. This indicates that dietary manipulation can influence insulin action independently of the level of adiposity and that the presence of specific ceramide species correlate with these differences.

Glutamine addiction promotes glucose oxidation in triple-negative breast cancer

Glutamine is a conditionally essential nutrient for many cancer cells, but it remains unclear how consuming glutamine in excess of growth requirements confers greater fitness to glutamine-addicted cancers. By contrasting two breast cancer subtypes with distinct glutamine dependencies, we show that glutamine-indispensable triple-negative breast cancer (TNBC) cells rely on a non-canonical glutamine-to-glutamate overflow, with glutamine carbon routed once through the TCA cycle. Importantly, this single-pass glutaminolysis increases TCA cycle fluxes and replenishes TCA cycle intermediates in TNBC cells, a process that achieves net oxidation of glucose but not glutamine. The coupling of glucose and glutamine catabolism appears hard-wired via a distinct TNBC gene expression profile biased to strip and then sequester glutamine nitrogen, but hampers the ability of TNBC cells to oxidise glucose when glutamine is limiting. Our results provide a new understanding of how metabolically rigid TNBC cells are sensitive to glutamine deprivation and a way to select vulnerable TNBC subtypes that may be responsive to metabolic-targeted therapies.

A feedback loop between the androgen receptor and 6-phosphogluoconate dehydrogenase (6PGD) drives prostate cancer growth

Alterations to the androgen receptor (AR) signalling axis and cellular metabolism are hallmarks of prostate cancer. This study provides insight into both hallmarks by uncovering a novel link between AR and the pentose phosphate pathway (PPP). Specifically, we identify 6-phosphogluoconate dehydrogenase (6PGD) as an androgen-regulated gene that is upregulated in prostate cancer. AR increased the expression of 6PGD indirectly via activation of sterol regulatory element binding protein 1 (SREBP1). Accordingly, loss of 6PGD, AR or SREBP1 resulted in suppression of PPP activity as revealed by 1,2-¹³C₂ glucose metabolic flux analysis. Knockdown of 6PGD also impaired growth and elicited death of prostate cancer cells, at least in part due to increased oxidative stress. We investigated the therapeutic potential of targeting 6PGD using two specific inhibitors, physcion and S3, and observed substantial anti-cancer activity in multiple models of prostate cancer, including aggressive, therapy-resistant models of castration-resistant disease as well as prospectively collected patient-derived tumour explants. Targeting of 6PGD was associated with two important tumour-suppressive mechanisms: first, increased activity of the AMP-activated protein kinase (AMPK), which repressed anabolic growth-promoting pathways regulated by acetyl-CoA carboxylase 1 (ACC1) and mammalian target of rapamycin complex 1 (mTORC1); and second, enhanced AR ubiquitylation, associated with a reduction in AR protein levels and activity. Supporting the biological relevance of positive feedback between AR and 6PGD, pharmacological co-targeting of both factors was more effective in suppressing the growth of prostate cancer cells than single-agent therapies. Collectively, this work provides new insight into the dysregulated metabolism of prostate cancer and provides impetus for further investigation of co-targeting AR and the PPP as a novel therapeutic strategy.

Exercise-induced benefits on glucose handling in a model of diet-induced obesity are reduced by concurrent nicotinamide mononucleotide

Almost 40% of adults worldwide are classified as overweight or obese. Exercise is a beneficial intervention in obesity, partly due to increases in mitochondrial activity and subsequent increases in nicotinamide adenine dinucleotide (NAD⁺), an important metabolic cofactor. Recent studies have shown that increasing NAD⁺ levels through pharmacological supplementation with precursors such as nicotinamide mononucleotide (NMN) improved metabolic health in high-fat-diet (HFD)-fed mice. However, the effects of combined exercise and NMN supplementation are unknown. Thus, here we examined the combined effects of NMN and treadmill exercise in female mice with established obesity after 10 wk of diet. Five-week-old female C57BL/6J mice were exposed to a control diet (n = 16) or HFD. Mice fed a HFD were either untreated (HFD; n = 16), received NMN in drinking water (400 mg/kg; HNMN; n = 16), were exposed to treadmill exercise 6 days/wk (HEx; n = 16), or were exposed to exercise combined with NMN (HNEx; n = 16). Although some metabolic benefits of NMN have been described, at this dose, NMN administration impaired several aspects of exercise-induced benefits in obese mice, including glucose tolerance, glucose-stimulated insulin secretion from islets, and hepatic triglyceride accumulation. HNEx mice also exhibited increased antioxidant and reduced prooxidant gene expression in both islets and muscle, suggesting that altered redox status is associated with the loss of exercise-induced health benefits with NMN cotreatment. Our data show that NMN treatment impedes the beneficial metabolic effects of exercise in a mouse model of diet-induced obesity in association with disturbances in redox metabolism.NEW & NOTEWORTHY NMN dampened exercise-induced benefits on glucose handling in diet-induced obesity. NMN administration alongside treadmill exercise enhanced the ratio of antioxidants to prooxidants. We suggest that NMN administration may not be beneficial when NAD⁺ levels are replete.

Nicotinamide riboside supplementation does not alter whole-body or skeletal muscle metabolic responses to a single bout of endurance exercise

KEY POINTS

Acute nicotinamide riboside (NR) supplementation does not alter substrate metabolism at rest, during or in recovery from endurance exercise. NR does not alter NAD⁺ -sensitive signalling pathways in human skeletal muscle. NR supplementation and acute exercise influence the NAD⁺ metabolome.

ABSTRACT

Oral supplementation of the NAD⁺ precursor nicotinamide riboside (NR) has been reported to alter metabolism alongside increasing sirtuin (SIRT) signalling and mitochondrial biogenesis in rodent skeletal muscle. However, whether NR supplementation can elicit a similar response in human skeletal muscle is unclear. This study assessed the effect of 7-day NR supplementation on whole-body metabolism and exercise-induced mitochondrial biogenic signalling in skeletal muscle. Eight male participants (age: 23 ± 4 years, V ̇ O 2 peak 46.5 ± 4.4 ml kg^-1  min^-1 ) received 1 week of NR or cellulose placebo (PLA) supplementation (1000 mg day^-1 ). Muscle biopsies were collected from the medial vastus lateralis prior to supplementation and pre-, immediately post- and 3 h post-exercise (1 h of 60% W_max cycling) performed following the supplementation period. There was no effect of NR supplementation on substrate utilisation at rest or during exercise or on skeletal muscle mitochondrial respiration. Global acetylation, auto-PARylation of poly ADP-ribose polymerase 1 (PARP1), acetylation of Tumour protein 53 (p53)^Lys382 and Manganese superoxide dismutase (MnSOD)^Lys122 were also unaffected by NR supplementation or exercise. NR supplementation did not increase skeletal muscle NAD⁺ concentration, but it did increase the concentration of deaminated NAD⁺ precursors nicotinic acid riboside (NAR) and nicotinic acid mononucleotide (NAM) and methylated nicotinamide breakdown products (Me2PY and Me4PY), demonstrating the skeletal muscle bioavailability of NR supplementation. In summary, 1 week of NR supplementation does not alter whole-body metabolism or skeletal muscle signal transduction pathways implicated in the mitochondrial adaptation to endurance exercise.

Erratum: Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

[This corrects the article DOI: 10.1016/j.isci.2020.100855.].

Abstract PO-036: ACSM1 and ACSM3 regulate fatty acid oxidation in prostate cancer to promote growth and protect against oxidative stress

Prostate tumours are highly reliant on lipids for growth and survival. Emerging evidence suggests that the androgen receptor (AR) is a major regulator of lipid metabolism in prostate cancer (PCa), but the molecular mechanisms underlying such regulation are largely unknown. By integrating cistromic and transcriptomic data, we identified Acyl-CoA Synthetase Medium Chain Family Members 1 and 3 (ACSM1 and ACSM3) as putative new AR-regulated genes in prostate cancer. These factors are thought to function to activate fatty acids for their utilisation in energy production via mitochondrial beta-oxidation. AR regulation was validated by demonstrating modulation of ACSM1 and ACSM3 by androgen and anti-androgen treatment and confirming direct binding of AR to proximal cis-regulatory elements by chromatin immunoprecipitation (ChIP). ACSM1 and ACSM3 are upregulated in prostate tumours compared to non-malignant prostate tissues and are expressed more highly in prostate cancer than other cancer types. We subsequently applied metabolomics, lipidomics and functional assays to decipher the roles of ACSM1 and ACSM3 in prostate cancer cells. Knockdown of ACSM1 and ACSM3 in PCa cells resulted in growth arrest and ATP depletion, supporting a key role for both factors in energy production from fatty acids. Furthermore, lipidomic analysis of cells showed that poly-unsaturated fatty acids accumulate in response to loss of ACSM1 and ACSM3. Metabolomics revealed that cells adapt to loss of ACSM1 and ACSM3 by switching to a glycolytic phenotype. The metabolic dysregulation induced by knockdown of ACSM1 and ACSM3 caused mitochondrial oxidative stress and subsequent lipid peroxidation, eventually resulting in cell death. Accumulation of mitochondrial reactive oxygen species was abrogated by ferrostatin-1 (an iron chelator), suggesting that cell death was due to an iron-dependent form of apoptosis termed ferroptosis. Supporting this concept, over-expression of ACSM1 and ACSM3 elicited resistance to the ferroptosis inducers Erastin and ML210. Our study has revealed a novel mechanism by which AR regulates lipid metabolism in prostate cancer cells. Importantly, the critical role of ACSM1 and ACSM3 as key regulators of growth and protectors against ferroptosis emphasises their potential as novel therapeutic targets

Citation Format: Raj Kumar Shrestha, Scott Townley, Adrienne Hanson, Marie Pickering, Zeyad D. Nassar, Chui Yan Mah, Mohammadreza A. Ghodsi, Andrew J. Hoy, Lake-Ee Quek, Wayne D. Tilley, Lisa M. Butler, Luke A. Selth. ACSM1 and ACSM3 regulate fatty acid oxidation in prostate cancer to promote growth and protect against oxidative stress [abstract]. In: Abstracts: AACR Special Virtual Conference on Epigenetics and Metabolism; October 15-16, 2020; 2020 Oct 15-16. Philadelphia (PA): AACR; Cancer Res 2020;80(23 Suppl):Abstract nr PO-036.

Kinetic Trans-omic Analysis Reveals Key Regulatory Mechanisms for Insulin-Regulated Glucose Metabolism in Adipocytes

Insulin regulates glucose metabolism through thousands of regulatory mechanisms; however, which regulatory mechanisms are keys to control glucose metabolism remains unknown. Here, we performed kinetic trans-omic analysis by integrating isotope-tracing glucose flux and phosphoproteomic data from insulin-stimulated adipocytes and built a kinetic mathematical model to identify key allosteric regulatory and phosphorylation events for enzymes. We identified nine reactions regulated by allosteric effectors and one by enzyme phosphorylation and determined the regulatory mechanisms for three of these reactions. Insulin stimulated glycolysis by promoting Glut4 activity by enhancing phosphorylation of AS160 at S595, stimulated fatty acid synthesis by promoting Acly activity through allosteric activation by glucose 6-phosphate or fructose 6-phosphate, and stimulated glutamate synthesis by alleviating allosteric inhibition of Gls by glutamate. Most of glycolytic reactions were regulated by amounts of substrates and products. Thus, phosphorylation or allosteric modulator-based regulation of only a few key enzymes was sufficient to change insulin-induced metabolism.

Insulin signaling requires glucose to promote lipid anabolism in adipocytes

Adipose tissue is essential for metabolic homeostasis, balancing lipid storage and mobilization based on nutritional status. This is coordinated by insulin, which triggers kinase signaling cascades to modulate numerous metabolic proteins, leading to increased glucose uptake and anabolic processes like lipogenesis. Given recent evidence that glucose is dispensable for adipocyte respiration, we sought to test whether glucose is necessary for insulin-stimulated anabolism. Examining lipogenesis in cultured adipocytes, glucose was essential for insulin to stimulate the synthesis of fatty acids and glyceride-glycerol. Importantly, glucose was dispensable for lipogenesis in the absence of insulin, suggesting that distinct carbon sources are used with or without insulin. Metabolic tracing studies revealed that glucose was required for insulin to stimulate pathways providing carbon substrate, NADPH, and glycerol 3-phosphate for lipid synthesis and storage. Glucose also displaced leucine as a lipogenic substrate and was necessary to suppress fatty acid oxidation. Together, glucose provided substrates and metabolic control for insulin to promote lipogenesis in adipocytes. This contrasted with the suppression of lipolysis by insulin signaling, which occurred independently of glucose. Given previous observations that signal transduction acts primarily before glucose uptake in adipocytes, these data are consistent with a model whereby insulin initially utilizes protein phosphorylation to stimulate lipid anabolism, which is sustained by subsequent glucose metabolism. Consequently, lipid abundance was sensitive to glucose availability, both during adipogenesis and in Drosophila flies in vivo Together, these data highlight the importance of glucose metabolism to support insulin action, providing a complementary regulatory mechanism to signal transduction to stimulate adipose anabolism.

Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.

Lactate production is a prioritized feature of adipocyte metabolism

Adipose tissue is essential for whole-body glucose homeostasis, with a primary role in lipid storage. It has been previously observed that lactate production is also an important metabolic feature of adipocytes, but its relationship to adipose and whole-body glucose disposal remains unclear. Therefore, using a combination of metabolic labeling techniques, here we closely examined lactate production of cultured and primary mammalian adipocytes. Insulin treatment increased glucose uptake and conversion to lactate, with the latter responding more to insulin than did other metabolic fates of glucose. However, lactate production did not just serve as a mechanism to dispose of excess glucose, because we also observed that lactate production in adipocytes did not solely depend on glucose availability and even occurred independently of glucose metabolism. This suggests that lactate production is prioritized in adipocytes. Furthermore, knocking down lactate dehydrogenase specifically in the fat body of Drosophila flies lowered circulating lactate and improved whole-body glucose disposal. These results emphasize that lactate production is an additional metabolic role of adipose tissue beyond lipid storage and release.

Metabolites downstream of predicted loss-of-function variants inform relationship to disease

A small minority (< 3%) of protein-coding genetic variants are predicted to lead to loss of protein function. However, these predicted loss-of-function (pLOF) variants can provide insight into mode of transcriptional effect. To examine how these changes are propagated to phenotype, we determined associations with downstream metabolites. We performed association analyses of 37 pLOF variants - previously reported to be significantly associated with disease in >400,000 subjects in UK Biobank - with metabolites. We conducted these analyses in three community-based cohorts: the Framingham Heart Study (FHS) Offspring Cohort, FHS Generation 3, and the KORA F4 cohort. We identified 19 new low-frequency or rare (minor allele frequency (MAF) <5%) pLOF variant-metabolite associations, and 12 new common (MAF > 5%) pLOF variant-metabolite associations. Rare pLOF variants in the genes BTN3A2, ENPEP, and GEM that have been associated with blood pressure in UK Biobank, were associated with vasoactive metabolites indoxyl sulfate, asymmetric dimethylarginine (ADMA), and with niacinamide, respectively. A common pLOF variant in gene CCHCR1, associated with asthma in UK Biobank, was associated with histamine and niacinamide in FHS Generation 3, both reported to play a role in this disease. Common variants in olfactory receptor gene OX4C11 that associated with blood pressure in UK Biobank were associated with the nicotine metabolite cotinine, suggesting an interaction between altered olfaction, smoking behaviour, and blood pressure. These findings provide biological validity for pLOF variant-disease associations, and point to the effector roles of common metabolites. Such an approach may provide novel disease markers and therapeutic targets.

Phenotypic screen for oxygen consumption rate identifies an anti-cancer naphthoquinone that induces mitochondrial oxidative stress

A hallmark of cancer cells is their ability to reprogram nutrient metabolism. Thus, disruption to this phenotype is a potential avenue for anti-cancer therapy. Herein we used a phenotypic chemical library screening approach to identify molecules that disrupted nutrient metabolism (by increasing cellular oxygen consumption rate) and were toxic to cancer cells. From this screen we discovered a 1,4-Naphthoquinone (referred to as BH10) that is toxic to a broad range of cancer cell types. BH10 has improved cancer-selective toxicity compared to doxorubicin, 17-AAG, vitamin K3, and other known anti-cancer quinones. BH10 increases glucose oxidation via both mitochondrial and pentose phosphate pathways, decreases glycolysis, lowers GSH:GSSG and NAPDH/NAPD⁺ ratios exclusively in cancer cells, and induces necrosis. BH10 targets mitochondrial redox defence as evidenced by increased mitochondrial peroxiredoxin 3 oxidation and decreased mitochondrial aconitase activity, without changes in markers of cytosolic or nuclear damage. Over-expression of mitochondria-targeted catalase protects cells from BH10-mediated toxicity, while the thioredoxin reductase inhibitor auranofin synergistically enhances BH10-induced peroxiredoxin 3 oxidation and cytotoxicity. Overall, BH10 represents a 1,4-Naphthoquinone with an improved cancer-selective cytotoxicity profile via its mitochondrial specificity.

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Phenotypic screen identifies a 1,4-Naphthoquinone BH10 with improved cancer-selective cytotoxicity

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BH10 decreases glycolysis and increases glucose oxidation

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BH10-mediated cytotoxicity is linked to mitochondrial oxidative stress

Using the Human Genome-Scale Metabolic Model Recon 2 for Steady-State Flux Analysis of Cancer Cell Metabolism

Flux analysis is performed to infer intracellular metabolic activity using measured rates. By applying the highly curated human metabolic reconstruction Recon 2 as the reference model, the investigation of cancer cell metabolic fluxes can encompass the full metabolic potential of a human cell. But in its full form, Recon 2 is unsuitable for conventional metabolic flux analysis due to a large number of redundant elements. Here, we describe a procedure to reduce Recon 2 to an appropriate scale for cancer cell flux analysis such that calculated flux intervals are still informative, without compromising the opportunity to explore alternative pathways encoded in Recon 2 that may reveal novel metabolic features.

Abstract B20: Glutamine metabolic vulnerabilities define triple-negative from luminal A breast cancer subsets

Although a nonessential amino acid in normal cells, the demand for glutamine is dramatically increased throughout malignant transformation to support increased metabolic demands; namely, provision of catabolic substrates for ATP production and anabolic substrates for the citric acid cycle and subsequent macromolecule biosynthesis, as well as potentiating the uptake of other critical amino acids by acting as an obligate exchange substrate. Elevated expression of glutamine metabolism-related genes, MYC-driven transcriptional events, and increased consumption and reliance on glutamine are all associated with aggressive breast cancers, including the high-risk triple-negative (TN) subtype. We recently showed that in breast cancer cells, glutamine uptake by the small neutral amino acid transporter, ASCT2, is required to sustain TN cell growth in vitro and in vivo. We therefore hypothesized that highly proliferative TN breast cancers that are sensitive to ASCT2 inhibition may have unique metabolic signatures that could be additionally exploited for therapeutic purposes.

Using a targeted metabolomics approach, we combined labeled substrate tracing, liquid chromatography coupled tandem-mass spectrometry (LC-MS/MS), and gas chromatography mass spectrometry (GC-MS) to analyze intracellular levels of key tricarboxylic acid (TCA) cycle intermediates, glycolytic metabolites, fatty acid precursors, and amino acids in human breast cancer cell lines. These analyses revealed distinct metabolic effects when glutamine uptake was blocked in vitro by L-γ-glutamyl-p-nitroanilide (GPNA), a pharmacologic inhibitor of ASCT2. These data confirm a broad reliance on glutamine availability in TN breast cancers, reinforced by TCGA gene expression data showing a specific upregulation of multiple glutamine metabolism enzymes that is completely absent in the luminal A subtype. These data emphasize the link between increased glutamine metabolism and clinically aggressive breast cancers, thus highlighting the therapeutic potential of targeting glutamine metabolism pathways in these patients.

Citation Format: Michelle van Geldermalsen, Lake-Ee Quek, Nigel Turner, Seher Balaban, Andrew Hoy, Qian Wang, Jeff Holst. Glutamine metabolic vulnerabilities define triple-negative from luminal A breast cancer subsets [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr B20.

Acute activation of pyruvate dehydrogenase increases glucose oxidation in muscle without changing glucose uptake

Pyruvate dehydrogenase (PDH) activity is a key component of the glucose/fatty acid cycle hypothesis for the regulation of glucose uptake and metabolism. We have investigated whether acute activation of PDH in muscle can alleviate the insulin resistance caused by feeding animals a high-fat diet (HFD). The importance of PDH activity in muscle glucose disposal under insulin-stimulated conditions was determined by infusing the PDH kinase inhibitor dichloroacetate (DCA) into HFD-fed Wistar rats during a hyperinsulinemic-euglycemic clamp. Acute DCA infusion did not alter glucose infusion rate, glucose disappearance, or hepatic glucose production but did decrease plasma lactate levels. DCA substantially increased muscle PDH activity; however, this did not improve insulin-stimulated glucose uptake in insulin-resistant muscle of HFD rats. DCA infusion increased the flux of pyruvate to acetyl-CoA and reduced glucose incorporation into glycogen and alanine in muscle. Similarly, in isolated muscle, DCA treatment increased glucose oxidation and decreased glycogen synthesis without changing glucose uptake. These results suggest that, although PDH activity controls the conversion of pyruvate to acetyl-CoA for oxidation, this has little effect on glucose uptake into muscle under insulin-stimulated conditions.

From reconstruction to C4 metabolic engineering: A case study for overproduction of polyhydroxybutyrate in bioenergy grasses

The compartmentalization of C₄ plants increases photosynthetic efficiency, while constraining how material and energy must flow in leaf tissues. To capture this metabolic phenomenon, a generic plant metabolic reconstruction was replicated into four connected spatiotemporal compartments, namely bundle sheath (B) and mesophyll (M) across the day and night cycle. The C₄ leaf model was used to explore how amenable polyhydroxybutyrate (PHB) production is with these four compartments working cooperatively. A strategic pattern of metabolite conversion and exchange emerged from a systems-level network that has very few constraints imposed; mainly the sequential two-step carbon capture in mesophyll, then bundle sheath and photosynthesis during the day only. The building of starch reserves during the day and their mobilization during the night connects day and night metabolism. Flux simulations revealed that PHB production did not require rerouting of metabolic pathways beyond what is already utilised for growth. PHB yield was sensitive to photoassimilation capacity, availability of carbon reserves, ATP maintenance, relative photosynthetic activity of B and M, and type of metabolites exchanged in the plasmodesmata, but not sensitive towards compartmentalization. Hence, the compartmentalization issues currently encountered are likely to be kinetic or thermodynamic limitations rather than stoichiometric.

Dynamic Metabolomics Reveals that Insulin Primes the Adipocyte for Glucose Metabolism

Insulin triggers an extensive signaling cascade to coordinate adipocyte glucose metabolism. It is considered that the major role of insulin is to provide anabolic substrates by activating GLUT4-dependent glucose uptake. However, insulin stimulates phosphorylation of many metabolic proteins. To examine the implications of this on glucose metabolism, we performed dynamic tracer metabolomics in cultured adipocytes treated with insulin. Temporal analysis of metabolite concentrations and tracer labeling revealed rapid and distinct changes in glucose metabolism, favoring specific glycolytic branch points and pyruvate anaplerosis. Integrating dynamic metabolomics and phosphoproteomics data revealed that insulin-dependent phosphorylation of anabolic enzymes occurred prior to substrate accumulation. Indeed, glycogen synthesis was activated independently of glucose supply. We refer to this phenomenon as metabolic priming, whereby insulin signaling creates a demand-driven system to "pull" glucose into specific anabolic pathways. This complements the supply-driven regulation of anabolism by substrate accumulation and highlights an additional role for insulin action in adipocyte glucose metabolism.

Protein hypoacylation induced by Sirt5 overexpression has minimal metabolic effect in mice

Sirtuins are a family of evolutionary conserved enzymes that dynamically regulate cellular physiology. Mammals have 7 sirtuins, which are located in different cellular compartments. Sirt5, a sirtuin isoform located in multiple subcellular sites, is involved in regulating a diverse range of cellular and metabolic processes through the removal of a range of acyl-lysine modifications on target proteins. Loss of Sirt5 leads to hyper-malonylation and hyper-succinylation of both mitochondrial and extra-mitochondrial proteins, influencing oxidative phosphorylation, the TCA cycle and glycolysis. However despite these findings, the effect of Sirt5 overexpression on metabolism remains poorly investigated. Here we report that overexpression of Sirt5 has minimal effect on mitochondrial metabolism and overall physiology in mice, despite inducing widespread decreases in protein acylation. Our data confirms the role of Sirt5 as an important demalonylase and desuccinylase enzyme in vivo, but questions the relevance of physiological changes in protein acylation levels in the regulation of cellular metabolism.

Benzylserine inhibits breast cancer cell growth by disrupting intracellular amino acid homeostasis and triggering amino acid response pathways

Background

Cancer cells require increased levels of nutrients such as amino acids to sustain their rapid growth. In particular, leucine and glutamine have been shown to be important for growth and proliferation of some breast cancers, and therefore targeting the primary cell-surface transporters that mediate their uptake, L-type amino acid transporter 1 (LAT1) and alanine, serine, cysteine-preferring transporter 2 (ASCT2), is a potential therapeutic strategy.

Methods

The ASCT2 inhibitor, benzylserine (BenSer), is also able to block LAT1 activity, thus inhibiting both leucine and glutamine uptake. We therefore aimed to investigate the effects of BenSer in breast cancer cell lines to determine whether combined LAT1 and ASCT2 inhibition could inhibit cell growth and proliferation.

Results

BenSer treatment significantly inhibited both leucine and glutamine uptake in MCF-7, HCC1806 and MDA-MB-231 breast cancer cells, causing decreased cell viability and cell cycle progression. These effects were not primarily leucine-mediated, as BenSer was more cytostatic than the LAT family inhibitor, BCH. Oocyte uptake assays with ectopically expressed amino acid transporters identified four additional targets of BenSer, and gas chromatography-mass spectrometry (GCMS) analysis of intracellular amino acid concentrations revealed that this BenSer-mediated inhibition of amino acid uptake was sufficient to disrupt multiple pathways of amino acid metabolism, causing reduced lactate production and activation of an amino acid response (AAR) through activating transcription factor 4 (ATF4).

Conclusions

Together these data showed that BenSer blockade inhibited breast cancer cell growth and viability through disruption of intracellular amino acid homeostasis and inhibition of downstream metabolic and growth pathways.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4599-8) contains supplementary material, which is available to authorized users.

Improving culture performance and antibody production in CHO cell culture processes by reducing the Warburg effect

Lactate is one of the key waste metabolites of mammalian cell culture. High lactate levels are caused by high aerobic glycolysis, also known as the Warburg effect, and are usually associated with adverse culture performance. Therefore, reducing lactate accumulation has been an ongoing challenge in the cell culture development to improve growth, productivity, and process robustness. The pyruvate dehydrogenase complex (PDC) plays a crucial role for the fate of pyruvate, as it converts pyruvate to acetyl coenzyme A (acetyl-CoA). The PDC activity can be indirectly increased by inhibiting the PDC inhibitor, pyruvate dehydrogenase kinase, using dichloroacetate (DCA), resulting in less pyruvate being available for lactate formation. Here, Chinese hamster ovary cells were cultivated either with 5 mM DCA or without DCA in various batch and fed-batch bioreactor processes. In all cultures, DCA increased peak viable cell density (VCD), culture length and final antibody titer. The strongest effect was observed in a fed batch with media and glucose feeding in which peak VCD was increased by more than 50%, culture length was extended by more than 3 days, and the final antibody titer increased by more than twofold. In cultures with DCA, lactate production and glucose consumption during exponential growth were on average reduced by approximately 40% and 35%, respectively. Metabolic flux analysis showed reduced glycolytic fluxes, whereas fluxes in the tricarboxylic acid (TCA) cycle were not affected, suggesting that cultures with DCA use glucose more efficiently. In a proteomics analysis, only few proteins were identified as being differentially expressed, indicating that DCA acts on a posttranslational level. Antibody quality in terms of aggregation, charge variant, and glycosylation pattern was unaffected. Subsequent bioreactor experiments with sodium lactate and sodium chloride feeding indicated that lower osmolality, rather than lower lactate concentration itself, improved culture performance in DCA cultures. In conclusion, the addition of DCA to the cell culture improved culture performance and increased antibody titers without any disadvantages for cell-specific productivity or antibody quality.

Fructose bisphosphatase 2 overexpression increases glucose uptake in skeletal muscle

Skeletal muscle is a major tissue for glucose metabolism and can store glucose as glycogen, convert glucose to lactate via glycolysis and fully oxidise glucose to CO₂ Muscle has a limited capacity for gluconeogenesis but can convert lactate and alanine to glycogen. Gluconeogenesis requires FBP2, a muscle-specific form of fructose bisphosphatase that converts fructose-1,6-bisphosphate (F-1,6-bisP) to fructose-6-phosphate (F-6-P) opposing the activity of the ATP-consuming enzyme phosphofructokinase (PFK). In mammalian muscle, the activity of PFK is normally 100 times higher than FBP2 and therefore energy wasting cycling between PFK and FBP2 is low. In an attempt to increase substrate cycling between F-6-P and F-1,6-bisP and alter glucose metabolism, we overexpressed FBP2 using a muscle-specific adeno-associated virus (AAV-tMCK-FBP2). AAV was injected into the right tibialis muscle of rats, while the control contralateral left tibialis received a saline injection. Rats were fed a chow or 45% fat diet (HFD) for 5 weeks after which, hyperinsulinaemic-euglycaemic clamps were performed. Infection of the right tibialis with AAV-tMCK-FBP2 increased FBP2 activity 10 fold on average in chow and HFD rats (P < 0.0001). Overexpression of FBP2 significantly increased insulin-stimulated glucose uptake in tibialis of chow animals (control 14.3 ± 1.7; FBP2 17.6 ± 1.6 µmol/min/100 g) and HFD animals (control 9.6 ± 1.1; FBP2 11.2 ± 1.1µmol/min/100 g). The results suggest that increasing the capacity for cycling between F-1,6-bisP and F-6-P can increase the metabolism of glucose by introducing a futile cycle in muscle, but this increase is not sufficient to overcome muscle insulin resistance.

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

Fast exchange fluxes around the pyruvate node: a leaky cell model to explain the gain and loss of unlabelled and labelled metabolites in a tracer experiment

BACKGROUND

Glucose and glutamine are the two dominant metabolic substrates in cancer cells. In (13)C tracer experiments, however, it is necessary to account for all significant input substrates, as some natural (unlabelled) substrate in the medium, often derived from serum, can be metabolised by cells despite not showing signs of net consumption.

RESULTS

Using [U-(13)C6]-glucose tracers and measuring extracellular metabolite enrichments by GC-MS, we found that pancreatic cells HPDE and PANC-1 secrete lactate, pyruvate, TCA cycle metabolites and non-essential amino acids synthesised from glucose. Focusing our investigations on pyruvate exchange in HEK293 cells, we observed that the four metabolites pools, intracellular and extracellular lactate and pyruvate, had similar (13)C enrichment trajectories. This indicated that these metabolites can mix rapidly. Using a hybrid (13)C-MFA, we followed to show that the lactate exchange flux had increased when extracellular lactate concentration was increased by 10-fold. By allowing rapid exchange fluxes around the pyruvate node, (13)C-MFA revealed that PANC-1 cells cultured in [U-(13)C6]-glucose doubled the conversion of unlabelled substrates to pyruvate when treated with TNF-α.

CONCLUSIONS

The current work established the possibility that a cell's range of significant input substrates may be broader than anticipated. Metabolite exchange can affect intracellular enrichments. In particular, we showed that pyruvate was more strongly connected to lactate than to upstream glycolytic intermediates and that a fast lactate exchange may alter the outcome of flux analyses. Nevertheless, the leaky cell model may be an opportunity in disguise-the ability to continuously monitor metabolism using only the enrichments of extracellular metabolites.

Loss of ceramide synthase 2 activity, necessary for myelin biosynthesis, precedes tau pathology in the cortical pathogenesis of Alzheimer's disease

The anatomical progression of neurofibrillary tangle pathology throughout Alzheimer's disease (AD) pathogenesis runs inverse to the pattern of developmental myelination, with the disease preferentially affecting thinly myelinated regions. Myelin is comprised 80% of lipids, and the prototypical myelin lipids, galactosylceramide, and sulfatide are critical for neurological function. We observed severe depletion of galactosylceramide and sulfatide in AD brain tissue, which can be traced metabolically to the loss of their biosynthetic precursor, very long chain ceramide. The synthesis of very long chain ceramides is catalyzed by ceramide synthase 2 (CERS2). We demonstrate a significant reduction in CERS2 activity as early as Braak stage I/II in temporal cortex, and Braak stage III/IV in hippocampus and frontal cortex, indicating that loss of myelin-specific ceramide synthase activity precedes neurofibrillary tangle pathology in cortical regions. These findings open a new vista on AD pathogenesis by demonstrating a defect in myelin lipid biosynthesis at the preclinical stages of the disease. We posit that, over time, this defect contributes significantly to myelin deterioration, synaptic dysfunction, and neurological decline.

Recon 2.2: from reconstruction to model of human metabolism

INTRODUCTION

The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.

OBJECTIVES

We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.

METHODS

Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.

RESULTS

Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.

CONCLUSION

Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).

Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism

Metabolic flux analysis (MFA) is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA) has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA) to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity.

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New dynamic MFA framework using B-spline (B-DMFA) generates smooth fit.

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B-DMFA performs better than linear DMFA when fitting fast dynamic changes.

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Heuristic algorithm for knot placement dramatically reduced computation time.

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Temperature shifted cultures maintain a constant IgG volume specific productivity.

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CHO cells shifted to 32 °C have a 42% higher IgG titer due to larger cell volume.

A multi-tissue genome-scale metabolic modeling framework for the analysis of whole plant systems

Genome scale metabolic modeling has traditionally been used to explore metabolism of individual cells or tissues. In higher organisms, the metabolism of individual tissues and organs is coordinated for the overall growth and well-being of the organism. Understanding the dependencies and rationale for multicellular metabolism is far from trivial. Here, we have advanced the use of AraGEM (a genome-scale reconstruction of Arabidopsis metabolism) in a multi-tissue context to understand how plants grow utilizing their leaf, stem and root systems across the day-night (diurnal) cycle. Six tissue compartments were created, each with their own distinct set of metabolic capabilities, and hence a reliance on other compartments for support. We used the multi-tissue framework to explore differences in the "division-of-labor" between the sources and sink tissues in response to: (a) the energy demand for the translocation of C and N species in between tissues; and (b) the use of two distinct nitrogen sources (NO(-) 3 or NH(+) 4). The "division-of-labor" between compartments was investigated using a minimum energy (photon) objective function. Random sampling of the solution space was used to explore the flux distributions under different scenarios as well as to identify highly coupled reaction sets in different tissues and organelles. Efficient identification of these sets was achieved by casting this problem as a maximum clique enumeration problem. The framework also enabled assessing the impact of energetic constraints in resource (redox and ATP) allocation between leaf, stem, and root tissues required for efficient carbon and nitrogen assimilation, including the diurnal cycle constraint forcing the plant to set aside resources during the day and defer metabolic processes that are more efficiently performed at night. This study is a first step toward autonomous modeling of whole plant metabolism.

Metabolic profiling and flux analysis of MEL-2 human embryonic stem cells during exponential growth at physiological and atmospheric oxygen concentrations

As human embryonic stem cells (hESCs) steadily progress towards regenerative medicine applications there is an increasing emphasis on the development of bioreactor platforms that enable expansion of these cells to clinically relevant numbers. Surprisingly little is known about the metabolic requirements of hESCs, precluding the rational design and optimisation of such platforms. In this study, we undertook an in-depth characterisation of MEL-2 hESC metabolic behaviour during the exponential growth phase, combining metabolic profiling and flux analysis tools at physiological (hypoxic) and atmospheric (normoxic) oxygen concentrations. To overcome variability in growth profiles and the problem of closing mass balances in a complex environment, we developed protocols to accurately measure uptake and production rates of metabolites, cell density, growth rate and biomass composition, and designed a metabolic flux analysis model for estimating internal rates. hESCs are commonly considered to be highly glycolytic with inactive or immature mitochondria, however, whilst the results of this study confirmed that glycolysis is indeed highly active, we show that at least in MEL-2 hESC, it is supported by the use of oxidative phosphorylation within the mitochondria utilising carbon sources, such as glutamine to maximise ATP production. Under both conditions, glycolysis was disconnected from the mitochondria with all of the glucose being converted to lactate. No difference in the growth rates of cells cultured under physiological or atmospheric oxygen concentrations was observed nor did this cause differences in fluxes through the majority of the internal metabolic pathways associated with biogenesis. These results suggest that hESCs display the conventional Warburg effect, with high aerobic activity despite high lactate production, challenging the idea of an anaerobic metabolism with low mitochondrial activity. The results of this study provide new insight that can be used in rational bioreactor design and in the development of novel culture media for hESC maintenance and expansion.

A depth-first search algorithm to compute elementary flux modes by linear programming

Background

The decomposition of complex metabolic networks into elementary flux modes (EFMs) provides a useful framework for exploring reaction interactions systematically. Generating a complete set of EFMs for large-scale models, however, is near impossible. Even for moderately-sized models (<400 reactions), existing approaches based on the Double Description method must iterate through a large number of combinatorial candidates, thus imposing an immense processor and memory demand.

Results

Based on an alternative elementarity test, we developed a depth-first search algorithm using linear programming (LP) to enumerate EFMs in an exhaustive fashion. Constraints can be introduced to directly generate a subset of EFMs satisfying the set of constraints. The depth-first search algorithm has a constant memory overhead. Using flux constraints, a large LP problem can be massively divided and parallelized into independent sub-jobs for deployment into computing clusters. Since the sub-jobs do not overlap, the approach scales to utilize all available computing nodes with minimal coordination overhead or memory limitations.

Conclusions

The speed of the algorithm was comparable to efmtool, a mainstream Double Description method, when enumerating all EFMs; the attrition power gained from performing flux feasibility tests offsets the increased computational demand of running an LP solver. Unlike the Double Description method, the algorithm enables accelerated enumeration of all EFMs satisfying a set of constraints.

Plant genome-scale modeling and implementation

Considerable progress has been made in plant genome-scale metabolic reconstruction and modeling in recent years. Such reconstructions made it possible to explore metabolic phenotypes through appropriate model formulation and optimization methods. As a result, plant genome-scale modeling has increasingly attracted interest from the plant research community. In this chapter, the first generation of plant genome-scale metabolic reconstructions is presented, along with the important concepts behind model and constraint formulation. A brief protocol describing the use of constraint-based reconstruction and analysis (COBRA) Toolbox in flux simulation and model modification is provided. This is followed by a presentation of metabolic constraints required to generate fluxes in AraGEM using COBRA that describe photosynthesis, photorespiration, and respiration, respectively. Overall, plant genome-scale modeling is a powerful approach that is accessible and readily adopted.

Steady-state ¹³C fluxomics using OpenFLUX

Metabolic flux estimation using (13)C isotopic tracers ((13)C-MFA) provides a greater resolution of intracellular fluxes than using only cell growth and consumption/production rates. However, (13)C-MFA is computationally more demanding. A nonlinear least-square optimization process is employed to constrain metabolic fluxes using atom balance models and experimentally measured (13)C labelling pattern of intracellular or proteinogenic metabolites. OpenFLUX was therefore developed for the purpose of streamlining the computational workflow. Here, we describe in detail the computational procedure for performing (13)C-MFA using OpenFLUX. We also provide some helpful information on model reconstruction and GC-MS data treatment.

Customization of ¹³C-MFA strategy according to cell culture system

(13)C-MFA is far from being a simple assay for quantifying metabolic activity. It requires considerable up-front experimental planning and familiarity with the cell culture system in question, as well as optimized analytics and adequate computation frameworks. The success of a (13)C-MFA experiment is ultimately rated by the ability to accurately quantify the flux of one or more reactions of interest. In this chapter, we describe the different (13)C-MFA strategies that have been developed for the various fermentation or cell culture systems, as well as the limitations of the respective strategies. The strategies are affected by many factors and the (13)C-MFA modeling and experimental strategy must be tailored to conditions. The prevailing philosophy in the computation process is that any metabolic processes that produce significant systematic bias in the labeling pattern of the metabolites being measured must be described in the model. It is equally important to plan a labeling strategy by analytical screening or by heuristics.

Flux balance analysis of CHO cells before and after a metabolic switch from lactate production to consumption

Mammalian cell cultures typically exhibit an energy inefficient phenotype characterized by the consumption of large quantities of glucose and the concomitant production of large quantities of lactate. Under certain conditions, mammalian cells can switch to a more energy efficient state during which lactate is consumed. Using a metabolic model derived from a mouse genome scale model we performed flux balance analysis of Chinese hamster ovary cells before and after a metabolic switch from lactate production (in the presence of glucose) to lactate consumption (after glucose depletion). Despite a residual degree of freedom after accounting for measurements, the calculated flux ranges and associated errors were narrow enough to enable investigation of metabolic changes across the metabolic switch. Surprisingly, the fluxes through the lower part of the TCA cycle from oxoglutarate to malate were very similar (around 60 µmol/gDW/h) for both phases. A detailed analysis of the energy metabolism showed that cells consuming lactate have an energy efficiency (total ATP produced per total C-mol substrate consumed) six times greater than lactate producing cells.

Metabolite profiling of CHO cells with different growth characteristics

Mammalian cell cultures are the predominant system for the production of recombinant proteins requiring post-translational modifications. As protein yields are a function of growth performance (among others), and performance varies greatly between culture medium (e.g., different growth rates and peak cell densities), an understanding of the biological mechanisms underpinning this variability would facilitate rational medium and process optimization, increasing product yields, and reducing costs. We employed a metabolomics approach to analyze differences in metabolite concentrations of CHO cells cultivated in three different media exhibiting different growth rates and maximum viable cell densities. Analysis of intra- and extracellular metabolite concentrations over the course of the cultures using a combination of HPLC and GC-MS, readily detected medium specific and time dependent changes. Using multivariate data analysis, we identified a range of metabolites correlating with growth rate, illustrating how metabolomics can be used to relate gross phenotypic changes to the fine details of cellular metabolism.

AlgaGEM--a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome

BACKGROUND

Microalgae have the potential to deliver biofuels without the associated competition for land resources. In order to realise the rates and titres necessary for commercial production, however, system-level metabolic engineering will be required. Genome scale metabolic reconstructions have revolutionized microbial metabolic engineering and are used routinely for in silico analysis and design. While genome scale metabolic reconstructions have been developed for many prokaryotes and model eukaryotes, the application to less well characterized eukaryotes such as algae is challenging not at least due to a lack of compartmentalization data.

RESULTS

We have developed a genome-scale metabolic network model (named AlgaGEM) covering the metabolism for a compartmentalized algae cell based on the Chlamydomonas reinhardtii genome. AlgaGEM is a comprehensive literature-based genome scale metabolic reconstruction that accounts for the functions of 866 unique ORFs, 1862 metabolites, 2249 gene-enzyme-reaction-association entries, and 1725 unique reactions. The reconstruction was compartmentalized into the cytoplasm, mitochondrion, plastid and microbody using available data for algae complemented with compartmentalisation data for Arabidopsis thaliana. AlgaGEM describes a functional primary metabolism of Chlamydomonas and significantly predicts distinct algal behaviours such as the catabolism or secretion rather than recycling of phosphoglycolate in photorespiration. AlgaGEM was validated through the simulation of growth and algae metabolic functions inferred from literature. Using efficient resource utilisation as the optimality criterion, AlgaGEM predicted observed metabolic effects under autotrophic, heterotrophic and mixotrophic conditions. AlgaGEM predicts increased hydrogen production when cyclic electron flow is disrupted as seen in a high producing mutant derived from mutational studies. The model also predicted the physiological pathway for H2 production and identified new targets to further improve H2 yield.

CONCLUSIONS

AlgaGEM is a viable and comprehensive framework for in silico functional analysis and can be used to derive new, non-trivial hypotheses for exploring this metabolically versatile organism. Flux balance analysis can be used to identify bottlenecks and new targets to metabolically engineer microalgae for production of biofuels.

C4GEM, a genome-scale metabolic model to study C4 plant metabolism

Leaves of C(4) grasses (such as maize [Zea mays], sugarcane [Saccharum officinarum], and sorghum [Sorghum bicolor]) form a classical Kranz leaf anatomy. Unlike C(3) plants, where photosynthetic CO(2) fixation proceeds in the mesophyll (M), the fixation process in C(4) plants is distributed between two cell types, the M cell and the bundle sheath (BS) cell. Here, we develop a C(4) genome-scale model (C4GEM) for the investigation of flux distribution in M and BS cells during C(4) photosynthesis. C4GEM, to our knowledge, is the first large-scale metabolic model that encapsulates metabolic interactions between two different cell types. C4GEM is based on the Arabidopsis (Arabidopsis thaliana) model (AraGEM) but has been extended by adding reactions and transporters responsible to represent three different C(4) subtypes (NADP-ME [for malic enzyme], NAD-ME, and phosphoenolpyruvate carboxykinase). C4GEM has been validated for its ability to synthesize 47 biomass components and consists of 1,588 unique reactions, 1,755 metabolites, 83 interorganelle transporters, and 29 external transporters (including transport through plasmodesmata). Reactions in the common C(4) model have been associated with well-annotated C(4) species (NADP-ME subtypes): 3,557 genes in sorghum, 11,623 genes in maize, and 3,881 genes in sugarcane. The number of essential reactions not assigned to genes is 131, 135, and 156 in sorghum, maize, and sugarcane, respectively. Flux balance analysis was used to assess the metabolic activity in M and BS cells during C(4) photosynthesis. Our simulations were consistent with chloroplast proteomic studies, and C4GEM predicted the classical C(4) photosynthesis pathway and its major effect in organelle function in M and BS. The model also highlights differences in metabolic activities around photosystem I and photosystem II for three different C(4) subtypes. Effects of CO(2) leakage were also explored. C4GEM is a viable framework for in silico analysis of cell cooperation between M and BS cells during photosynthesis and can be used to explore C(4) plant metabolism.

AraGEM, a genome-scale reconstruction of the primary metabolic network in Arabidopsis

Genome-scale metabolic network models have been successfully used to describe metabolism in a variety of microbial organisms as well as specific mammalian cell types and organelles. This systems-based framework enables the exploration of global phenotypic effects of gene knockouts, gene insertion, and up-regulation of gene expression. We have developed a genome-scale metabolic network model (AraGEM) covering primary metabolism for a compartmentalized plant cell based on the Arabidopsis (Arabidopsis thaliana) genome. AraGEM is a comprehensive literature-based, genome-scale metabolic reconstruction that accounts for the functions of 1,419 unique open reading frames, 1,748 metabolites, 5,253 gene-enzyme reaction-association entries, and 1,567 unique reactions compartmentalized into the cytoplasm, mitochondrion, plastid, peroxisome, and vacuole. The curation process identified 75 essential reactions with respective enzyme associations not assigned to any particular gene in the Kyoto Encyclopedia of Genes and Genomes or AraCyc. With the addition of these reactions, AraGEM describes a functional primary metabolism of Arabidopsis. The reconstructed network was transformed into an in silico metabolic flux model of plant metabolism and validated through the simulation of plant metabolic functions inferred from the literature. Using efficient resource utilization as the optimality criterion, AraGEM predicted the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. AraGEM is a viable framework for in silico functional analysis and can be used to derive new, nontrivial hypotheses for exploring plant metabolism.

On the reconstruction of the Mus musculus genome-scale metabolic network model

Genome-scale metabolic modeling is a systems-based approach that attempts to capture the metabolic complexity of the whole cell, for the purpose of gaining insight into metabolic function and regulation. This is achieved by organizing the metabolic components and their corresponding interactions into a single context. The reconstruction process is a challenging and laborious task, especially during the stage of manual curation. For the mouse genome-scale metabolic model, however, we were able to rapidly reconstruct a compartmentalized model from well-curated metabolic databases online. The prototype model was comprehensive. Apart from minor compound naming and compartmentalization issues, only nine additional reactions without gene associations were added during model curation before the model was able to simulate growth in silico. Further curation led to a metabolic model that consists of 1399 genes mapped to 1757 reactions, with a total of 2037 reactions compartmentalized into the cytoplasm and mitochondria, capable of reproducing metabolic functions inferred from literatures. The reconstruction is made more tractable by developing a formal system to update the model against online databases. Effectively, we can focus our curation efforts into establishing better model annotations and gene-protein-reaction associations within the core metabolism, while relying on genome and proteome databases to build new annotations for peripheral pathways, which may bear less relevance to our modeling interest.

OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

Background

The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on ¹³C substrates, (ii) ¹³C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis.

Results

We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale ¹³C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU) framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly (<20 sec).

Conclusion

We have developed a fast, accurate application to perform steady-state ¹³C metabolic flux analysis. OpenFLUX will strongly facilitate and enhance the design, calculation and interpretation of metabolic flux studies. By providing the software open source, we hope it will evolve with the rapidly growing field of fluxomics.