Itaconate Links Inhibition of Succinate Dehydrogenase with Macrophage Metabolic Remodeling and Regulation of Inflammation

Remodeling of the tricarboxylic acid (TCA) cycle is a metabolic adaptation accompanying inflammatory macrophage activation. During this process, endogenous metabolites can adopt regulatory roles that govern specific aspects of inflammatory response, as recently shown for succinate, which regulates the pro-inflammatory IL-1β-HIF-1α axis. Itaconate is one of the most highly induced metabolites in activated macrophages, yet its functional significance remains unknown. Here, we show that itaconate modulates macrophage metabolism and effector functions by inhibiting succinate dehydrogenase-mediated oxidation of succinate. Through this action, itaconate exerts anti-inflammatory effects when administered in vitro and in vivo during macrophage activation and ischemia-reperfusion injury. Using newly generated Irg1(−/−) mice, which lack the ability to produce itaconate, we show that endogenous itaconate regulates succinate levels and function, mitochondrial respiration, and inflammatory cytokine production during macrophage activation. These studies highlight itaconate as a major physiological regulator of the global metabolic rewiring and effector functions of inflammatory macrophages

Metabolic adaptation and its role in tumorigenesis

The study of cancer metabolism has gained in appreciation and development over the decades since the original discoveries of Otto Warburg. "The Warburg Effect", named after the discoverer, described a unique set of metabolic features of tumours where glucose was preferentially fermented to lactate despite abundant oxygen in the environment. This was in contrast to the metabolic phenotype of normal, non-transformed tissue, where glucose is oxidized to CO2 in the mitochondria. This lead Warburg to the hypothesis that cancer cells originate due to dysfunctional mitochondria. Since that observation, progress in the field of oncometabolism remained relatively slow. By contrast, genetic research in cancer identified oncogenes and tumour suppressors that were strong drivers in tumourigenesis. Thus, metabolism took a backseat in cancer research and was understood to be a secondary effect, meant to supply a demand imposed by oncogenic mutations. However, with the development of better technology and a understanding, oncometabolism is now a fast growing and maturing field. Tumour metabolism is now appreciated more as a driving force in cancer. In this thesis, tumour metabolism is the central focus of study as a driver of tumour growth and a means of adaptations to stress. Specifically, a metabolic mechanism is detailed underlying the anti-tumour role of the widely prescribed anti-diabetic drug metformin. Moreover, this metabolic mechanism, and the role of AMP-activated protein kinase (AMPK), are exploited to reveal synthetic lethality between metformin treatment, glucose starvation, and silencing of AMPK. Lastly, gluatamtic-acid decarboxylase 1 (GAD1), an overlooked protein in the field of cancer metabolism, is revealed to be involved in important mechanisms of amino acid balance in a subset of cancer cells. The work in this thesis highlights metabolic adaptation and its role in tumourigenesis.Le domaine de recherche de métabolisme du cancer a prit des gains en développement et en appréciation au fil des décennies depuis les découvertes d'Otto Warburg. «L'Effet Warburg», nommé après son découvreur, décrit l'unique métabolisme de certaines tumeurs où le glucose est préférentiellement fermenté au lactate malgré une abondance d'oxygène dans l'environnement. Ceci est en contraste au métabolisme de tissu non-transformé, où le glucose est oxydé en CO2 dans la mitochondrie. Warburg a développé l'hypothèse que les cellules cancéreuses sont dues à des mitochondries dysfonctionnelles. Depuis cette observation, le progrès dans l'étude du métabolisme oncologique était au ralenti. Contrairement, il y avait des avancements dans le domaine de recherche génétique avec l'identification des oncogènes et des suppresseurs de tumeurs, des moteurs important dans la tumorigénèse. Donc, le métabolisme a été relégué à un rôle passif, il existait simplement pour remplir les demandes des mutations oncogéniques. Cependant, avec l'avancement de technologies et un changement de point de vue, le métabolisme oncologique a fait une réapparition et est un domaine qui avance rapidement. Le métabolisme est maintenant compris comme étant un facteur important de la progression des tumeurs. Le métabolisme des tumeurs est le sujet principal de cette thèse, précisément par rapport à son rôle dans la croissance des tumeurs et leurs adaptation aux stresses. Un mécanisme métabolique est détaillé expliquant les effets anti-tumorale de la metformin. De plus, ce mécanisme, et le rôle adaptatif du kinase activé par l'AMP (AMPK), sont exploités pour induire une létalité synthétique entre la metformin, la privation de glucose, et le silence de l'AMPK. Finalement, un rôle important dans l'équilibre des acides aminées est attribué au glutamic-acid decarboxylase 1 (GAD1), une protéine négligée dans le domaine de métabolisme du cancer. Le travail de cette thèse surligne l'adaptation métabolique et son rôle dans la tumorigénèse

Metformin Antagonizes Cancer Cell Proliferation by Suppressing Mitochondrial-Dependent Biosynthesis.

Metformin is a biguanide widely prescribed to treat Type II diabetes that has gained interest as an antineoplastic agent. Recent work suggests that metformin directly antagonizes cancer cell growth through its actions on complex I of the mitochondrial electron transport chain (ETC). However, the mechanisms by which metformin arrests cancer cell proliferation remain poorly defined. Here we demonstrate that the metabolic checkpoint kinases AMP-activated protein kinase (AMPK) and LKB1 are not required for the antiproliferative effects of metformin. Rather, metformin inhibits cancer cell proliferation by suppressing mitochondrial-dependent biosynthetic activity. We show that in vitro metformin decreases the flow of glucose- and glutamine-derived metabolic intermediates into the Tricarboxylic Acid (TCA) cycle, leading to reduced citrate production and de novo lipid biosynthesis. Tumor cells lacking functional mitochondria maintain lipid biosynthesis in the presence of metformin via glutamine-dependent reductive carboxylation, and display reduced sensitivity to metformin-induced proliferative arrest. Our data indicate that metformin inhibits cancer cell proliferation by suppressing the production of mitochondrial-dependent metabolic intermediates required for cell growth, and that metabolic adaptations that bypass mitochondrial-dependent biosynthesis may provide a mechanism of tumor cell resistance to biguanide activity

Loss of the tumor suppressor LKB1 promotes metabolic reprogramming of cancer cells via HIF-1α

One of the major metabolic changes associated with cellular transformation is enhanced nutrient utilization, which supports tumor progression by fueling both energy production and providing biosynthetic intermediates for growth. The liver kinase B1 (LKB1) is a serine/threonine kinase and tumor suppressor that couples bioenergetics to cell-growth control through regulation of mammalian target of rapamycin (mTOR) activity; however, the influence of LKB1 on tumor metabolism is not well defined. Here, we show that loss of LKB1 induces a progrowth metabolic program in proliferating cells. Cells lacking LKB1 display increased glucose and glutamine uptake and utilization, which support both cellular ATP levels and increased macromolecular biosynthesis. This LKB1-dependent reprogramming of cell metabolism is dependent on the hypoxia-inducible factor-1α (HIF-1α), which accumulates under normoxia in LKB1-deficient cells and is antagonized by inhibition of mTOR complex I signaling. Silencing HIF-1α reverses the metabolic advantages conferred by reduced LKB1 signaling and impairs the growth and survival of LKB1-deficient tumor cells under low-nutrient conditions. Together, our data implicate the tumor suppressor LKB1 as a central regulator of tumor metabolism and growth control through the regulation of HIF-1α–dependent metabolic reprogramming

Metformin requires functional mitochondrial electron transport to suppress de novo lipogenesis.

<p>A–B. Abundance and distribution of U-[¹³C]-glucose-derived citrate in metformin-treated 143B osteosarcoma cells. 143B<i>wt</i> and 143B<i>cytb</i> cells were cultured with (+) or without (−) metformin (10 mM) for 12 h, and intracellular metabolites extracted and analyzed by GC-MS. U-[¹³C]-glucose was added for the final 6 h of culture. Shown is the isotopomer distribution (<b>A</b>) and relative abundance (<b>B</b>) of U-[¹³C]-glucose-derived citrate in 143B<i>wt</i> and 143B<i>cytb</i> cells treated as indicated. Data are normalized to cell number and are presented as mean ± SEM for each condition (<i>n</i> = 3), and are representative of two independent experiments. <b>C–D.</b> Abundance and distribution of U-[¹³C]-glutamine-derived citrate in metformin-treated 143B cells. 143B Cells were treated as in (<b>A</b>), with U-[¹³C]-glutamine added for the final 6 h of culture. Isotopomer distribution (<b>C</b>) and relative abundance (<b>D</b>) of U-[¹³C]-glutamine-derived citrate in 143B<i>wt</i> and 143B<i>cytb</i> cells is shown. Data are normalized to cell number. <b>E</b>. Relative palmitate abundance in 143B<i>wt</i> and 143B<i>cytb</i> cells cultured with (+) or without (−) metformin (10 mM) for 72 h. Data are normalized to cell number and presented as mean ± SEM for each condition (<i>n</i> = 3). <b>F–G</b>. Relative abundance of U-[¹³C]-glucose-derived (<b>F</b>) and U-[¹³C]-glutamine-derived (<b>G</b>) lipogenic acetyl-CoA and palmitate in 143B<i>wt</i> and 143B<i>cytb</i> cells cultured in the presence (+) or absence (−) of metformin (10 mM) for 72 h. Cells were cultured for 72 h, with U-[¹³C]-glucose or U-[¹³C]-glutamine added for the final 24 h of culture. Data are normalized to cell number, are presented as mean ± SEM for triplicate samples, and are representative of three independent experiments. *, <i>p</i> < 0.05; **, <i>p</i> < 0.01. Raw data for this figure can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002309#pbio.1002309.s005" target="_blank">S5 Data</a>.</p

Metformin suppresses glucose- and glutamine-dependent TCA cycle activity.

<p><b>A.</b> Relative abundance of TCA metabolites in metformin-treated H1299 cells. Cells were treated with or without metformin (5 mM) for 8 h, and TCA cycle metabolites determined by gas chromatography-mass spectrometry (GC-MS). Data are expressed as the ratio of metabolite levels in metformin-treated cells relative to cells cultured without metformin. Data shown is normalized to cell number. The data represent the mean ± SEM for triplicate samples. <b>B.</b> Heat map of relative metabolite abundances in metformin-treated H1299 cells. H1299 cells were treated with (+) or without (−) 5 mM metformin for 6 h, followed by culture with U-[¹³C]-glucose or U-[¹³C]-glutamine for an additional 2 h. Shown is the relative abundance of U-[¹³C]-glucose-derived (left panel) or U-[¹³C]-glutamine-derived (right panel) TCA cycle metabolites under each culture condition. Data are expressed relative to the ¹³C metabolite abundance in H1299 cells cultured under control conditions (no metformin). <b>C.</b> Relative abundance of glucose-derived citrate in metformin-treated H1299 cells. Cells were treated for 24 h with the indicated doses of metformin followed by incubation with U-[¹³C]-glucose for 2 h. The abundance of unlabeled (¹²C, white) and U-[¹³C]-glucose-labeled (¹³C, black) citrate was determined by GC-MS. Data are normalized to cell number. <b>D.</b> Schematic of U-[¹³C]-glucose labeling in the TCA cycle. Input of fully-labeled Ac-CoA (m + 2) results in the generation of m + 2-labeled metabolites on the first turn of the TCA cycle, and m + 4-labeled metabolites on the second turn. <b>E.</b> Distribution of U-[¹³C]-glucose-derived isotopomers of citrate in H1299 cells cultured with or without metformin as in (<b>B</b>). The data represent the mean ± SEM for triplicate samples. <b>F.</b> Relative abundance of glutamine-derived citrate in metformin-treated H1299 cells. Cells were treated as in (<b>B</b>), and the abundance of unlabeled (¹²C, white) and U-[¹³C]-glutamine-labeled (¹³C, black) citrate was determined by GC-MS. Data are normalized to cell number. <b>G.</b> Schematic of U-[¹³C]-glutamine labeling in the TCA cycle. Anaplerotic U-[¹³C]-glutamine flux into the TCA cycle follows clockwise flow resulting in m + 4 labeling during the first round of the TCA cycle. Reductive carboxylation of α-KG results in m + 5 labeling in citrate. <b>H.</b> Distribution of U-[¹³C]-glutamine-derived isotopomers of citrate in H1299 cells cultured with or without metformin as in (<b>B</b>). The data represent the mean ± SEM for triplicate samples. <b>I.</b> Relative abundance of citrate produced via oxidative (m + 4) and reductive (m + 5) pathways in H1299 cells treated with (+) or without (−) metformin. Cells were treated as in (<b>B</b>), and the abundance of U-[¹³C]-glutamine-labeled m+4 and m+5 citrate was determined by GC-MS. *, <i>p</i> < 0.05; **, <i>p</i> < 0.01; ***, <i>p</i> < 0.001. Raw data for this figure can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002309#pbio.1002309.s003" target="_blank">S3 Data</a>.</p

Cancer cells with defective ETC activity display resistance to the antiproliferative effects of metformin.

<p><b>A.</b> Proliferation of 143B<i>wt</i> and 143B<i>cytb</i> cells cultured in medium containing the indicated doses of metformin. Cell numbers were determined after 72 h of treatment, and are expressed relative to cell counts in control conditions (0 mM metformin). Each data point represents the mean ± SEM for each condition (<i>n</i> = 10). <b>B.</b> Proliferation of 143B<i>wt</i> and 143B<i>cytb</i> cells treated with control siRNA (CTL) or ACL-specific siRNA. Cell counts were determined after 48 h of culture in medium containing 10 mM metformin and expressed relative to cell counts in control conditions. The data represent the mean ± SEM for each condition (<i>n</i> = 10) and are representative of three independent experiments. <b>C.</b> U-[¹³C]-acetate-derived lipogenic acetyl-CoA in 143B<i>wt</i> cells with or without 5 mM metformin treatment for 72 h. <b>D.</b> Proliferation of 143B<i>wt</i> cells cultured in the absence or presence of 5 mM metformin under control (white) or acetate supplementation (black, 5 mM) conditions. Growth curves over time are shown. Each data point represents the mean ± SD for each condition (<i>n</i> = 10), and is representative of three independent experiments. Raw data for this figure can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002309#pbio.1002309.s006" target="_blank">S6 Data</a>.</p

Metformin exerts AMPK-independent effects on cancer cell metabolism.

<p><b>A.</b> Proliferation of H1299 NSCLC cells treated with the indicated concentrations of metformin for 72 h. Cell numbers are expressed relative to cell counts in control conditions (0 mM metformin). Each data point represents the mean ± standard error of the mean (SEM) for triplicate samples. <b>B.</b> Immunoblot of AMPK activation in metformin-treated H1299 cells. H1299 cells were treated for 1 h with various doses of metformin (from left to right: 0, 2.5, 5, and 10 mM), and cell lysates analyzed for AMPK (total and pT172), ACCα (total and pS79), and Raptor (total and pS792) levels. <b>C.</b> ATP:ADP ratio of H1299 cells cultured with varying doses of metformin for 14 h. Ratios are expressed relative to cells grown in complete growth medium. The data represents the mean ± standard deviation (SD) for triplicate samples. <b>D–G.</b> Metabolic characterization of metformin-treated mouse embryonic fibroblasts (MEFs). Wild type (WT) or AMPKα-deficient (knockout, KO) MEFs were cultured in the presence or absence of metformin. Shown are the O₂ consumption rate (OCR) (<b>D</b>) and extracellular acidification rate (ECAR) (<b>E</b>) of cells cultured for 24 h in the presence or absence of 10 mM metformin. Glucose consumption (<b>F</b>) and lactate production (<b>G</b>) were assessed after 48 h of culture with metformin (5 mM). All data are normalized to cell number and represent the mean ± SEM for triplicate samples per condition. The data are representative of three independent experiments. Raw data for this figure can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002309#pbio.1002309.s001" target="_blank">S1 Data</a>.</p