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Keywords = NADH/NAD imbalance

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16 pages, 4792 KiB  
Article
Multiple Cofactor Engineering Strategies to Enhance Pyridoxine Production in Escherichia coli
by Lijuan Wu, Jinlong Li, Yahui Zhang, Zhizhong Tian, Zhaoxia Jin, Linxia Liu and Dawei Zhang
Microorganisms 2024, 12(5), 933; https://doi.org/10.3390/microorganisms12050933 - 3 May 2024
Viewed by 1694
Abstract
Pyridoxine, also known as vitamin B6, is an essential cofactor in numerous cellular processes. Its importance in various applications has led to a growing interest in optimizing its production through microbial biosynthesis. However, an imbalance in the net production of NADH [...] Read more.
Pyridoxine, also known as vitamin B6, is an essential cofactor in numerous cellular processes. Its importance in various applications has led to a growing interest in optimizing its production through microbial biosynthesis. However, an imbalance in the net production of NADH disrupts intracellular cofactor levels, thereby limiting the efficient synthesis of pyridoxine. In our study, we focused on multiple cofactor engineering strategies, including the enzyme design involved in NAD+-dependent enzymes and NAD+ regeneration through the introduction of heterologous NADH oxidase (Nox) coupled with the reduction in NADH production during glycolysis. Finally, the engineered E. coli achieved a pyridoxine titer of 676 mg/L in a shake flask within 48 h by enhancing the driving force. Overall, the multiple cofactor engineering strategies utilized in this study serve as a reference for enhancing the efficient biosynthesis of other target products. Full article
(This article belongs to the Section Microbial Biotechnology)
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Figure 1

Figure 1
<p>Scheme of the biosynthesis pathway of PN in <span class="html-italic">E. coli</span>: glycerol and glucose serve as carbon sources for the production of PN. The orange line represents the heterologous gene introduced in this study. The blue line, along with the accompanying words, illustrates the cofactor-related pathways and enzymes involved. The green box displays the chemical structure of the compounds involved in PN synthesis. Epd, D-erythrose-4-phosphate dehydrogenase; PdxB, erythronate-4-phosphate dehydrogenase; PdxA, 4-hydroxythreonine-4-phosphate dehydrogenase; GapA, glyceraldehyde-3-phosphate dehydrogenase A; GapC, NADP<sup>+</sup>-dependent G3P dehydrogenase; GapN, NADP-dependent glyceraldehyde 3-phosphate dehydrogenase; SerC, 3-phosphoserine aminotransferase; Xfp, xylulose 5-phosphate/fructose 6-phosphate phosphoketolase; PdxJ, PNP synthase; PdxP, PNP phosphatase; GlpD, glycerol-3-phosphate dehydrogenase; GlpK, glycerol kinase; TpiA, triosephosphate isomerase; Pgk, phosphoglycerate kinase; PpsA, phosphoenolpyruvate synthase.</p>
Full article ">Figure 2
<p>Scheme of the biosynthesis pathway of PN in <span class="html-italic">E. coli</span> and the PN titer and cell growth of the introduced <span class="html-italic">xfp</span> strains: PN titer and cell growth of the introduced <span class="html-italic">xfp</span> strains. The data are means ± SD of three independent biological replicates (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 3
<p>Enzyme design of PdxA. (<b>A</b>): The PN titer and cell growth of PdxA mutants with single and double mutations. The data are means ± SD of three independent biological replicates (<span class="html-italic">n</span> = 3). (<b>B</b>): The root-mean-square deviation (RMSD) variations were assessed for the substrate 4HTP and the coenzyme NAD<sup>+</sup> in both the WT and F140I mutant strains throughout the molecular dynamics (MD) process (100 ns production trajectory) in comparison to the initial structures. (<b>C</b>,<b>D</b>): The intermolecular interaction networks between the substrates (4HTP and NAD<sup>+</sup>) and proteins were investigated in the representative conformations of the WT and F140I mutant strains. Hydrogen bond interactions are denoted by yellow dashed lines, metal coordination bonds by green dashed lines, and distance and angle relationships by orange lines. Protein residues are highlighted in magenta, while ligands are represented in cyan.</p>
Full article ">Figure 4
<p>Cofactor engineering through leaky expression of SpNox for PN production. (<b>A</b>): The intracellular concentrations of NAD<sup>+</sup> and NADH for all the main strains. (<b>B</b>): PN titer and cell growth (OD<sub>600</sub>) of WL03 and WL04 were measured after treatment with various concentrations of L-arabinose (Ara) and glucose (Glu). (<b>C</b>): The GFP fluorescence/OD<sub>600</sub> of strain WL05 under varying concentrations of fructose (Fru), Glu, and Ara. (<b>D</b>): The PN titer was determined by sequentially subculturing from the 1st to the 100th generations. (<b>E</b>): Growth of cells in the 1st, 30th, 60th, and 100th generations. (<b>F</b>): The PN titer and cell growth (OD<sub>600</sub>) of strains WL04, WL08, and WL09. The data are means ± SD of three independent biological replicates (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 5
<p>The PN titer, cell growth (OD<sub>600</sub>) and stability of plasmid (%) of the strains. (<b>A</b>): The PN titer and cell growth (OD<sub>600</sub>) of strains WL09, WL158, and WL159. (<b>B</b>): The stability of plasmid (%) of strains WL03, WL04, WL09 and WL159. The data are means ± SD of three independent biological replicates (<span class="html-italic">n</span> = 3), and significance (<span class="html-italic">p</span>-value) was assessed using a two-sided Student’s <span class="html-italic">t</span>-test.</p>
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6 pages, 666 KiB  
Communication
Assessment of NADH/NAD+ Redox Imbalance in Psoriatic Lesions Using the FMSF Technique: Therapeutic Aspects
by Jerzy Gebicki, Tomasz Filipiak, Andrzej Marcinek and Anna Wozniacka
Sensors 2023, 23(21), 8718; https://doi.org/10.3390/s23218718 - 25 Oct 2023
Cited by 3 | Viewed by 2626
Abstract
Mitochondrial dysfunction has been linked to psoriasis, and it may be an important underlying factor contributing to this disease. However, a precise methodology for assessing mitochondrial dysfunction has yet to be developed. One promising approach is to measure NADH autofluorescence from the affected [...] Read more.
Mitochondrial dysfunction has been linked to psoriasis, and it may be an important underlying factor contributing to this disease. However, a precise methodology for assessing mitochondrial dysfunction has yet to be developed. One promising approach is to measure NADH autofluorescence from the affected skin areas. In this study, we show that Flow-Mediated Skin Fluorescence (FMSF) can be used for the non-invasive assessment of mitochondrial dysfunction in psoriasis. The fluorescence level at baseline and the half-time of ischemic growth (t1/2) derived from the FMSF traces can be used for the non-invasive assessment of NADH/NAD+ redox imbalance in psoriatic lesions compared to unaffected skin. These results are supported by an analysis of the key FMSF parameters: Reactive Hyperemia Response (RHR) and Hypoxia Sensitivity (HS). This method not only contributes to understanding the biochemical processes involved in the etiopathogenesis of psoriasis, but it also provides a basis for identifying new drug targets and improving the treatment process. Full article
(This article belongs to the Special Issue Advanced Biosensors for Human Disease Detection and Monitoring)
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<p>Photographs of unaffected skin (<b>a</b>) and psoriatic lesions (<b>b</b>) for a single patient (code 004L) and FMSF traces measured from these areas (<b>c</b>,<b>d</b>).</p>
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28 pages, 1129 KiB  
Review
Bioactive Compounds as Inhibitors of Inflammation, Oxidative Stress and Metabolic Dysfunctions via Regulation of Cellular Redox Balance and Histone Acetylation State
by Hyunju Kang and Bohkyung Kim
Foods 2023, 12(5), 925; https://doi.org/10.3390/foods12050925 - 22 Feb 2023
Cited by 19 | Viewed by 47974
Abstract
Bioactive compounds (BCs) are known to exhibit antioxidant, anti-inflammatory, and anti-cancer properties by regulating the cellular redox balance and histone acetylation state. BCs can control chronic oxidative states caused by dietary stress, i.e., alcohol, high-fat, or high-glycemic diet, and adjust the redox balance [...] Read more.
Bioactive compounds (BCs) are known to exhibit antioxidant, anti-inflammatory, and anti-cancer properties by regulating the cellular redox balance and histone acetylation state. BCs can control chronic oxidative states caused by dietary stress, i.e., alcohol, high-fat, or high-glycemic diet, and adjust the redox balance to recover physiological conditions. Unique functions of BCs to scavenge reactive oxygen species (ROS) can resolve the redox imbalance due to the excessive generation of ROS. The ability of BCs to regulate the histone acetylation state contributes to the activation of transcription factors involved in immunity and metabolism against dietary stress. The protective properties of BCs are mainly ascribed to the roles of sirtuin 1 (SIRT1) and nuclear factor erythroid 2–related factor 2 (NRF2). As a histone deacetylase (HDAC), SIRT1 modulates the cellular redox balance and histone acetylation state by mediating ROS generation, regulating nicotinamide adenine dinucleotide (NAD+)/NADH ratio, and activating NRF2 in metabolic progression. In this study, the unique functions of BCs against diet-induced inflammation, oxidative stress, and metabolic dysfunction have been considered by focusing on the cellular redox balance and histone acetylation state. This work may provide evidence for the development of effective therapeutic agents from BCs. Full article
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<p>Role of bioactive compounds (BCs) in dietary stress-induced inflammation, oxidative stress, and metabolic disturbances. The role of BCs in dietary stress can be divided into two categories. One is directly scavenging or quenching reactive radicals, such as ROS, due to their conjugated double-bond chemical structure. The other role is to activate biological systems through the activation of the enzyme, SIRT1, and the transcription factor, NRF2. The function of SIRT1 is to activate forkhead box protein O (FOXOs) while inactivating NF-κB to suppress inflammation. BC-induced NRF2 activation prevents oxidative stress by activating antioxidants, including superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX). BCs prevent inflammation, oxidative stress, and metabolic disturbances through the activation of SIRT1 and NRF2.</p>
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<p>BCs activate SIRT1 for histone deacetylation, whereas dietary stress stimulates HAT for histone acetylation. Histones are the major components of chromatin and assemble with DNA to form nucleosomes. Dietary stress-induced HATs acetylate histone lysine residues, neutralizing the histone positive charge and enabling inflammatory gene transcription. However, BC-activated SIRT1 removes acetyl groups from histones, leading to chromatin condensation and the inhibition of inflammatory gene transcription.</p>
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16 pages, 7327 KiB  
Article
Effects of Calcium Ions on the Antimicrobial Activity of Gramicidin A
by Shang-Ting Fang, Shu-Hsiang Huang, Chin-Hao Yang, Jen-Wen Liou, Hemalatha Mani and Yi-Cheng Chen
Biomolecules 2022, 12(12), 1799; https://doi.org/10.3390/biom12121799 - 1 Dec 2022
Cited by 8 | Viewed by 1837
Abstract
Gramicidin A (gA) is a linear antimicrobial peptide that can form a channel and specifically conduct monovalent cations such as H+ across the lipid membrane. The antimicrobial activity of gA is associated with the formation of hydroxyl free radicals and the imbalance [...] Read more.
Gramicidin A (gA) is a linear antimicrobial peptide that can form a channel and specifically conduct monovalent cations such as H+ across the lipid membrane. The antimicrobial activity of gA is associated with the formation of hydroxyl free radicals and the imbalance of NADH metabolism, possibly a consequence caused by the conductance of cations. The ion conductivity of gramicidin A can be blocked by Ca2+ ions. However, the effect of Ca2+ ions on the antimicrobial activity of gA is unclear. To unveil the role of Ca2+ ions, we examined the effect of Ca2+ ions on the antimicrobial activity of gramicidin A against Staphylococcus aureus (S. aureus). Results showed that the antimicrobial mechanism of gA and antimicrobial activity by Ca2+ ions are concentration-dependent. At the low gA concentration (≤1 μM), the antimicrobial mechanism of gA is mainly associated with the hydroxyl free radical formation and NADH metabolic imbalance. Under this mode, Ca2+ ions can significantly inhibit the hydroxyl free radical formation and NADH metabolic imbalance. On the other hand, at high gA concentration (≥5 μM), gramicidin A acts more likely as a detergent. Gramicidin A not only causes an increase in hydroxyl free radical levels and NAD+/NADH ratios but also induces the destruction of the lipid membrane composition. At this condition, Ca2+ ions can no longer reduce the gA antimicrobial activity but rather enhance the bacterial killing ability of gramicidin A. Full article
(This article belongs to the Special Issue Functional Peptides and Their Interactions: From Molecules to Systems)
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Figure 1
<p>The growth curve of <span class="html-italic">S. aureus</span> in the presence of gramicidin A 0, 1, 5, and 10 μM, and 1% TFE without gramicidin A, at the different growth phases, (<b>A</b>) lag phase, (<b>B</b>) elongation phase, and (<b>C</b>) stationary phase, respectively. (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.001, related to 0 μM gA).</p>
Full article ">Figure 1 Cont.
<p>The growth curve of <span class="html-italic">S. aureus</span> in the presence of gramicidin A 0, 1, 5, and 10 μM, and 1% TFE without gramicidin A, at the different growth phases, (<b>A</b>) lag phase, (<b>B</b>) elongation phase, and (<b>C</b>) stationary phase, respectively. (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.001, related to 0 μM gA).</p>
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<p>(<b>A</b>) Hydroxyl free radical level for <span class="html-italic">S. aureus</span> under the treatment of 0, 0.1, 1, and 5 μM of gramicidin A, and (<b>B</b>) the NAD<sup>+</sup>/NADH ratio measured for <span class="html-italic">S. aureus</span> under the treatment of 0, 1, and 5 μM of gramicidin A and 0, 30, 60, 90, and 120 min at the elongation state. (<span class="html-italic">n</span> = 9, ** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 2 Cont.
<p>(<b>A</b>) Hydroxyl free radical level for <span class="html-italic">S. aureus</span> under the treatment of 0, 0.1, 1, and 5 μM of gramicidin A, and (<b>B</b>) the NAD<sup>+</sup>/NADH ratio measured for <span class="html-italic">S. aureus</span> under the treatment of 0, 1, and 5 μM of gramicidin A and 0, 30, 60, 90, and 120 min at the elongation state. (<span class="html-italic">n</span> = 9, ** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Effects of calcium ions on the growth rate of <span class="html-italic">S. aureus</span> in the presence of (<b>A</b>) 0–500 mM Ca<sup>2+</sup> concentrations only, (<b>B</b>) 0–500 mM of Ca<sup>2+</sup> ions and 1 μM gA treatment, and (<b>C</b>) 0–500 mM Ca<sup>2+</sup> and 5 μM gA treatment, respectively. (<span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.001, related to 1 μM gA in (<b>B</b>)).</p>
Full article ">Figure 3 Cont.
<p>Effects of calcium ions on the growth rate of <span class="html-italic">S. aureus</span> in the presence of (<b>A</b>) 0–500 mM Ca<sup>2+</sup> concentrations only, (<b>B</b>) 0–500 mM of Ca<sup>2+</sup> ions and 1 μM gA treatment, and (<b>C</b>) 0–500 mM Ca<sup>2+</sup> and 5 μM gA treatment, respectively. (<span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.001, related to 1 μM gA in (<b>B</b>)).</p>
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<p>Hydroxyl radical level in the presence of gA and 10 μM–500 mM of gramicidin A, (<b>A</b>) 1 μM gA/0–10 mM of Ca<sup>2+</sup> ions, (<b>B</b>) 1 μM gA/100–500 mM of Ca<sup>2+</sup> ions, (<b>C</b>) 5 μM gA/0–10 mM of Ca<sup>2+</sup> ions, and (<b>D</b>) 5 μM gA/100–500 mM of Ca<sup>2+</sup> ions, respectively. (<span class="html-italic">n</span> = 9, ** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4 Cont.
<p>Hydroxyl radical level in the presence of gA and 10 μM–500 mM of gramicidin A, (<b>A</b>) 1 μM gA/0–10 mM of Ca<sup>2+</sup> ions, (<b>B</b>) 1 μM gA/100–500 mM of Ca<sup>2+</sup> ions, (<b>C</b>) 5 μM gA/0–10 mM of Ca<sup>2+</sup> ions, and (<b>D</b>) 5 μM gA/100–500 mM of Ca<sup>2+</sup> ions, respectively. (<span class="html-italic">n</span> = 9, ** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>The NAD<sup>+</sup>/NADH ratios for <span class="html-italic">S. aureus</span> treated with (<b>A</b>) 1 and (<b>B</b>) 5 μM gramicidin A and 10, 100, 200, and 500 mM Ca<sup>2+</sup> ions at 0, 30, 60, 90, and 120 min, respectively. (<span class="html-italic">n</span> = 9, ** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Atomic force microscopic morphologies of <span class="html-italic">S. aureus</span> under treatment with gramicidin A and CA<sup>2+</sup> ions, (<b>A</b>) <span class="html-italic">S. aureus</span> only without gA, (<b>B</b>) with 100 mM Ca<sup>2+</sup> ions, (<b>C</b>) with 1 μM gA, (<b>D</b>) with 5 μM gA, (<b>E</b>) with 1 μM gA and 100 mM Ca<sup>2+</sup> ions and (<b>F</b>) with 5 μM gA and 100 mM Ca<sup>2+</sup> ions.</p>
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16 pages, 2736 KiB  
Review
A Synopsis of the Associations of Oxidative Stress, ROS, and Antioxidants with Diabetes Mellitus
by Homer S. Black
Antioxidants 2022, 11(10), 2003; https://doi.org/10.3390/antiox11102003 - 10 Oct 2022
Cited by 47 | Viewed by 3999
Abstract
The Greek physician, Aretaios, coined the term “diabetes” in the 1st Century A.D. “Mellitus” arose from the observation that the urine exhibits a sweetness due to its elevated glucose levels. Diabetes mellitus (DM) accounted for 6.7 million deaths globally in 2021 with expenditures [...] Read more.
The Greek physician, Aretaios, coined the term “diabetes” in the 1st Century A.D. “Mellitus” arose from the observation that the urine exhibits a sweetness due to its elevated glucose levels. Diabetes mellitus (DM) accounted for 6.7 million deaths globally in 2021 with expenditures of USD 966 billion. Mortality is predicted to rise nearly 10-fold by 2030. Oxidative stress, an imbalance between the generation and removal of reactive oxygen species (ROS), is implicated in the pathophysiology of diabetes. Whereas ROS are generated in euglycemic, natural insulin-regulated glucose metabolism, levels are regulated by factors that regulate cellular respiration, e.g., the availability of NAD-linked substrates, succinate, and oxygen; and antioxidant enzymes that maintain the cellular redox balance. Only about 1–2% of total oxygen consumption results in the formation of superoxide anion and hydrogen peroxide under normal reduced conditions. However, under hyperglycemic conditions, about 10% of the respiratory oxygen consumed may be lost as free radicals. Under hyperglycemic conditions, the two-reaction polyol pathway is activated. Nearly 30% of blood glucose can flux through this pathway—a major path contributing to NADH/NAD+ redox imbalance. Under these conditions, protein glycation and lipid peroxidation increase, and inflammatory cytokines are formed, leading to the further formation of ROS. As mitochondria are the major site of intracellular ROS, these organelles are subject to the deleterious effects of ROS themselves and eventually become dysfunctional—a milestone in Metabolic Syndrome (MetS) of which insulin resistance and diabetes predispose to cardiovascular disease. Full article
(This article belongs to the Topic Redox Metabolism)
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Figure 1
<p>Reductive Pathway of Molecular Oxygen. An important alternate step is shown where an excited state species, singlet oxygen, is produced either via the interaction of molecular oxygen with the excited triplet state of another molecule or an energy exchange reaction upon the absorption of energy from another source, e.g., ultraviolet light [<a href="#B22-antioxidants-11-02003" class="html-bibr">22</a>].</p>
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<p>Euglycemic, normal insulin-regulated glucose metabolism. ★ Sites in the respiratory sequence at which low levels of superoxide may be formed through the transfer of electrons via the electron transport chain (ETC). Once glucose moves into the cell, it is retained though phosphorylation by hexokinase and ATP. The product, glucose-6-phosphate, is phosphorylated again to form fructose-1,6-diphosphare prior to splitting into 3-carbon fragments. These 3-carbon fragments are converted to pyruvic acid. All these reactions occur in the cell cytosol. Pyruvic acid enters the mitochondrial matrix and is decarboxylated and oxidized to the 2-carbon, acetyl CoA. This oxidization results in the formation of 2 NADH and the potential formation of low levels of superoxide as the electrons are passed through the ETC. Acetyl CoA enters the Krebs cycle by condensation onto oxaloacetate to form citrate that is decarboxylated and oxidized in the Krebs cycle to form 6 NADH and 2 FADH. These are potential ROS sources as the electrons are passed through the ETC. Flavin mononucleotide (FMN) is a highly oxidative cofactor associated with NADH and FADH dehydrogenases that can accept two electrons to become reduced. The figure depicts GLUT-2, an intestinal glucose transporter that allows effective glucose transport at high glucose concentrations. There are now a wide range of glucose transporters that are tissue specific [<a href="#B23-antioxidants-11-02003" class="html-bibr">23</a>].</p>
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<p>Schema Depicting Major Antioxidant Enzymes Involved in Maintaining Intracellular Redox Balance [<a href="#B22-antioxidants-11-02003" class="html-bibr">22</a>].</p>
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<p>Hyperglycemic, insulin-resistant glucose metabolism. Although ROS are shown being formed at the starred sites of glucose metabolism, the actual formation of ROS occurs as electrons are being transferred from NADH and FADH<sub>2</sub> down the ETC through complexes I, II, III and IV.</p>
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<p>Hexosamine Pathway. GFAT, glutamine:fructose-6-phosphate-aminotransferase; UDP-GlucNAc, Uridine-5-diphosphate-N-acetylglucosamine c; GlutN, Glutamine; Glu, Glutamic acid; UDP, Uridine 5′-diphosphate; Pi, inorganic phosphate.</p>
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<p>PKC Pathway and Pathogenic Effects. <b>DHAP</b>, dihydroxyacetone phosphate; <b>DAG</b>, diacylglycerol [<a href="#B41-antioxidants-11-02003" class="html-bibr">41</a>]; <b>PKC</b>, Protein Kinase C. Diagram depicts effects of isoforms ß and ð, which are both activated by DAG. The upregulation of <b>PAI-1</b>, Plasminogen activator inhibitor-1 (serpin E1), is a risk factor for thrombosis and atherosclerosis [<a href="#B40-antioxidants-11-02003" class="html-bibr">40</a>]; the downregulation of <b>eNOS</b>, Endothelial nitric oxide synthase, leads to vasodilation and upregulation of <b>ET-1</b>, Endothelin-1, a vasoconstrictor [<a href="#B42-antioxidants-11-02003" class="html-bibr">42</a>]; upregulation of <b>VEGF</b>, Vascular endothelial growth factor (a glycoprotein), mediating retinopathy and nephropathy [<a href="#B43-antioxidants-11-02003" class="html-bibr">43</a>]; <b>TGF-ß</b>, Transforming growth factor-beta (a multifunctional cytokine) that is pro-inflammatory and affects host immunity [<a href="#B44-antioxidants-11-02003" class="html-bibr">44</a>]; <b>NF-kß</b>, Nuclear factor-kappa B, a DNA binding protein factor required for the transcription of pro-inflammatory gene expression [<a href="#B45-antioxidants-11-02003" class="html-bibr">45</a>]; <b>NADPH Oxidase</b>, nicotinamide adenine dinucleotide phosphate oxidase (a flavocytochrome B heterodimer), a major source of ROS [<a href="#B46-antioxidants-11-02003" class="html-bibr">46</a>].</p>
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<p>The influence of hyperglycemia on ROS level and activation of polyol pathway, hexosamine pathway, advanced glycation end products, and the PKC pathway, leading to tissue damage and diabetic complications [<a href="#B30-antioxidants-11-02003" class="html-bibr">30</a>]. Acute or chronic hyperglycemia upregulation of ROS production elevates PARP levels and downregulates GADPH levels. The latter activates and upregulates polyol and hexosamine pathways, accelerates the formation of AGE and activate PKC. These actions increase oxidative stress and ultimately impact the diabetic complications depicted.</p>
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<p>Lipid Oxidation and Cell Signaling [<a href="#B52-antioxidants-11-02003" class="html-bibr">52</a>]. FFA, free fatty acid; FATP, free fatty acid transport protein; FACS, free fatty acid acyl-CoA synthase; CPT1, carnitine palmitoyl transferase 1; DAG, diacylglycerol (refer to <a href="#antioxidants-11-02003-f005" class="html-fig">Figure 5</a>); PDH, pyruvate dehydrogenase; PFK, phosphofructokinase; HK, hexokinase; GLUT 4, glucose transporter 4; PKC, protein kinase C; IKKß, inhibitory kß kinase ß; NFkß, nuclear factor kß; P13K, phosphoinositide 3-kinase; PkB/Akt, protein kinase B; IRS-1/IRS-2, Insulin receptor substrate 1 and 2.</p>
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<p>Acute Inflammatory Response. EC, endothelial cells; M, monocyte/macrophage; RBC, red blood cell; ECJ, endothelial cell junction. Upon tissue insult, several vasoactive and chemotactic substances are released at the injury site. The vasoactive substances act upon the endothelial cells of the venule, producing vascular effects. The activated macrophages escape through the endothelial cell junctions and are attracted to the inflammatory site where cytokines are released [<a href="#B60-antioxidants-11-02003" class="html-bibr">60</a>,<a href="#B61-antioxidants-11-02003" class="html-bibr">61</a>,<a href="#B62-antioxidants-11-02003" class="html-bibr">62</a>].</p>
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<p>Pro-Inflammatory Leukotrienes (LT) and Prostaglandins (PG) Metabolized from Arachidonic Acid (AA). Isoforms of phospholipase A<sub>2</sub> have been reported to be activated by ROS [<a href="#B63-antioxidants-11-02003" class="html-bibr">63</a>]. phospholipase A<sub>2</sub> cleaves AA from cell membrane phospholipids. AA is oxidized through the lipoxygenase pathway to yield leukotrienes, eicosanoid inflammatory mediators, which are released by macrophages and are involved in the inflammatory reactions [<a href="#B64-antioxidants-11-02003" class="html-bibr">64</a>]. LTB<sub>4</sub> is a potent chemotactic agent. The prostaglandins are derived from AA and metabolized through the cyclooxygenase pathway. They are involved in the inflammatory response as well as other pathogenic mechanisms [<a href="#B65-antioxidants-11-02003" class="html-bibr">65</a>]. PGE<sub>2</sub> is a potent pro-inflammatory PG and is involved in all the signs of inflammation, although it also can exert anti-inflammatory effects during neuroinflammation.</p>
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23 pages, 4749 KiB  
Article
Glutamate-Induced Deregulation of Krebs Cycle in Mitochondrial Encephalopathy Lactic Acidosis Syndrome Stroke-Like Episodes (MELAS) Syndrome Is Alleviated by Ketone Body Exposure
by Sophie Belal, David Goudenège, Cinzia Bocca, Florent Dumont, Juan Manuel Chao De La Barca, Valérie Desquiret-Dumas, Naïg Gueguen, Guillaume Geffroy, Rayane Benyahia, Selma Kane, Salim Khiati, Céline Bris, Tamas Aranyi, Daniel Stockholm, Aurore Inisan, Aurélie Renaud, Magalie Barth, Gilles Simard, Pascal Reynier, Franck Letournel, Guy Lenaers, Dominique Bonneau, Arnaud Chevrollier and Vincent Procaccioadd Show full author list remove Hide full author list
Biomedicines 2022, 10(7), 1665; https://doi.org/10.3390/biomedicines10071665 - 11 Jul 2022
Cited by 11 | Viewed by 3605
Abstract
(1) Background: The development of mitochondrial medicine has been severely impeded by a lack of effective therapies. (2) Methods: To better understand Mitochondrial Encephalopathy Lactic Acidosis Syndrome Stroke-like episodes (MELAS) syndrome, neuronal cybrid cells carrying different mutation loads of the m.3243A > G [...] Read more.
(1) Background: The development of mitochondrial medicine has been severely impeded by a lack of effective therapies. (2) Methods: To better understand Mitochondrial Encephalopathy Lactic Acidosis Syndrome Stroke-like episodes (MELAS) syndrome, neuronal cybrid cells carrying different mutation loads of the m.3243A > G mitochondrial DNA variant were analysed using a multi-omic approach. (3) Results: Specific metabolomic signatures revealed that the glutamate pathway was significantly increased in MELAS cells with a direct correlation between glutamate concentration and the m.3243A > G heteroplasmy level. Transcriptomic analysis in mutant cells further revealed alterations in specific gene clusters, including those of the glutamate, gamma-aminobutyric acid pathways, and tricarboxylic acid (TCA) cycle. These results were supported by post-mortem brain tissue analysis from a MELAS patient, confirming the glutamate dysregulation. Exposure of MELAS cells to ketone bodies significantly reduced the glutamate level and improved mitochondrial functions, reducing the accumulation of several intermediate metabolites of the TCA cycle and alleviating the NADH-redox imbalance. (4) Conclusions: Thus, a multi-omic integrated approach to MELAS cells revealed glutamate as a promising disease biomarker, while also indicating that a ketogenic diet should be tested in MELAS patients. Full article
(This article belongs to the Special Issue Mitochondrial Genetics and Pathologies)
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Figure 1
<p>Metabolomic analysis between MELAS and control cells. (<b>A</b>) Unsupervised Principal Component Analysis (PCA) scatter plot carried on metabolomics data from parental control cells (n = 10, green dots) and mutant (MT, blue dots) cells with different m.3243A &gt; G mutation loads (n = 30). The first two principal components (PC1 and PC2) explain more than 75% of the total variance. Control and mutant cells clearly group separately with control cells plotting in the upper right quadrant of the first principal plan determined by PC1 and PC2. (<b>B</b>) Supervised Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) scatter plot model aiming at classifying parental control cells from mutant cells based on the metabolomic data matrix. As expected from the PCA plot, both populations are very well separated in a predictive and non-overfitted model. Predictive (pLV) and orthogonal (oLV) latent variables are dimensionless. (<b>C</b>) OPLS score plot of MELAS cells with different MT loads. MT cybrids are separated according to the mutation load: 70% (blue circles), 90% (green circles), and 98% (red circles), along with the predictive latent variable (pLV). (<b>D</b>) Volcano plot obtained from the supervised OPLS models for MT cells with 70%, 90% to 98% mutation loads vs parental cells (<a href="#biomedicines-10-01665-f001" class="html-fig">Figure 1</a>B). Only the most discriminating metabolites with high Variable importance on projection (VIP Ipiab and their loading rescaled as the correlation coefficient between the predictive latent variable and the corresponding metabolite or Pcorr (≥ 0.02 or ≤−0.02) have been labelled. Negative coefficients (left) indicate diminished metabolite concentrations in MT cells versus parental cells, whereas positive coefficients (right) indicate increased metabolite concentrations. (<b>E</b>) Volcano plot for the OPLS-DA model obtained from the metabolomic analysis of MELAS cells with 70%, 90%, and 98% mutation loads (<a href="#biomedicines-10-01665-f001" class="html-fig">Figure 1</a>C). Only the most discriminating metabolites with high variable importance in the projection (VIP) values (&gt;1) and Pcorr values (OPLS-DA model obtained from the metabolomic analysis of MELAS cells with 70%, 90%, 98% mutation loads (<a href="#biomedicines-10-01665-f001" class="html-fig">Figure 1</a>C). Only the most discriminating metabolites with high variable importance in the projection (VIP) values (&gt;1) and amino acids and biogenic amines are represented as green bubbles; phosphatidylcholines (PC) as yellow bubbles and lysophosphatidylcholines (lysoPC) as pink bubbles. In PC, “aa” indicates that both moieties at the sn-1 and sn-2 positions are fatty acids and bound to the glycerol backbone via ester bonds, whilst “ae” denotes that one of the moieties, either in the sn-1 or sn-2 position is a fatty alcohol and bound via an ether bond. For lysoPCs and PCs, the total number of carbon atoms and double bonds present in the lipid fatty acid chain(s) are denoted as “C x:y”, where x is the total carbon number (of both chains for PCs) and y is the total number of double bonds. Ala: Alanine; alpha-AAA: α-Aminoadipic acid; Ac-Orn: Acetylornithine; Asp: Aspartate; c4-OH-Pro: cis-4-Hydroxyproline; DOPA: 3,4-Dihydroxyphenylalanine; Gln: Glutamine; Glu: Glutamate; His: Histidine; Ile: Isoleucine; Leu: Leucine; Met: Methionine; Orn: Ornithine; Phe: Phenylalanine; Thr: Threonine; Trp: Tryptophane; Tyr: Tyrosine; Val: Valine. The metabolic signature is characterised by lower levels of 6 acylcarnitines (C0, C2, C4, C16, C18, C18:1) (blue bubbles), 10 amino acids and biogenic amines (green bubbles) and higher levels of several PC (yellow bubbles) and sphingomyelins (orange bubbles). Ala: Alanine, Gln: Glutamine, Ser: Serine, Lys: Lysine, Pro: Proline, Gly: Glycine, Arg: Arginine, Taurine, Serotonin, and Spermine.</p>
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<p>Glutamate concentration is correlated with complex I deficiency in MELAS cells. (<b>A</b>) Intracellular levels of glutamate in control (Ctrl) and mutant (MT) cells (70%, 90%, and 98%). (<b>B</b>) Biochemical assessment of mitochondrial complex I activity in Ctrl and MT cells (70%, 90%, and 98%). (<b>C</b>) Intracellular level of glutamate in Ctrl cells treated for 15 h with rotenone (200 nM) or a vehicle. (<b>D</b>) Biochemical assessment of mitochondrial complex I activity in Ctrl cells treated for 15 h with rotenone or a vehicle. (<b>E</b>) Extracellular glutamate levels. Ctrl: control cells and MT cells carrying different mutation loads (70%, 90%, and 98%). (<b>F</b>) Intracellular glutamate levels in Ctrl and 98% MT cells with (+) or without (−) the addition of glutamine. Results are presented as the mean ± SEM relative to Ctrl cells of at least 4 independent experiments. Statistical differences between MT and Ctrl cells are indicated with an asterisk (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Gene expression profiling of mutant cells. (<b>A</b>) Principal component analysis (PCA) and unsupervised clustering of MT (red) vs Ctrl cells (blue). (<b>B</b>) Heatmap diagram of two-way hierarchical clustering analysis of the 4943 probes, showing different expression levels with a <span class="html-italic">p</span>-value ≤ 0.05 and abs (FC) ≥ 1.5. Red and green colours represent an expression level above or lower than the mean, respectively. The X-axis represents samples with, from the left to the right, control cells compared to 98% MT cells (n = 4) while the Y-axis represents Illumina probes. (<b>C</b>) Volcano plot representation of the differentially expressed genes in a pairwise comparison of control vs 98% MT cells. The significant cut-off was set at a <span class="html-italic">p</span>-value ≤ 0.05 and abs (FC) ≥ 1.5. Differentially expressed genes annotated as glutamate-glutamine metabolism, GABA, and TCA cycle in the REACTOME pathway database (see <a href="#biomedicines-10-01665-t001" class="html-table">Table 1</a>) are labelled with their corresponding gene symbols.</p>
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<p>Treatment with ketone bodies restores a normal intracellular glutamate concentration and improves the mitochondrial network in MELAS cells. (<b>A</b>) Intracellular and (<b>B</b>) extracellular glutamate levels in Ctrl and 98% MT cells treated for 48 h with (+) or without (−) KB. Results are from at least four independent experiments, expressed as the mean ± SEM relative to Ctrl cells. (* <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) Cell growth of 98% MT cells cultured in a standard medium (SM, light green curve), or exposed to KB (orange curve), or with 50 µM glutamate (Glu) and KB (red curve) or a standard medium (SM + Glu, green curve). (<b>D</b>) Mitochondrial morphology, and percentages of fragmented (black) or connected (white) mitochondria in 98% MT cells with (+) or without (−) KB, and with or without glutamate (30 µM). (<b>E</b>) Representative images showing the MitoTracker (green fluorescence) and Hoechst (blue fluorescence) staining of 98% MT cells, incubated for 24 h in E-1: standard medium, E-2: with KB, E-3: with glutamate (Glu), and E-4: with Glu and KB. Scale Bar: 10 um.</p>
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<p>Treatment with ketone bodies improves mitochondrial respiration and enzyme activities in MELAS cells. (<b>A</b>) Oxygraphic measurements of routine (<b>B</b>) and maximal respiration capacity in Ctrl and 98% MT cells, treated with or without KB for 48 h. (<b>C</b>) Enzyme activities of mitochondrial complex I, II, and SDH, relative to citrate synthase (CS) in control and 98% MT cells, treated for 48 h with or without KB. Results are presented as the mean ± SEM, relative to Ctrl cells, of at least 4 independent experiments. Statistical differences between 98% MT and Ctrl cells are indicated with an asterisk (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The Glutamate and GABA metabolic pathways are altered in MELAS cells. (<b>A</b>) Graphical representation of the glutamate pathway and TCA cycle. GAD1 (glutamate decarboxylase), ABAT (4 aminobutyrate transaminase), and GDH (glutamate dehydrogenase). (<b>B</b>) Measurement of GDH activity, (<b>C</b>) intracellular levels of αKG concentration, and (<b>D</b>) intracellular levels of GABA in Ctrl and 98% MT cells, exposed for 48 h with (+) or without (−) KB. (<b>E1</b>) Western blots showing GAD1, ABAT, and GDH expression profiles in Ctrl and 98% MT cells, treated for 48 h with (+) or without (−) KB. (<b>E2</b>) Quantification of GAD1, ABAT, and GDH relative expression related to tubulin and actin in Ctrl and 98% MT cells treated with (+) or without (−) KB. Results are presented as the mean ± SEM, relative to Ctrl cells of at least 4 independent experiments. Statistical differences between 98% MT and Ctrl cells are indicated with an asterisk (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>TCA cycle dysfunction in MELAS cells is alleviated by ketone bodies. (<b>A</b>) Pyruvate, (<b>B</b>) lactate, (<b>C</b>) citrate, (<b>D</b>) αKG, (<b>E</b>) succinate, (<b>F</b>) fumarate, and (<b>G</b>) malate levels in Ctrl and 98% MT cells treated for 48 h with (+, dotted line) or without (−, colour bar) ketone bodies (KB). Results are presented as the mean ± SEM relative to Ctrl cells of at least 4 independent experiments. Statistical differences between 98% MT and Ctrl cells are indicated with an asterisk (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The glutamate pathway is altered in the brain tissue of a patient with MELAS. Immunohistochemical analysis of paraffin-embedded human frontal brain tissue labelled with GDH (<b>A1</b>,<b>A2</b>), GAD1 (<b>B1</b>,<b>B2</b>), and ABAT (<b>C1</b>,<b>C2</b>) antibodies, from Ctrl individuals (left panel) and a patient with MELAS (right panel). Immunohistochemical staining intensities of GDH (<b>A2</b>), GAD1 (<b>B2</b>), and ABAT (<b>C2</b>) were examined microscopically and scored semi-quantitatively as part of two independent analyses on five Ctrl individuals and one patient with MELAS as follows: 0 = absent, + = mild, ++ = moderate, and +++ = intense. FL: frontal lobe; LN: lentiform nucleus; T+SN: thalamus + subthalamic nucleus, C: cerebellum.</p>
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<p>Graphical representation of metabolic pathways of MELAS cells (<b>A</b>) untreated (<b>B</b>) or treated with ketone bodies (KB). +: metabolite increase. –: metabolite reduction, = metabolite unchanged. <tt>↑</tt>: increased gene expression. <tt>↓</tt>: decreased gene expression. Metabolic consequences of KB treatment on mitochondrial metabolism are summarised in 4 main steps: 1. significant reduction of glutamate concentration; 2. reduction of the accumulation of TCA intermediates restoring the physiological function of the TCA cycle; 3. re-equilibration of the redox/NADH balance; 4 improving complex I enzyme activity.</p>
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13 pages, 1661 KiB  
Article
The Role of Acetate Kinase in the Human Parasite Entamoeba histolytica
by Thanh Dang, Matthew Angel, Jin Cho, Diana Nguyen and Cheryl Ingram-Smith
Parasitologia 2022, 2(2), 147-159; https://doi.org/10.3390/parasitologia2020014 - 16 Jun 2022
Viewed by 2621
Abstract
The human parasite Entamoeba histolytica, which causes approximately 100 million cases of amoebic dysentery each year, relies on glycolysis as the major source of ATP production from glucose as it lacks a citric acid cycle and oxidative phosphorylation. Ethanol and acetate, the [...] Read more.
The human parasite Entamoeba histolytica, which causes approximately 100 million cases of amoebic dysentery each year, relies on glycolysis as the major source of ATP production from glucose as it lacks a citric acid cycle and oxidative phosphorylation. Ethanol and acetate, the two major glycolytic end products for E. histolytica, are produced at a ratio of 2:1 under anaerobic conditions, creating an imbalance between NADH production and utilization. In this study we investigated the role of acetate kinase (ACK) in acetate production during glycolysis in E. histolytica metabolism. Analysis of intracellular and extracellular metabolites demonstrated that acetate levels were unaffected in an ACK RNAi cell line, but acetyl-CoA levels and the NAD+/NADH ratio were significantly elevated. Moreover, we demonstrated that glyceraldehyde 3-phosphate dehydrogenase catalyzes the ACK-dependent conversion of acetaldehyde to acetyl phosphate in E. histolytica. We propose that ACK is not a major contributor to acetate production, but instead provides a mechanism for maintaining the NAD+/NADH balance during ethanol production in the extended glycolytic pathway. Full article
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<p>Ethanol and acetate production in <span class="html-italic">E. histolytica</span>. ADHE (<b>left</b>) catalyzes production of ethanol from acetyl-CoA. ACD (<b>middle</b>) and ACK (<b>right</b>) produce acetate from acetyl-CoA and acetyl phosphate, respectively.</p>
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<p>ACK expression and activity in the <span class="html-italic">EhACK</span> RNAi cell line. (<b>a</b>) Expression of <span class="html-italic">EhACK</span> in the wild-type (WT), control LUC RNAi, and <span class="html-italic">EhACK</span> RNAi cell lines was examined by RT-PCR (top). Expression of a constitutive control gene encoding a small ribosomal subunit was used as a loading control (bottom). Each RT-PCR reaction was performed in triplicate. (<b>b</b>) ACK activity in the acetate-forming direction was measured using the reverse hydroxamate assay. Activities are the mean ± standard deviation of three replicates. All specific activities are normalized to that observed for extracts from the wild-type, represented as 100%.</p>
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<p>Growth of the <span class="html-italic">ACK</span> RNAi cell line in (<b>a</b>) TYI glucose medium, and (<b>b</b>) TYI low glucose medium. Open circles (○), wild-type; closed circles (●), <span class="html-italic">LUC</span> RNAi cell line; gray squares (<span style="color:#A9A9A9">■</span>), <span class="html-italic">EhACK</span> RNAi cell line. Cell counts are the mean ± standard deviation of three biological replicates.</p>
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<p>Intracellular metabolite levels in <span class="html-italic">ACK</span> RNAi cells. Metabolites were extracted using methanol extraction from log-phase trophozoites and concentrations were measured using LC-MS/MS. (<b>a</b>) Concentrations of acetyl-CoA and ATP. Wild-type (■), <span class="html-italic">LUC</span> RNAi (<span style="color:#A9A9A9">■</span>), <span class="html-italic">EhACK</span> RNAi cells (<span style="color:#DCDCDC">■</span>). (<b>b</b>) Ratio of NAD<sup>+</sup>/NADH, normalized to wild-type ratio. Measurements are the mean ± standard deviation of three to five replicates. ** <span class="html-italic">p</span>-value ≤ 0.01; **** <span class="html-italic">p</span>-value ≤ 0.0001.</p>
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<p>Extracellular ethanol and acetate levels in spent TYI glucose medium. Ethanol (■) and acetate (<span style="color:#A9A9A9">■</span>) were measured in spent medium from cultures of wild-type, <span class="html-italic">LUC</span> RNAi, and <span class="html-italic">ACK</span> RNAi cell lines grown in TYI glucose medium for 48 h. The results shown represent the mean ± standard deviation for four to five biological replicates for each cell line. Unpaired <span class="html-italic">t</span>-test revealed no statistical difference between cell lines for either ethanol or acetate.</p>
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<p>Growth of <span class="html-italic">EhACK</span> RNAi cells in basal medium supplemented with short chain fatty acids (SCFAs). Cells were grown for 72 h in TYI basal medium or TYI basal medium supplemented with acetate (Ac), propionate (Prop), or butyrate (But). Wild-type (■), <span class="html-italic">LUC</span> RNAi (<span style="color:#A9A9A9">■</span>), <span class="html-italic">EhACK</span> RNAi cells (<span style="color:#DCDCDC">■</span>). Cell counts are the mean ± standard deviation of three biological replicates.</p>
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<p>Effects of oxidative and nitrosative stress on <span class="html-italic">ACK</span> RNAi cells. Log-phase trophozoites in liquid medium were exposed to (<b>a</b>) 5 mM hydrogen peroxide (final concentration) for three hours at 37 °C to examine the effects of oxidative stress or to (<b>b</b>) 5 mM sodium nitroprusside (final concentration) for three hours at 37 °C to examine the effects of nitrosative stress. Viability for TYI glucose-grown (■) and TYI basal-grown (<span style="color:#A9A9A9">■</span>) cells was determined using trypan blue exclusion. Values shown are the mean ± SD of three biological replicates. Unpaired <span class="html-italic">t</span>-test showed statistically significant difference in viability reduction in response to oxidative stress when grown on TYI glucose medium compared to growth on TYI basal medium.</p>
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<p>The extended glycolytic pathway in <span class="html-italic">E. histolytica</span> and the proposed role for ACK and GAPDH. Abbreviations are as follows: PFOR: pyruvate:ferredoxin oxidoreductase; ADHE: alcohol/aldehyde dehydrogenase; GAPDH: glyceraldehyde 3-phosphate dehydrogenase; ACK: acetate kinase; ACD: acetyl-CoA synthetase (ADP-forming).</p>
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28 pages, 3994 KiB  
Article
Targeting Glioblastoma via Selective Alteration of Mitochondrial Redox State
by Akira Sumiyoshi, Sayaka Shibata, Zhivko Zhelev, Thomas Miller, Dessislava Lazarova, Ichio Aoki, Takayuki Obata, Tatsuya Higashi and Rumiana Bakalova
Cancers 2022, 14(3), 485; https://doi.org/10.3390/cancers14030485 - 19 Jan 2022
Cited by 16 | Viewed by 3970
Abstract
Glioblastoma is one of the most aggressive brain tumors, characterized by a pronounced redox imbalance, expressed in a high oxidative capacity of cancer cells due to their elevated glycolytic and mitochondrial oxidative metabolism. The assessment and modulation of the redox state of glioblastoma [...] Read more.
Glioblastoma is one of the most aggressive brain tumors, characterized by a pronounced redox imbalance, expressed in a high oxidative capacity of cancer cells due to their elevated glycolytic and mitochondrial oxidative metabolism. The assessment and modulation of the redox state of glioblastoma are crucial factors that can provide highly specific targeting and treatment. Our study describes a pharmacological strategy for targeting glioblastoma using a redox-active combination drug. The experiments were conducted in vivo on glioblastoma mice (intracranial model) and in vitro on cell lines (cancer and normal) treated with the redox cycling pair menadione/ascorbate (M/A). The following parameters were analyzed in vivo using MRI or ex vivo on tissue and blood specimens: tumor growth, survival, cerebral perfusion, cellular density, tissue redox state, expression of tumor-associated NADH oxidase (tNOX) and transforming growth factor-beta 1 (TGF-β1). Dose-dependent effects of M/A on cell viability, mitochondrial functionality, and redox homeostasis were evaluated in vitro. M/A treatment suppressed tumor growth and significantly increased survival without adverse side effects. This was accompanied by increased oxidative stress, decreased reducing capacity, and decreased cellular density in the tumor only, as well as increased cerebral perfusion and down-regulation of tNOX and TGF-β1. M/A induced selective cytotoxicity and overproduction of mitochondrial superoxide in isolated glioblastoma cells, but not in normal microglial cells. This was accompanied by a significant decrease in the over-reduced state of cancer cells and impairment of their “pro-oncogenic” functionality, assessed by dose-dependent decreases in: NADH, NAD+, succinate, glutathione, cellular reducing capacity, mitochondrial potential, steady-state ATP, and tNOX expression. The safety of M/A on normal cells was compromised by treatment with cerivastatin, a non-specific prenyltransferase inhibitor. In conclusion, M/A differentiates glioblastoma cells and tissues from normal cells and tissues by redox targeting, causing severe oxidative stress only in the tumor. The mechanism is complex and most likely involves prenylation of menadione in normal cells, but not in cancer cells, modulation of the immune response, a decrease in drug resistance, and a potential role in sensitizing glioblastoma to conventional chemotherapy. Full article
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<p>(<b>A</b>) Effect of single intracranial injection (5 μL) of menadione/ascorbate (M/A) on tumor growth in the brain of U87MG glioblastoma-grafted mice, detected by T<sub>2</sub>-weighted magnetic resonance imaging (MRI) within 35 days after cell transplantation and 28 days after drug administration (70 μg/7 mg of M/A per kg body weight). The drug was administered on day 7 of the brain cell transplant, when the tumor size was 14.17 ± 4.5 mm<sup>3</sup> in the control group and 22.0 ± 6.4 mm<sup>3</sup> in the M/A-treated group. Number of mice in each experimental group: control group (<span class="html-italic">n</span> = 7); M/A-treated group (<span class="html-italic">n</span> = 5). Data are the mean ± SD from 3 mice at each time point. (<b>B</b>) Comparison of tumor size between control group and M/A-treated group, measured 3 weeks after intracranial injection of saline solution or M/A injection (*** <span class="html-italic">p</span> &lt; 0.001 versus control group). (<b>C</b>) Comparison of tumor size in the control group, detected before and 1 week after intracranial injection of saline solution (*** <span class="html-italic">p</span> &lt; 0.001 versus before injection). (<b>D</b>) Comparison of tumor size in the M/A-treated group, detected before and 1 week after intracranial injection of M/A. (<b>E</b>) Effect of single intracranial injection of M/A on survival of U87MG glioblastoma-grafted mice. Red arrow indicates the time of injection (day 7 after cell transplantation). Data are the mean ± SD from 7 mice in the control group and 5 mice in the M/A-treated group. (<b>F</b>) Median survival of mice in the groups described in (<b>E</b>) (** <span class="html-italic">p</span> &lt; 0.01 versus control group). Data are the mean ± SD from 7 mice in the control group and 5 mice in the M/A-treated group. (<b>G</b>) Dynamics of body weight of control and M/A-treated glioblastoma-grafted mice. Red arrow indicates the time of injection (day 7 after cell transplantation). At each time point, the data are the mean ± SD from 2–7 mice in the control group and 2–5 mice in the M/A-treated group, depending on their survival. (<b>H</b>) Hematological parameters analyzed in healthy mice before and after intravenous administration of M/A (140 μg/14 mg per kg body weight). * INR—international normalized ratio (reference value ≤ 1.1); PT—prothrombin time. Data are the mean ± SD from 3 mice in each group with three measurements for each specimen in the case of Hb and Hct, and six measurements for each specimen in the case of INR. (<b>I</b>–<b>K</b>) Multiparametric MRI analysis in M/A-treated and untreated glioblastoma mice (U87MG intracranial model). (<b>I</b>) Definition of regions of interest (tumor area and contralateral hemisphere). (<b>J</b>) Effect of M/A on cerebral perfusion (cerebral blood flow, CBF) and (<b>K</b>) apparent diffusion coefficient (ADC). Absolute values of CBF and ADC were detected in the tumor area and contralateral hemisphere of the brain. Both parameters were analyzed 21 days after cell transplantation and 14 days after drug administration. Data are the mean ± SD from 3 mice in each group with two measurements (slices) per mouse. * <span class="html-italic">p</span> &lt; 0.05, M/A-treated tumor or contralateral hemisphere versus subsequent untreated (control) tumor or contralateral hemisphere; <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 for CBF and <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05 for ADC, contralateral hemisphere versus tumor hemisphere in untreated mice; <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 for CBF and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 for ADC, contralateral hemisphere versus tumor hemisphere in M/A-treated mice.</p>
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<p>Redox imaging in glioblastoma-bearing mice using nitroxide-enhanced MRI. (<b>A</b>) Definition of regions of interest (ROIs): ROI1—tumor area; ROI2—contralateral hemisphere; ROI3—non-brain tissues (black and white image), and representative nitroxide-enhanced magnetic resonance images of glioblastoma-bearing brain and healthy brain, obtained 5 min after intravenous injection of nitroxide probe (mito-TEMPO)—a marker of tissue redox activity (color images). Color images—calculated extracted MRI signal obtained after injection of nitroxide probe and normalized to the baseline (native) signal obtained before injection. (<b>B</b>–<b>D</b>) Kinetic curves of nitroxide-enhanced MRI signal in U87MG glioblastoma-grafted mice (M/A treated and untreated) and healthy untreated mice. Kinetic curves were analyzed 7 and 14 days after drug administration. Data are the mean ± SD from 6 mice in each group. (<b>G</b>–<b>I</b>) Integrated areas under the kinetic curves shown in D, E, and F, respectively. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. (<b>H</b>) Total reducing capacity of tissues isolated from untreated and M/A-treated glioblastoma-bearing mice. (<b>I</b>,<b>J</b>) Expression of tNOX (<b>I</b>) and TGF-β1 (<b>J</b>) in the brain tissue and serum, respectively, isolated from untreated and M/A-treated glioblastoma-bearing mice. In (<b>B</b>–<b>G</b>), data are the mean ± SD from 3 mice in each group with three measurements (slices) per mouse. In (<b>H</b>–<b>J</b>), data are the mean ± SD from 3 mice in each group with three measurements for each specimen. Tissue and blood specimens were collected 1 week after the start of M/A administration and 2 weeks after cell transplantation. Treatment of mice was the same as described in <a href="#cancers-14-00485-f001" class="html-fig">Figure 1</a>. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 versus the untreated group.</p>
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<p>Effects of menadione/ascorbate (M/A) on mitochondrial and cellular redox state and viability. (<b>A</b>) Concentration-dependent and time-dependent effects of M/A on proliferation and viability of glioblastoma cells (U87MG). (<b>B</b>) Concentration-dependent and time-dependent effects of M/A on viability of normal microglial cells (EOC2). (<b>C</b>) Concentration-dependent effect of M/A on the induction of apoptosis in glioblastoma (blue columns) and normal microglial cells (red columns) after 48 h of incubation. (<b>D</b>) Concentration-dependent effects of M/A on steady-state levels of mitochondrial superoxide in normal (red columns) and glioblastoma cells (blue columns), analyzed after 48 h of incubation in humidified atmosphere. (<b>E</b>) Concentration-dependent effects of M/A on parameters representative of mitochondrial and cellular redox homeostasis: mitochondrial membrane potential (ψ<sub>0</sub>), succinate, NADH, NAD<sup>+</sup>, total glutathione (GSH and GSSG), total reducing capacity (TRC), and tumor-associated NADH oxidase (tNOX). All parameters were analyzed after incubation of glioblastoma cells (U87MG) with M/A for 48 h in humidified atmosphere. (<b>F</b>) Effect of cerivastatin (5 μM) on viability of M/A-treated glioblastoma cells (U87MG) and normal microglial cells (EOC2) after 48 h of incubation. The cells in the control sample were treated with cerivastatin only. The initial number of cells in all samples was 0.6 × 10<sup>5</sup> cells per well. Data are the mean ± SD from three independent experiments with two parallel measurements for each experiment in (<b>A</b>–<b>D</b>,<b>F</b>), and two independent experiments with four parallel measurements for each experiment in (<b>E</b>). In all charts, the value of each parameter in the untreated (control) samples was considered as 100% (red dashed lines). All differences exceeding 15% were statistically significant.</p>
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<p>Potential molecular mechanism(s) for selective targeting of cancer cells by M/A via specific redox cycling in the overloaded and overcharged cancerous mitochondria due to down-regulation of UBIAD1 and inhibition of menadione prenylation, and up-regulation of vitamin C transporters in cancer cells. Role of tNOX and TGF-β1 in M/A-mediated anticancer effect on cancer-bearing organisms.</p>
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18 pages, 1297 KiB  
Review
NADH/NAD+ Redox Imbalance and Diabetic Kidney Disease
by Liang-Jun Yan
Biomolecules 2021, 11(5), 730; https://doi.org/10.3390/biom11050730 - 14 May 2021
Cited by 29 | Viewed by 8667
Abstract
Diabetic kidney disease (DKD) is a common and severe complication of diabetes mellitus. If left untreated, DKD can advance to end stage renal disease that requires either dialysis or kidney replacement. While numerous mechanisms underlie the pathogenesis of DKD, oxidative stress driven by [...] Read more.
Diabetic kidney disease (DKD) is a common and severe complication of diabetes mellitus. If left untreated, DKD can advance to end stage renal disease that requires either dialysis or kidney replacement. While numerous mechanisms underlie the pathogenesis of DKD, oxidative stress driven by NADH/NAD+ redox imbalance and mitochondrial dysfunction have been thought to be the major pathophysiological mechanism of DKD. In this review, the pathways that increase NADH generation and those that decrease NAD+ levels are overviewed. This is followed by discussion of the consequences of NADH/NAD+ redox imbalance including disruption of mitochondrial homeostasis and function. Approaches that can be applied to counteract DKD are then discussed, which include mitochondria-targeted antioxidants and mimetics of superoxide dismutase, caloric restriction, plant/herbal extracts or their isolated compounds. Finally, the review ends by pointing out that future studies are needed to dissect the role of each pathway involved in NADH-NAD+ metabolism so that novel strategies to restore NADH/NAD+ redox balance in the diabetic kidney could be designed to combat DKD. Full article
(This article belongs to the Special Issue Redox Imbalance and Mitochondrial Abnormalities in Kidney Disease)
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Graphical abstract

Graphical abstract
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<p>The conventional metabolic pathways that generate NADH from NAD<sup>+</sup>. Shown are the glycolytic pathway, fatty acid oxidation, and the Krebs cycle. These are the major pathways that store electrons in NADH by breaking the chemical bonds in dietary components including glucose, fatty acids. Enzymes involved in direct production of NADH are also indicated in the diagram.</p>
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<p>The polyol pathway. This pathway contains two reactions. The first reaction converting glucose to sorbitol is catalyzed by aldose reductase. This enzyme is rate-limiting for the whole pathway. The second reaction converting sorbitol to fructose is catalyzed by sorbitol dehydrogenase. The final products are NADH and fructose, and sorbitol is an intermediate product. Note that NADPH is consumed by aldose reductase in the first reaction. Additionally, accumulation of sorbitol in the kidney could cause osmotic problems for nephrons [<a href="#B63-biomolecules-11-00730" class="html-bibr">63</a>,<a href="#B64-biomolecules-11-00730" class="html-bibr">64</a>].</p>
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<p>Major pathways that consume NAD<sup>+</sup>. Shown are (<b>A</b>) the poly ADP ribosylase reaction; (<b>B</b>) the sirtuin-catalyzed deacetylation reaction; (<b>C</b>) the CD38 NAD<sup>+</sup> degradation pathway; (<b>D</b>) the NAD kinase pathway converting NAD<sup>+</sup> to NADP<sup>+</sup>. All the shown pathways or reactions use NAD<sup>+</sup> as the respective enzyme’s substrate.</p>
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<p>Diagram summarizing the pathways that cause NADH increase and NAD<sup>+</sup> decrease in the diabetic kidneys. Regeneration of NAD<sup>+</sup> from NADH by either mitochondrial complex I or lactate dehydrogenase (under hypoxic conditions) is also shown.</p>
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<p>Mitochondrial dysfunction driven by NADH/NAD<sup>+</sup> redox imbalance and the potential mitochondrial mechanisms underlying pathophysiology of DKD. These mechanisms include increased mitochondrial oxidative damage, decreased ATP production, perturbed mitochondrial membrane potential and deranged mitochondrial homeostasis and impaired sirt3 pathway as well as Nrf2 signaling pathway. The ultimate manifestation of these mitochondrial dysfunctional mechanisms is renal inflammation, fibrosis and diabetic kidney injury.</p>
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18 pages, 1929 KiB  
Article
NADH-GOGAT Overexpression Does Not Improve Maize (Zea mays L.) Performance Even When Pyramiding with NAD-IDH, GDH and GS
by Rafael A. Cañas, Zhazira Yesbergenova-Cuny, Léo Belanger, Jacques Rouster, Lenaïg Brulé, Françoise Gilard, Isabelle Quilleré, Christophe Sallaud and Bertrand Hirel
Plants 2020, 9(2), 130; https://doi.org/10.3390/plants9020130 - 21 Jan 2020
Cited by 29 | Viewed by 5508
Abstract
Maize plants overexpressing NADH-GOGAT were produced in order to determine if boosting 2-Oxoglurate production used as a carbon skeleton for the biosynthesis of amino acids will improve plant biomass and kernel production. The NADH-GOGAT enzyme recycles glutamate and incorporates carbon skeletons into the [...] Read more.
Maize plants overexpressing NADH-GOGAT were produced in order to determine if boosting 2-Oxoglurate production used as a carbon skeleton for the biosynthesis of amino acids will improve plant biomass and kernel production. The NADH-GOGAT enzyme recycles glutamate and incorporates carbon skeletons into the ammonium assimilation pathway using the organic acid 2-Oxoglutarate as a substrate. Gene pyramiding was then conducted with NAD-IDH and NADH-GDH, two enzymes also involved in the synthesis of 2-Oxoglurate. NADH-GOGAT overexpression was detrimental for shoot biomass production but did not markedly affect kernel yield. Additional NAD-IDH and NADH-GDH activity did not improve plant performance. A decrease in kernel production was observed when NADH-GDH was pyramided to NADH-GOGAT and NAD-IDH. This decrease could not be restored even when additional cytosolic GS activity was present in the plants overexpressing the three enzymes producing 2-Oxoglutarate. Detailed leaf metabolic profiling of the different transgenic plants revealed that the NADH-GOGAT over-expressors were characterized by an accumulation of amino acids derived from glutamate and a decrease in the amount of carbohydrates further used to provide carbon skeletons for its synthesis. The study suggests that 2-Oxoglutarate synthesis is a key element acting at the interface of carbohydrate and amino acid metabolism and that its accumulation induces an imbalance of primary carbon and nitrogen metabolism that is detrimental for maize productivity. Full article
(This article belongs to the Special Issue Plant Nitrogen Assimilation and Metabolism)
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Figure 1
<p>Enzyme activities of control and transgenic plants modified for 2-Oxoglutarate production and ammonium assimilation. The white column corresponds to the WT plants (A188). The grey columns correspond to transgenic line overexpressing NADH-GOGAT (construct T02291) and NADH-GOGAT stacked with NAD-IDH (construct T02289), NAD-IDH + NADH-GDH1 (construct T02308) and NAD-IDH + NADH-GDH1 + GS1.3 (construct T02312). NADH-GOGAT, (<b>A</b>). NAD-IDH, (<b>B</b>). NADH-GDH, (<b>C</b>). GS1.3, (<b>D</b>). The error bars correspond to the standard error (SE). Data were analyzed with a t-test. Significant differences are indicated with asterisks on top of the columns. * at <span class="html-italic">p</span> ≤ 0.05; ** at <span class="html-italic">p</span> ≤ 0.01, *** at <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>Shoot biomass production and yield-related traits in WT and transgenic plants modified for 2-Oxoglutarate production and ammonium assimilation. The white column corresponds to the WT plants (A188). The grey columns correspond to transgenic line overexpressing NADH-GOGAT (construct T02291) and NADH-GOGAT stacked with NAD-IDH (construct T02289), NAD-IDH + NADH-GDH1 (construct T02308) and NAD-IDH + NADH-GDH1 + GS1.3 (construct T02312). Shoot dry weight, (<b>A</b>). Kernel yield, (<b>B</b>). Thousand kernel weight, (<b>C</b>). Kernel number, (<b>D</b>). The error bars correspond to standard error (SE). Data were analyzed with a one-way ANOVA and the Newman-Keuls comparison test. The different letters (a, b) on top of the columns indicate significant differences at <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Principal component analysis (PCA) of the different leaf metabolites detected at the V stage and 15DAS of WT (A188) plants and transgenic maize lines overexpressing NADH-GOGAT (construct T02291) and NADH-GOGAT stacked with NAD-IDH (construct T02289), NAD-IDH + NADH-GDH1 (construct T02308) and NAD-IDH + NADH-GDH1 + GS1.3 (construct T02312). Metabolic and molecular traits were measured in the leaves of plants harvested at the vegetative (V) stage and 15 days after silking (15DAS). The four colored dots for each transgenic line correspond to the four independent transformation events selected for the metabolomic study. The values of the different metabolites were projected on to two biplots of principal components arranged in descending order of variance. Each component allowed the identification of groups of metabolites, depending on the plant developmental stage and of the nature of the line.</p>
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<p>Network diagrams showing significant correlations (<span class="html-italic">p</span> ≤ 0.05) between leaf metabolite accumulation at the V stage and agronomic traits based on the calculation of Pearson coefficients. (<b>A</b>) Correlations between leaf metabolites and shoot dry weight (DW). (<b>B</b>) Correlations between leaf metabolites and kernel yield (KY). The red lines and blue lines represent positive and negative correlations between groups of metabolites, respectively. The names of the metabolites positively or negatively correlated with shoot DW and KY are highlighted in black and red, respectively. The circles correspond to the six groups of metabolites obtained following hierarchical clustering of the Pearson correlations between the amount of leaf metabolites at the V stage, shoot dry weight and kernel-related traits. The list of metabolites belonging to each of the six groups are provided in <a href="#app1-plants-09-00130" class="html-app">Supplemental dataset 5</a>.</p>
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<p>Scheme of amino acid biosynthesis derived from glutamate. Metabolites in red font are present in higher amounts in the leaves of maize plants overexpressing NADH-GOGAT (red box). Those in blue font are present in lower amounts. Red arrows indicate the putative metabolic pathways involved in the synthesis of amino acids and the release of 2-Oxoglutarate. The blue arrow corresponds to the use of carbohydrates to produce Pyruvate. The other enzymes used for gene pyramiding are boxed with a red line.</p>
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