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Knock-Out Mice Reveals Decreased Levels of Elaidic Trans-Fatty Acid

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Knock-Out Mice Reveals Decreased Levels of Elaidic Trans-Fatty Acid H OH metabolites OH Article Metabolomic Analysis of Plasma from GABAB(1) Knock-Out Mice Reveals Decreased Levels of Elaidic Trans-Fatty Acid Claudia Fattuoni 1,* , Luigi Barberini 2, Antonio Noto 2 and Paolo Follesa 3 1 Department of Chemical and Geological Sciences, University of Cagliari, 09042 Monserrato, Italy 2 Department of Medical Sciences and Public Health, University of Cagliari, 09042 Monserrato, Italy; [email protected] (L.B.); [email protected] (A.N.) 3 Department of Life and Environment Sciences, Section of Neuroscience and Anthropology and Center of Excellence for Neurobiology of Dependence, University of Cagliari, 09042 Monserrato, Italy; [email protected] * Correspondence: [email protected] Received: 27 October 2020; Accepted: 22 November 2020; Published: 26 November 2020 Abstract: Mice lacking the GABAB(1) subunit of gamma-aminobutyric acid (GABA) type B receptors exhibit spontaneous seizures, hyperalgesia, hyperlocomotor activity, and memory impairment. Although mice lacking the GABAB(1) subunit are viable, they are sterile, and to generate knockout (KO) mice, it is necessary to cross heterozygous (HZ) mice. The aim of our study was to detect the metabolic differences between the three genotypes of GABAB(1) KO mice in order to further characterize this experimental animal model. Plasma samples were collected from wild-type (WT), HZ, and KO mice. Samples were analyzed by means of a gas chromatography-mass spectrometry (GC-MS) platform. Univariate t-test, and partial least square discriminant analysis (PLS-DA) were performed to compare the metabolic pattern of different genotypes. The metabolomic analysis highlighted differences between the three genotypes and identified some metabolites less abundant in KO mice, namely elaidic acid and other fatty acids, and chiro-inositol. Keywords: murine model; plasma; metabolomics; GC-MS; elaidic acid 1. Introduction Gamma-aminobutyric acid (GABA) regulates inhibitory neurotransmission in the adult mammalian brain acting on GABAA and GABAB receptors, and both types of receptors are involved in the fine and precise regulation of neuronal excitability. GABAB receptors are G protein-coupled receptors and exist as heterodimers composed by the R1 and R2 subunits encoded by different genes [1]. Accumulating evidences suggest that GABA receptors may promote cell migration, differentiation, and synaptogenesis, therefore affecting Central Nervous System (CNS) development. Accordingly, the knocking down of GABAB receptors in mice, by eliminating the gene coding for the R1 subunit (GABAB(1) knock-out), causes behavioral alterations and abnormalities including epilepsy, impaired memory, hyperalgesia, hyperthermia, and hyperactivity [2–6]. Moreover, recent findings in our laboratory demonstrate that both GABAB(1) knockout (KO) and heterozygous (HZ) mice consumed high amounts of ethanol and prefer to drink alcohol rather than water [7] and could be used as an experimental model to study alcohol addiction. All these observations suggest a rearrangement in the neuronal networks and altered neuronal excitability in the CNS of these mice [7] accompanied by changes in expression of a number of genes. Accordingly, GABAB(1) KO mice are characterized by altered levels of mRNA encoding for the different GABAA receptor subunits [7] as well as growth factors, transcription factors, and enzymes encoding Metabolites 2020, 10, 484; doi:10.3390/metabo10120484 www.mdpi.com/journal/metabolites Metabolites 2020, 10, x FOR PEER REVIEW 2 of 13 different GABAA receptor subunits [7] as well as growth factors, transcription factors, and enzymes Metabolitesencoding2020 genes, 10, 484 (Follesa et al. unpublished observations), and these alterations in gene expression2 of 12 may be regulated by changes in DNA methylation [8,9]. Nevertheless, little is known about the genesfunctional (Follesa consequences et al. unpublished that these observations), changes can and produce, these alterationsand to the inbest gene of expressionour knowledge, may be no regulatedinformation by changesis available in DNA on methylationmetabolomic [ 8,studies9]. Nevertheless, performed little in isGABA knownB(1) KO about mice. the functionalTo further consequencescharacterize this that mouse these changesstrain, the can aims produce, of our andresearch to the were best to of investigate our knowledge, the metabolic no information differences is between plasma from three genotypes of mice obtained by crossing GABAB(1) HZ mice. The ultimate available on metabolomic studies performed in GABAB(1) KO mice. To further characterize this mouse strain,goal of the this aims study of ourwas research to characterize were to GABA investigateB(1) KO themice metabolic and identify differences metabolic between routes plasmathan could from be exploited to further understand the molecular, cellular, and functional alterations that could play a three genotypes of mice obtained by crossing GABAB(1) HZ mice. The ultimate goal of this study was pivotal role in epilepsy, impaired memory, hyperalgesia, hyperthermia, hyperactivity [2–6], changes to characterize GABAB(1) KO mice and identify metabolic routes than could be exploited to further understandin gene expression, the molecular, and drinking cellular, andbehavior functional [7] observed alterations in these that couldmice and play give a pivotal some rolenew in insights epilepsy, for impairedintervention memory, to treat hyperalgesia, and/or restore hyperthermia, these CNS alterations. hyperactivity Biological [2–6], changes samples, in such gene as expression, blood, can andprovide drinking comprehensive behavior [7] information observed in being these miceminimally and give invasive some to new obtain, insights rendering for intervention it a good medium to treat andfor/ orclinical restore diagnostics. these CNS alterations. Biological samples, such as blood, can provide comprehensive information being minimally invasive to obtain, rendering it a good medium for clinical diagnostics. 2. Results 2. ResultsPlasma samples from 82 mice (32 WT, 41 HZ, and 9 KO) underwent metabolomic analysis. The threePlasma possible samples genotypes from were 82 mice compared (32 WT, in differe 41 HZ,nt and combinations: 9 KO) underwent WT vs. HZ, metabolomic WT vs. KO, analysis. and HZ Thevs. threeKO. possible genotypes were compared in different combinations: WT vs. HZ, WT vs. KO, and HZWT vs. vs. KO. HZ: After a preliminary outlier removal, the groups resulted formed by 29 WT and 31 HZ.WT Univariate vs. HZ: analysis After a preliminarydid not reveal outlier any significant removal, themetabolite. groups resultedPartial least formed square by 29discriminant WT and 31analysis HZ. Univariate (PLS-DA) analysis analysis did allowed not reveal to build any a significant statistically metabolite. validated Partialmodel least(p < 0.01): square the discriminant relative two- analysisdimensional (PLS-DA) (2D) analysisscore plot allowed and the to corresponding build a statistically VIP (Variable validated Importance model (p < in0.01): Projection) the relative score two-dimensionalwere plotted and (2D) are scorereported plot in and Figure the corresponding 1a and 1b, respectively. VIP (Variable Importance in Projection) score were plotted and are reported in Figure1a,b, respectively. (a) Figure 1. Cont. MetabolitesMetabolites 20202020, 10, 10, x, FOR 484 PEER REVIEW 3 of3 of13 12 (b) FigureFigure 1. 1. PLS-DAPLS-DA analysisanalysis of of WT WT vs. HZ.vs. HZ. (a) Two-dimensional (a) Two-dimensional (2D) score (2D) plot, score and (plot,b) the and corresponding (b) the correspondingVIP score plot VIP (score score> 1.0).plot (score > 1.0). AllAll metabolites metabolites resulted resulted moremore abundantabundant in in WT WT except except for lactose,for lactose, 3-hydroxybutyric 3-hydroxybutyric acid, sucrose,acid, sucrose,glycerol, glycerol, and 4-hydroxyproline and 4-hydroxyproline (Figure (Figure1b). 1b). WTWT vs. vs. KO: KO: Two Two groups groups formed formed by by 29 29(WT) (WT) and and 9 (KO) 9 (KO) were were submitted submitted to tostatistical statistical analysis. analysis. 4 The t-test revealed the elaidic acid as statistically different between groups (p = 4.1417 10 , FDR−4 (False The t-test revealed the elaidic acid as statistically different between groups (p = 4.1417× −× 10 , FDR (FalseDiscovery Discovery Rate) Rate)= 0.0207). = 0.0207). The unequivocalThe unequivocal identification identification of elaidic of elaidic acid, in acid, comparison in comparison with the with more theabundant more abundantcis-isomer cis-isomer oleic acid, oleic is reportedacid, is reported as Supplementary as Supplementary Figures Figures S1–S3. S1–S3. TheThe PLS-DA PLS-DA analysis analysis allowed toto buildbuild the the model model whose whose plots plots are reportedare reported in Figure in Figure2. As evident2. As evidentfrom the from VIP the score VIP plot, score all plot, metabolites all metabolites resulted re moresulted abundant more abundant in WT, except in WT, for except mannitol for mannitol (Figure2b). (FigureHZ 2b). vs. KO: Two groups formed by 34 (HZ) and 9 (KO) were submitted to statistical analysis. Again, the t-test revealed the elaidic acid as statistically different between groups (p = 6.9305 10 4, × − FDR = 0.034652). The PLS-DA analysis allowed to build the model whose plots are reported in Figure3. Metabolites 2020, 10, x FOR PEER REVIEW 4 of 13 Metabolites 2020, 10, 484 4 of 12 (a) (b) FigureFigure 2. 2.PLS-DAPLS-DA analysis analysis of of WT WT vs. vs. KO. KO. (a ()a 2D) 2D scores scores plot, plot, and and (b
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