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ABCD2 Alters PPARα Signaling in Vitro, but Does Not Impair Responses to Fenofibrate Therapy in a Mouse Model of Diet-induced Obesity Xiaoxi Liu, Jingjing Liu, Shuang Liang, Agatha Schlüter, Stephane Fourcade, Stella Aslibekyan, Aurora Pujol, Gregory A. Graf. Submitted to Molecular Pharmacology WT A KO ** 15 ) g ( n o i t 10 p m u s n o C 5 d o o F 0 HFD Fibrate B **** 15 e r u t i ) d g n 10 k / e r p h x / l E a c y k g ( r 5 e n E 0 C HFD Fibrate ) s 150000 t n * u o c ( y 100000 t i v i t c A r o 50000 t o m o c o L 0 HFD Fibrate Supplemental Figure 1. Metabolic parameters. Accumulative food consumption (A) and locomotor activity (C) of a subgroup of mice were recorded during 72 hour stay in metabolic cages. Energy expenditure (B) was calculated based on recorded oxygen and carbon dioxide flow. Statistical comparison between fibrate treatment and control groups was made using two-way ANOVA (mean±SEM, n=3~6). Asterisks over lines terminating in horizontal bars indicate a significant overall effect of fibrate treatment regardless of genotype. ** p<0.01, **** p<0.0001. Significance of difference between two genotypes within each group was analyzed using student test (mean±SEM, n=3~6). Asterisks over bars terminating in vertical lines indicate a significant difference between genotypes within either fibrate treated or control groups. * p<0.05. D2+feno vs WT+feno WT+feno vs WT D2 vs WT KEGG pathways GSEA.MIXED GSEA.UP GSEA.DOWN HyperG GSEA.MIXED GSEA.UP GSEA.DOWN HyperG GSEA.MIXED GSEA.UP GSEA.DOWN HyperG Fatty acid metabolism 1 1 1 1 3.20E-17 3.70E-22 1 2.13E-13 0.95100957 0.00270026 0.99729988 1 PPAR signaling pathway 0.00096912 0.12464977 0.87535272 1 8.80E-23 3.27E-21 1 5.39E-13 0.65427925 0.00162494 0.99837512 1 Biosynthesis of unsaturated0 f.a0tt00y6 a5c8id11s 0.95465039 0.04535147 0.00343984 4.79E-13 8.19E-14 1 3.24E-12 0.99188656 3.30E-05 0.99996698 1 Peroxisome 1 1 1 1 5.86E-16 1.94E-12 1 8.52E-08 0.53427295 0.00898987 0.9910104 1 Retinol metabolism 3.96E-05 0.92187491 0.07812845 1 2.16E-09 4.80E-06 0.9999952 5.35E-05 1 1 1 1 alpha-Linolenic acid metabo0li.s0m0697004 0.39266755 0.60734404 1 0.00190909 0.00160139 0.99839877 0.00045712 1 1 1 1 Linoleic acid metabolism 0.00174859 0.98447744 0.01552355 1 0.0042867 0.64672064 0.35328874 0.0027794 0.07920467 0.98623573 0.01376516 1 Steroid hormone biosynthesis1.78E-05 0.98809055 0.01191031 1 0.00018913 0.59544969 0.40456102 0.0027794 1 1 1 1 Arachidonic acid metabolism0.05419413 0.01316915 0.9868314 1 8.44E-05 0.16370998 0.83629399 0.00473957 1 1 1 1 Metabolic pathways 0.00056624 0.99750506 0.00249497 1 1.44E-12 3.28E-10 1 0.00527475 1 1 1 1 Primary bile acid biosynthes0is.00492676 0.44229647 0.55771383 1 0.04597224 0.1874081 0.81259892 0.01036848 1 1 1 1 Butanoate metabolism 0.03726383 0.93293917 0.06706406 1 0.00354978 0.00042459 0.99957545 0.02995828 1 1 1 1 Ascorbate and aldarate meta0b.0o1l2is4m0464 0.99520207 0.00479842 1 0.00815005 0.00266385 0.99733644 0.04016961 1 1 1 1 Pentose and glucuronate int0e.r0c4o3n3v3e4r8s7ion0s.98274899 0.01725244 1 1 1 1 0.04903351 1 1 1 1 Drug metabolism - cytochrom0.e01 P448580436 0.99990426 9.57E-05 1 1 1 1 1 0.01910067 0.98181433 0.01818633 0.00550969 Metabolism of xenobiotics b0y.0 c2y4t8o6c0h8ro9me0. P95415902918 0.04807263 1 0.0465167 0.00475572 0.99524453 1 0.95944975 0.00247296 0.99752718 0.00812141 Bile secretion 1 1 1 1 1 1 1 1 0.75951193 0.02263671 0.97736418 0.01942718 Glycerophospholipid metab0o.l0is0m782757 0.99999432 5.68E-06 0.01079493 1 1 1 1 0.03107313 0.99999313 6.87E-06 1 Protein processing in endop0la.0s1m6i9c4 r7e3ti6cul0u.9m9999388 6.12E-06 0.02189606 0.66359472 0.9999146 8.54E-05 1 0.00241366 0.99998424 1.58E-05 1 Pyruvate metabolism 0.00023007 0.99996588 3.41E-05 0.02262259 0.03103441 0.99999966 3.43E-07 1 2.28E-05 0.99999981 1.95E-07 1 Citrate cycle (TCA cycle) 1 1 1 0.03759077 0.35226227 0.00216206 0.997838 1 0.04100324 0.65631236 0.34369053 1 Nitrogen metabolism 0.00502667 0.99978246 0.00021756 0.0426084 0.12524887 4.12E-05 0.99995882 1 1 1 1 1 Cell cycle 0.04797371 0.96322433 0.03677822 1 0.15139167 0.98944154 0.01055935 1 0.0062972 0.99506534 0.00493511 1 Spliceosome 0.14981607 0.99847551 0.0015246 1 0.00080659 0.16845591 0.83154952 1 1 1 1 1 RNA transport 0.2379308 0.99447448 0.00552587 1 0.00092794 0.25383159 0.74617549 1 1 1 1 1 RNA degradation 0.01970374 0.99317123 0.00682906 1 0.00133719 0.01120835 0.9887921 1 1 1 1 1 Glycolysis / Gluconeogenesi0s.00186937 0.76849499 0.23150931 1 0.02129655 0.01899757 0.98100308 1 1 1 1 1 Vasopressin-regulated wate0r. r0e4a5b7s4o6r8p2tio0n.83020095 0.16980368 1 1 1 1 1 1 1 1 1 Supplemental Table 1. Statistical analysis of KEGG pathway enrichment. Table showing the pathway enrichment probabilities (p-values) of the comparisons: D2+fenofibrate vs WT+fenofibrate, WT+fenofibrate vs WT, and D2 vs WT. We computed the Gene Set Enrichment Analysis (GSEA) based on a set of probe-wise t statistics arising from microarray analysis. GSEA.MIXED) upregulated or downregulated genes black-shading, GSEA.UP) upregulated genes with positive t statistics red-shading when enrichment probability p<0.05, GSEA.DOWN) downregulated genes with negative t statistics green-shading when enrichment probability p<0.05; and Hypergeometric distribution function (HyperG) arising from the subset of genes with differential expression in each comparison at p< 0.05. Supplemental Table 2. The MicroarraysExpression file includes the differential expressed genes of the microarray data analysis from livers of WT and D2 KO mice treated with fibrate. The Excel file sheets correspond to the gene lists for the contrasts: D2 vs WT, WT+feno vs WT and D2+feno vs WT+feno, after fitting a linear model and computing moderated t-statistics by the empirical Bayesian model. Column fields: (A) the average log2-expression for the probe over all arrays and channels, (B) the estimate of the log2-fold-change corresponding to the contrast, (C) moderated t-statistics which is computed for each probe and for each contrast. This has the same interpretation as an ordinary t-statistic except that the standard errors have been moderated across genes, using a simple Bayesian model, (D) t statistic p-values, (E) t-statistic p-values adjusted for multiple testing by the Benjamini & Hochberg method (Benjamini and Hochberg, 1995), which controls the expected false discovery rate (FDR) below 0.05, (F) the moderated F-statistic that combines the t-statistics for all the contrasts into an overall test of significance for that gene. The F-statistic tests calculates whether a given gene is differentially expressed Benjamini Y and Hochberg Y (1995) Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. J Roy Stat Soc B Met 57(1): 289-300. D2+feno vs WT+feno A log2 expression t p.value p.value.adj F F.p.value Genes.Spot_Id Genes.Product_Id Genes.Bank_Id Genes.Clone_Id Genes.UGCluster Genes.Name Genes.Symbol Genes.Chromosome Genes.GeneID 15.33 -1.577 -7.96 0 1.90E-05 63.44 0 s20470 p13635 NIA H3082C01 Mm.312593 Serine (or cysteine) proteinase inhibitor, clade A, member 1e Serpina1e 12 20704 11.92 2.839 7.58 0 3.30E-05 57.44 0 s08069 p03659 NIA H3020C02 Mm.192991 Metallothionein 1 Mt1 8 17748 8.3 -1.611 -7.17 0 8.20E-05 51.37 0 s14534 p13527 NIA H3081G11 Mm.290563 Centromere autoantigen A Cenpa 5 12615 11.25 2.577 7.06 0 8.70E-05 49.82 0 s11679 p02073 IMAGE 848481 Mm.9221 RAB4A, member RAS oncogene family Rab4a 8 19341 10.5 -1.512 -6.61 0 3.00E-04 43.68 0 s24253 p16411 IMAGE 514817 Mm.2567 Elongation of very long chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 2 Elovl2 13 54326 8.09 1.544 6.54 0 0.000308 42.83 0 s11987 p01804 IMAGE 576417 Mm.24636 Processing of precursor 5, ribonuclease P/MRP family (S. cerevisiae) Pop5 5 117109 9.34 -1.441 -6.34 0 0.000518 40.19 0 s05740 p12174 NIA H3073F10 Mm.19306 Calpain 2 Capn2 1 12334 14.89 -1.966 -6.22 0 0.000672 38.67 0 s00234 p08175 NIA H3045G02 Mm.275608 Dystrophin, muscular dystrophy Dmd X 13405 8.26 -1.185 -6.08 0 0.000946 36.93 0 s09094 p06744 NIA H3036H03 Mm.27154 Vanin 1 Vnn1 10 22361 8.27 -1.103 -6.05 0 0.000946 36.55 0 s21443 p20300 NIA H3128D06 Mm.341204 SH3 domain protein 1B Sh3d1B 12 20403 10.91 2.285 6.01 0 0.000964 36.13 0 s09089 p02388 NIA H3013D11 Mm.147226 Metallothionein 2 Mt2 8 17750 10.06 -2.831 -5.96 0 0.001041 35.53 0 s15801 p20129 CNS-CB CW0CG89YH09 Mm.295397 DEP domain containing 6 Depdc6 15 97998 9.87 -1.566 -5.89 0 0.001196 34.74 0 s04977 p06027 NIA H3032C10 Mm.316652 3-hydroxy-3-methylglutaryl-Coenzyme A reductase Hmgcr 13 15357 10.33 1.824 5.81 0 0.001475 33.72 0 s09285 p02396 NIA H3013D12 NA 15.15 -1.783 -5.75 0 0.00155 33.07 0 s12822 p23023 NIA H3148G10 Mm.105230 Protein phosphatase 1, regulatory (inhibitor) subunit 8 Ppp1r8 4 100336 8.3 1.308 5.77 0 0.00155 33.26 0 s18434 p20630 NIA H3130F11 Mm.295660 Expressed sequence AI428795 AI428795 5 209683 7.89 -1.047 -5.7 0 0.00165 32.5 0 s10542 p11824 CNS-CB CW0CG85YB18 Mm.331640 ROD1 regulator of differentiation 1 (S.