DOCSLIB.ORG

Integrated Proteomic and Mirna Transcriptional Analysis Reveals the Hepatotoxicity Mechanism of PFNA Exposure in Mice

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Integrated Proteomic and Mirna Transcriptional Analysis Reveals the Hepatotoxicity Mechanism of PFNA Exposure in Mice Integrated proteomic and miRNA transcriptional analysis reveals the hepatotoxicity mechanism of PFNA exposure in mice Jianshe Wang, Shengmin Yan, Wei Zhang, Jiayin Dai * Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P.R. China *Corresponding author: Dai JY; Tel. +86-10-64807185; E-mail: [email protected] Supplementary materials and methods PFNA concentration detection in the serum and liver PFNA in liver and serum samples were quantified using HPLC-MS/MS. Briefly, samples with internal standard were extracted with 5 mL of acetonitrile in 15 mL polypropylene (PP) tubes, and all tubes were placed on a mechanical shaker for 20 min followed by centrifugation at 3,000 × g for 10 min. The top layers, which contained PFNA (analytes and internal standard), were transferred into new PP tubes. The extraction procedure was repeated and a final solution of 10 mL of acetonitrile was combined and concentrated to 0.5 mL under nitrogen gas at 40°C. After the addition of 0.5 mL methanol, the final solution was diluted into 10 mL Milli-Q water for SPE cleanup. All samples were then extracted using an Oasis WAX cartridge (Oasis1 HLB; 150 mg, 6 cc; Waters). The cartridge was pre-equilibrated by the addition of a sequence of 4 mL of 0.1% NH 4OH in methanol, 4 mL methanol, and 4 mL water at a rate of 1 drop per second. Samples (11 mL) were then passed through these cartridges at a rate of 1 drop per second. After loading all samples, cartridges were rinsed with 5 mL Milli-Q water and then washed with 4 mL of 25 mM acetate buffer solution (pH 4). Any water remaining in the cartridges was removed by centrifugation at 3,000 rpm for 2 min, and PFNA were eluted by 4 mL of 0.1% NH 4OH in methanol and then concentrated to 1 mL under a stream of nitrogen. The instrumental chromatographic setup consisted of a P680 binary gradient pump, an UltiMate 3000 autosampler, and a Chromeleon 6.70 chromatography workstation (Dionex, USA). Mass spectra were collected using an API 3200 triple quadrupole tandem mass spectrometer, fitted with an electrospray ionization source and operated in negative ionization mode. Quantification using these transitions was performed using Analyst 1.4.1 software. Chromatographic separations were carried out on an Acclaim 120 C18 column (4.6 × 150 mm, 3 µm) (Dionex, USA), with a binary gradient. Methanol (A) and 50 mM ammonium acetate (NH 4Ac) (B) were employed as mobile phases. The flow rate was 1 mL/min and the injection volume was 10 µL. The elution gradient was: 0 to 4 min, from 28 to 5% B linearly; 4 to 7 min, 5% B; 7 to 10 min, 28% B. A calibration curve was prepared from a series of concentrations (0, 10, 50, 100, 500, 1000, 5000, 20000, and 50000 pg/mL), and standard deviations were less than 20%. Blanks and recoveries were assessed following the same procedure as described above with each group of extractions. The blanks were all below the limit of quantifications (LOQs). Quality control is given in the Supplementary Table S1. The concentrations of PFNA in the experimental samples were not corrected for their corresponding recoveries. Supplementary Fig. S1. The PFNA content in mouse liver (A) and serum (B) after treatment. Supplementary Fig. S2. Volcano plots of miRNAs expression in PFNA treatment mice liver tissues. (A) miRNA expression in 1 mg/kg/d dose of PFNA treatment groups compared with control. (B) miRNA expression in 5 mg/kg/d dose of PFNA treatment groups compared with control. On all plots, the X axis represents the log2 ratio of the normalized miRNA signal (mean of the three replicates) of the treatment condition compared with the appropriate control, and the Y axis represents the -log10 P value obtained from the student’s t-test comparing the mean normalized miRNA signal in treatment to that in control. Differentially expressed miRNAs were selected based on fold change at least 2 and student’s t-test ( P < 0.05). Supplementary Fig. S3. Potential binding sites of target genes. (A) Lactate dehydrogenase A (Ldha); (B) fucosyltransferase 8 (Fut8). Supplementary Table S1. Quality control for PFNA concentration detection. Analyte LOQ Instrument Cartridge Procedural Procedural blank blank blank ( n = 3) recovery % ( n = 3) Native Mean Mean Mean Mean (ng/mL) Mean S. D chemical (ng/mL) (ng/mL) (ng/mL) PFNA 0.01 < 0.01 < 0.01 < 0.01 94 8 Surrogate 13 C5-PFNA 0.01 < 0.01 < 0.01 < 0.01 71 1 Supplementary Table S2. Gene-specific primers used in qPCR. Gene symbol Genbank Sequence (5'-3') Amplicon Accession no. size (bp) Me1-F NM_008615 ACAAGGTGACCAAGGGAC Me1-R CAGGGAACACGTAGGAATT 117 Elovl6-F NM_130450 TCAGTTACCTGGGAGTGT Elovl6-R TCTGTATCTGGCAGTTCTT 76 Apoa4-F NM_007468 GGAGCACCTGAAGCCCTAT Apoa4-R ATGCGCTGGATGTATGG 96 Apoc3-F NM_023114 AAGTAGCGTGCAGGAGTC Apoc3-R ATAGCTGGAGTTGGTTGG 150 Gapdh-F NM_008084 CCTTCCGTGTTCCTACCC Gapdh-R GCCTGCTTCACCACCTTC 100 Fut8-F NM_178155 TTCAAGTGGTCGAGCTTCCC 96 Fut8-R GTACAAGTCGATCTGCGAGGT Ldha-F NM_005566 ATGGCAACTCTAAAGGATCAGC 86 Ldha-R CCAACCCCAACAACTGTAATCT Ldlr-F NM_010700 GAGGAACTGGCGGCTGAA Ldlr-R GTGCTGGATGGGGAGGTCT 239 Hmgcr-F NM_008255 GATTCTGGCAGTCAGTGGGAA Hmgcr-R GTTGTAGCCGCCTATGCTCC 214 Fasn-F NM_007988 TGCTCCCAGCTGCAGGC Fasn-R GCCCGGTAGCTCTGGGTGTA 107 Acaca-F NM_133360 TGAAGGGCTACCTCTAATG Acaca-R TCACAACCCAAGAACCAC 182 Hmgcs2-F NM_008256 CCGTGCTCCCTTCTTAG Hmgcs2-R GCTCTTCGTGGGTTCTGT 100 Fdft1-F NM_010191 GCCTTTCTCGTCTATTCTC Fdft1-R GCTGTAGGGTGTTGGTTATG 261 Lpl-F NM_008509 TCTCCTGATGACGCTGAT Lpl-R CTTGGAGTTGCACCTGTAT 288 Gpam-F NM_008149 CCGTGGGCATCTCGTAT Gpam -R CGGACGTAGCCGTAGTTT 139 Acox1-F NM_015729 AGCACTGGTCTCCGTCAT Acox1-R TTCCCTCATCTTCTTCACC 244 Acsl1-F NM_007981 ATTTCAGGTCGCAGATAGA Acsl1-R TGGTACGAGGAGGATTGT 102 Mlycd-F NM_019966 GGCTGTGATGTGGCGTAT Mlycd-R TTGGAGCCCAGGTAGGA 135 Scd1-F NM_009127 GACCTGAAAGCCGAGAA Scd1-R CGTTGAGCACCAGAGTGT 169 Cyp4a10-F NM_010011 CCCAAGTGCCTTTCCTA Cyp4a10-R GCAAACCATACCCAATCC 149 Abbreviations: Me1, malic enzyme 1, NADP(+)-dependent, cytosolic; Elovl6, ELOVL family member 6, elongation of long chain fatty acids; Ldlr, low density lipoprotein receptor; Hmgcr, 3-hydroxy-3-methylglutaryl-Coenzyme A reductase; Fasn, fatty acid synthase; Acaca, acetyl-Coenzyme A carboxylase alpha; Fut8, Fucosyltransferase 8; Ldha, Lactate dehydrogenase; Fdft1, farnesyl diphosphate farnesyl transferase 1; Lpl, lipoprotein lipase; Gpam, glycerol-3-phosphate acyltransferase, mitochondrial; Acsl1, acyl-CoA synthetase long-chain family member 1; Hmgcs2, 3-hydroxy-3-methylglutaryl Coenzyme A synthase 2; Scd1, stearoyl-Coenzyme A desaturase 1; Apoa4, apolipoprotein A-IV; Apoc3, apolipoprotein C-III; Acox1, acyl-Coenzyme A oxidase 1, palmitoyl; Mlycd, malonyl-CoA decarboxylase; Cyp4a10, cytochrome P450, family 4, subfamily a, polypeptide 10 (Cyp4a10); Gapdh, glyceraldehyde-3-phosphate dehydrogenase. Supplementary Table S3. The primers used for 3’ UTR psiCHECK-2 vector preparation. Name Genbank Primer sequence accession no. Ldha-F NM_010699 ACCGCTCGAGACACCCTTCTCGTCTGA L dha-R ATAAGAATGCGGCCGCGACTTAACTGGGAACTCG Fut8-F NM_016893 ACCGCTCGAGAGAAGACGCAGACTAACA Fut8-R ATAAGAATGCGGCCGCGAGGTGGATAAACTGAACT Abbreviations: Ldha, Lactate dehydrogenase A; Fut8, fucosyltransferase 8. The XhoI/NotI sites were underlined. Supplementary Table S4. Significantly altered proteins after 1 mg/kg/d PFNA treatment. Fold change (1 mg/kg/d Unique Accession Description Score Coverage Proteins PFNA treatment P value Peptides group/Ctrl) Q8VCH0 3-ketoacyl-CoA thiolase B, peroxisomal OS=Mus musculus GN=Acaa1b 1264.18 66.51 1 9 2.72 0.0000 PE=2 SV=1 [THIKB_MOUSE] P97412 Lysosomal-trafficking regulator OS=Mus musculus GN=Lyst PE=1 SV=1 0.00 0.32 1 1 2.48 0.0000 [LYST_MOUSE] Q9DBM2 Peroxisomal bifunctional enzyme OS=Mus musculus GN=Ehhadh PE=1 2744.07 70.33 1 61 2.21 0.0000 SV=4 [ECHP_MOUSE] O35728 Cytochrome P450 4A14 OS=Mus musculus GN=Cyp4a14 PE=2 SV=1 54.29 20.32 1 9 1.93 0.0000 [CP4AE_MOUSE] Q9Z0K8 Pantetheinase OS=Mus musculus GN=Vnn1 PE=1 SV=3 33.64 5.27 1 2 1.89 0.0000 [VNN1_MOUSE] P47740 Fatty aldehyde dehydrogenase OS=Mus musculus GN=Aldh3a2 PE=2 412.74 32.02 4 18 1.81 0.0000 SV=2 [AL3A2_MOUSE] Q9EQ06 Estradiol 17-beta-dehydrogenase 11 OS=Mus musculus GN=Hsd17b11 72.92 20.13 1 4 1.78 0.0075 PE=2 SV=1 [DHB11_MOUSE] Q9R0H0 Peroxisomal acyl-coenzyme A oxidase 1 OS=Mus musculus GN=Acox1 588.04 53.4 1 31 1.74 0.0000 PE=1 SV=5 [ACOX1_MOUSE] Q9QYR9 Acyl-coenzyme A thioesterase 2, mitochondrial OS=Mus musculus 489.06 60.71 1 10 1.70 0.0001 GN=Acot2 PE=1 SV=2 [ACOT2_MOUSE] P41216 Long-chain-fatty-acid--CoA ligase 1 OS=Mus musculus GN=Acsl1 PE=1 569.85 46.35 3 35 1.69 0.0000 SV=2 [ACSL1_MOUSE] O55137 Acyl-coenzyme A thioesterase 1 OS=Mus musculus GN=Acot1 PE=1 350.31 62.53 1 6 1.65 0.0002 SV=1 [ACOT1_MOUSE] O88833 Cytochrome P450 4A10 OS=Mus musculus GN=Cyp4a10 PE=2 SV=2 125.23 26.52 1 11 1.64 0.0000 [CP4AA_MOUSE] P47934 Carnitine O-acetyltransferase OS=Mus musculus GN=Crat PE=1 SV=3 49.18 19.33 1 11 1.62 0.0000 [CACP_MOUSE] P12710 Fatty acid-binding protein, liver OS=Mus musculus GN=Fabp1 PE=1 922.06 70.87 1 13 1.61 0.0000 SV=2 [FABPL_MOUSE] Q08857 Platelet glycoprotein 4 OS=Mus musculus GN=Cd36 PE=1 SV=2 0.00 2.54 1 1 1.60 0.0191 [CD36_MOUSE] P10648 Glutathione S-transferase A2 OS=Mus musculus GN=Gsta2 PE=1 SV=2 387.86 37.39 2 6 1.59 0.0004 [GSTA2_MOUSE] P12791 Cytochrome P450 2B10 OS=Mus musculus GN=Cyp2b10 PE=1 SV=1 32.22 6.2 1 3 1.58 0.0001 [CP2BA_MOUSE] Q8JZR0 Long-chain-fatty-acid--CoA ligase 5 OS=Mus musculus GN=Acsl5 PE=2 185.27 33.24 1 21 1.56 0.0000 SV=1 [ACSL5_MOUSE] P55096 ATP-binding cassette sub-family D member
Load more

Recommended publications
  • High-Throughput, Pooled Sequencing Identifies Mutations in NUBPL And
    ARTICLES High-throughput, pooled sequencing identifies mutations in NUBPL and FOXRED1 in human complex I deficiency Sarah E Calvo1–3,10, Elena J Tucker4,5,10, Alison G Compton4,10, Denise M Kirby4, Gabriel Crawford3, Noel P Burtt3, Manuel Rivas1,3, Candace Guiducci3, Damien L Bruno4, Olga A Goldberger1,2, Michelle C Redman3, Esko Wiltshire6,7, Callum J Wilson8, David Altshuler1,3,9, Stacey B Gabriel3, Mark J Daly1,3, David R Thorburn4,5 & Vamsi K Mootha1–3 Discovering the molecular basis of mitochondrial respiratory chain disease is challenging given the large number of both mitochondrial and nuclear genes that are involved. We report a strategy of focused candidate gene prediction, high-throughput sequencing and experimental validation to uncover the molecular basis of mitochondrial complex I disorders. We created seven pools of DNA from a cohort of 103 cases and 42 healthy controls and then performed deep sequencing of 103 candidate genes to identify 151 rare variants that were predicted to affect protein function. We established genetic diagnoses in 13 of 60 previously unsolved cases using confirmatory experiments, including cDNA complementation to show that mutations in NUBPL and FOXRED1 can cause complex I deficiency. Our study illustrates how large-scale sequencing, coupled with functional prediction and experimental validation, can be used to identify causal mutations in individual cases. Complex I of the mitochondrial respiratory chain is a large ~1-MDa ­assembly factors are probably required, as suggested by the 20 factors macromolecular machine composed of 45 protein subunits encoded necessary for assembly of the smaller complex IV9 and by cohort by both the nuclear and mitochondrial (mtDNA) genomes.
    [Show full text]
  • Proteomic and Metabolomic Analyses of Mitochondrial Complex I-Deficient
    THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 287, NO. 24, pp. 20652–20663, June 8, 2012 © 2012 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. Proteomic and Metabolomic Analyses of Mitochondrial Complex I-deficient Mouse Model Generated by Spontaneous B2 Short Interspersed Nuclear Element (SINE) Insertion into NADH Dehydrogenase (Ubiquinone) Fe-S Protein 4 (Ndufs4) Gene*□S Received for publication, November 25, 2011, and in revised form, April 5, 2012 Published, JBC Papers in Press, April 25, 2012, DOI 10.1074/jbc.M111.327601 Dillon W. Leong,a1 Jasper C. Komen,b1 Chelsee A. Hewitt,a Estelle Arnaud,c Matthew McKenzie,d Belinda Phipson,e Melanie Bahlo,e,f Adrienne Laskowski,b Sarah A. Kinkel,a,g,h Gayle M. Davey,g William R. Heath,g Anne K. Voss,a,h René P. Zahedi,i James J. Pitt,j Roman Chrast,c Albert Sickmann,i,k Michael T. Ryan,l Gordon K. Smyth,e,f,h b2 a,h,m,n3 David R. Thorburn, and Hamish S. Scott Downloaded from From the aMolecular Medicine Division, gImmunology Division, and eBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia, the bMurdoch Childrens Research Institute, Royal Children’s Hospital and Department of Paediatrics, University of Melbourne, Parkville, Victoria 3052, Australia, the cDépartement de Génétique Médicale, Université de Lausanne, 1005 Lausanne, Switzerland, the dCentre for Reproduction and Development, Monash Institute of Medical Research, Clayton, Victoria 3168, Australia, the hDepartment of Medical Biology
    [Show full text]
  • Health Effects Support Document for Perfluorooctanoic Acid (PFOA)
    United States Office of Water EPA 822-R-16-003 Environmental Protection Mail Code 4304T May 2016 Agency Health Effects Support Document for Perfluorooctanoic Acid (PFOA) Perfluorooctanoic Acid – May 2016 i Health Effects Support Document for Perfluorooctanoic Acid (PFOA) U.S. Environmental Protection Agency Office of Water (4304T) Health and Ecological Criteria Division Washington, DC 20460 EPA Document Number: 822-R-16-003 May 2016 Perfluorooctanoic Acid – May 2016 ii BACKGROUND The Safe Drinking Water Act (SDWA), as amended in 1996, requires the Administrator of the U.S. Environmental Protection Agency (EPA) to periodically publish a list of unregulated chemical contaminants known or anticipated to occur in public water systems and that may require regulation under SDWA. The SDWA also requires the Agency to make regulatory determinations on at least five contaminants on the Contaminant Candidate List (CCL) every 5 years. For each contaminant on the CCL, before EPA makes a regulatory determination, the Agency needs to obtain sufficient data to conduct analyses on the extent to which the contaminant occurs and the risk it poses to populations via drinking water. Ultimately, this information will assist the Agency in determining the most appropriate course of action in relation to the contaminant (e.g., developing a regulation to control it in drinking water, developing guidance, or deciding not to regulate it). The PFOA health assessment was initiated by the Office of Water, Office of Science and Technology in 2009. The draft Health Effects Support Document for Perfluoroctanoic Acid (PFOA) was completed in 2013 and released for public comment in February 2014.
    [Show full text]
  • Supplementary Materials
    Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • THE FUNCTIONAL SIGNIFICANCE of MITOCHONDRIAL SUPERCOMPLEXES in C. ELEGANS by WICHIT SUTHAMMARAK Submitted in Partial Fulfillment
    THE FUNCTIONAL SIGNIFICANCE OF MITOCHONDRIAL SUPERCOMPLEXES in C. ELEGANS by WICHIT SUTHAMMARAK Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Dissertation Advisor: Drs. Margaret M. Sedensky & Philip G. Morgan Department of Genetics CASE WESTERN RESERVE UNIVERSITY January, 2011 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of _____________________________________________________ candidate for the ______________________degree *. (signed)_______________________________________________ (chair of the committee) ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ (date) _______________________ *We also certify that written approval has been obtained for any proprietary material contained therein. Dedicated to my family, my teachers and all of my beloved ones for their love and support ii ACKNOWLEDGEMENTS My advanced academic journey began 5 years ago on the opposite side of the world. I traveled to the United States from Thailand in search of a better understanding of science so that one day I can return to my homeland and apply the knowledge and experience I have gained to improve the lives of those affected by sickness and disease yet unanswered by science. Ultimately, I hoped to make the academic transition into the scholarly community by proving myself through scientific research and understanding so that I can make a meaningful contribution to both the scientific and medical communities. The following dissertation would not have been possible without the help, support, and guidance of a lot of people both near and far. I wish to thank all who have aided me in one way or another on this long yet rewarding journey. My sincerest thanks and appreciation goes to my advisors Philip Morgan and Margaret Sedensky.
    [Show full text]
  • NDUFS8 Antibody Cat
    NDUFS8 Antibody Cat. No.: 43-249 NDUFS8 Antibody Specifications HOST SPECIES: Goat SPECIES REACTIVITY: Human, Mouse HOMOLOGY: Expected Species Reactivity based on sequence homology: Rat, Dog, Cow IMMUNOGEN: The immunogen for this antibody is: C-AEPRADGSRR TESTED APPLICATIONS: ELISA, WB Peptide ELISA: antibody detection limit dilution 1:2000.Western Blot:Approx 25kDa band observed in Human and Mouse Heart lysates (calculated MW of 23.7kDa according to NP_002487.1). Recommended concentration: 0.1-0.3ug/ml. An additional fainter band of APPLICATIONS: 90kDa was consistently observed, however this band was not blocked by the immunizing peptide and it is therefore a non-specific signal. We call for caution when used for other assays than Western blot. PREDICTED MOLECULAR Approx 25kDa WEIGHT: Properties Purified from goat serum by ammonium sulphate precipitation followed by antigen PURIFICATION: affinity chromatography using the immunizing peptide. CLONALITY: Polyclonal September 25, 2021 1 https://www.prosci-inc.com/ndufs8-antibody-43-249.html CONJUGATE: Unconjugated PHYSICAL STATE: Liquid Supplied at 0.5 mg/ml in Tris saline, 0.02% sodium azide, pH7.3 with 0.5% bovine serum BUFFER: albumin. Aliquot and store at -20°C. Minimize freezing and thawing. CONCENTRATION: 500 ug/mL STORAGE CONDITIONS: Aliquot and store at -20˚C. Minimize freezing and thawing. Additional Info OFFICIAL SYMBOL: NDUFS8 NDUFS8, NADH dehydrogenase (ubiquinone) Fe-S protein 8, 23kDa (NADH-coenzyme Q ALTERNATE NAMES: reductase), CI23KD, TYKY, NADH dehydrogenase ubiquinone Fe-S 8, NADH-ubiquinone oxidoreductase 23 kDa subunit, complex I-23kD ACCESSION NO.: NP_002487.1 PROTEIN GI NO.: 4505371 GENE ID: 4728 Background and References 1) Saito A, Kawamoto M, Kamatani N, Association study between single-nucleotide REFERENCES: polymorphisms in 199 drug-related genes and commonly measured quantitative traits of 752 healthy Japanese subjects.
    [Show full text]
  • Higher NDUFS8 Serum Levels Correlate with Better Insulin Sensitivity in Type 1 Diabetes
    Higher NDUFS8 Serum Levels Correlate with Better Insulin Sensitivity in Type 1 Diabetes Justyna Flotyńska ( [email protected] ) Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Daria Klause Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Michał Kulecki Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Aleksandra Cieluch Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Martyna Pakuła Poznan University of Medical Sciences, Department of Hypertensiology, Angiology and Internal Medicine Dorota Zozulińska-Ziółkiewicz Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Aleksandra Uruska Poznan University of Medical Sciences, Department of Internal Medicine and Diabetology Research Article Keywords: diabetes mellitus type 1, insulin resistance, e-GDR: estimated glucose disposal rate, NADH dehydrogenase iron-sulfur protein 8 Posted Date: May 11th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-496330/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Higher NDUFS8 serum levels correlate with better insulin sensitivity in Type 1 Diabetes. Authors: Justyna Flotyńska1*, Daria Klause1*, Michał Kulecki1, Aleksandra Cieluch1, Martyna Pakuła2, Dorota Zozulińska-Ziółkiewicz1, Aleksandra Uruska1 1Department of Internal Medicine and Diabetology, Poznan University of Medical Sciences, Raszeja Hospital,
    [Show full text]
  • Colon Cancer and Its Molecular Subsystems: Network Approaches to Dissecting Driver Gene Biology
    COLON CANCER AND ITS MOLECULAR SUBSYSTEMS: NETWORK APPROACHES TO DISSECTING DRIVER GENE BIOLOGY by VISHAL N. PATEL Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Genetics CASE WESTERN RESERVE UNIVERSITY August 2011 Case Western Reserve University School of Graduate Studies We hereby approve the dissertation* of Vishal N. Patel, candidate for the degree of Doctor of Philosophy on July 6, 2011. Committee Chair: Georgia Wiesner Mark R. Chance Sudha Iyengar Mehmet Koyuturk * We also certify that written approval has been obtained for any proprietary material contained therein 2 Table of Contents I. List of Tables 6 II. List of Figures 7 III. List of Abbreviations 8 IV. Glossary 10 V. Abstract 14 VI. Colon Cancer and its Molecular Subsystems 15 Construction, Interpretation, and Validation a. Colon Cancer i. Etiology ii. Development iii. The Pathway Paradigm iv. Cancer Subtypes and Therapies b. Molecular Subsystems i. Introduction ii. Construction iii. Interpretation iv. Validation c. Summary VII. Prostaglandin dehydrogenase signaling 32 One driver and an unknown path a. Introduction i. Colon Cancer ii. Mass spectrometry 3 b. Methods c. Results d. Discussion e. Summary VIII. Apc signaling with Candidate Drivers 71 Two drivers, many paths a. Introduction b. Methods c. Results and Discussion d. Summary IX. Apc-Cdkn1a signaling 87 Two drivers, one path a. Introduction b. Methods c. Results i. Driver Gene Network Prediction ii. Single Node Perturbations 1. mRNA profiling 2. Proteomic profiling d. Discussion e. Summary X. Molecular Subsystems in Cancer 114 The Present to the Future XI. Appendix I 119 Prostaglandin dehydrogenase associated data XII.
    [Show full text]
  • Supercomplexes of Prokaryotic Aerobic Respiratory Chains Escherichia Coli and Bacillus Subtilis Supramolecular Assemblies Pedro M.F
    Supercomplexes of Prokaryotic Aerobic Respiratory Chains Escherichia coli and Bacillus subtilis supramolecular assemblies Pedro M.F. Sousa Dissertation presented to obtain the Ph.D degree in Biochemistry Instituto de Tecnologia Química e Biológica | Universidade Nova de Lisboa Instituto de Investigação Científica Tropical Oeiras, December, 2013 Supercomplexes of Prokaryotic Aerobic Respiratory Chains Escherichia coli and Bacillus subtilis supramolecular assemblies Pedro M.F. Sousa Dissertation presented to obtain the Ph.D degree in Biochemistry Instituto de Tecnologia Química e Biológica | Universidade Nova de Lisboa Instituto de Investigação Científica Tropical Supervisor: Ana M.P. Melo Co-supervisor: Miguel Teixeira Oeiras, December, 2013 From left to right: Prof. Miguel Teixeira, Dr. Lígia Saraiva, Prof. Carlos Romão, Prof. Thorsten Friedrich, Pedro Sousa, Dr. Margarida Duarte, Prof. João Arrabaça, Dr. Ana Melo. Instituto de Investigação Científica Tropical (IICT) Rua da Junqueira Nº86, 1º 1300-344 Lisboa Portugal Tel. (+351) 213 616 340 Instituto de Tecnologia Química e Biológica (ITQB) Av. da República Estação Agronómica Nacional 2780-157 Oeiras Portugal Tel. (+351) 214 469 323 The molecular cup is now empty. The time has come to replace the purely reductionist “eyes-down” molecular perspective with a new and genuinely holistic “eyes-up” view of the living world, one whose primary focus is on evolution, emergence, and biology’s innate complexity. Carl R.Woese (1928 – 2012) in “A new biology for a new century” Microbiology and Molecular Biology Reviews 68(2), 173 – 186 (2004) Acknowledgements The work summarized in this thesis is the product of several collaborations established during my research grant. It is with great appreciation that I would like to acknowledge the following groups and people: Ana Melo, my supervisor, for her endless support on my work.
    [Show full text]
  • Indoxyl Sulfate and P-Cresyl Sulfate Promote Vascular Calcification and Associate with Glucose Intolerance
    BASIC RESEARCH www.jasn.org Indoxyl Sulfate and p-Cresyl Sulfate Promote Vascular Calcification and Associate with Glucose Intolerance Britt Opdebeeck ,1 Stuart Maudsley,2,3 Abdelkrim Azmi,3 Annelies De Maré,1 Wout De Leger,4 Bjorn Meijers,5,6 Anja Verhulst,1 Pieter Evenepoel,5,6 Patrick C. D’Haese,1 and Ellen Neven1 1Laboratory of Pathophysiology, Department of Biomedical Sciences, 2Receptor Biology Lab, Department of Biomedical Sciences, and 3Translational Neurobiology Group, Flanders Institute of Biotechnology Center for Molecular Neurology, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium; 4Division of Molecular Design and Synthesis, Department of Chemistry and 6Laboratory of Nephrology, Department of Immunology and Microbiology, Catholic University of Leuven, Leuven, Belgium; and 5Division of Internal Medicine, Nephrology, University Hospitals Leuven, Leuven, Belgium ABSTRACT Background Protein-bound uremic toxins indoxyl sulfate (IS) and p-cresyl sulfate (PCS) have been associ- ated with cardiovascular morbidity and mortality in patients with CKD. However, direct evidence for a role of these toxins in CKD-related vascular calcification has not been reported. Methods To study early and late vascular alterations by toxin exposure, we exposed CKD rats to vehicle, IS (150 mg/kg per day), or PCS (150 mg/kg per day) for either 4 days (short-term exposure) or 7 weeks (long-term exposure). We also performed unbiased proteomic analyses of arterial samples coupled to functional bioinformatic annotation analyses to investigate molecular signaling events associated with toxin-mediated arterial calcification. Results Long-term exposure to either toxin at serum levels similar to those experienced by patients with CKD significantly increased calcification in the aorta and peripheral arteries.
    [Show full text]
  • Munkácsy E. & Rea, S. L. the Paradox Of
    NIH Public Access Author Manuscript Exp Gerontol. Author manuscript; available in PMC 2015 August 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Exp Gerontol. 2014 August ; 56: 221–233. doi:10.1016/j.exger.2014.03.016. The Paradox of Mitochondrial Dysfunction and Extended Longevity Erin Munkácsy1,2 and Shane L. Rea1,3,* 1Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78245-3207 USA 2Department of Cell and Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78245-3207 USA 3Department of Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78245-3207 USA Abstract Mitochondria play numerous, essential roles in the life of eukaryotes. Disruption of mitochondrial function in humans is often pathological or even lethal. Surprisingly, in some organisms mitochondrial dysfunction can result in life extension. This paradox has been studied most extensively in the long-lived Mit mutants of the nematode Caenorhabditis elegans. In this review, we explore the major responses that are activated following mitochondrial dysfunction in these animals and how these responses potentially act to extend their life. We focus our attention on five broad areas of current research – reactive oxygen species signaling, the mitochondrial unfolded protein response, autophagy, metabolic adaptation, and the roles played by various transcription factors. Lastly, we also examine why disruption of complexes I and II differ in their ability to induce the Mit phenotype and extend lifespan. Keywords C. elegans; Mitochondria; Mit Mutant; Lifespan; Aging; Metabolism 1.
    [Show full text]