Proteome Differences Between Brown and White Fat Mitochondria Reveal Specialized Metabolic Functions
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Acetyl-Coa Synthetase 3 Promotes Bladder Cancer Cell Growth Under Metabolic Stress Jianhao Zhang1, Hongjian Duan1, Zhipeng Feng1,Xinweihan1 and Chaohui Gu2
Zhang et al. Oncogenesis (2020) 9:46 https://doi.org/10.1038/s41389-020-0230-3 Oncogenesis ARTICLE Open Access Acetyl-CoA synthetase 3 promotes bladder cancer cell growth under metabolic stress Jianhao Zhang1, Hongjian Duan1, Zhipeng Feng1,XinweiHan1 and Chaohui Gu2 Abstract Cancer cells adapt to nutrient-deprived tumor microenvironment during progression via regulating the level and function of metabolic enzymes. Acetyl-coenzyme A (AcCoA) is a key metabolic intermediate that is crucial for cancer cell metabolism, especially under metabolic stress. It is of special significance to decipher the role acetyl-CoA synthetase short chain family (ACSS) in cancer cells confronting metabolic stress. Here we analyzed the generation of lipogenic AcCoA in bladder cancer cells under metabolic stress and found that in bladder urothelial carcinoma (BLCA) cells, the proportion of lipogenic AcCoA generated from glucose were largely reduced under metabolic stress. Our results revealed that ACSS3 was responsible for lipogenic AcCoA synthesis in BLCA cells under metabolic stress. Interestingly, we found that ACSS3 was required for acetate utilization and histone acetylation. Moreover, our data illustrated that ACSS3 promoted BLCA cell growth. In addition, through analyzing clinical samples, we found that both mRNA and protein levels of ACSS3 were dramatically upregulated in BLCA samples in comparison with adjacent controls and BLCA patients with lower ACSS3 expression were entitled with longer overall survival. Our data revealed an oncogenic role of ACSS3 via regulating AcCoA generation in BLCA and provided a promising target in metabolic pathway for BLCA treatment. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction acetyl-CoA synthetase short chain family (ACSS), which In cancer cells, considerable number of metabolic ligates acetate and CoA6. -
Type of the Paper (Article
Supplementary Material A Proteomics Study on the Mechanism of Nutmeg-induced Hepatotoxicity Wei Xia 1, †, Zhipeng Cao 1, †, Xiaoyu Zhang 1 and Lina Gao 1,* 1 School of Forensic Medicine, China Medical University, Shenyang 110122, P. R. China; lessen- [email protected] (W.X.); [email protected] (Z.C.); [email protected] (X.Z.) † The authors contributed equally to this work. * Correspondence: [email protected] Figure S1. Table S1. Peptide fraction separation liquid chromatography elution gradient table. Time (min) Flow rate (mL/min) Mobile phase A (%) Mobile phase B (%) 0 1 97 3 10 1 95 5 30 1 80 20 48 1 60 40 50 1 50 50 53 1 30 70 54 1 0 100 1 Table 2. Liquid chromatography elution gradient table. Time (min) Flow rate (nL/min) Mobile phase A (%) Mobile phase B (%) 0 600 94 6 2 600 83 17 82 600 60 40 84 600 50 50 85 600 45 55 90 600 0 100 Table S3. The analysis parameter of Proteome Discoverer 2.2. Item Value Type of Quantification Reporter Quantification (TMT) Enzyme Trypsin Max.Missed Cleavage Sites 2 Precursor Mass Tolerance 10 ppm Fragment Mass Tolerance 0.02 Da Dynamic Modification Oxidation/+15.995 Da (M) and TMT /+229.163 Da (K,Y) N-Terminal Modification Acetyl/+42.011 Da (N-Terminal) and TMT /+229.163 Da (N-Terminal) Static Modification Carbamidomethyl/+57.021 Da (C) 2 Table S4. The DEPs between the low-dose group and the control group. Protein Gene Fold Change P value Trend mRNA H2-K1 0.380 0.010 down Glutamine synthetase 0.426 0.022 down Annexin Anxa6 0.447 0.032 down mRNA H2-D1 0.467 0.002 down Ribokinase Rbks 0.487 0.000 -
Mouse Acss3 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Acss3 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Acss3 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Acss3 gene (NCBI Reference Sequence: NM_001142804 ; Ensembl: ENSMUSG00000035948 ) is located on Mouse chromosome 10. 16 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 16 (Transcript: ENSMUST00000165067). Exon 2 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Acss3 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-414G20 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 2 starts from about 14.52% of the coding region. The knockout of Exon 2 will result in frameshift of the gene. The size of intron 1 for 5'-loxP site insertion: 38336 bp, and the size of intron 2 for 3'-loxP site insertion: 31290 bp. The size of effective cKO region: ~645 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 2 16 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Acss3 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
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. -
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 -
Curcumin Alters Gene Expression-Associated DNA Damage, Cell Cycle, Cell Survival and Cell Migration and Invasion in NCI-H460 Human Lung Cancer Cells in Vitro
ONCOLOGY REPORTS 34: 1853-1874, 2015 Curcumin alters gene expression-associated DNA damage, cell cycle, cell survival and cell migration and invasion in NCI-H460 human lung cancer cells in vitro I-TSANG CHIANG1,2, WEI-SHU WANG3, HSIN-CHUNG LIU4, SU-TSO YANG5, NOU-YING TANG6 and JING-GUNG CHUNG4,7 1Department of Radiation Oncology, National Yang‑Ming University Hospital, Yilan 260; 2Department of Radiological Technology, Central Taiwan University of Science and Technology, Taichung 40601; 3Department of Internal Medicine, National Yang‑Ming University Hospital, Yilan 260; 4Department of Biological Science and Technology, China Medical University, Taichung 404; 5Department of Radiology, China Medical University Hospital, Taichung 404; 6Graduate Institute of Chinese Medicine, China Medical University, Taichung 404; 7Department of Biotechnology, Asia University, Taichung 404, Taiwan, R.O.C. Received March 31, 2015; Accepted June 26, 2015 DOI: 10.3892/or.2015.4159 Abstract. Lung cancer is the most common cause of cancer CARD6, ID1 and ID2 genes, associated with cell survival and mortality and new cases are on the increase worldwide. the BRMS1L, associated with cell migration and invasion. However, the treatment of lung cancer remains unsatisfactory. Additionally, 59 downregulated genes exhibited a >4-fold Curcumin has been shown to induce cell death in many human change, including the DDIT3 gene, associated with DNA cancer cells, including human lung cancer cells. However, the damage; while 97 genes had a >3- to 4-fold change including the effects of curcumin on genetic mechanisms associated with DDIT4 gene, associated with DNA damage; the CCPG1 gene, these actions remain unclear. Curcumin (2 µM) was added associated with cell cycle and 321 genes with a >2- to 3-fold to NCI-H460 human lung cancer cells and the cells were including the GADD45A and CGREF1 genes, associated with incubated for 24 h. -
Visual Gene Network Analysis of Aging-Specific Gene Co-Expression
4open 2018, 1,4 © B.P. Parida et al., Published by EDP Sciences 2018 https://doi.org/10.1051/fopen/2018004 Available online at: www.4open-sciences.org RESEARCH ARTICLE Visual gene network analysis of aging-specific gene co-expression in human indicates overlaps with immuno-pathological regulations Bibhu Prasad Parida1,*, Biswapriya Biswavas Misra2, Amarendra Narayan Misra3,4 1 Post-Graduate Department of Biosciences and Biotechnology, School of Biotechnology, Fakir Mohan University, Balasore 756020, Odisha, India 2 Department of Internal Medicine, Section on Molecular Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem 27157, NC, USA 3 Central University of Jharkhand, Brambe, Ratu-Lohardaga Road, Ranchi 835205, Jharkhand, India 4 Khallikote University, Berhampur 760001, Odisha, India Received 19 September 2017, Accepted 4 July 2018 Abstract- - Introduction: Aging is a complex biological process that brings about a gradual decline of physiological and metabolic machineries as a result of maturity. Also, aging is irreversible and leads ultimately to death in biological organisms. Methods: We intend to characterize aging at the gene expression level using publicly available human gene expression arrays obtained from gene expression omnibus (GEO) and ArrayExpress. Candidate genes were identified by rigorous screening using filtered data sets, i.e., GSE11882, GSE47881, and GSE32719. Using Aroma and Limma packages, we selected the top 200 genes showing up and down regulation (p < 0.05 and fold change >2.5) out of which 185 were chosen for further comparative analysis. Results: This investigation enabled identification of candidate genes involved in aging that are associated with several signaling cascades demonstrating strong correlation with ATP binding and protease functions. -
Kidney V-Atpase-Rich Cell Proteome Database
A comprehensive list of the proteins that are expressed in V-ATPase-rich cells harvested from the kidneys based on the isolation by enzymatic digestion and fluorescence-activated cell sorting (FACS) from transgenic B1-EGFP mice, which express EGFP under the control of the promoter of the V-ATPase-B1 subunit. In these mice, type A and B intercalated cells and connecting segment principal cells of the kidney express EGFP. The protein identification was performed by LC-MS/MS using an LTQ tandem mass spectrometer (Thermo Fisher Scientific). For questions or comments please contact Sylvie Breton ([email protected]) or Mark A. Knepper ([email protected]). -
Virus-Infected (V), and Virus-Infected Binase-Treated (VB) Samples
Table S1. Abundance of proteins affected by the virus and/or binase in mock-treated (M), binase-treated (B), virus-infected (V), and virus-infected binase-treated (VB) samples. The blue and white colors indicate that the respective protein was either detected or not detected, respectively, in the sample above 1% FDR cut-off. Protein Mock Binase Virus Virus+Binase Description ACTB Actin, cytoplasmic 1 ATL2 Atlastin-2 CCT7 T-complex protein 1 subunit eta CS Citrate synthase, mitochondrial DES Desmin EEF1A1 Elongation factor 1-alpha 1 EFTUD2 116 kDa U5 small nuclear ribonucleoprotein component ENO1 Alpha-enolase EZR Ezrin GPI Glucose-6-phosphate isomerase HIST1H2BB Histone H2B type 1-B HNRNPA2B1 Heterogeneous nuclear ribonucleoproteins A2/B1 HSPD1 60 kDa heat shock protein, mitochondrial KRT75 Keratin, type II cytoskeletal 75 LRPPRC Leucine-rich PPR motif-containing protein, mitochondrial NAP1L1 Nucleosome assembly protein 1-like 1 NCL Nucleolin NADH dehydrogenase [ubiquinone] iron-sulfur protein 8, NDUFS8 mitochondrial PGK1 Phosphoglycerate kinase 1 POTEE POTE ankyrin domain family member E POTEI POTE ankyrin domain family member I PRPH Peripherin RAP1A Ras-related protein Rap-1A RPS2 40S ribosomal protein S2 SF3B1 Splicing factor 3B subunit 1 TALDO1 Transaldolase TARS Threonine--tRNA ligase, cytoplasmic TARSL2 Probable threonine--tRNA ligase 2, cytoplasmic TKT Transketolase AHSA1 Activator of 90 kDa heat shock protein ATPase homolog 1 HSPA2 Heat shock-related 70 kDa protein 2 RPL15 60S ribosomal protein L15 TXNDC5 Thioredoxin domain-containing protein 5 DDX18 ATP-dependent RNA helicase DDX18 Int. J. Mol. Sci. 2020, 21, x; doi: FOR PEER REVIEW www.mdpi.com/journal/ijms Int. -
(Print)Table S4 Identified Glycopeptides and Glycoproteins Of
Electronic Supplementary Material (ESI) for ChemComm. This journal is © The Royal Society of Chemistry 2019 Table S4 Identified N-glycoproteins and N-glycopeptides sequence from the tryptic digest of proteins extracted from HepG2 cells after enrichment by AuGC/ZIF-8 Unique Protein Group No. Sequence Protein Descriptions Sequence Accessions Histone H2A type 1-D OS=Homo sapiens OX=9606 GN=HIST1H2AD PE=1 SV=2 - 1 KGNYSER 603 [H2A1D_HUMAN]|Histone H2A type 1-H OS=Mus musculus OX=10090 P20671;Q8CGP6 GN=Hist1h2ah PE=1 SV=3 - [H2A1H_MOUSE] Spectrin alpha chain, non-erythrocytic 1 OS=Homo sapiens OX=9606 GN=SPTAN1 2 KnNHHEENISSK 3137 Q13813 PE=1 SV=3 - [SPTN1_HUMAN] TATA-binding protein-associated factor 2N OS=Homo sapiens OX=9606 GN=TAF15 3 ENYSHHTQDDRR 3684 Q92804 PE=1 SV=1 - [RBP56_HUMAN] Pre-mRNA 3'-end-processing factor FIP1 OS=Homo sapiens OX=9606 GN=FIP1L1 4 NSTSSQSQTSTASR 3961 Q6UN15 PE=1 SV=1 - [FIP1_HUMAN] Nucleolar and coiled-body phosphoprotein 1 OS=Homo sapiens OX=9606 GN=NOLC1 5 NSSNKPAVTTK 4223 Q14978 PE=1 SV=2 - [NOLC1_HUMAN] 6 SGNLTEDDKHNNAK 4249 Plastin-3 OS=Homo sapiens OX=9606 GN=PLS3 PE=1 SV=4 - [PLST_HUMAN] P13797 Keratin, type I cytoskeletal 18 OS=Homo sapiens OX=9606 GN=KRT18 PE=1 SV=2 - 7 VVSETNDTK 5000 P05783 [K1C18_HUMAN] Osteopetrosis-associated transmembrane protein 1 OS=Homo sapiens OX=9606 8 AAGnTSESQScAR 5528 Q86WC4 GN=OSTM1 PE=1 SV=1 - [OSTM1_HUMAN] Transcription elongation factor A protein 1 OS=Homo sapiens OX=9606 GN=TCEA1 9 EESTSSGNVSNR 5530 P23193 PE=1 SV=2 - [TCEA1_HUMAN] Nuclear protein localization protein -
Supplemental Figures 04 12 2017
Jung et al. 1 SUPPLEMENTAL FIGURES 2 3 Supplemental Figure 1. Clinical relevance of natural product methyltransferases (NPMTs) in brain disorders. (A) 4 Table summarizing characteristics of 11 NPMTs using data derived from the TCGA GBM and Rembrandt datasets for 5 relative expression levels and survival. In addition, published studies of the 11 NPMTs are summarized. (B) The 1 Jung et al. 6 expression levels of 10 NPMTs in glioblastoma versus non‐tumor brain are displayed in a heatmap, ranked by 7 significance and expression levels. *, p<0.05; **, p<0.01; ***, p<0.001. 8 2 Jung et al. 9 10 Supplemental Figure 2. Anatomical distribution of methyltransferase and metabolic signatures within 11 glioblastomas. The Ivy GAP dataset was downloaded and interrogated by histological structure for NNMT, NAMPT, 12 DNMT mRNA expression and selected gene expression signatures. The results are displayed on a heatmap. The 13 sample size of each histological region as indicated on the figure. 14 3 Jung et al. 15 16 Supplemental Figure 3. Altered expression of nicotinamide and nicotinate metabolism‐related enzymes in 17 glioblastoma. (A) Heatmap (fold change of expression) of whole 25 enzymes in the KEGG nicotinate and 18 nicotinamide metabolism gene set were analyzed in indicated glioblastoma expression datasets with Oncomine. 4 Jung et al. 19 Color bar intensity indicates percentile of fold change in glioblastoma relative to normal brain. (B) Nicotinamide and 20 nicotinate and methionine salvage pathways are displayed with the relative expression levels in glioblastoma 21 specimens in the TCGA GBM dataset indicated. 22 5 Jung et al. 23 24 Supplementary Figure 4. -
Lupus Nephritis Supp Table 5
Supplementary Table 5 : Transcripts and DAVID pathways correlating with the expression of CD4 in lupus kidney biopsies Positive correlation Negative correlation Transcripts Pathways Transcripts Pathways Identifier Gene Symbol Correlation coefficient with CD4 Annotation Cluster 1 Enrichment Score: 26.47 Count P_Value Benjamini Identifier Gene Symbol Correlation coefficient with CD4 Annotation Cluster 1 Enrichment Score: 3.16 Count P_Value Benjamini ILMN_1727284 CD4 1 GOTERM_BP_FAT translational elongation 74 2.50E-42 1.00E-38 ILMN_1681389 C2H2 zinc finger protein-0.40001984 INTERPRO Ubiquitin-conjugating enzyme/RWD-like 17 2.00E-05 4.20E-02 ILMN_1772218 HLA-DPA1 0.934229063 SP_PIR_KEYWORDS ribosome 60 2.00E-41 4.60E-39 ILMN_1768954 RIBC1 -0.400186083 SMART UBCc 14 1.00E-04 3.50E-02 ILMN_1778977 TYROBP 0.933302249 KEGG_PATHWAY Ribosome 65 3.80E-35 6.60E-33 ILMN_1699190 SORCS1 -0.400223681 SP_PIR_KEYWORDS ubl conjugation pathway 81 1.30E-04 2.30E-02 ILMN_1689655 HLA-DRA 0.915891173 SP_PIR_KEYWORDS protein biosynthesis 91 4.10E-34 7.20E-32 ILMN_3249088 LOC93432 -0.400285215 GOTERM_MF_FAT small conjugating protein ligase activity 35 1.40E-04 4.40E-02 ILMN_3228688 HLA-DRB1 0.906190291 SP_PIR_KEYWORDS ribonucleoprotein 114 4.80E-34 6.70E-32 ILMN_1680436 CSH2 -0.400299744 SP_PIR_KEYWORDS ligase 54 1.50E-04 2.00E-02 ILMN_2157441 HLA-DRA 0.902996561 GOTERM_CC_FAT cytosolic ribosome 59 3.20E-33 2.30E-30 ILMN_1722755 KRTAP6-2 -0.400334007 GOTERM_MF_FAT acid-amino acid ligase activity 40 1.60E-04 4.00E-02 ILMN_2066066 HLA-DRB6 0.901531942 SP_PIR_KEYWORDS