DOCSLIB.ORG

The Proteasomal Deubiquitinating Enzyme PSMD14 Regulates Macroautophagy by Controlling Golgi-To-ER Retrograde Transport

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Supplementary Materials The proteasomal deubiquitinating enzyme PSMD14 regulates macroautophagy by controlling Golgi-to-ER retrograde transport Bustamante HA., et al. Figure S1. siRNA sequences directed against human PSMD14 used for Validation Stage. Figure S2. Primer pairs sequences used for RT-qPCR. Figure S3. The PSMD14 DUB inhibitor CZM increases the Golgi apparatus area. Immunofluorescence microscopy analysis of the Golgi area in parental H4 cells treated for 4 h either with the vehicle (DMSO; Control) or CZM. The Golgi marker GM130 was used to determine the region of interest in each condition. Statistical significance was determined by Student's t-test. Bars represent the mean ± SEM (n =43 cells). ***P <0.001. Figure S4. CZM causes the accumulation of KDELR1-GFP at the Golgi apparatus. HeLa cells expressing KDELR1-GFP were either left untreated or treated with CZM for 30, 60 or 90 min. Cells were fixed and representative confocal images were acquired. Figure S5. Effect of CZM on proteasome activity. Parental H4 cells were treated either with the vehicle (DMSO; Control), CZM or MG132, for 90 min. Protein extracts were used to measure in vitro the Chymotrypsin-like peptidase activity of the proteasome. The enzymatic activity was quantified according to the cleavage of the fluorogenic substrate Suc-LLVY-AMC to AMC, and normalized to that of control cells. The statistical significance was determined by One-Way ANOVA, followed by Tukey’s test. Bars represent the mean ± SD of biological replicates (n=3). **P <0.01; n.s., not significant. Figure S6. Effect of CZM and MG132 on basal macroautophagy. (A) Immunofluorescence microscopy analysis of the subcellular localization of LC3 in parental H4 cells treated with either with the vehicle (DMSO; Control), CZM for 4 h or MG132 for 6 h. Cells were fixed, permeabilized and stained with a rabbit polyclonal antibody to LC3B followed by Alexa-594-conjugated donkey anti-Rabbit IgG. Scale bar 10 μm. (B) Parental H4 cells were treated as in (A) and the protein extracts were analyzed by western blot with a polyclonal antibody to LC3B. Densitometric quantification of the protein levels of LC3B were depicted as the Ratio LC3B-II/LC3B-I. The statistical significance was determined by One-Way ANOVA, followed by Tukey’s test. Bars represent the mean ± SD of biological replicates (n=3). ***P <0.001; n.s., not significant. Figure S7. Distribution of RAB1A upon CZM treatment. Immunofluorescence analysis of endogenous RAB1A in H4 parental cells treated either with vehicle (DMSO; Control) (A-C) or CZM for 4 h (D-F). Cells were fixed, permeabilized, and double stained with a rabbit monoclonal antibody to RAB1A (clone D3X9S) (A and D) and a mouse monoclonal antibody to GM130 (clone35/GM130) (B and E), followed by Alexa-594-conjugated donkey anti-Rabbit IgG and Alexa-488- conjugated donkey anti-Mouse IgG. Merging of the images generated the third picture (C and F). Scale bar, 10 compared to control cells. The statistical significance was determined by Student's t-test. Bars represent the mean ± SEM of the fluorescent signal per cell area (n=173 cells). *P< 0.05. Figure S8. ATG9A is distributed in the swollen Golgi apparatus upon CZM treatment. Immunofluorescence analysis of endogenous ATG9A in H4 parental cells treated either with the vehicle (DMSO; Control) (A-C) or CZM for 4 h (D-F). Cells were fixed, permeabilized, and double stained with a rabbit monoclonal antibody to ATG9A (clone EPR2450(2)) (A and D) and a mouse monoclonal antibody to GM130 (clone35/GM130) (B and E), followed by Alexa-594-conjugated donkey anti-Rabbit IgG and Alexa-488- conjugated donkey anti-Mouse IgG. Merging of the images generated the third picture (C and F). Scale bar, 10 compared to control cells. The statistical significance was determined by Student's t-test. Bars represent the mean ± SEM of the fluorescent signal per cell area (n=93 cells). **P <0.01. Sequence siRNA #1 (5´-GAACAAGUCUAUAUCUCUU-3´) siRNA #2 (5´-GGCAUUAAUUCAUGGACUA-3´) siRNA #3 (5´-AGAGUUGGAUGGAAGGUUU-3´) siRNA #4 (5´-GAUGGUUGUUGGUUGGUAU-3´) Figure S1 Target S Sequence hTBP1 f(5´-TAGTCCAATGATGCCTTACG-3´) r(5´-TGGTCAGAGTTTGAGAATGG-3´) hPSMD14 f(5´-ACCTTAAGAGTTGTAGTTACTGACC-3´) r(5´-TTTAACAGTGCCAGGGAAGAG-3´) hAPP f(5´-CCTAAAGCATTTCGAGCATG-3´) r(5´-GTTTCCGTAACTGATCCTTG-3´) Figure S2 1.5 2.53 *** ) 2 m 1.0 µ 0.5 Golgi Area ( 0.0 Control µM CZM 10 Figure S3 15.24 150 n.s.** 125 100 75 50 normalized (%) 25 Chymotrypsin-like peptidase activity 0 Control 10 µM CZM 10 µM MG132 90 min Figure S5 A Control 10 µM CZM 10 µM MG132 LC3B B 4.03 5 *** B-I 3 4 C L / I I 3 B- 3 n.s. C 2 L o i t a 1 R 0 Control 10 µM CZM 10 µM MG132 Figure S6 RAB1A GM130 Merge A B C Control D E F M CZM µ 10 G 60 1.08 * ) 40 otal (% T 20 Fraction RAB1A Ratio GM130/ 0 Control 10 µM CZM Figure S7 ATG9A GM130 Merge A B C Control D E F M CZM µ 10 G 1.19 50 ** ) 40 otal (% 30 T 20 Fraction ATG9A Ratio GM130/ 10 0 Control 10 µM CZM Figure S8 Target List High-Content siRNA Screening “Ubiquitinome” Gene Symbol NCBI Reference Sequence PCGF2 NM_007144 PSMD14 NM_005805 RNF34 NM_025126 PSMD7 NM_002811 FBXO4 NM_012176 KCTD3 NM_016121 RNF141 NM_016422 UBE2E2 NM_152653 BRPF3 NM_015695 NACA NM_005594 CAND2 XM_944849 EPN1 NM_013333 UBXD4 NM_181713 SIAH2 NM_005067 TRIM23 NM_033228 UBA52 NM_003333 FAU NM_001997 EIF3S5 NM_003754 RSPRY1 NM_133368 MARK4 NM_031417 TRIM42 NM_152616 UBC NM_021009 FBXW10 NM_031456 UBE2E3 NM_182678 MDM2 NM_006879 RBM6 NM_005777 TOM1 NM_005488 ZBTB12 NM_181842 SOCS3 NM_003955 PHF12 NM_020889 FBXO44 NM_183413 DNAJB2 NM_001039550 RNF130 NM_018434 BIRC7 NM_022161 CREBL1 NM_004381 KBTBD2 NM_015483 RNF39 NM_170770 RYBP NM_012234 HRC NM_002152 NEURL NM_004210 VPRBP NM_014703 HECTD3 NM_024602 FAF1 NM_131917 ZNF592 NM_014630 PSMD4 NM_002810 FLJ25076 XM_940609 RNF187 XM_047499 TNK2 NM_001010938 SHFM3 NM_022039 PRPF8 NM_006445 EIF2AK4 NM_001013703 TRIM31 NM_052816 SUMO2 NM_001005849 UCHL3 NM_006002 FLJ20280 NM_017741 UBE2D4 NM_015983 TCEB1 NM_005648 MDM4 NM_002393 RAMP NM_016448 TRIM63 NM_032588 PHF23 NM_024297 UBE2J1 NM_016021 KUA-UEV NM_003349 DDI2 NM_032341 NICE-4 NM_014847 RNF146 NM_030963 UBB NM_018955 CHD5 NM_015557 ZBTB16 NM_001018011 CISH NM_145071 OTUD5 NM_017602 SENP8 NM_145204 ASPSCR1 NM_024083 FLJ43374 NM_198582 LOC652557 XM_942059 HIP2 NM_005339 SF3B3 NM_012426 UBE2V1 NM_001032288 LGALS3BP NM_005567 ZNF216 NM_006007 TRIM56 NM_030961 KIAA1536 NM_020898 SAE1 NM_005500 WDR11 NM_018117 KLHL1 NM_020866 SH3RF2 NM_152550 MNAT1 NM_002431 RAI17 NM_020338 KCTD17 NM_024681 PCF11 NM_015885 USP6 NM_004505 USP42 NM_032172 KCMF1 NM_020122 PHF21A NM_016621 VPS11 NM_021729 TRIM74 NM_198853 KRTAP5-9 NM_005553 KLHL7 NM_001031710 USP26 NM_031907 RNF32 NM_030936 USP16 NM_001001992 TRIM60 NM_152620 USP8 NM_005154 UBE2D2 NM_003339 KCTD12 NM_138444 UFC1 NM_016406 USP10 NM_005153 TA-KRP NM_032505 RPS27A NM_002954 UBE2J2 NM_194457 UBE2M NM_003969 RANBP9 NM_005493 LOC51035 NM_015853 BMI1 NM_005180 RKHD1 NM_203304 PC326 NM_001017977 HACE1 NM_020771 EIF3S3 NM_003756 FANCD2 NM_001018115 CDC34 NM_004359 YAF2 NM_005748 UBXD3 NM_152376 SIP NM_001007214 KCND1 NM_004979 RNF44 NM_014901 PEX10 NM_002617 ZNF151 NM_003443 USP52 NM_014871 ZRANB1 NM_017580 PLAA NM_001031689 TCEB2 NM_207013 BMI1 NM_005180 TCEB3 NM_003198 PDZRN4 NM_013377 RNF186 NM_019062 FLJ25555 NM_152345 LOC441061 XM_941081 BIRC2 NM_001166 BTBD14A NM_144653 STAMBPL1 NM_020799 LOC646862 XM_929820 MIB2 NM_080875 LMO7 NM_005358 PIAS1 NM_016166 FLJ10719 NM_018193 TRIM7 NM_203294 AB026190 NM_014458 LL0XNC01- UBE2NL NM_001012989 237H1.1 NM_001031834 FBXO5 NM_012177 USP9Y NM_004654 HECTD1 NM_015382 TRIM33 NM_033020 DKFZP547C195 NM_207343 LOC646862 XM_929820 TRIM32 NM_012210 TSG101 NM_006292 HECW1 NM_015052 TRIM6-TRIM34 NM_001003819 AIRE NM_000659 FBXO2 NM_012168 KCNC1 NM_004976 WDR26 NM_025160 UNK NM_001080419 SKP1A NM_170679 TRIM8 NM_030912 CUL5 NM_003478 SBBI54 NM_138334 C13ORF22 NM_005800 C20ORF18 NM_031227 TRAF7 NM_206835 RNF167 NM_015528 RBM10 NM_152856 KCNA1 NM_000217 FBXL20 NM_032875 OTUB2 NM_023112 ASB18 NM_212556 SPSB2 NM_032641 LONRF2 NM_198461 GGA3 NM_014001 USP45 XM_371838 SPSB3 NM_080861 PHF5A NM_032758 SHARPIN NM_030974 UBE4B NM_006048 HGS NM_004712 KLHDC5 NM_020782 TIP120A NM_018448 KCNC3 NM_004977 UEVLD NM_018314 RNF121 NM_194452 ATG10 NM_031482 PARK7 NM_007262 CHD4 NM_001273 UBE2N NM_003348 FBXO34 NM_017943 CUEDC1 NM_017949 UBQLN2 NM_013444 BARD1 NM_000465 ZNF185 NM_007150 TAB3 NM_198312 FBXO17 NM_148169 FBXL13 NM_145032 ANKFY1 NM_020740 MID2 NM_052817 USP43 XM_371015 FBXW5 NM_178226 PARC NM_015089 PRPF19 NM_014502 HR NM_018411 WDR40A NM_015397 ZNF297B NM_014007 RAB40C NM_021168 UBL5 NM_024292 FBXL12 NM_017703 PHF19 NM_001009936 BTBD9 NM_152733 KCTD5 NM_018992 PHF6 NM_032335 MARCH4 NM_020814 LRRC29 NM_001004055 ASB14 NM_130387 USP54 NM_152586 FLJ34154 NM_173813 HSHIN6 NM_207320 HUWE1 NM_031407 MYO6 NM_004999 ZBTB1 NM_014950 FBXL2 NM_012157 FBXL22 NM_203373 FBXO39 NM_153230 RNF207 NM_207396 UBE2H NM_182697 RFWD3 NM_018124 ZNF131 NM_003432 UBE2L6 NM_004223 LATS1 NM_004690 PHF16 NM_014735 EEA1 NM_003566 MARCH8 NM_001002266 ITCH NM_031483 FBXL14 NM_152441 BAZ1B NM_032408 BACH2 NM_021813 RFP NM_030950 DDB1 NM_001923 TOM1L1 NM_005486 TRIM2 NM_015271 BIRC3 NM_182962 RNF38 NM_194331 MSL2L1 NM_018133 DTX3 NM_178502 BRE NM_199191 SH3MD4 XM_293090 WDR71 NM_025155 NSMCE1 NM_145080 NOSIP NM_015953 PML NM_033247 RUFY1 NM_025158 C9ORF60 NM_006336 COPS4 NM_016129 SENP1 NM_014554 LOC392188 XM_373238 SIAH1 NM_003031 TRIM29 NM_058193 CCL20 NM_004591 VPS41 NM_080631 COPS7A NM_016319 ATG16L1 NM_198890 FEM1C NM_020177 MGC3123 NM_024107 ATG7 NM_006395 FBXO11 NM_012167
Recommended publications
  • Analysis of Trans Esnps Infers Regulatory Network Architecture

    Analysis of Trans Esnps Infers Regulatory Network Architecture

    Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation.
  • Genetic Screens in Isogenic Mammalian Cell Lines Without Single Cell Cloning

    Genetic Screens in Isogenic Mammalian Cell Lines Without Single Cell Cloning

    ARTICLE https://doi.org/10.1038/s41467-020-14620-6 OPEN Genetic screens in isogenic mammalian cell lines without single cell cloning Peter C. DeWeirdt1,2, Annabel K. Sangree1,2, Ruth E. Hanna1,2, Kendall R. Sanson1,2, Mudra Hegde 1, Christine Strand 1, Nicole S. Persky1 & John G. Doench 1* Isogenic pairs of cell lines, which differ by a single genetic modification, are powerful tools for understanding gene function. Generating such pairs of mammalian cells, however, is labor- 1234567890():,; intensive, time-consuming, and, in some cell types, essentially impossible. Here, we present an approach to create isogenic pairs of cells that avoids single cell cloning, and screen these pairs with genome-wide CRISPR-Cas9 libraries to generate genetic interaction maps. We query the anti-apoptotic genes BCL2L1 and MCL1, and the DNA damage repair gene PARP1, identifying both expected and uncharacterized buffering and synthetic lethal interactions. Additionally, we compare acute CRISPR-based knockout, single cell clones, and small- molecule inhibition. We observe that, while the approaches provide largely overlapping information, differences emerge, highlighting an important consideration when employing genetic screens to identify and characterize potential drug targets. We anticipate that this methodology will be broadly useful to comprehensively study gene function across many contexts. 1 Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, MA 02142, USA. 2These authors contributed equally: Peter C. DeWeirdt,
  • Computational Genome-Wide Identification of Heat Shock Protein Genes in the Bovine Genome [Version 1; Peer Review: 2 Approved, 1 Approved with Reservations]

    Computational Genome-Wide Identification of Heat Shock Protein Genes in the Bovine Genome [Version 1; Peer Review: 2 Approved, 1 Approved with Reservations]

    F1000Research 2018, 7:1504 Last updated: 08 AUG 2021 RESEARCH ARTICLE Computational genome-wide identification of heat shock protein genes in the bovine genome [version 1; peer review: 2 approved, 1 approved with reservations] Oyeyemi O. Ajayi1,2, Sunday O. Peters3, Marcos De Donato2,4, Sunday O. Sowande5, Fidalis D.N. Mujibi6, Olanrewaju B. Morenikeji2,7, Bolaji N. Thomas 8, Matthew A. Adeleke 9, Ikhide G. Imumorin2,10,11 1Department of Animal Breeding and Genetics, Federal University of Agriculture, Abeokuta, Nigeria 2International Programs, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14853, USA 3Department of Animal Science, Berry College, Mount Berry, GA, 30149, USA 4Departamento Regional de Bioingenierias, Tecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Queretaro, Mexico 5Department of Animal Production and Health, Federal University of Agriculture, Abeokuta, Nigeria 6Usomi Limited, Nairobi, Kenya 7Department of Animal Production and Health, Federal University of Technology, Akure, Nigeria 8Department of Biomedical Sciences, Rochester Institute of Technology, Rochester, NY, 14623, USA 9School of Life Sciences, University of KwaZulu-Natal, Durban, 4000, South Africa 10School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30032, USA 11African Institute of Bioscience Research and Training, Ibadan, Nigeria v1 First published: 20 Sep 2018, 7:1504 Open Peer Review https://doi.org/10.12688/f1000research.16058.1 Latest published: 20 Sep 2018, 7:1504 https://doi.org/10.12688/f1000research.16058.1 Reviewer Status Invited Reviewers Abstract Background: Heat shock proteins (HSPs) are molecular chaperones 1 2 3 known to bind and sequester client proteins under stress. Methods: To identify and better understand some of these proteins, version 1 we carried out a computational genome-wide survey of the bovine 20 Sep 2018 report report report genome.
  • The Mineralocorticoid Receptor Leads to Increased Expression of EGFR

    The Mineralocorticoid Receptor Leads to Increased Expression of EGFR

    www.nature.com/scientificreports OPEN The mineralocorticoid receptor leads to increased expression of EGFR and T‑type calcium channels that support HL‑1 cell hypertrophy Katharina Stroedecke1,2, Sandra Meinel1,2, Fritz Markwardt1, Udo Kloeckner1, Nicole Straetz1, Katja Quarch1, Barbara Schreier1, Michael Kopf1, Michael Gekle1 & Claudia Grossmann1* The EGF receptor (EGFR) has been extensively studied in tumor biology and recently a role in cardiovascular pathophysiology was suggested. The mineralocorticoid receptor (MR) is an important efector of the renin–angiotensin–aldosterone‑system and elicits pathophysiological efects in the cardiovascular system; however, the underlying molecular mechanisms are unclear. Our aim was to investigate the importance of EGFR for MR‑mediated cardiovascular pathophysiology because MR is known to induce EGFR expression. We identifed a SNP within the EGFR promoter that modulates MR‑induced EGFR expression. In RNA‑sequencing and qPCR experiments in heart tissue of EGFR KO and WT mice, changes in EGFR abundance led to diferential expression of cardiac ion channels, especially of the T‑type calcium channel CACNA1H. Accordingly, CACNA1H expression was increased in WT mice after in vivo MR activation by aldosterone but not in respective EGFR KO mice. Aldosterone‑ and EGF‑responsiveness of CACNA1H expression was confrmed in HL‑1 cells by Western blot and by measuring peak current density of T‑type calcium channels. Aldosterone‑induced CACNA1H protein expression could be abrogated by the EGFR inhibitor AG1478. Furthermore, inhibition of T‑type calcium channels with mibefradil or ML218 reduced diameter, volume and BNP levels in HL‑1 cells. In conclusion the MR regulates EGFR and CACNA1H expression, which has an efect on HL‑1 cell diameter, and the extent of this regulation seems to depend on the SNP‑216 (G/T) genotype.
  • Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model

    Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model

    Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A.
  • Recent Advances of M6a Methylation Modification in Esophageal Squamous Cell Carcinoma

    Recent Advances of M6a Methylation Modification in Esophageal Squamous Cell Carcinoma

    Zhang et al. Cancer Cell Int (2021) 21:421 https://doi.org/10.1186/s12935-021-02132-2 Cancer Cell International REVIEW Open Access Recent advances of m6A methylation modifcation in esophageal squamous cell carcinoma Xiaoqing Zhang1†, Ning Lu1†, Li Wang2†, Yixuan Wang1, Minna Li1, Ying Zhou3, Manli Cui1*, Mingxin Zhang1,3* and Lingmin Zhang4* Abstract In recent years, with the development of RNA sequencing technology and bioinformatics methods, the epigenetic modifcation of RNA based on N6-methyladenosine (m6A) has gradually become a research hotspot in the feld of bioscience. m6A is the most abundant internal modifcation in eukaryotic messenger RNAs (mRNAs). m6A methylation modifcation can dynamically and reversibly regulate RNA transport, localization, translation and degradation through the interaction of methyltransferase, demethylase and reading protein. m6A methylation can regulate the expression of proto-oncogenes and tumor suppressor genes at the epigenetic modifcation level to afect tumor occurrence and metastasis. The morbidity and mortality of esophageal cancer (EC) are still high worldwide. Esophageal squamous cell carcinoma (ESCC) is the most common tissue subtype of EC. This article reviews the related concepts, biological functions and recent advances of m6A methylation in ESCC, and looks forward to the prospect of m6A methylation as a new diagnostic biomarker and potential therapeutic target for ESCC. Keywords: N6-methyladenosine, Methylation, Esophageal squamous cell carcinoma Introduction surgical resection, combined radiotherapy and chemo- Esophageal cancer (EC) is one of the most invasive malig- therapy have improved the prognosis of patients with nant tumors of digestive tract in the world, and its mor- ESCC, the 5-year overall survival rate is still very low [5], bidity and mortality are still high in China [1].
  • ` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2

    ` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2

    ` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2, Stefan Knapp3,4,*, Matthieu Schapira1,5,* 1. Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada 2. Princess Margaret Cancer Centre and Department of Medical Biophysics, University of Toronto , Toronto, ON M5G 1L7, Canada 3. Nuffield Department of Clinical Medicine, Target Discovery Institute, and Structural Genomic Consortium, University of Oxford, Headington, Oxford OX3 7DQ, United Kingdom 4. Institute for Pharmaceutical Chemistry, Johann Wolfgang Goethe University, D-60438 Frankfurt am Main, Germany 5. Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada * Correspondence: [email protected], [email protected] Epigenetic chemical probes are having a strong impact on biological discovery and target validation. Systematic coverage of emerging epigenetic target classes with these potent, selective, cell-active chemical tools will profoundly influence our understanding of the human biology and pathology of chromatin-templated mechanisms. ` Chemical probes are research-enablers Advances in genomics and proteomics methodologies in recent years have made it possible to associate thousands of genes and proteins with specific diseases, biological processes, molecular networks and pathways. However, data from these large scale initiatives alone has not translated widely into new studies on these disease-associated proteins, and the biomedical research community still tends to focus on proteins that were already known before the sequencing of the human genome1. The human kinome for instance, a target class of direct relevance to cancer and other disease areas, is a telling example: based on the number of research articles indexed in pubmed in 2011, 75% of the research activity focused on only 10% of the 518 human kinases – largely the same kinases that were the focus of research before sequencing of the human genome - while 60% of the kinome, some 300 enzymes, was virtually ignored by the community2.
  • Potassium Channels in Epilepsy

    Potassium Channels in Epilepsy

    Downloaded from http://perspectivesinmedicine.cshlp.org/ on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Potassium Channels in Epilepsy Ru¨diger Ko¨hling and Jakob Wolfart Oscar Langendorff Institute of Physiology, University of Rostock, Rostock 18057, Germany Correspondence: [email protected] This review attempts to give a concise and up-to-date overview on the role of potassium channels in epilepsies. Their role can be defined from a genetic perspective, focusing on variants and de novo mutations identified in genetic studies or animal models with targeted, specific mutations in genes coding for a member of the large potassium channel family. In these genetic studies, a demonstrated functional link to hyperexcitability often remains elusive. However, their role can also be defined from a functional perspective, based on dy- namic, aggravating, or adaptive transcriptional and posttranslational alterations. In these cases, it often remains elusive whether the alteration is causal or merely incidental. With 80 potassium channel types, of which 10% are known to be associated with epilepsies (in humans) or a seizure phenotype (in animals), if genetically mutated, a comprehensive review is a challenging endeavor. This goal may seem all the more ambitious once the data on posttranslational alterations, found both in human tissue from epilepsy patients and in chronic or acute animal models, are included. We therefore summarize the literature, and expand only on key findings, particularly regarding functional alterations found in patient brain tissue and chronic animal models. INTRODUCTION TO POTASSIUM evolutionary appearance of voltage-gated so- CHANNELS dium (Nav)andcalcium (Cav)channels, Kchan- nels are further diversified in relation to their otassium (K) channels are related to epilepsy newer function, namely, keeping neuronal exci- Psyndromes on many different levels, ranging tation within limits (Anderson and Greenberg from direct control of neuronal excitability and 2001; Hille 2001).
  • 14321 NAE1/APPBP1 (D9I4Z) Rabbit Mab

    14321 NAE1/APPBP1 (D9I4Z) Rabbit Mab

    Revision 1 C 0 2 - t NAE1/APPBP1 (D9I4Z) Rabbit mAb a e r o t S Orders: 877-616-CELL (2355) [email protected] 1 Support: 877-678-TECH (8324) 2 3 Web: [email protected] 4 www.cellsignal.com 1 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source/Isotype: UniProt ID: Entrez-Gene Id: WB H M R Mk Endogenous 60 Rabbit IgG Q13564 8883 Product Usage Information 2. Huang, D.T. et al. (2005) Mol Cell 17, 341-50. 3. Liakopoulos, D. et al. (1998) EMBO J 17, 2208-14. Application Dilution 4. Gong, L. and Yeh, E.T. (1999) J Biol Chem 274, 12036-42. 5. Wada, H. et al. (2000) J Biol Chem 275, 17008-15. Western Blotting 1:1000 6. Sakata, E. et al. (2007) Nat Struct Mol Biol 14, 167-8. 7. Kawakami, T. et al. (2001) EMBO J 20, 4003-12. Storage 8. Podust, V.N. et al. (2000) Proc Natl Acad Sci USA 97, 4579-84. 9. Wu, K. et al. (2002) J Biol Chem 277, 516-27. Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA, 50% 10. Amir, R.E. et al. (2002) J Biol Chem 277, 23253-9. glycerol and less than 0.02% sodium azide. Store at –20°C. Do not aliquot the antibody. 11. Herrmann, J. et al. (2007) Circ Res 100, 1276-91. 12. Walden, H. et al. (2003) Mol Cell 12, 1427-37.
  • Is APP Key to the Appbp1 Pathway?

    Is APP Key to the Appbp1 Pathway?

    Open Access Full Text Article Austin Alzheimer’s and Parkinson’s Disease A Austin Publishing Group Review Article Cycle on Wheels: Is APP Key to the AppBp1 Pathway? Chen Y1,2*, Neve RN4, Zheng H3, Griffin WST1,2, Barger SW1,2 and Mrak RE5 Abstract 1Department of Geriatrics, University of Arkansas for Alzheimer’s disease (AD) is the gradual loss of the cognitive function due Medical Sciences, USA to neuronal death. Currently no therapy is available to slow down, reverse 2Department of Neurobiology and Developmental or prevent the disease. Here we analyze the existing data in literature and Sciences, University of Arkansas for Medical Sciences, hypothesize that the physiological function of the Amyloid Precursor Protein USA (APP) is activating the AppBp1 pathway and this function is gradually lost during 3Huffington Center on Aging, Baylor College of Medicine, the progression of AD pathogenesis. The AppBp1 pathway, also known as the USA neddylation pathway, activates the small ubiquitin-like protein nedd8, which 4Department of Brain and Cognitive Sciences, covalently modifies and switches on Cullin ubiquitin ligases, which are essential Massachusetts Institute of Technology, USA in the turnover of cell cycle proteins. Here we discuss how APP may activate the 5Department of Pathology, University of Toledo Health AppBp1 pathway, which downregulates cell cycle markers and protects genome Sciences Campus, USA integrity. More investigation of this mechanism-driven hypothesis may provide *Corresponding author: Chen Y, Department insights into disease treatment and prevention strategies. of Geriatrics and Department of Neurobiology and Keywords: APP; Alzheimer’s disease; Ubiquitination; Neddylation; Cell Developmental Sciences, University of Arkansas for cycle Medical Sciences, Little Rock, AR 72205, USA Received: September 02, 2014; Accepted: September 29, 2014; Published: September 30, 2014 Abbreviations at least 18 proteins have been identified to bind AICD [25-27].
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
  • To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants

    To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants

    Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin.