DOCSLIB.ORG

Flexible Visualization of the Human Phosphatome

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Flexible Visualization of the Human Phosphatome bioRxiv preprint doi: https://doi.org/10.1101/701508; this version posted July 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. CoralP: Flexible visualization of the human phosphatome Amit Min1, Erika Deoudes1, Marielle L. Bond1, Eric S. Davis2, Douglas H. Phanstiel1,2,3,4,5,6 1Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC 27599, USA 2Curriculum in Bioinformatics & Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA 3Curriculum in Genetics & Molecular Biology, University of North Carolina, Chapel Hill, NC 27599, USA 4Department of Cell Biology & Physiology, University of North Carolina, Chapel Hill, NC 27599, USA 5Lineberger Comprehensive Cancer Research Center, University of North Carolina, Chapel Hill, NC 27599, USA 6Correspondence: [email protected] Protein phosphatases and kinases play critical roles phosphatases, there exists a great need for methods to in a host of biological processes and diseases via the analyze, interpret, and communicate experimental results removal and addition of phosphoryl groups. While within the context of the entire protein family (Chen et al., kinases have been extensively studied for decades, 2017). recent findings regarding the specificity and activities While numerous methods have been developed to of phosphatases have generated an increased visualize the human kinome (Chartier et al., 2013; Eid et interest in targeting phosphatases for pharmaceutical al., 2017; Metz et al., 2018), no such software exists for development. This increased focus has created a the human phosphatome. Existing methods to visualize need for methods to visualize this important class of kinases make use of a phylogenetic kinase tree that was proteins within the context of the entire phosphatase constructed shortly after the sequencing of the human protein family. Here, we present CoralP, an interactive genome and later modified by Cell Signaling (www. web application for the generation of customizable, cellsignal.com). These software packages allow for the publication-quality representations of human encoding of multiple kinase attributes and data types phosphatome data. Phosphatase attributes can be through colors, sizes, and shapes laid out in a kinase tree encoded through edge colors, node colors, and node organized by sequence and functional similarity. Last sizes. CoralP is the first and currently the only tool year, we developed Coral, an interactive web application designed for phosphatome visualization and should that produces publication-quality visualizations of the be of great use to the signaling community. The source human kinome (Metz et al., 2018). Coral allows for the code and web application are available at https:// simultaneous encoding of three attributes per kinase, github.com/PhanstielLab/coralp and http://phanstiel- supports three modes of visualization, and produces high- lab.med.unc.edu/coralp respectively. resolution vector images. Recently, Chen et al. published a phylogenetic phosphatase tree (Chen et al., 2017); INTRODUCTION however, to the best of our knowledge, there are currently no available tools to visualize phosphatase data within the P Protein phosphorylation is an important post- context of this or any other format. translational modification that plays a major role in Here, we describe CoralP, a web application for regulating protein activity and function. Misregulation of the generation of customizable, publication-quality phosphorylation has been implicated in a host of human visualizations of the human phosphatome. Qualitative diseases including cancer (Ostman et al., 2006; Tonks, and quantitative features can be represented in branch 2006), rheumatoid arthritis (Begovich et al., 2004; Hendriks colors, node colors, and node sizes. Phosphatases can et al., 2013), and various neurological disorders (Pulido and be organized using the published phosphatome tree or Hooft van Huijsduijnen, 2008; Robinson and Dixon, 2005). As as radial or force-directed networks. CoralP is simple to such, altering protein phosphorylation levels has become a use, well documented, and freely available. It is the first and major focus of pharmaceutical development (Cohen, 2002). only dedicated tool for phosphatome visualization and is Protein phosphorylation is regulated primarily by protein widely applicable to a variety of data types including those kinases and protein phosphatases which add and remove generated from proteomic, genomic, epidemiological, and phosphoryl groups respectively. While protein kinases high-throughput screening experiments. have been the primary focus of research for the past several decades, recent findings regarding the activities RESULTS and specificities of their counterparts have generated an increased interest in the role of phosphatases in human CoralP is built using the same underlying framework disease research (Andersen et al., 2004; Sacco et al., as Coral and therefore makes use of similar strategies 2012; Tiganis and Bennett, 2007; Tonks, 2006). Because for data input, setting selection, and data download. of this interest and the fact that there are over 180 human Phosphatase attributes can be entered using pull-down 1 bioRxiv preprint doi: https://doi.org/10.1101/701508; this version posted July 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. PTPN14 PTPN13 PTPN21 Auto-generate legend PTPN20Color branches by value Match text color to branches PTPN3 PTPN1 PTPN23 PTPN2 PTPN4 PPP4C PPP6C BranchPTPN18 Color PPP2CB log2 RNA (ES / fibroblast)PTPN9 -3 0 3 PTPRS-D2 PTPRG-D2 PPP2CA PTPRD-D2 RPTPZ1-D2 PTPRN2 PTPRU-D2 PPP1CA Node Color PTPRN PTPRK-D2 PTPRF-D2 PPP1CB log2 RNA (ES / fibroblast) -3 0 3 PTPRT-D2 PPP1CC PTPRM-D2 PPP3CA PTPRA-D2 PPP3CB Node Size PTPRE-D2 PPP ES — RNA RPKM PPP3CC 0 100 FIG4 SACM1L CC1 PTPRC-D2 PPP4C PPP6C PPPL PPP2CB PTP PTPRR PTPN6 PTPN11 INPP5F PPP2CA PPP5C PAP PTPN5 PTPN14 PTPN13 PTPN21 PTPN7 SYNJ1 PPP1CA Paladin PTPN20 SAC PTPN3 PPP1CB PTPN1 SYNJ2 PTPN2 PTPN23 PPP1CC PTPN4 PPP3CA PTPN22 PTPN12PTPN18 PTPRB PTPN9 MTMR10 PPP3CB PPEF2 MTMR14 MTMR11 PTPRS-D2 PTPRG-D2 PTPRO PTPRD-D2 PPP PTPRJ RPTPZ1-D2 PPP3CC PTPRS-D1 PTPRQ PTPRN2 MTMR12 PTPRU-D2 PTPRD-D1 PPEF1 ACP5 PTPRN SBF1 PTPRK-D2 PTPRH PTPRF-D2 PTPRF-D1 ACP7 PTPRZ1-D1 PTPRT-D2 PPP5C PAP PTPRM-D2 PTPRG-D1 PTPRK-D1 PTPRA-D2 PTPRU-D1 PTPRE-D2 PPEF2 PTPRM-D1 FIG4 PGAM1 PTPRT-D1 SACM1L PTPRC-D2 PGAM2 PTPRC-D1 PPEF1 BPGM PGAM4 PALD1 PTP INPP5F HP PTPRA-D1 SYNJ1 Paladin MINPP1 TIGAR SAC SYNJ2 PTPRE-D1 SSH1 DUSP1 MTMR10 PPIP5K2 DUSP4 SSH3 DSP + MTMR14 MTMR11 PFKFB3 DUSP15 HP1 DUSP22 PTEN MTMR12 PPIP5K1 DUSP2 PFKFB2 SSH2 SBF1 MTMR6 Myotubularin SBF2 PFKFB1 DUSP5 MTMR7 PXYLP1 DUSP8 DUSP19 PFKFB4 PGAM5 DUSP16 MTMR8 HP2 DUSP12 ACP6 DUSP10 DUSP28 MTMR9 UBASH3B DUSP9 DUSP21 PPM MTMR1 UBASH3A DUSP18 ACPT DUSP7 MTMR2 ACPP MTMR4 MTM1 MTMR3 PDP1 PDP2 ACP2 PTPMT1 DUSP14 DUSP6 STYXL1 TPTE2 PHLPP1 RNGTT PHLPP2 TPTE PPTC7 STYX Laforin DUSP11 PTEN PPM1A DUPD1 ILKAP TNS1 PPM1B DUSP13 CDKN3 HAD DUSP26 TNS3 PPM1F PPM1N DUSP3 CDC14B DUSP23 TNS2 DUSP27 Dullard CDC14A DNAJC6 PPM1E SCP3 GAK SCP2 TIMM50 PPM1G PTPDC1 SCP1 PTP4A3 PPM1D PTP4A1 PTP4A2 PP2D1 FCP1 CTDSPL2 TAB1 PPM1L PPMFCP PPM1M PPM1H PPM1J PPM1K UBLCP1 CDC25A CC3 EYA3 PDP1EYA4 PDP2 CC2 AP CECR5 PHLPP1 PGP EYA2 EYA ALPL PHLPP2 ALPI PPTC7 CIN CDC25B PHP RTR1 EYA1 NagD ALPP LMWPTP SSU72 HDHD2 CDC25C LHPP ALPPL2 PHPT1 RPAP2 PPM1A ILKAP PTPRE-D1 PTPRE-D2 PPM1B DUSP1 SSH1 SSH3 FIG4 DUSP4 DUSP15 DSP + SACM1L PTPRC-D2 PPM1F PPM1N DUSP22 PTEN DUSP2 INPP5F SSH2 PPM1E SYNJ1 DUSP5Paladin PPM1G SAC SYNJ2 DUSP8 PPM1D DUSP16 PP2D1 MTMR14 MTMR11 MTMR10 DUSP10 MTMR12 TAB1 PPM1L DUSP9 SBF1 PPM1M SBF2 MTMR6 PPM1H PPM1J PPM1K DUSP7 Myotubularin MTMR7 DUSP6 STYXL1 MTMR8 STYX MTMR9 Add color nodes Resize nodes byMTMR1 value Set node opacity stroke Figure 1. CoralP tree plot highlighting some of it’s features. The default view of a CoralP tree plot is shown in grey. Circular inserts reveal some of the formatting options. (Top left) Legends are automatically generated as users configure settings. (Top middle) Branch color can be used to encode quantitative or qualitative information. (Top right) Users can adjust the font type and color of phosphatase labels and even match the label color to the branch color. (Bottom left) Nodes can be added and recolored to depict qualitative or quantitative information. (Bottom middle) Node size can be used to encode quantitative information. (Bottom right) Users can control many aesthetic options including node opacity and stroke color. 2 bioRxiv preprint doi: https://doi.org/10.1101/701508; this version posted July 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. menus or pasted into text boxes. CoralP supports multiple dashboard (Chang and Borges Ribeiro, 2018), shinyBS (Bailey, identifiers including UniProt, ENSEMBL, Entrez, and HGNC. 2015) and shinyWidgets (Perrier et al., 2019) were used for the web framework. Visualization options including color palettes, data scales, fonts, and protein identifiers can all be edited via an intuitive The R packages readr (Wickham et al., 2018) and rsvg (Ooms, graphical user interface. CoralP was written using the 2018) were used for data manipulation and rendering the SVG reactive programming package Shiny (Chang et al., 2018), elements. so CoralP plots update in real-time as users adjust settings, RColorBrewer (Neuwirth, 2014) was utilized for color palettes. making it easy to generate a plot perfectly customized to the user's preferences. The Circle and Force layouts were written using the D3.js library CoralP offers highly flexible methods for visualizing (Bostock et al., 2011).
Load more

Recommended publications
  • Gene Expression Profiling Identifies Candidate Biomarkers for Active And
    Lee et al. BMC Bioinformatics 2016, 17(Suppl 1):3 DOI 10.1186/s12859-015-0848-x PROCEEDINGS Open Access Gene expression profiling identifies candidate biomarkers for active and latent tuberculosis Shih-Wei Lee1,2†, Lawrence Shih-Hsin Wu3†, Guan-Mau Huang4, Kai-Yao Huang4, Tzong-Yi Lee4,5 and Julia Tzu-Ya Weng4,5* From The Fourteenth Asia Pacific Bioinformatics Conference (APBC 2016) San Francisco, CA, USA. 11 - 13 January 2016 Abstract Background: Tuberculosis (TB) is a serious infectious disease in that 90 % of those latently infected with Mycobacterium tuberculosis present no symptoms, but possess a 10 % lifetime chance of developing active TB. To prevent the spread of the disease, early diagnosis is crucial. However, current methods of detection require improvement in sensitivity, efficiency or specificity. In the present study, we conducted a microarray experiment, comparing the gene expression profiles in the peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population. Results: Bioinformatics analysis revealed that most of the differentially expressed genes belonged to immune responses, inflammation pathways, and cell cycle control. Subsequent RT-PCR validation identified four differentially expressed genes, NEMF, ASUN, DHX29, and PTPRC, as potential biomarkers for the detection of active and latent TB infections. Receiver operating characteristic analysis showed that the expression level of PTPRC may discriminate active TB patients from healthy individuals, while ASUN could differentiate between the latent state of TB infection and healthy condidtion. In contrast, DHX29 may be used to identify latently infected individuals among active TB patients or healthy individuals. To test the concept of using these biomarkers as diagnostic support, we constructed classification models using these candidate biomarkers and found the Naïve Bayes-based model built with ASUN, DHX29,and PTPRC to yield the best performance.
    [Show full text]
  • Supplemental Figure 1. Vimentin
    Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672
    [Show full text]
  • 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.
    [Show full text]
  • Analysis of the Stability of 70 Housekeeping Genes During Ips Reprogramming Yulia Panina1,2*, Arno Germond1 & Tomonobu M
    www.nature.com/scientificreports OPEN Analysis of the stability of 70 housekeeping genes during iPS reprogramming Yulia Panina1,2*, Arno Germond1 & Tomonobu M. Watanabe1 Studies on induced pluripotent stem (iPS) cells highly rely on the investigation of their gene expression which requires normalization by housekeeping genes. Whether the housekeeping genes are stable during the iPS reprogramming, a transition of cell state known to be associated with profound changes, has been overlooked. In this study we analyzed the expression patterns of the most comprehensive list to date of housekeeping genes during iPS reprogramming of a mouse neural stem cell line N31. Our results show that housekeeping genes’ expression fuctuates signifcantly during the iPS reprogramming. Clustering analysis shows that ribosomal genes’ expression is rising, while the expression of cell-specifc genes, such as vimentin (Vim) or elastin (Eln), is decreasing. To ensure the robustness of the obtained data, we performed a correlative analysis of the genes. Overall, all 70 genes analyzed changed the expression more than two-fold during the reprogramming. The scale of this analysis, that takes into account 70 previously known and newly suggested genes, allowed us to choose the most stable of all genes. We highlight the fact of fuctuation of housekeeping genes during iPS reprogramming, and propose that, to ensure robustness of qPCR experiments in iPS cells, housekeeping genes should be used together in combination, and with a prior testing in a specifc line used in each study. We suggest that the longest splice variants of Rpl13a, Rplp1 and Rps18 can be used as a starting point for such initial testing as the most stable candidates.
    [Show full text]
  • Cytokine-Driven Cell Cycling Is Mediated Through Cdc25a
    JCB: ARTICLE Cytokine-driven cell cycling is mediated through Cdc25A Annette R. Khaled,1,3 Dmitry V. Bulavin,2 Christina Kittipatarin,1 Wen Qing Li,3 Michelle Alvarez,1 Kyungjae Kim,3,5 Howard A. Young,4 Albert J. Fornace,2 and Scott K. Durum3 1University of Central Florida, BioMolecular Science Center, Orlando, FL 32628 2Division of Basic Sciences, National Cancer Institute, Bethesda, MD 20892 3Laboratory of Molecular Immunoregulation and 4Laboratory of Experimental Immunology, National Cancer Institute at Frederick, Frederick, MD 21702 5Department of Pharmacy, Sahm-Yook University, Seoul, Korea, 139-742 ymphocytes are the central mediators of the im- the critical mediator of proliferation. Withdrawal of IL-7 mune response, requiring cytokines for survival and or IL-3 from dependent lymphocytes activates the stress L proliferation. Survival signaling targets the Bcl-2 kinase, p38 MAPK, which phosphorylates Cdc25A, in- family of apoptotic mediators, however, the pathway for ducing its degradation. As a result, Cdk/cyclin com- the cytokine-driven proliferation of lymphocytes is poorly plexes remain phosphorylated and inactive and cells understood. Here we show that cytokine-induced cell arrest before the induction of apoptosis. Inhibiting p38 cycle progression is not solely dependent on the synthe- MAPK or expressing a mutant Cdc25A, in which the two sis of cyclin-dependent kinases (Cdks) or cyclins. Rather, p38 MAPK target sites, S75 and S123, are altered, ren- we observe that in lymphocyte cell lines dependent on ders cells resistant to cytokine withdrawal, restoring the interleukin-3 or interleukin-7, or primary lymphocytes activity of Cdk/cyclin complexes and driving the cell cycle dependent on interleukin 7, the phosphatase Cdc25A is independent of a growth stimulus.
    [Show full text]
  • 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.
    [Show full text]
  • A Rapid Transcriptome Response Is Associated with Desiccation Resistance in Aerially-Exposed Killifish Embryos
    A Rapid Transcriptome Response Is Associated with Desiccation Resistance in Aerially-Exposed Killifish Embryos Ange`le Tingaud-Sequeira1¤a, Juan-Jose´ Lozano2, Cinta Zapater1, David Otero1, Michael Kube3¤b, Richard Reinhardt3¤c, Joan Cerda` 1* 1 Institut de Recerca i Tecnologia Agroalimenta`ries (IRTA)-Institut de Cie`ncies del Mar, CSIC, Barcelona, Spain, 2 Bioinformatics Platform, CIBERHED, Barcelona, Spain, 3 Max Planck Institute for Molecular Genetics, Berlin-Dahlem, Germany Abstract Delayed hatching is a form of dormancy evolved in some amphibian and fish embryos to cope with environmental conditions transiently hostile to the survival of hatchlings or larvae. While diapause and cryptobiosis have been extensively studied in several animals, very little is known concerning the molecular mechanisms involved in the sensing and response of fish embryos to environmental cues. Embryos of the euryhaline killifish Fundulus heteroclitus advance dvelopment when exposed to air but hatching is suspended until flooding with seawater. Here, we investigated how transcriptome regulation underpins this adaptive response by examining changes in gene expression profiles of aerially incubated killifish embryos at ,100% relative humidity, compared to embryos continuously flooded in water. The results confirm that mid-gastrula embryos are able to stimulate development in response to aerial incubation, which is accompanied by the differential expression of at least 806 distinct genes during a 24 h period. Most of these genes (,70%) appear to be differentially expressed within 3 h of aerial exposure, suggesting a broad and rapid transcriptomic response. This response seems to include an early sensing phase, which overlaps with a tissue remodeling and activation of embryonic development phase involving many regulatory and metabolic pathways.
    [Show full text]
  • PRODUCT SPECIFICATION Anti-DUSP15
    Anti-DUSP15 Product Datasheet Polyclonal Antibody PRODUCT SPECIFICATION Product Name Anti-DUSP15 Product Number HPA076649 Gene Description dual specificity phosphatase 15 Clonality Polyclonal Isotype IgG Host Rabbit Antigen Sequence Recombinant Protein Epitope Signature Tag (PrEST) antigen sequence: ICLCFGEEDPGPTQHPKEQLIMADVQVQLRPGSSSCTLSASTERPDGSST PGNPDGITHLQCSCLHPKRA Purification Method Affinity purified using the PrEST antigen as affinity ligand Verified Species Human Reactivity Recommended IHC (Immunohistochemistry) Applications - Antibody dilution: 1:200 - 1:500 - Retrieval method: HIER pH6 ICC-IF (Immunofluorescence) - Fixation/Permeabilization: PFA/Triton X-100 - Working concentration: 0.25-2 µg/ml Characterization Data Available at atlasantibodies.com/products/HPA076649 Buffer 40% glycerol and PBS (pH 7.2). 0.02% sodium azide is added as preservative. Concentration Lot dependent Storage Store at +4°C for short term storage. Long time storage is recommended at -20°C. Notes Gently mix before use. Optimal concentrations and conditions for each application should be determined by the user. For protocols, additional product information, such as images and references, see atlasantibodies.com. Product of Sweden. For research use only. Not intended for pharmaceutical development, diagnostic, therapeutic or any in vivo use. No products from Atlas Antibodies may be resold, modified for resale or used to manufacture commercial products without prior written approval from Atlas Antibodies AB. Warranty: The products supplied by Atlas Antibodies are warranted to meet stated product specifications and to conform to label descriptions when used and stored properly. Unless otherwise stated, this warranty is limited to one year from date of sales for products used, handled and stored according to Atlas Antibodies AB's instructions. Atlas Antibodies AB's sole liability is limited to replacement of the product or refund of the purchase price.
    [Show full text]
  • Exosome-Mediated MIR211 Modulates Tumor Microenvironment Via the DUSP6-ERK5 Axis and Contributes to BRAFV600E Inhibitor Resistan
    bioRxiv preprint doi: https://doi.org/10.1101/548818; this version posted February 13, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Exosome-mediated MIR211 modulates tumor microenvironment via the DUSP6-ERK5 axis and contributes to BRAFV600E inhibitor resistance in melanoma. Bongyong Lee1,3, Anupama Sahoo3, Junko Sawada1,3, John Marchica1,3, Sanjay Sahoo3, Fabiana I. A. L. Layng4, Darren Finlay4, Joseph Mazar5, Piyush Joshi1, Masanobu Komatsu1,3, Kristiina Vuori4, Garth Powis4, Petrus R. de Jong4, Animesh Ray6,7, and Ranjan J. Perera 1,2,3* 1 Department of Cancer and Blood Disorders Institute, Johns Hopkins All Children’s Hospital, St. Petersburg, FL 33701 USA 2 Department of Oncology, Sydney Kimmel Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA 3 Sanford Burnham Prebys Medical Discovery Institute, Orlando, FL 32827 USA 4 Sanford Burnham Prebys Medical Discovery Institute, NCI-Designated Cancer Center, La Jolla, CA 92037, USA 5 Nemours Children Hospital, Orlando, FL 32827 USA 6 Keck Graduate Institute, Claremont CA 91711 USA, 7 Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 USA. *Correspondence: Ranjan Perera Tel: 1-727-767-3491 Email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/548818; this version posted February 13, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. ABSTRACT The microRNA MIR211 is an important regulator of melanoma tumor cell behavior.
    [Show full text]
  • 9. Atypical Dusps: 19 Phosphatases in Search of a Role
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Digital.CSIC Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India Emerging Signaling Pathways in Tumor Biology, 2010: 185-208 ISBN: 978-81-7895-477-6 Editor: Pedro A. Lazo 9. Atypical DUSPs: 19 phosphatases in search of a role Yolanda Bayón and Andrés Alonso Instituto de Biología y Genética Molecular, CSIC-Universidad de Valladolid c/ Sanz y Forés s/n, 47003 Valladolid, Spain Abstract. Atypical Dual Specificity Phosphatases (A-DUSPs) are a group of 19 phosphatases poorly characterized. They are included among the Class I Cys-based PTPs and contain the active site motif HCXXGXXR conserved in the Class I PTPs. These enzymes present a phosphatase domain similar to MKPs, but lack any substrate targeting domain similar to the CH2 present in this group. Although most of these phosphatases have no more than 250 amino acids, their size ranges from the 150 residues of the smallest A-DUSP, VHZ/DUSP23, to the 1158 residues of the putative PTP DUSP27. The substrates of this family include MAPK, but, in general terms, it does not look that MAPK are the general substrates for the whole group. In fact, other substrates have been described for some of these phosphatases, like the 5’CAP structure of mRNA, glycogen, or STATs and still the substrates of many A-DUSPs have not been identified. In addition to the PTP domain, most of these enzymes present no additional recognizable domains in their sequence, with the exception of CBM-20 in laforin, GTase in HCE1 and a Zn binding domain in DUSP12.
    [Show full text]
  • Review Article PTEN Gene: a Model for Genetic Diseases in Dermatology
    The Scientific World Journal Volume 2012, Article ID 252457, 8 pages The cientificWorldJOURNAL doi:10.1100/2012/252457 Review Article PTEN Gene: A Model for Genetic Diseases in Dermatology Corrado Romano1 and Carmelo Schepis2 1 Unit of Pediatrics and Medical Genetics, I.R.C.C.S. Associazione Oasi Maria Santissima, 94018 Troina, Italy 2 Unit of Dermatology, I.R.C.C.S. Associazione Oasi Maria Santissima, 94018 Troina, Italy Correspondence should be addressed to Carmelo Schepis, [email protected] Received 19 October 2011; Accepted 4 January 2012 Academic Editors: G. Vecchio and H. Zitzelsberger Copyright © 2012 C. Romano and C. Schepis. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. PTEN gene is considered one of the most mutated tumor suppressor genes in human cancer, and it’s likely to become the first one in the near future. Since 1997, its involvement in tumor suppression has smoothly increased, up to the current importance. Germline mutations of PTEN cause the PTEN hamartoma tumor syndrome (PHTS), which include the past-called Cowden, Bannayan- Riley-Ruvalcaba, Proteus, Proteus-like, and Lhermitte-Duclos syndromes. Somatic mutations of PTEN have been observed in glioblastoma, prostate cancer, and brest cancer cell lines, quoting only the first tissues where the involvement has been proven. The negative regulation of cell interactions with the extracellular matrix could be the way PTEN phosphatase acts as a tumor suppressor. PTEN gene plays an essential role in human development. A recent model sees PTEN function as a stepwise gradation, which can be impaired not only by heterozygous mutations and homozygous losses, but also by other molecular mechanisms, such as transcriptional regression, epigenetic silencing, regulation by microRNAs, posttranslational modification, and aberrant localization.
    [Show full text]
  • Supplementary Material
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.
    [Show full text]