Rnd3-Induced Cell Rounding Requires Interaction with Plexin-B2 Brad Mccoll*,¶, Ritu Garg¶, Philippe Riou‡, Kirsi Riento§ and Anne J
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Neural Map Formation in the Mouse Olfactory System
Cell. Mol. Life Sci. (2014) 71:3049–3057 DOI 10.1007/s00018-014-1597-0 Cellular and Molecular Life Sciences REVIEW Neural map formation in the mouse olfactory system Haruki Takeuchi · Hitoshi Sakano Received: 25 November 2013 / Revised: 26 February 2014 / Accepted: 27 February 2014 / Published online: 18 March 2014 © The Author(s) 2014. This article is published with open access at Springerlink.com Abstract In the mouse olfactory system, odorants are Introduction detected by ~1,000 different odorant receptors (ORs) pro- duced by olfactory sensory neurons (OSNs). Each OSN In the mouse, various odorants are detected with approxi- expresses only one functional OR species, which is referred mately 1,000 different odorant receptors (ORs) expressed to as the “one neuron–one receptor” rule. Furthermore, OSN in the olfactory sensory neurons (OSNs) [1]. Each OSN in axons bearing the same OR converge to a specific projection the olfactory epithelium (OE) expresses only one functional site in the olfactory bulb (OB) forming a glomerular struc- OR gene in a mono-allelic manner [2]. Furthermore, OSNs ture, i.e., the “one glomerulus–one receptor” rule. Based on expressing the same OR converge their axons to a spe- these basic rules, binding signals of odorants detected by cific pair of glomeruli at stereotyped locations in the olfac- OSNs are converted to topographic information of activated tory bulb (OB) (Fig. 1a, b) [3]. Thus, the odor information glomeruli in the OB. During development, the glomerular detected in the OE is topographically represented as the pat- map is formed by the combination of two genetically pro- tern of activated glomeruli in the OB (Fig. -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
Ran Activation Assay Kit
Product Manual Ran Activation Assay Kit Catalog Number STA-409 20 assays FOR RESEARCH USE ONLY Not for use in diagnostic procedures Introduction Small GTP-binding proteins (or GTPases) are a family of proteins that serve as molecular regulators in signaling transduction pathways. Ran, a 25 kDa protein of the Ras superfamily, regulates a variety of biological response pathways that include DNA synthesis, cell cycle progression, and translocation of RNA/proteins through the nuclear pore complex. Like other small GTPases, Ran regulates molecular events by cycling between an inactive GDP-bound form and an active GTP-bound form. In its active (GTP-bound) state, Ran binds specifically to RanBP1 to control downstream signaling cascades. Cell Biolabs’ Ran Activation Assay Kit utilizes RanBP1 Agarose beads to selectively isolate and pull- down the active form of Ran from purified samples or endogenous lysates. Subsequently, the precipitated GTP-Ran is detected by western blot analysis using an anti-Ran antibody. Cell Biolabs’ Ran Activation Assay Kit provides a simple and fast tool to monitor the activation of Ran. The kit includes easily identifiable RanBP1 Agarose beads (see Figure 1), pink in color, and a GTPase Immunoblot Positive Control for quick Ran identification. Each kit provides sufficient quantities to perform 20 assays. Figure 1: RanBP1 Agarose beads, in color, are easy to visualize, minimizing potential loss during washes and aspirations. 2 Assay Principle Related Products 1. STA-400: Pan-Ras Activation Assay Kit 2. STA-400-H: H-Ras Activation Assay Kit 3. STA-400-K: K-Ras Activation Assay Kit 4. STA-400-N: N-Ras Activation Assay Kit 5. -
Rhob Controls Endothelial Barrier Recovery by Inhibiting Rac1 Trafficking to the Cell Border
JCB: Article RhoB controls endothelial barrier recovery by inhibiting Rac1 trafficking to the cell border Beatriz Marcos‑Ramiro,1 Diego García‑Weber,1 Susana Barroso,1 Jorge Feito,2 María C. Ortega,1 Eva Cernuda‑Morollón,3 Natalia Reglero‑Real,1 Laura Fernández‑Martín,1 Maria C. Durán,4 Miguel A. Alonso,1 Isabel Correas,1 Susan Cox,5 Anne J. Ridley,5 and Jaime Millán1 1Centro de Biología Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas, Universidad Autónoma de Madrid, 28049 Madrid, Spain 2Servicio de Anatomía Patológica, Hospital Universitario de Salamanca, 37007 Salamanca, Spain 3Neurology Department, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain 4Biomedicine, Biotechnology and Public Health Department, University of Cadiz, 11519 Cadiz, Spain 5Randall Division of Cell and Molecular Biophysics, King’s College London, SE1 1UL London, England, UK Endothelial barrier dysfunction underlies chronic inflammatory diseases. In searching for new proteins essential to the human endothelial inflammatory response, we have found that the endosomal GTPase RhoB is up-regulated in response to inflammatory cytokines and expressed in the endothelium of some chronically inflamed tissues. We show that al- though RhoB and the related RhoA and RhoC play additive and redundant roles in various aspects of endothelial barrier function, RhoB specifically inhibits barrier restoration after acute cell contraction by preventing plasma membrane ex- tension. During barrier restoration, RhoB trafficking is induced between vesicles containing RhoB nanoclusters and plasma membrane protrusions. The Rho GTPase Rac1 controls membrane spreading and stabilizes endothelial barriers. We show that RhoB colocalizes with Rac1 in endosomes and inhibits Rac1 activity and trafficking to the cell border during barrier recovery. -
Figure S1. DMD Module Network. the Network Is Formed by 260 Genes from Disgenet and 1101 Interactions from STRING. Red Nodes Are the Five Seed Candidate Genes
Figure S1. DMD module network. The network is formed by 260 genes from DisGeNET and 1101 interactions from STRING. Red nodes are the five seed candidate genes. Figure S2. DMD module network is more connected than a random module of the same size. It is shown the distribution of the largest connected component of 10.000 random modules of the same size of the DMD module network. The green line (x=260) represents the DMD largest connected component, obtaining a z-score=8.9. Figure S3. Shared genes between BMD and DMD signature. A) A meta-analysis of three microarray datasets (GSE3307, GSE13608 and GSE109178) was performed for the identification of differentially expressed genes (DEGs) in BMD muscle biopsies as compared to normal muscle biopsies. Briefly, the GSE13608 dataset included 6 samples of skeletal muscle biopsy from healthy people and 5 samples from BMD patients. Biopsies were taken from either biceps brachii, triceps brachii or deltoid. The GSE3307 dataset included 17 samples of skeletal muscle biopsy from healthy people and 10 samples from BMD patients. The GSE109178 dataset included 14 samples of controls and 11 samples from BMD patients. For both GSE3307 and GSE10917 datasets, biopsies were taken at the time of diagnosis and from the vastus lateralis. For the meta-analysis of GSE13608, GSE3307 and GSE109178, a random effects model of effect size measure was used to integrate gene expression patterns from the two datasets. Genes with an adjusted p value (FDR) < 0.05 and an │effect size│>2 were identified as DEGs and selected for further analysis. A significant number of DEGs (p<0.001) were in common with the DMD signature genes (blue nodes), as determined by a hypergeometric test assessing the significance of the overlap between the BMD DEGs and the number of DMD signature genes B) MCODE analysis of the overlapping genes between BMD DEGs and DMD signature genes. -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Lysophosphatidic Acid Signaling in the Nervous System
Neuron Review Lysophosphatidic Acid Signaling in the Nervous System Yun C. Yung,1,3 Nicole C. Stoddard,1,2,3 Hope Mirendil,1 and Jerold Chun1,* 1Molecular and Cellular Neuroscience Department, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, CA 92037, USA 2Biomedical Sciences Graduate Program, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA 3Co-first author *Correspondence: [email protected] http://dx.doi.org/10.1016/j.neuron.2015.01.009 The brain is composed of many lipids with varied forms that serve not only as structural components but also as essential signaling molecules. Lysophosphatidic acid (LPA) is an important bioactive lipid species that is part of the lysophospholipid (LP) family. LPA is primarily derived from membrane phospholipids and signals through six cognate G protein-coupled receptors (GPCRs), LPA1-6. These receptors are expressed on most cell types within central and peripheral nervous tissues and have been functionally linked to many neural pro- cesses and pathways. This Review covers a current understanding of LPA signaling in the nervous system, with particular focus on the relevance of LPA to both physiological and diseased states. Introduction LPA synthesis/degradative enzymes (reviewed in Sigal et al., The human brain is composed of approximately 60%–70% lipids 2005; Brindley and Pilquil, 2009; Perrakis and Moolenaar, by dry weight (Svennerholm et al., 1994). These lipids can be 2014). In view of the broad neurobiological influences of LPA divided into two major pools, structural and signaling, which signaling, its dysregulation may lead to diverse neuropathologies include well-known families such as cholesterol, fatty acids, ei- (Bandoh et al., 2000; Houben and Moolenaar, 2011; Yung et al., cosanoids, endocannabinoids, and prostaglandins (Figure 1). -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
The Identification of Proteins That Interact with the N-Terminal Domain of Pitx2c
The identification of proteins that interact with the N-terminal domain of Pitx2c Dora Siontas A thesis submitted to McGill University in partial fulfillment of the requirement of the degree of Master of Science Department of Experimental Medicine McGill University Montreal, Quebec Canada August, 2011 © Dora Siontas Table of Contents Page ABSTRACT……………………………………………………………………..… i RÉSUMÉ………………….…………………………………………………...….. ii ACKNOWLEDGMENTS……………….……………………...…………...…... iii ABBREVIATIONS……………………...……………………………………..… iv LIST OF FIGURES ………………………………………………………..…... viii LIST OF TABLES……………………..……………………………………......... x 1. INTRODUCTION…………………………………………………………….... 1 1.1 Left-right asymmetric patterning……………………………………...…. 1 1.2 The left-right asymmetric molecular cascade………………………..…... 2 1.2.1 The left-right molecular cascade in the chick embryo..……………. 2 1.2.2 The left-right molecular cascade in the mouse embryo……….…… 7 1.3 The Pitx2 gene and protein isoforms………………………………….… 10 1.3.1 Identification of PITX2 as a mutated gene in ARS…………......… 11 1.3.2 Pitx2 function….……………………………..………………........… 11 1.3.3 Pitx2 isoforms…………………………………………..………..….. 13 1.3.4 Expression patterns of the different Pitx2 isoforms………............. 15 1.3.5 Pitx2 is important for asymmetric morphogenesis………………... 17 1.4 The Pitx2c N-terminal domain………………………………………...… 19 1.4.1 The Pitx2c N-terminal domain………………………………..…..… 19 1.4.2 Functional experiments with the Pitx2c N-terminal domain….….. 20 1.4.3 Pitx2-interacting proteins…………….……………………………... 23 2. HYPOTHESIS AND OBJECTIVES……………………………………..….. 25 2.1 Rationale…………………………………………………………………. 25 2.2 Hypothesis…………………………………………………………......… 25 2.3 Objectives……………………………………………………….……….. 26 3. MATERIALS AND METHODS………………………………………….…… 27 3.1 Cloning of the m2cN into pGBKT7………………………………………. 27 3.1.1 Midipreparation of pGBKT7…………………………………...…… 27 3.1.2 RT-PCR of m2cN cDNA…………………………………………..…. 27 3.1.3 Purification and digestion of the m2cN and the pGBKT7 vector…. -
Four-Dimensional Live Imaging of Apical Biosynthetic Trafficking Reveals a Post-Golgi Sorting Role of Apical Endosomal Intermediates
Four-dimensional live imaging of apical biosynthetic trafficking reveals a post-Golgi sorting role of apical endosomal intermediates Roland Thuenauera,b,1,2, Ya-Chu Hsua, Jose Maria Carvajal-Gonzaleza,3, Sylvie Debordea,4, Jen-Zen Chuanga, Winfried Römerc,d, Alois Sonnleitnerb, Enrique Rodriguez-Boulana,5, and Ching-Hwa Sunga,5 aMargaret M. Dyson Vision Research Institute, Weill Medical College of Cornell University, New York, NY 10065; bCenter for Advanced Bioanalysis Linz, 4020 Linz, Austria; and cInstitute of Biology II, and dBIOSS Centre for Biological Signalling Studies, Albert-Ludwigs-University Freiburg, 79104 Freiburg, Germany Edited by Keith E. Mostov, University of California School of Medicine, San Francisco, CA, and accepted by the Editorial Board January 17, 2014 (received for review March 11, 2013) Emerging data suggest that in polarized epithelial cells newly is an important regulator of biological processes that require synthesized apical and basolateral plasma membrane proteins apical trafficking, e.g., lumen formation during epithelial tubu- traffic through different endosomal compartments en route to the logenesis (11), apical secretion of discoidal/fusiform vesicles in respective cell surface. However, direct evidence for trans-endo- bladder umbrella cells (12), and apical microvillus morphogenesis somal pathways of plasma membrane proteins is still missing and and rhodopsin localization in fly photoreceptors (13). However, the mechanisms involved are poorly understood. Here, we imaged despite the physiological importance of trans-endosomal traf- the entire biosynthetic route of rhodopsin-GFP, an apical marker in ficking, the underlying mechanisms remain largely unclear. epithelial cells, synchronized through recombinant conditional ag- Previous studies on trans-endosomal trafficking in polarized gregation domains, in live Madin-Darby canine kidney cells using epithelial cells have relied on pulse chase/cell fractionation pro- spinning disk confocal microscopy. -
Genome-Wide Screen for Genes Involved in Edna Release During
Genome-wide screen for genes involved in eDNA PNAS PLUS release during biofilm formation by Staphylococcus aureus Alicia S. DeFrancescoa,1, Nadezda Masloboevaa,1, Adnan K. Syeda, Aaron DeLougherya,b, Niels Bradshawa, Gene-Wei Lib, Michael S. Gilmorec,d, Suzanne Walkerd, and Richard Losicka,2 aDepartment of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138; bDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142; cDepartment of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA 02114; and dDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115 Edited by Ralph R. Isberg, Howard Hughes Medical Institute, Tufts University School of Medicine, Boston, MA, and approved June 13, 2017 (received for review March 20, 2017) Staphylococcus aureus is a leading cause of both nosocomial and We have shown that the major components of the biofilm community-acquired infection. Biofilm formation at the site of infec- matrix of HG003 are proteins and eDNA, which associate with tion reduces antimicrobial susceptibility and can lead to chronic infec- the biofilm in a manner that depends on a drop in pH during tion. During biofilm formation, a subset of cells liberate cytoplasmic growth in the presence of glucose (5, 6). Many of these proteins proteins and DNA, which are repurposed to form the extracellular are cytoplasmic in origin and are thus moonlighting in their matrix that binds the remaining cells together in large clusters. Using second role as components of the biofilm matrix (5). These a strain that forms robust biofilms in vitro during growth under glu- moonlighting proteins do not depend on eDNA to remain as- cose supplementation, we carried out a genome-wide screen for genes sociated with cells.