MT1-MMP Recruits the ER-Golgi SNARE Bet1 for Efficient MT1-MMP Transport to the Plasma Membrane
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Directed Proximity-Dependent Biotin Labelling in Zebrafish
TOOLS AND RESOURCES In vivo proteomic mapping through GFP- directed proximity-dependent biotin labelling in zebrafish Zherui Xiong1, Harriet P Lo1, Kerrie-Ann McMahon1, Nick Martel1, Alun Jones1, Michelle M Hill2, Robert G Parton1,3*, Thomas E Hall1* 1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; 2QIMR Berghofer Medical Research Institute, Herston, Australia; 3Centre for Microscopy and Microanalysis, The University of Queensland, Brisbane, Australia Abstract Protein interaction networks are crucial for complex cellular processes. However, the elucidation of protein interactions occurring within highly specialised cells and tissues is challenging. Here, we describe the development, and application, of a new method for proximity- dependent biotin labelling in whole zebrafish. Using a conditionally stabilised GFP-binding nanobody to target a biotin ligase to GFP-labelled proteins of interest, we show tissue-specific proteomic profiling using existing GFP-tagged transgenic zebrafish lines. We demonstrate the applicability of this approach, termed BLITZ (Biotin Labelling In Tagged Zebrafish), in diverse cell types such as neurons and vascular endothelial cells. We applied this methodology to identify interactors of caveolar coat protein, cavins, in skeletal muscle. Using this system, we defined specific interaction networks within in vivo muscle cells for the closely related but functionally distinct Cavin4 and Cavin1 proteins. *For correspondence: Introduction [email protected] (RGP); [email protected] (TEH) The understanding of the biological functions of a protein requires detailed knowledge of the mole- cules with which it interacts. However, robust elucidation of interacting proteins, including not only Competing interests: The strong direct protein-protein interactions, but also weak, transient or indirect interactions is challeng- authors declare that no ing. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
Cell-Free Fusion of Bacteria-Containing Phagosomes with Endocytic Compartments
Cell-free fusion of bacteria-containing phagosomes with endocytic compartments Ulrike Becken, Andreas Jeschke, Katharina Veltman1, and Albert Haas2 Cell Biology Institute, University of Bonn, Ulrich-Haberland-Strasse 61a, 53121 Bonn, Germany Edited by Reinhard Jahn, Max Planck Institute for Biophysical Chemistry, Goettingen, Germany, and accepted by the Editorial Board October 4, 2010 (received for review June 2, 2010) Uptake of microorganisms by professional phagocytic cells leads to duced fusion of SCPs with lysosomes compared to phagosomes formation of a new subcellular compartment, the phagosome, containing inert particles (10–12), others did not (13). Fusogeni- which matures by sequential fusion with early and late endocytic city of SCPs with other endocytic organelles in macrophages has compartments, resulting in oxidative and nonoxidative killing of been investigated little (10). the enclosed microbe. Few tools are available to study membrane To truly understand the (dys)function of phagosome matura- fusion between phagocytic and late endocytic compartments in tion at a molecular level, the fusion of endocytic with microbe- general and with pathogen-containing phagosomes in particular. containing phagocytic organelles ought to be investigated in We have developed and applied a fluorescence microscopy assay reconstituted systems, yet most published assays used bead- to study fusion of microbe-containing phagosomes with different- containing but not microbe-containing phagosomes (3, 5) and aged endocytic compartments in vitro. This revealed that fusion were limited to fusion of early phagosomes with early endocytic of phagosomes containing nonpathogenic Escherichia coli with organelles (14, 15). Fusion of lysosomes with microbe-containing lysosomes requires Rab7 and SNARE proteins but not organelle phagosomes has been reconstituted only in permeabilized macro- acidification. -
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 Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
UVRAG Is Required for Virus Entry Through Combinatorial Interaction with the Class C-Vps Complex and Snares
UVRAG is required for virus entry through combinatorial interaction with the class C-Vps complex and SNAREs Sara Dolatshahi Pirooza, Shanshan Hea, Tian Zhanga, Xiaowei Zhanga, Zhen Zhaoa, Soohwan Oha, Douglas O’Connella, Payam Khalilzadeha, Samad Amini-Bavil-Olyaeea, Michael Farzanb, and Chengyu Lianga,1 aDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033; and bDepartment of Infectious Diseases, The Scripps Research Institute, Jupiter, FL 33458 Edited by Peter Palese, Icahn School of Medicine at Mount Sinai, New York, NY, and approved January 15, 2014 (received for review November 4, 2013) Enveloped viruses exploit the endomembrane system to enter host (R)-SNAREs embedded in the other (3). Specifically, syntaxin 7 cells. Through a cascade of membrane-trafficking events, virus-bearing (STX7; Qa), Vti1b (Qb), and STX8 (Qc) on the LE, when paired vesicles fuse with acidic endosomes and/or lysosomes mediated by with VAMP7 (R), mediate the LE fusion with the lysosome, but SNAREs triggering viral fusion. However, the molecular mechanisms when paired with VAMP8 (R), regulate homotypic fusion of the underlying this process remain elusive. Here, we found that UV- LEs (4). The upstream process regulating LE-associated SNARE radiation resistance-associated gene (UVRAG), an autophagic tumor pairing relies on the class C vacuolar protein sorting (Vps) complex suppressor, is required for the entry of the prototypic negative- (hereafter referred to as C-Vps), composed of Vps11, Vps16, strand RNA virus, including influenza A virus and vesicular stoma- Vps18, and Vps33 as core subunits (5, 6). A recent study indicated titis virus, by a mechanism independent of IFN and autophagy. -
Autophagy Suppresses Ras-Driven Epithelial Tumourigenesis by Limiting the Accumulation of Reactive Oxygen Species
OPEN Oncogene (2017) 36, 5576–5592 www.nature.com/onc ORIGINAL ARTICLE Autophagy suppresses Ras-driven epithelial tumourigenesis by limiting the accumulation of reactive oxygen species This article has been corrected since Advance Online Publication and a corrigendum is also printed in this issue. J Manent1,2,3,4,5,12, S Banerjee2,3,4,5, R de Matos Simoes6, T Zoranovic7,13, C Mitsiades6, JM Penninger7, KJ Simpson4,5, PO Humbert3,5,8,9,10 and HE Richardson1,2,5,8,11 Activation of Ras signalling occurs in ~ 30% of human cancers; however, activated Ras alone is not sufficient for tumourigenesis. In a screen for tumour suppressors that cooperate with oncogenic Ras (RasV12)inDrosophila, we identified genes involved in the autophagy pathway. Bioinformatic analysis of human tumours revealed that several core autophagy genes, including GABARAP, correlate with oncogenic KRAS mutations and poor prognosis in human pancreatic cancer, supporting a potential tumour- suppressive effect of the pathway in Ras-driven human cancers. In Drosophila, we demonstrate that blocking autophagy at any step of the pathway enhances RasV12-driven epithelial tissue overgrowth via the accumulation of reactive oxygen species and activation of the Jun kinase stress response pathway. Blocking autophagy in RasV12 clones also results in non-cell-autonomous effects with autophagy, cell proliferation and caspase activation induced in adjacent wild-type cells. Our study has implications for understanding the interplay between perturbations in Ras signalling and autophagy in tumourigenesis, -
On the Move : Endocytic Trafficking in Cell Migration
Erschienen in: Cellular and Molecular Life Sciences ; 72 (2015), 11. - S. 2119-2134 https://dx.doi.org/10.1007/s00018-015-1855-9 On the move: endocytic trafficking in cell migration Tanja Maritzen • Hannah Schachtner • Daniel F. Legler Abstract Directed cell migration is a fundamental process unraveling the contribution of cellular trafficking pathways underlying diverse physiological and pathophysiological to cell migration. phenomena ranging from wound healing and induction of immune responses to cancer metastasis. Recent advances Keywords Endocytosis Á Cellular motility Á Clathrin Á reveal that endocytic trafficking contributes to cell migration Chemotaxis Á Signal transduction Á Vesicular transport in multiple ways. (1) At the level of chemokines and che- mokine receptors: internalization of chemokines by scavenger receptors is essential for shaping chemotactic Introduction gradients in tissue, whereas endocytosis of chemokine re- ceptors and their subsequent recycling is key for maintaining Diverse physiological processes ranging from embryonic a high responsiveness of migrating cells. (2) At the level of development to the induction of immune responses require integrin trafficking and focal adhesion dynamics: endosomal coordinated cell migration within the organism. In addi- pathways do not only modulate adhesion by delivering in- tion, migratory abilities of cells also represent a tegrins to their site of action, but also by supplying factors determining factor in pathological settings such as metas- for focal adhesion disassembly. (3) At the level of extra- tasis and inflammatory diseases. The term cell migration cellular matrix reorganization: endosomal transport comprises a number of different migration modes with contributes to tumor cell migration not only by targeting different mechanistic requirements. -
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924). -
Supplementary Table 4
Li et al. mir-30d in human cancer Table S4. The probe list down-regulated in MDA-MB-231 cells by mir-30d mimic transfection Gene Probe Gene symbol Description Row set 27758 8119801 ABCC10 ATP-binding cassette, sub-family C (CFTR/MRP), member 10 15497 8101675 ABCG2 ATP-binding cassette, sub-family G (WHITE), member 2 18536 8158725 ABL1 c-abl oncogene 1, receptor tyrosine kinase 21232 8058591 ACADL acyl-Coenzyme A dehydrogenase, long chain 12466 7936028 ACTR1A ARP1 actin-related protein 1 homolog A, centractin alpha (yeast) 18102 8056005 ACVR1 activin A receptor, type I 20790 8115490 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 15688 7979904 ADAM21 ADAM metallopeptidase domain 21 14937 8054254 AFF3 AF4/FMR2 family, member 3 23560 8121277 AIM1 absent in melanoma 1 20209 7921434 AIM2 absent in melanoma 2 19272 8136336 AKR1B10 aldo-keto reductase family 1, member B10 (aldose reductase) 18013 7954777 ALG10 asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog (S. pombe) 30049 7954789 ALG10B asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog B (yeast) 28807 7962579 AMIGO2 adhesion molecule with Ig-like domain 2 5576 8112596 ANKRA2 ankyrin repeat, family A (RFXANK-like), 2 23414 7922121 ANKRD36BL1 ankyrin repeat domain 36B-like 1 (pseudogene) 29782 8098246 ANXA10 annexin A10 22609 8030470 AP2A1 adaptor-related protein complex 2, alpha 1 subunit 14426 8107421 AP3S1 adaptor-related protein complex 3, sigma 1 subunit 12042 8099760 ARAP2 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 2 30227 8059854 ARL4C ADP-ribosylation factor-like 4C 32785 8143766 ARP11 actin-related Arp11 6497 8052125 ASB3 ankyrin repeat and SOCS box-containing 3 24269 8128592 ATG5 ATG5 autophagy related 5 homolog (S. -
Uncoupling the Functions of CALM in VAMP Sorting and Clathrin-Coated Pit Formation
Uncoupling the Functions of CALM in VAMP Sorting and Clathrin-Coated Pit Formation Daniela A. Sahlender¤a, Patrycja Kozik¤b, Sharon E. Miller, Andrew A. Peden¤c, Margaret S. Robinson* Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom Abstract CALM (clathrin assembly lymphoid myeloid leukemia protein) is a cargo-selective adaptor for the post-Golgi R-SNAREs VAMPs 2, 3, and 8, and it also regulates the size of clathrin-coated pits and vesicles at the plasma membrane. The present study has two objectives: to determine whether CALM can sort additional VAMPs, and to investigate whether VAMP sorting contributes to CALM-dependent vesicle size regulation. Using a flow cytometry-based endocytosis efficiency assay, we demonstrate that CALM is also able to sort VAMPs 4 and 7, even though they have sorting signals for other clathrin adaptors. CALM homologues are present in nearly every eukaryote, suggesting that the CALM family may have evolved as adaptors for retrieving all post-Golgi VAMPs from the plasma membrane. Using a knockdown/rescue system, we show that wild-type CALM restores normal VAMP sorting in CALM-depleted cells, but that two non-VAMP-binding mutants do not. However, when we assayed the effect of CALM depletion on coated pit morphology, using a fluorescence microscopy- based assay, we found that the two mutants were as effective as wild-type CALM. Thus, we can uncouple the sorting function of CALM from its structural role. Citation: Sahlender DA, Kozik P, Miller SE, Peden AA, Robinson MS (2013) Uncoupling the Functions of CALM in VAMP Sorting and Clathrin-Coated Pit Formation. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).