Structure and Function of the Fgd Family of Divergent FYVE Domain Proteins
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Regulation of Cdc42 and Its Effectors in Epithelial Morphogenesis Franck Pichaud1,2,*, Rhian F
© 2019. Published by The Company of Biologists Ltd | Journal of Cell Science (2019) 132, jcs217869. doi:10.1242/jcs.217869 REVIEW SUBJECT COLLECTION: ADHESION Regulation of Cdc42 and its effectors in epithelial morphogenesis Franck Pichaud1,2,*, Rhian F. Walther1 and Francisca Nunes de Almeida1 ABSTRACT An overview of Cdc42 Cdc42 – a member of the small Rho GTPase family – regulates cell Cdc42 was discovered in yeast and belongs to a large family of small – polarity across organisms from yeast to humans. It is an essential (20 30 kDa) GTP-binding proteins (Adams et al., 1990; Johnson regulator of polarized morphogenesis in epithelial cells, through and Pringle, 1990). It is part of the Ras-homologous Rho subfamily coordination of apical membrane morphogenesis, lumen formation and of GTPases, of which there are 20 members in humans, including junction maturation. In parallel, work in yeast and Caenorhabditis elegans the RhoA and Rac GTPases, (Hall, 2012). Rho, Rac and Cdc42 has provided important clues as to how this molecular switch can homologues are found in all eukaryotes, except for plants, which do generate and regulate polarity through localized activation or inhibition, not have a clear homologue for Cdc42. Together, the function of and cytoskeleton regulation. Recent studies have revealed how Rho GTPases influences most, if not all, cellular processes. important and complex these regulations can be during epithelial In the early 1990s, seminal work from Alan Hall and his morphogenesis. This complexity is mirrored by the fact that Cdc42 can collaborators identified Rho, Rac and Cdc42 as main regulators of exert its function through many effector proteins. -
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. -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
A Rac/Cdc42 Exchange Factor Complex Promotes Formation of Lateral filopodia and Blood Vessel Lumen Morphogenesis
ARTICLE Received 1 Oct 2014 | Accepted 26 Apr 2015 | Published 1 Jul 2015 DOI: 10.1038/ncomms8286 OPEN A Rac/Cdc42 exchange factor complex promotes formation of lateral filopodia and blood vessel lumen morphogenesis Sabu Abraham1,w,*, Margherita Scarcia2,w,*, Richard D. Bagshaw3,w,*, Kathryn McMahon2,w, Gary Grant2, Tracey Harvey2,w, Maggie Yeo1, Filomena O.G. Esteves2, Helene H. Thygesen2,w, Pamela F. Jones4, Valerie Speirs2, Andrew M. Hanby2, Peter J. Selby2, Mihaela Lorger2, T. Neil Dear4,w, Tony Pawson3,z, Christopher J. Marshall1 & Georgia Mavria2 During angiogenesis, Rho-GTPases influence endothelial cell migration and cell–cell adhesion; however it is not known whether they control formation of vessel lumens, which are essential for blood flow. Here, using an organotypic system that recapitulates distinct stages of VEGF-dependent angiogenesis, we show that lumen formation requires early cytoskeletal remodelling and lateral cell–cell contacts, mediated through the RAC1 guanine nucleotide exchange factor (GEF) DOCK4 (dedicator of cytokinesis 4). DOCK4 signalling is necessary for lateral filopodial protrusions and tubule remodelling prior to lumen formation, whereas proximal, tip filopodia persist in the absence of DOCK4. VEGF-dependent Rac activation via DOCK4 is necessary for CDC42 activation to signal filopodia formation and depends on the activation of RHOG through the RHOG GEF, SGEF. VEGF promotes interaction of DOCK4 with the CDC42 GEF DOCK9. These studies identify a novel Rho-family GTPase activation cascade for the formation of endothelial cell filopodial protrusions necessary for tubule remodelling, thereby influencing subsequent stages of lumen morphogenesis. 1 Institute of Cancer Research, Division of Cancer Biology, 237 Fulham Road, London SW3 6JB, UK. -
Molecular Mechanism of Membrane Targeting by the GRP1 PH Domain
Supplemental Material can be found at: http://www.jlr.org/cgi/content/full/M800150-JLR200/DC1 Molecular mechanism of membrane targeting by the GRP1 PH domain † † † Ju He,* Rachel M. Haney, ,§ Mohsin Vora, Vladislav V. Verkhusha,** Robert V. Stahelin, ,§ and Tatiana G. Kutateladze1,* Department of Pharmacology,* University of Colorado Health Sciences Center, Aurora, CO; † Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, South Bend, IN; Department of Chemistry and Biochemistry and The Walther Center for Cancer Research,§ University of Notre Dame, South Bend, IN; and Department of Anatomy and Structural Biology,** Downloaded from Albert Einstein College of Medicine, Bronx, NY Abstract The general receptor for phosphoinositides iso- Supplementary key words general receptor for phosphoinositides iso- • • • form 1 (GRP1) is recruited to the plasma membrane in re- form 1 pleckstrin homology domain phosphoinositide phosphati- dylinositol 3,4,5-trisphosphate sponse to activation of phosphoinositide 3-kinases and www.jlr.org accumulation of phosphatidylinositol 3,4,5-trisphosphate ʼ [PtdIns(3,4,5)P3]. GRP1 s pleckstrin homology (PH) do- main recognizes PtdIns(3,4,5)P3 with high specificity and af- The signaling lipid phosphatidylinositol 3,4,5-trisphos- finity, however, the precise mechanism of its association phate [PtdIns(3,4,5)P3] is produced in plasma membranes at Albert Einstein College of Medicine Library on July 14, 2008 with membranes remains unclear. Here, we detail the mo- in response to stimulation of cell surface receptors by lecular basis of membrane anchoring by the GRP1 PH do- growth factors and hormones (1). Class I phosphoinositide main. Our data reveal a multivalent membrane docking (PI) 3-kinases phosphorylate the inositol headgroup of the involving PtdIns(3,4,5)P binding, regulated by pH and fa- 3 relatively abundant phosphatidylinositol 4,5-bisphosphate cilitated by electrostatic interactions with other anionic lip- [Ptdns(4,5)P2], transiently elevating the level of PtdIns ids. -
The PX Domain Protein Interaction Network in Yeast
The PX domain protein interaction network in yeast Zur Erlangung des akademischen Grades eines DOKTORS DER NATURWISSENSCHAFTEN (Dr. rer. nat.) der Fakultät für Chemie und Biowissenschaften der Universität Karlsruhe (TH) vorgelegte DISSERTATION von Dipl. Biol. Carolina S. Müller aus Buenos Aires Dekan: Prof. Dr. Manfred Kappes Referent: Dr. Nils Johnsson Korreferent: HD. Dr. Adam Bertl Tag der mündlichen Prüfung: 17.02.2005 I dedicate this work to my Parents and Alex TABLE OF CONTENTS Table of contents Introduction 1 Yeast as a model organism in proteome analysis 1 Protein-protein interactions 2 Protein Domains in Yeast 3 Classification of protein interaction domains 3 Phosphoinositides 5 Function 5 Structure 5 Biochemistry 6 Localization 7 Lipid Binding Domains 8 The PX domain 10 Function of PX domain containing proteins 10 PX domain structure and PI binding affinities 10 Yeast PX domain containing proteins 13 PX domain and protein-protein interactions 13 Lipid binding domains and protein-protein interactions 14 The PX-only proteins Grd19p and Ypt35p and their phenotypes 15 Aim of my PhD work 16 Project outline 16 Searching for interacting partners 16 Confirmation of obtained interactions via a 16 second independent method Mapping the interacting region 16 The Two-Hybrid System 17 Definition 17 Basic Principle of the classical Yeast-Two Hybrid System 17 Peptide Synthesis 18 SPOT synthesis technique 18 Analysis of protein- peptide contact sites based on SPOT synthesis 19 TABLE OF CONTENTS Experimental procedures 21 Yeast two-hybrid assay -
Antigen-Specific Memory CD4 T Cells Coordinated Changes in DNA
Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021 is online at: average * The Journal of Immunology The Journal of Immunology published online 18 March 2013 from submission to initial decision 4 weeks from acceptance to publication http://www.jimmunol.org/content/early/2013/03/17/jimmun ol.1202267 Coordinated Changes in DNA Methylation in Antigen-Specific Memory CD4 T Cells Shin-ichi Hashimoto, Katsumi Ogoshi, Atsushi Sasaki, Jun Abe, Wei Qu, Yoichiro Nakatani, Budrul Ahsan, Kenshiro Oshima, Francis H. W. Shand, Akio Ametani, Yutaka Suzuki, Shuichi Kaneko, Takashi Wada, Masahira Hattori, Sumio Sugano, Shinichi Morishita and Kouji Matsushima J Immunol Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Author Choice option 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 Freely available online through http://www.jimmunol.org/content/suppl/2013/03/18/jimmunol.120226 7.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Author Choice Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 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 24, 2021. Published March 18, 2013, doi:10.4049/jimmunol.1202267 The Journal of Immunology Coordinated Changes in DNA Methylation in Antigen-Specific Memory CD4 T Cells Shin-ichi Hashimoto,*,†,‡ Katsumi Ogoshi,* Atsushi Sasaki,† Jun Abe,* Wei Qu,† Yoichiro Nakatani,† Budrul Ahsan,x Kenshiro Oshima,† Francis H. -
HER2 Gene Signatures: (I) Novel and (Ii) Established by Desmedt Et Al 2008 (31)
Table S1: HER2 gene signatures: (i) Novel and (ii) Established by Desmedt et al 2008 (31). Pearson R [neratinib] is the correlation with neratinib response using a pharmacogenomic model of breast cancer cell lines (accessed online via CellMinerCDB). *indicates significantly correlated genes. n/a = data not available in CellMinerCDB Genesig N Gene ID Pearson R [neratinib] p-value (i) Novel 20 ERBB2 0.77 1.90E-08* SPDEF 0.45 4.20E-03* TFAP2B 0.2 0.24 CD24 0.38 0.019* SERHL2 0.41 0.0097* CNTNAP2 0.12 0.47 RPL19 0.29 0.073 CAPN13 0.51 1.00E-03* RPL23 0.22 0.18 LRRC26 n/a n/a PRODH 0.42 9.00E-03* GPRC5C 0.44 0.0056* GGCT 0.38 1.90E-02* CLCA2 0.31 5.70E-02 KDM5B 0.33 4.20E-02* SPP1 -0.25 1.30E-01 PHLDA1 -0.54 5.30E-04* C15orf48 0.06 7.10E-01 SUSD3 -0.09 5.90E-01 SERPINA1 0.14 4.10E-01 (ii) Established 24 ERBB2 0.77 1.90E-08* PERLD1 0.77 1.20E-08* PSMD3 0.33 0.04* PNMT 0.33 4.20E-02* GSDML 0.4 1.40E-02* CASC3 0.26 0.11 LASP1 0.32 0.049* WIPF2 0.27 9.70E-02 EPN3 0.42 8.50E-03* PHB 0.38 0.019* CLCA2 0.31 5.70E-02 ORMDL2 0.06 0.74 RAP1GAP 0.53 0.00059* CUEDC1 0.09 0.61 HOXC11 0.2 0.23 CYP2J2 0.45 0.0044* HGD 0.14 0.39 ABCA12 0.07 0.67 ATP2C2 0.42 0.0096* ITGA3 0 0.98 CEACAM5 0.4 0.012* TMEM16K 0.15 0.37 NR1D1 n/a n/a SNX7 -0.28 0.092 FJX1 -0.26 0.12 KCTD9 -0.11 0.53 PCTK3 -0.04 0.83 CREG1 0.17 0.3 Table S2: Up-regulated genes from the top 500 DEGs for each comparison by WAD score METABRIC METABRIC METABRIC TCGA ERBB2amp ERBB2mut oncERBB2mut HER2+ ERBB2 PIP ANKRD30A ERBB2 GRB7 CYP4Z1 CYP4Z1 SCGB2A2 PGAP3 PROM1 LRRC26 SPDEF GSDMB CD24 PPP1R1B FOXA1 -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Membrane Insertion of the FYVE Domain Is Modulated by Ph Ju He,1 Mohsin Vora,2 Rachel M
proteins STRUCTURE O FUNCTION O BIOINFORMATICS Membrane insertion of the FYVE domain is modulated by pH Ju He,1 Mohsin Vora,2 Rachel M. Haney,2,3 Grigory S. Filonov,4 Catherine A. Musselman,1 Christopher G. Burd,5 Andrei G. Kutateladze,6 Vladislav V. Verkhusha,4 Robert V. Stahelin,2,3,7* and Tatiana G. Kutateladze1* 1 Department of Pharmacology, University of Colorado Denver School of Medicine, Aurora, Colorado 80045 2 Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, South Bend, Indiana 46617 3 Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556 4 Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York 10461 5 Department of Cell and Developmental Biology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104 6 Department of Chemistry and Biochemistry, University of Denver, Denver, Colorado 80210 7 The Walther Center for Cancer Research, University of Notre Dame, Notre Dame, Indiana 46556 INTRODUCTION ABSTRACT Phosphoinositide (PI) 3-kinases regulate membrane trafficking, pro- The FYVE domain associates with phosphati- tein sorting and signaling by generating phosphatidylinositol (PtdIns) dylinositol 3-phosphate [PtdIns(3)P] in mem- derivatives phosphorylated at the third position of the inositol ring.1,2 branes of early endosomes and penetrates bilayers. Here, we detail principles of mem- Of the four known products of PI 3-kinases, PtdIns 3-phosphate brane anchoring and show that the FYVE do- [PtdIns(3)P] is the most abundant and is constitutively produced in the main insertion into PtdIns(3)P-enriched cytosolic leaflet of membranes of early endosomes. -
Supp Table 6.Pdf
Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin -
Systems-Level Identification of PKA-Dependent Signaling In
Systems-level identification of PKA-dependent PNAS PLUS signaling in epithelial cells Kiyoshi Isobea, Hyun Jun Junga, Chin-Rang Yanga,J’Neka Claxtona, Pablo Sandovala, Maurice B. Burga, Viswanathan Raghurama, and Mark A. Kneppera,1 aEpithelial Systems Biology Laboratory, Systems Biology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892-1603 Edited by Peter Agre, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, and approved August 29, 2017 (received for review June 1, 2017) Gproteinstimulatoryα-subunit (Gαs)-coupled heptahelical receptors targets are as yet unidentified. Some of the known PKA targets regulate cell processes largely through activation of protein kinase A are other protein kinases and phosphatases, meaning that PKA (PKA). To identify signaling processes downstream of PKA, we de- activation is likely to result in indirect changes in protein phos- leted both PKA catalytic subunits using CRISPR-Cas9, followed by a phorylation manifest as a signaling network, the details of which “multiomic” analysis in mouse kidney epithelial cells expressing the remain unresolved. To identify both direct and indirect targets of Gαs-coupled V2 vasopressin receptor. RNA-seq (sequencing)–based PKA in mammalian cells, we used CRISPR-Cas9 genome editing transcriptomics and SILAC (stable isotope labeling of amino acids in to introduce frame-shifting indel mutations in both PKA catalytic cell culture)-based quantitative proteomics revealed a complete loss subunit genes (Prkaca and Prkacb), thereby eliminating PKA-Cα of expression of the water-channel gene Aqp2 in PKA knockout cells. and PKA-Cβ proteins. This was followed by use of quantitative SILAC-based quantitative phosphoproteomics identified 229 PKA (SILAC-based) phosphoproteomics to identify phosphorylation phosphorylation sites.