Phosphorylation of LRRK2 by Casein Kinase 1&Alpha
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
LRRK2 at the Crossroad of Aging and Parkinson's Disease
G C A T T A C G G C A T genes Review LRRK2 at the Crossroad of Aging and Parkinson’s Disease Eun-Mi Hur 1 and Byoung Dae Lee 2,3,* 1 Department of Neuroscience, College of Veterinary Medicine, Research Institute for Veterinary Science and BK21 Four Future Veterinary Medicine Leading Education & Research Center, Seoul National University, Seoul 08826, Korea; [email protected] 2 Department of Physiology, Kyung Hee University School of Medicine, Seoul 02447, Korea 3 Department of Neuroscience, Kyung Hee University, Seoul 02447, Korea * Correspondence: [email protected]; Tel.: +82-2-961-9381 Abstract: Parkinson’s disease (PD) is a heterogeneous neurodegenerative disease characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta and the widespread occurrence of proteinaceous inclusions known as Lewy bodies and Lewy neurites. The etiology of PD is still far from clear, but aging has been considered as the highest risk factor influencing the clinical presentations and the progression of PD. Accumulating evidence suggests that aging and PD induce common changes in multiple cellular functions, including redox imbalance, mitochondria dysfunction, and impaired proteostasis. Age-dependent deteriorations in cellular dysfunction may predispose individuals to PD, and cellular damages caused by genetic and/or environmental risk factors of PD may be exaggerated by aging. Mutations in the LRRK2 gene cause late-onset, autosomal dominant PD and comprise the most common genetic causes of both familial and sporadic PD. LRRK2-linked PD patients show clinical and pathological features indistinguishable from idiopathic PD patients. Here, we review cellular dysfunctions shared by aging and PD-associated LRRK2 mutations and discuss how the interplay between the two might play a role in PD pathologies. -
Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug
cancers Article Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia David G.J. Cucchi 1 , Costa Bachas 1 , Marry M. van den Heuvel-Eibrink 2,3, Susan T.C.J.M. Arentsen-Peters 3, Zinia J. Kwidama 1, Gerrit J. Schuurhuis 1, Yehuda G. Assaraf 4, Valérie de Haas 3 , Gertjan J.L. Kaspers 3,5 and Jacqueline Cloos 1,* 1 Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; [email protected] (D.G.J.C.); [email protected] (C.B.); [email protected] (Z.J.K.); [email protected] (G.J.S.) 2 Department of Pediatric Oncology/Hematology, Erasmus MC–Sophia Children’s Hospital, 3015 CN Rotterdam, The Netherlands; [email protected] 3 Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; [email protected] (S.T.C.J.M.A.-P.); [email protected] (V.d.H.); [email protected] (G.J.L.K.) 4 The Fred Wyszkowski Cancer Research, Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003 Haifa, Israel; [email protected] 5 Emma’s Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Oncology, 1081 HV Amsterdam, The Netherlands * Correspondence: [email protected] Received: 21 April 2020; Accepted: 12 May 2020; Published: 15 May 2020 Abstract: Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization. -
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. -
Casein Kinase 1 Isoforms in Degenerative Disorders
CASEIN KINASE 1 ISOFORMS IN DEGENERATIVE DISORDERS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Theresa Joseph Kannanayakal, M.Sc., M.S. * * * * * The Ohio State University 2004 Dissertation Committee: Approved by Professor Jeff A. Kuret, Adviser Professor John D. Oberdick Professor Dale D. Vandre Adviser Professor Mike X. Zhu Biophysics Graduate Program ABSTRACT Casein Kinase 1 (CK1) enzyme is one of the largest family of Serine/Threonine protein kinases. CK1 has a wide distribution spanning many eukaryotic families. In cells, its kinase activity has been found in various sub-cellular compartments enabling it to phosphorylate many proteins involved in cellular maintenance and disease pathogenesis. Tau is one such substrate whose hyperphosphorylation results in degeneration of neurons in Alzheimer’s disease (AD). AD is a slow neuroprogessive disorder histopathologically characterized by Granulovacuolar degeneration bodies (GVBs) and intraneuronal accumulation of tau in Neurofibrillary Tangles (NFTs). The level of CK1 isoforms, CK1α, CK1δ and CK1ε has been shown to be elevated in AD. Previous studies of the correlation of CK1δ with lesions had demonstrated its importance in tau hyperphosphorylation. Hence we investigated distribution of CK1α and CK1ε with the lesions to understand if they would play role in tau hyperphosphorylation similar to CK1δ. The kinase results were also compared with lesion correlation studies of peptidyl cis/trans prolyl isomerase (Pin1) and caspase-3. Our results showed that among the enzymes investigated, CK1 isoforms have the greatest extent of colocalization with the lesions. We have also investigated the distribution of CK1α with different stages of NFTs that follow AD progression. -
Pleiotropic Effects for Parkin and LRRK2 in Leprosy Type-1 Reactions and Parkinson’S Disease
Pleiotropic effects for Parkin and LRRK2 in leprosy type-1 reactions and Parkinson’s disease Vinicius M. Favaa,b,1,2, Yong Zhong Xua,b, Guillaume Lettrec,d, Nguyen Van Thuce, Marianna Orlovaa,b, Vu Hong Thaie, Shao Taof,g, Nathalie Croteauh, Mohamed A. Eldeebi, Emma J. MacDougalli, Geison Cambrij, Ramanuj Lahirik, Linda Adamsk, Edward A. Foni, Jean-François Trempeh, Aurélie Cobatl,m, Alexandre Alcaïsl,m, Laurent Abell,m,n, and Erwin Schurra,b,o,1,2 aProgram in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada H4A3J1; bMcGill International TB Centre, Montreal, QC, Canada H4A 3J1; cMontreal Heart Institute, Montreal, QC, Canada H1T 1C8; dDepartment of Medicine, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada H3T 1J4; eHospital for Dermato-Venereology, District 3, Ho Chi Minh City, Vietnam; fDivision of Experimental Medicine, Faculty of Medicine, McGill University, Montreal, QC, Canada H3G 2M1; gThe Translational Research in Respiratory Diseases Program, The Research Institute of the McGill University Health Centre, Montreal, QC, Canada H4A 3J1; hCentre for Structural Biology, Department of Pharmacology & Therapeutics, McGill University, Montreal, QC, Canada H3G 1Y6; iMcGill Parkinson Program, Neurodegenerative Diseases Group, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada H3A 2B4; jGraduate Program in Health Sciences, Pontifícia Universidade Católica do Paraná, Curitiba, PR, 80215-901, Brazil; kNational Hansen’s Disease Program, Health Resources and Services Administration, Baton Rouge, LA 70803; lLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale 1163, 75015 Paris, France; mImagine Institute, Paris Descartes-Sorbonne Paris Cité University, 75015 Paris, France; nSt. -
Integrative Survival-Based Molecular Profiling of Human Pancreatic Cancer
Published OnlineFirst January 18, 2012; DOI: 10.1158/1078-0432.CCR-11-1539 Clinical Cancer Imaging, Diagnosis, Prognosis Research Integrative Survival-Based Molecular Profiling of Human Pancreatic Cancer Timothy R. Donahue1,2,3,4, Linh M. Tran2,3, Reginald Hill2,3, Yunfeng Li2,3, Anne Kovochich5, Joseph H. Calvopina3, Sanjeet G. Patel1, Nanping Wu2,3, Antreas Hindoyan2,3, James J. Farrell6, Xinmin Li5, David W. Dawson4,5, and Hong Wu2,3,4,7 Abstract Purpose: To carry out an integrative profile of human pancreatic ductal adenocarcinoma (PDAC) to identify prognosis-significant genes and their related pathways. Experimental Design: A concordant survival-based whole genome in silico array analysis of DNA copy number, and mRNA and miRNA expression in 25 early-stage PDAC was carried out. A novel composite score simultaneously integrated gene expression with regulatory mechanisms to identify the signature genes with the most levels of prognosis-significant evidence. The predominant signaling pathways were determined via a pathway-based approach. Independent patient cohorts (n ¼ 148 and 42) were then used as in vitro validation of the array findings. Results: The composite score identified 171 genes in which expressions were able to define two prognosis subgroups (P ¼ 3.8e-5). Eighty-eight percent (151 of 171) of the genes were regulated by prognosis-significant miRNAs. The phosphoinositide 3-kinase/AKT pathway and SRC signaling were densely populated by prognosis-significant genes and driven by genomic amplification of SRC and miRNA regulation of p85a and CBL. On tissue microarray validation (n ¼ 148), p85a protein expression was associated with improved survival for all patients (P ¼ 0.02), and activated P-SRC (Y418) was associated shorter survival for patients with low-grade histology tumors (P ¼ 0.04). -
LRRK2) Inhibitors Using a Crystallographic Surrogate Derived from Checkpoint Kinase 1 (CHK1
This is a repository copy of Design of Leucine-Rich Repeat Kinase 2 (LRRK2) Inhibitors Using a Crystallographic Surrogate Derived from Checkpoint Kinase 1 (CHK1). White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/130583/ Version: Accepted Version Article: Williamson, Douglas S., Smith, Garrick P., Acheson-Dossang, Pamela et al. (20 more authors) (2017) Design of Leucine-Rich Repeat Kinase 2 (LRRK2) Inhibitors Using a Crystallographic Surrogate Derived from Checkpoint Kinase 1 (CHK1). JOURNAL OF MEDICINAL CHEMISTRY. pp. 8945-8962. ISSN 0022-2623 https://doi.org/10.1021/acs.jmedchem.7b01186 Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Design of LRRK2 inhibitors using a CHK1-derived crystallographic surrogate Douglas S. Williamson,†* Garrick P. Smith,‡ Pamela Acheson-Dossang,† Simon T. Bedford,† Victoria Chell,† I-Jen Chen,† Justus C. A. Daechsel,‡ Zoe Daniels,† Laurent David,‡ Pawel Dokurno,† Morten Hentzer,‡ Martin C. Herzig,‡ Roderick E. -
Protein Kinases Phosphorylation/Dephosphorylation Protein Phosphorylation Is One of the Most Important Mechanisms of Cellular Re
Protein Kinases Phosphorylation/dephosphorylation Protein phosphorylation is one of the most important mechanisms of cellular responses to growth, stress metabolic and hormonal environmental changes. Most mammalian protein kinases have highly a homologous 30 to 32 kDa catalytic domain. • Most common method of reversible modification - activation and localization • Up to 1/3 of cellular proteins can be phosphorylated • Leads to a very fast response to cellular stress, hormonal changes, learning processes, transcription regulation .... • Different than allosteric or Michealis Menten regulation Protein Kinome To date – 518 human kinases known • 50 kinase families between yeast, invertebrate and mammaliane kinomes • 518 human PKs, most (478) belong to single super family whose catalytic domain are homologous. • Kinase dendrogram displays relative similarities based on catalytic domains. • AGC (PKA, PKG, PKC) • CAMK (Casein kinase 1) • CMGC (CDC, MAPK, GSK3, CLK) • STE (Sterile 7, 11 & 20 kinases) • TK (Tryosine kinases memb and cyto) • TKL (Tyrosine kinase-like) • Phosphorylation stabilized thermodynamically - only half available energy used in adding phosphoryl to protein - change in free energy forces phosphorylation reaction in one direction • Phosphatases reverse direction • The rate of reaction of most phosphatases are 1000 times faster • Phosphorylation occurs on Ser/The or Tyr • What differences occur due to the addition of a phosphoryl group? • Regulation of protein phosphorylation varies depending on protein - some turned on or off -
Supplementary Table 1. in Vitro Side Effect Profiling Study for LDN/OSU-0212320. Neurotransmitter Related Steroids
Supplementary Table 1. In vitro side effect profiling study for LDN/OSU-0212320. Percent Inhibition Receptor 10 µM Neurotransmitter Related Adenosine, Non-selective 7.29% Adrenergic, Alpha 1, Non-selective 24.98% Adrenergic, Alpha 2, Non-selective 27.18% Adrenergic, Beta, Non-selective -20.94% Dopamine Transporter 8.69% Dopamine, D1 (h) 8.48% Dopamine, D2s (h) 4.06% GABA A, Agonist Site -16.15% GABA A, BDZ, alpha 1 site 12.73% GABA-B 13.60% Glutamate, AMPA Site (Ionotropic) 12.06% Glutamate, Kainate Site (Ionotropic) -1.03% Glutamate, NMDA Agonist Site (Ionotropic) 0.12% Glutamate, NMDA, Glycine (Stry-insens Site) 9.84% (Ionotropic) Glycine, Strychnine-sensitive 0.99% Histamine, H1 -5.54% Histamine, H2 16.54% Histamine, H3 4.80% Melatonin, Non-selective -5.54% Muscarinic, M1 (hr) -1.88% Muscarinic, M2 (h) 0.82% Muscarinic, Non-selective, Central 29.04% Muscarinic, Non-selective, Peripheral 0.29% Nicotinic, Neuronal (-BnTx insensitive) 7.85% Norepinephrine Transporter 2.87% Opioid, Non-selective -0.09% Opioid, Orphanin, ORL1 (h) 11.55% Serotonin Transporter -3.02% Serotonin, Non-selective 26.33% Sigma, Non-Selective 10.19% Steroids Estrogen 11.16% 1 Percent Inhibition Receptor 10 µM Testosterone (cytosolic) (h) 12.50% Ion Channels Calcium Channel, Type L (Dihydropyridine Site) 43.18% Calcium Channel, Type N 4.15% Potassium Channel, ATP-Sensitive -4.05% Potassium Channel, Ca2+ Act., VI 17.80% Potassium Channel, I(Kr) (hERG) (h) -6.44% Sodium, Site 2 -0.39% Second Messengers Nitric Oxide, NOS (Neuronal-Binding) -17.09% Prostaglandins Leukotriene, -
The Role of Casein Kinase 1 in Meiosis
e & Ch m rom ro o d s n o y m S Zhao and Liang, J Down Syndr Chr Abnorm 2016, 2:1 e n A Journal of Down Syndrome & w b o n DOI: 10.4172/2472-1115.1000106 D o f r m o l ISSN: 2472-1115a a l i n t r i e u s o J Chromosome Abnormalities Review Article Open Access The Role of Casein Kinase 1 in Meiosis Yue-Fang Zhao and Cheng-Guang Liang* The Key Laboratory of National Education Ministry for Mammalian Reproductive Biology and Biotechnology, The Research Center for Laboratory Animal Science, College of Life Science, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China Abstract The casein kinase 1 (CK1) belongs to the serine/threonine protein kinases. CK1 members, which commonly exist in all eukaryotes, are involved in the regulation of many cellular processes linked to cell cycle progression, spindle- dynamics, and chromosome segregation. Additionally, CK1 regulate key signaling pathways such as Wnt (Wingless/ Int-1), Hh (Hedgehog), and Hippo, known to be critically involved in tumor progression. Considering the importance of CK1 for accurate cell division and regulation of tumor suppressor functions, it is not surprising scientific effort has enormously increased. In mammals, CK1 regulate the transition from interphase to metaphase in mitosis. In budding yeast and fission yeast, CK1 phosphorylate Rec8 subunits of cohesin complex and regulate chromosome segregation in meiosis. During meiosis, two rounds of chromosome segregation after a single round of DNA replication produce haploid gametes from diploid precursors. Any mistake in chromosome segregation may result in aneuploidy, which in meiosis are one of the main causes of infertility, abortion and many genetic diseases in humans. -
Elucidating the Host Interactome of EV-A71 2C Reveals Viral Dependency Factors
fmicb-10-00636 March 29, 2019 Time: 18:51 # 1 ORIGINAL RESEARCH published: 02 April 2019 doi: 10.3389/fmicb.2019.00636 Elucidating the Host Interactome of EV-A71 2C Reveals Viral Dependency Factors Ye Li1†, Xia Jian1†, Peiqi Yin1, Guofeng Zhu2 and Leiliang Zhang3* 1 NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China, 2 National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, and Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 3 Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China Viral protein 2C plays a critical role in EV-A71 replication. The discovery of 2C binding proteins will likely provide potential targets to treat EV-A71 infection. Here, we provide a global proteomic analysis of the human proteins that interact with the EV-A71 2C protein. TRIM4, exportin2, and ARFGAP1 were validated as 2C binding partners. Further functional studies revealed that TRIM4, exportin2, and ARFGAP1 were novel host Edited by: dependency factors for EV-A71. Moreover, enteroviruses’ 2C family proteins interacted Ju-Tao Guo, with exportin2 and ARFGAP1. In conclusion, our study provides a cellular interactome Baruch S. Blumberg Institute, United States of the EV-A71 2C and identifies the proviral roles of TRIM4, exportin2, and ARFGAP1 in Reviewed by: EV-A71 infection. Ping Zhao, Second Military Medical University, Keywords: EV-A71, 2C, TRIM4, exportin2, ARFGAP1 China Ke Lan, State Key Laboratory of Virology, INTRODUCTION Wuhan University, China *Correspondence: Enterovirus A71 (EV-A71) is one of the major pathogens that leads to hand, foot and mouth disease Leiliang Zhang (HFMD) in young children and infants, and has become a serious threat to global public health [email protected] (Baggen et al., 2018). -
ISS National Lab Q1FY19 Report Quarterly Report for the Period October 1 – December 31, 2018
NASAWATCH.COM ISS National Lab Q1FY19 Report Quarterly Report for the Period October 1 – December 31, 2018 Contents Q1FY19 Metrics ........................................................................................................................................... 2 Key Portfolio Data Charts ............................................................................................................................. 6 Program Successes ...................................................................................................................................... 6 In-Orbit Activities ........................................................................................................................................ 7 Research Solicitations in Progress ................................................................................................................ 7 Appendix .................................................................................................................................................... 8 Authorized for submission to NASA by: _______________________________ Print Name _______________ Signature ________________________________________________________ 1 NASAWATCH.COM NASAWATCH.COM ISS National Lab Q1FY19 Report Q1FY19 Metrics SECURE STRATEGIC FLIGHT PROJECTS: Generate significant, impactful, and measurable demand from customers that recognize value of the ISS National Lab as an innovation platform TARGET ACTUAL Q1 ACTUAL Q2 ACTUAL Q3 ACTUAL Q4 YTD FY19 FY19 ISS National Lab payloads manifested