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Domanegg K, Sleeman JP, Schmaus A. CEMIP, a Promising Biomarker That Promotes the Progression and Metastasis of Colorectal and Other Types of Cancer. Cancers (Basel) 2022; 14:cancers14205093. [PMID: 36291875 PMCID: PMC9600181 DOI: 10.3390/cancers14205093] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 10/05/2022] [Accepted: 10/12/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary CEMIP (cell migration-inducing and hyaluronan-binding protein) has been implicated in the pathogenesis of numerous diseases, including colorectal and other forms of cancer. The molecular functions of CEMIP are currently under investigation and include the degradation of the extracellular matrix component hyaluronic acid (HA), as well as the regulation of a number of signaling pathways. In this review, we survey our current understanding of how CEMIP contributes to tumor growth and metastasis, focusing particularly on colorectal cancer, for which it serves as a promising biomarker. Abstract Originally discovered as a hypothetical protein with unknown function, CEMIP (cell migration-inducing and hyaluronan-binding protein) has been implicated in the pathogenesis of numerous diseases, including deafness, arthritis, atherosclerosis, idiopathic pulmonary fibrosis, and cancer. Although a comprehensive definition of its molecular functions is still in progress, major functions ascribed to CEMIP include the depolymerization of the extracellular matrix component hyaluronic acid (HA) and the regulation of a number of signaling pathways. CEMIP is a promising biomarker for colorectal cancer. Its expression is associated with poor prognosis for patients suffering from colorectal and other types of cancer and functionally contributes to tumor progression and metastasis. Here, we review our current understanding of how CEMIP is able to foster the process of tumor growth and metastasis, focusing particularly on colorectal cancer. Studies in cancer cells suggest that CEMIP exerts its pro-tumorigenic and pro-metastatic activities through stimulating migration and invasion, suppressing cell death and promoting survival, degrading HA, regulating pro-metastatic signaling pathways, inducing the epithelial–mesenchymal transition (EMT) program, and contributing to the metabolic reprogramming and pre-metastatic conditioning of future metastatic microenvironments. There is also increasing evidence indicating that CEMIP may be expressed in cells within the tumor microenvironment that promote tumorigenesis and metastasis formation, although this remains in an early stage of investigation. CEMIP expression and activity can be therapeutically targeted at a number of levels, and preliminary findings in animal models show encouraging results in terms of reduced tumor growth and metastasis, as well as combating therapy resistance. Taken together, CEMIP represents an exciting new player in the progression of colorectal and other types of cancer that holds promise as a therapeutic target and biomarker.
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Affiliation(s)
- Kevin Domanegg
- European Center for Angioscience (ECAS), Medical Faculty Mannheim, University of Heidelberg, 68167 Mannheim, Germany
| | - Jonathan P. Sleeman
- European Center for Angioscience (ECAS), Medical Faculty Mannheim, University of Heidelberg, 68167 Mannheim, Germany
- Institute of Biological and Chemical Systems-Biological Information Processing, Karlsruhe Institute of Technology (KIT) Campus Nord, 76344 Eggenstein-Leopoldshafen, Germany
- Correspondence:
| | - Anja Schmaus
- European Center for Angioscience (ECAS), Medical Faculty Mannheim, University of Heidelberg, 68167 Mannheim, Germany
- Institute of Biological and Chemical Systems-Biological Information Processing, Karlsruhe Institute of Technology (KIT) Campus Nord, 76344 Eggenstein-Leopoldshafen, Germany
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Wang Y, Li N, Zheng Y, Wang A, Yu C, Song Z, Wang S, Sun Y, Zheng L, Wang G, Liu L, Yi J, Huang Y, Zhang M, Bao Y, Sun L. KIAA1217 Promotes Epithelial-Mesenchymal Transition and Hepatocellular Carcinoma Metastasis by Interacting with and Activating STAT3. Int J Mol Sci 2021; 23:104. [PMID: 35008530 PMCID: PMC8745027 DOI: 10.3390/ijms23010104] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/18/2021] [Accepted: 12/21/2021] [Indexed: 12/01/2022] Open
Abstract
The survival and prognosis of hepatocellular carcinoma (HCC) are poor, mainly due to metastasis. Therefore, insights into the molecular mechanisms underlying HCC invasion and metastasis are urgently needed to develop a more effective antimetastatic therapy. Here, we report that KIAA1217, a functionally unknown macromolecular protein, plays a crucial role in HCC metastasis. KIAA1217 expression was frequently upregulated in HCC cell lines and tissues, and high KIAA1217 expression was closely associated with shorter survival of patients with HCC. Overexpression and knockdown experiments revealed that KIAA1217 significantly promoted cell migration and invasion by inducing epithelial-mesenchymal transition (EMT) in vitro. Consistently, HCC cells overexpressing KIAA1217 exhibited markedly enhanced lung metastasis in vivo. Mechanistically, KIAA1217 enhanced EMT and accordingly promoted HCC metastasis by interacting with and activating JAK1/2 and STAT3. Interestingly, KIAA1217-activated p-STAT3 was retained in the cytoplasm instead of translocating into the nucleus, where p-STAT3 subsequently activated the Notch and Wnt/β-catenin pathways to facilitate EMT induction and HCC metastasis. Collectively, KIAA1217 may function as an adaptor protein or scaffold protein in the cytoplasm and coordinate multiple pathways to promote EMT-induced HCC metastasis, indicating its potential as a therapeutic target for curbing HCC metastasis.
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Affiliation(s)
- Yanhong Wang
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Na Li
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Yanping Zheng
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Anqing Wang
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Chunlei Yu
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Zhenbo Song
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Shuyue Wang
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Ying Sun
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Lihua Zheng
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Guannan Wang
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Lei Liu
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Jingwen Yi
- NMPA Key Laboratory for Quality of Cell and Gene Therapy Medicinal Products, Northeast Normal University, Changchun 130024, China; (Z.S.); (S.W.); (L.Z.); (G.W.); (L.L.); (J.Y.)
| | - Yanxin Huang
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Muqing Zhang
- School of Molecular and Cellular Biology, University of Illinois Urbana Champaign, Urbana, IL 61801, USA;
| | - Yongli Bao
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
| | - Luguo Sun
- National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China; (Y.W.); (N.L.); (Y.Z.); (A.W.); (C.Y.); (Y.S.); (Y.H.); (Y.B.)
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Zhou J, Chen C, Liu S, Zhou W, Du J, Jiang Y, Dai J, Jin G, Ma H, Hu Z, Chen J, Shen H. Potential functional variants of KIAA genes are associated with breast cancer risk in a case control study. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:549. [PMID: 33987247 DOI: 10.21037/atm-20-6108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background KIAA genes identified in the Kazusa cDNA-sequencing project may play important roles in biological processes and are involved in carcinogenesis of many cancers. Genetic variants of KIAA genes are implicated in the abnormal expression of these genes and are linked to susceptibility of several human complex diseases. Methods The differentially expressed KIAA genes were screened and identified in The Cancer Genome Atlas (TCGA) database of breast cancer. A total of 48 variants located in the 28 KIAA genes were selected to investigate the associations between polymorphism and breast cancer in 1,032 cases and 1,063 cancer-free controls in a Chinese population. Results Two coding variants, which included a SNP rs2306369 in KIAA1109 and a SNP rs1205434 in KIAA1755, were identified to be associated with the incidences of breast cancer. Logistic regression analysis showed that the SNP rs2306369 G allele was associated with a decreased risk of breast cancer (additive model: OR =0.81, 95% CI: 0.66-0.99, P=0.038), whereas the SNP rs1205434 A allele was involved with a higher risk of breast cancer (additive model: OR =1.19, 95% CI: 1.02-1.38, P= 0.025). Further stratified analysis revealed that the SNP rs1205434 showed a significant difference for age at menarche strata (heterogeneity test P=0.009). Multiplicative interaction analysis indicated that there was positive multiplicative interaction between the SNP rs1205434 and menarche age (OR =1.09, 95% CI: 1.01-1.17, P=0.036). Additionally, expression quantitative trait loci analysis revealed that the SNP rs1205434 A allele could decrease the KIAA1755 expression in the Genotype-Tissue Expression (GTEx) database (P=0.002). The Kaplan-Meier plotter showed that breast cancer patients with high KIAA1755 expression have significantly better outcomes than those with low levels of expression (HR =0.84, 95% CI: 0.72-0.99, P=0.033). Conclusions The results indicate that the genetic variants (rs2306369 and rs1205434) in the coding region of KIAA1109 and KIAA1755 respectively may affect Chinese females' breast cancer susceptibility and act as potential predictive biomarkers for breast cancer.
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Affiliation(s)
- Jing Zhou
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Statistical Center, Information Department, Northern Jiangsu People's Hospital and Clinical Medical College of Yangzhou University, Yangzhou, China
| | - Congcong Chen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Sijun Liu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wen Zhou
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Jiangbo Du
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Jiaping Chen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
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KIAA0100 Modulates Cancer Cell Aggression Behavior of MDA-MB-231 through Microtubule and Heat Shock Proteins. Cancers (Basel) 2018; 10:cancers10060180. [PMID: 29867023 PMCID: PMC6025110 DOI: 10.3390/cancers10060180] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 05/29/2018] [Indexed: 12/25/2022] Open
Abstract
The KIAA0100 gene was identified in the human immature myeloid cell line cDNA library. Recent studies have shown that its expression is elevated in breast cancer and associated with more aggressive cancer types as well as poor outcomes. However, its cellular and molecular function is yet to be understood. Here we show that silencing KIAA0100 by siRNA in the breast cancer cell line MDA-MB-231 significantly reduced the cancer cells’ aggressive behavior, including cell aggregation, reattachment, cell metastasis and invasion. Most importantly, silencing the expression of KIAA0100 particularly sensitized the quiescent cancer cells in suspension culture to anoikis. Immunoprecipitation, mass spectrometry and immunofluorescence analysis revealed that KIAA0100 may play multiple roles in the cancer cells, including stabilizing microtubule structure as a microtubule binding protein, and contributing to MDA-MB-231 cells Anoikis resistance by the interaction with stress protein HSPA1A. Our study also implies that the interaction between KIAA0100 and HSPA1A may be targeted for new drug development to specifically induce anoikis cell death in the cancer cell.
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Cui H, Lan X, Lu S, Zhang F, Zhang W. Preparation of monoclonal antibody against human KIAA0100 protein and Northern blot analysis of human KIAA0100 gene. J Pharm Anal 2018; 7:190-195. [PMID: 29404037 PMCID: PMC5790689 DOI: 10.1016/j.jpha.2017.02.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 11/21/2016] [Accepted: 02/07/2017] [Indexed: 10/27/2022] Open
Abstract
Monoclonal antibodies (MAbs) are important tools for the study of proteins' function and structure. But there has been no report on the preparation of MAbs against human KIAA0100 protein up to date. Here, first, we generated the mouse MAb against human KIAA0100 protein using purified recombinant 6×Histidinc (6×His)-tagged human KIAA0100 protein segment (1557-2234) as an antigen; then, the mRNA expression of human KIAA0100 gene was detected in U937 cells using Northern blot analysis. The results showed that the mouse MAb against human KIAA0100 protein could sensitively recognize the human KIAA0100 protein using Western blot analysis and immunocytochemistry analysis. Besides, Western blot analysis revealed that human KIAA0100 gene possibly encoded two different protein products (254 kDa and <250 kDa) in U937 cells. Moreover, Northern blot analysis confirmed that human KIAA0100 gene might produced two different mRNA products (6000-10000 bp and 5000-6000 bp) in U937 cells. The results provide a basis for large-scale production of the MAb against human KIAA0100 protein, which will be useful for the study of human KIAA0100 protein's function/structure and MAb-targeted drugs in the future.
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Affiliation(s)
- He Cui
- Department of Clinical Hematology, The Affiliated Hospital, Inner Mongolia Medical University, No. 1 Tongdao North Street, Hohhot 010059, China
| | - Xi Lan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, No. 76 The Yanta West Road, Xi'an, Shaanxi 710061, China
| | - Shemin Lu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, No. 76 The Yanta West Road, Xi'an, Shaanxi 710061, China
| | - Fujun Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, No. 76 The Yanta West Road, Xi'an, Shaanxi 710061, China
| | - Wanggang Zhang
- Department of Clinical Hematology, The Second Affiliated No. 2 Hospital, Xi'an Jiaotong University, No. 157 West Five Road, Xi'an, Shaanxi 710004, China
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Distribution and function of hyaluronan binding protein involved in hyaluronan depolymerization (HYBID, KIAA1199) in the mouse central nervous system. Neuroscience 2017; 347:1-10. [PMID: 28189611 DOI: 10.1016/j.neuroscience.2017.01.049] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 01/27/2017] [Accepted: 01/30/2017] [Indexed: 12/15/2022]
Abstract
HYBID (HYaluronan Binding Protein Involved in hyaluronan [HA] Depolymerization, KIAA1199) is one of the HA binding proteins that is involved in the depolymerization of HA. HYBID mRNA is highly expressed in the brain, however, the role of HYBID in the brain remains unclear. In this study, we bred Hybid knock-out (KO) mice and evaluated the function of Hybid in the central nervous system. Hybid mRNA was expressed in the brain, especially in the hippocampus and cerebellum, in wild-type mice. Hybid KO mice demonstrated decreased mnemonic ability in novel object recognition and Morris water maze tests. The average molecular mass of hippocampal HA increased in KO mice, accompanied by a significant increase in the total HA amount. Hybid KO mice did not differ in behavior from wild-type mice in the open field test, evaluation of acoustic startle responses, or drug-induced seizure test. In real-time PCR, Hyal1 and Hyal2 mRNA levels, which code hyaluronidases 1 and 2, respectively, did not differ between the Hybid KO and wild-type mouse brain. These results indicate that Hybid plays a key role in memory function in the brain.
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Nouri K, Fansa EK, Amin E, Dvorsky R, Gremer L, Willbold D, Schmitt L, Timson DJ, Ahmadian MR. IQGAP1 Interaction with RHO Family Proteins Revisited: KINETIC AND EQUILIBRIUM EVIDENCE FOR MULTIPLE DISTINCT BINDING SITES. J Biol Chem 2016; 291:26364-26376. [PMID: 27815503 PMCID: PMC5159498 DOI: 10.1074/jbc.m116.752121] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 10/27/2016] [Indexed: 11/16/2022] Open
Abstract
IQ motif-containing GTPase activating protein 1 (IQGAP1) plays a central role in the physical assembly of relevant signaling networks that are responsible for various cellular processes, including cell adhesion, polarity, and transmigration. The RHO family proteins CDC42 and RAC1 have been shown to mainly interact with the GAP-related domain (GRD) of IQGAP1. However, the role of its RASGAP C-terminal (RGCT) and C-terminal domains in the interactions with RHO proteins has remained obscure. Here, we demonstrate that IQGAP1 interactions with RHO proteins underlie a multiple-step binding mechanism: (i) a high affinity, GTP-dependent binding of RGCT to the switch regions of CDC42 or RAC1 and (ii) a very low affinity binding of GRD and a C terminus adjacent to the switch regions. These data were confirmed by phosphomimetic mutation of serine 1443 to glutamate within RGCT, which led to a significant reduction of IQGAP1 affinity for CDC42 and RAC1, clearly disclosing the critical role of RGCT for these interactions. Unlike CDC42, an extremely low affinity was determined for the RAC1-GRD interaction, suggesting that the molecular nature of IQGAP1 interaction with CDC42 partially differs from that of RAC1. Our study provides new insights into the interaction characteristics of IQGAP1 with RHO family proteins and highlights the complementary importance of kinetic and equilibrium analyses. We propose that the ability of IQGAP1 to interact with RHO proteins is based on a multiple-step binding process, which is a prerequisite for the dynamic functions of IQGAP1 as a scaffolding protein and a critical mechanism in temporal regulation and integration of IQGAP1-mediated cellular responses.
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Affiliation(s)
- Kazem Nouri
- From the Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich-Heine University, 40225 Düsseldorf, Germany
| | - Eyad K Fansa
- From the Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich-Heine University, 40225 Düsseldorf, Germany
| | - Ehsan Amin
- From the Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich-Heine University, 40225 Düsseldorf, Germany
| | - Radovan Dvorsky
- From the Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich-Heine University, 40225 Düsseldorf, Germany
| | - Lothar Gremer
- the Institute of Physical Biology, Heinrich-Heine University, 40225 Düsseldorf, Germany.,Forschungszentrum Jülich, ICS-6, 52428 Jülich, Germany
| | - Dieter Willbold
- the Institute of Physical Biology, Heinrich-Heine University, 40225 Düsseldorf, Germany.,Forschungszentrum Jülich, ICS-6, 52428 Jülich, Germany
| | - Lutz Schmitt
- the Institute of Biochemistry, Heinrich-Heine University, 40225 Düsseldorf, Germany, and
| | - David J Timson
- the School of Pharmacy and Biomolecular Sciences, University of Brighton, Huxley Building, Lewes Road, Brighton BN2 4GJ, United Kingdom
| | - Mohammad R Ahmadian
- From the Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich-Heine University, 40225 Düsseldorf, Germany,
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Cui H, Lan X, Lu S, Zhang F, Zhang W. Bioinformatic prediction and functional characterization of human KIAA0100 gene. J Pharm Anal 2016; 7:10-18. [PMID: 29404013 PMCID: PMC5686863 DOI: 10.1016/j.jpha.2016.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/11/2016] [Accepted: 09/12/2016] [Indexed: 12/26/2022] Open
Abstract
Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA) gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil) , and four domains from mitochondrial protein 27 (FMP27). The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.
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Affiliation(s)
- He Cui
- Department of Clinical Hematology, Affiliated No. 2 Hospital, Xi'an Jiaotong University, The West Five Road, 157#, Xi'an, Shaanxi 710004, China
| | - Xi Lan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, The Yanta West Road, 76#, Xi'an, Shaanxi 710061, China
| | - Shemin Lu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, The Yanta West Road, 76#, Xi'an, Shaanxi 710061, China
| | - Fujun Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, The Yanta West Road, 76#, Xi'an, Shaanxi 710061, China
| | - Wanggang Zhang
- Department of Clinical Hematology, Affiliated No. 2 Hospital, Xi'an Jiaotong University, The West Five Road, 157#, Xi'an, Shaanxi 710004, China
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Distinct Expression Pattern of a Deafness Gene, KIAA1199, in a Primate Cochlea. BIOMED RESEARCH INTERNATIONAL 2016; 2016:1781894. [PMID: 27403418 PMCID: PMC4923552 DOI: 10.1155/2016/1781894] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Revised: 05/12/2016] [Accepted: 05/23/2016] [Indexed: 11/17/2022]
Abstract
Deafness is one of the most common types of congenital impairments, and at least half of the cases are caused by hereditary mutations. Mutations of the gene KIAA1199 are associated with progressive hearing loss. Its expression is abundant in human cochlea, but interestingly the spatial expression patterns are different between mouse and rat cochleae; the pattern in humans has not been fully investigated. We performed immunohistochemical analysis of a nonhuman primate, common marmoset (Callithrix jacchus), cochlea with a KIAA1199-specific antibody. In the common marmoset cochlea, KIAA1199 protein expression was more widespread than in rodents, with all epithelial cells, including hair cells, expressing KIAA1199. Our results suggest that the primate pattern of KIAA1199 expression is wider in comparison with rodents and may play an essential role in the maintenance of cochlear epithelial cells.
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Cain NE, Tapley EC, McDonald KL, Cain BM, Starr DA. The SUN protein UNC-84 is required only in force-bearing cells to maintain nuclear envelope architecture. ACTA ACUST UNITED AC 2014; 206:163-72. [PMID: 25023515 PMCID: PMC4107780 DOI: 10.1083/jcb.201405081] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
SUN-KASH bridges that connect the nucleoskeleton to the cytoskeleton are only required to maintain nuclear envelope spacing in cells subjected to increased mechanical forces, such as muscle cells. The nuclear envelope (NE) consists of two evenly spaced bilayers, the inner and outer nuclear membranes. The Sad1p and UNC-84 (SUN) proteins and Klarsicht, ANC-1, and Syne homology (KASH) proteins that interact to form LINC (linker of nucleoskeleton and cytoskeleton) complexes connecting the nucleoskeleton to the cytoskeleton have been implicated in maintaining NE spacing. Surprisingly, the NE morphology of most Caenorhabditis elegans nuclei was normal in the absence of functional SUN proteins. Distortions of the perinuclear space observed in unc-84 mutant muscle nuclei resembled those previously observed in HeLa cells, suggesting that SUN proteins are required to maintain NE architecture in cells under high mechanical strain. The UNC-84 protein with large deletions in its luminal domain was able to form functional NE bridges but had no observable effect on NE architecture. Therefore, SUN-KASH bridges are only required to maintain NE spacing in cells subjected to increased mechanical forces. Furthermore, SUN proteins do not dictate the width of the NE.
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Affiliation(s)
- Natalie E Cain
- Department of Molecular and Cellular Biology and Department of Physics, University of California, Davis, Davis, CA 95616
| | - Erin C Tapley
- Department of Molecular and Cellular Biology and Department of Physics, University of California, Davis, Davis, CA 95616
| | - Kent L McDonald
- Electron Microscope Laboratory, University of California, Berkeley, Berkeley, CA 94720
| | - Benjamin M Cain
- Department of Molecular and Cellular Biology and Department of Physics, University of California, Davis, Davis, CA 95616
| | - Daniel A Starr
- Department of Molecular and Cellular Biology and Department of Physics, University of California, Davis, Davis, CA 95616
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11
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ZHANG YONGSHENG, JIA SHUQIN, JIANG WENG. KIAA1199 and its biological role in human cancer and cancer cells (Review). Oncol Rep 2014; 31:1503-8. [DOI: 10.3892/or.2014.3038] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2013] [Accepted: 01/24/2014] [Indexed: 11/05/2022] Open
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12
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Andrews WJ, Bradley CA, Hamilton E, Daly C, Mallon T, Timson DJ. A calcium-dependent interaction between calmodulin and the calponin homology domain of human IQGAP1. Mol Cell Biochem 2012; 371:217-23. [PMID: 22944912 DOI: 10.1007/s11010-012-1438-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Accepted: 08/25/2012] [Indexed: 01/01/2023]
Abstract
IQGAPs are cytoskeletal scaffolding proteins which collect information from a variety of signalling pathways and pass it on to the microfilaments and microtubules. There is a well-characterised interaction between IQGAP and calmodulin through a series of IQ-motifs towards the middle of the primary sequence. However, it has been shown previously that the calponin homology domain (CHD), located at the N-terminus of the protein, can also interact weakly with calmodulin. Using a recombinant fragment of human IQGAP1 which encompasses the CHD, we have demonstrated that the CHD undergoes a calcium ion-dependent interaction with calmodulin. The CHD can also displace the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulphonate from calcium-calmodulin, suggesting that the interaction involves non-polar residues on the surface of calmodulin. Molecular modelling identified a possible site on the CHD for calmodulin interaction. The physiological significance of this interaction remains to be discovered.
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Affiliation(s)
- William J Andrews
- School of Biological Sciences, Queen's University Belfast, Medical Biology Centre, 97 Lisburn Road, Belfast, BT9 7BL, UK
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13
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Elliott SF, Allen G, Timson DJ. Biochemical analysis of the interactions of IQGAP1 C-terminal domain with CDC42. World J Biol Chem 2012; 3:53-60. [PMID: 22451851 PMCID: PMC3312201 DOI: 10.4331/wjbc.v3.i3.53] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2011] [Revised: 01/31/2012] [Accepted: 02/07/2012] [Indexed: 02/05/2023] Open
Abstract
AIM: To understand the interaction of human IQGAP1 and CDC42, especially the effects of phosphorylation and a cancer-associated mutation.
METHODS: Recombinant CDC42 and a novel C-terminal fragment of IQGAP1 were expressed in, and purified from, Escherichia coli. Site directed mutagenesis was used to create coding sequences for three phosphomimicking variants (S1441E, S1443D and S1441E/S1443D) and to recapitulate a cancer-associated mutation (M1231I). These variant proteins were also expressed and purified. Protein-protein crosslinking using 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide was used to investigate interactions between the C-terminal fragment and CDC42. These interactions were quantified using surface plasmon resonance measurements. Molecular modelling was employed to make predictions about changes to the structure and flexibility of the protein which occur in the cancer-associated variant.
RESULTS: The novel, C-terminal region of human IQGAP1 (residues 877-1558) is soluble following expression and purification. It is also capable of binding to CDC42, as judged by crosslinking experiments. Interaction appears to be strongest in the presence of added GTP. The three phosphomimicking mutants had different affinities for CDC42. S1441E had an approximately 200-fold reduction in affinity compared to wild type. This was caused largely by a dramatic reduction in the association rate constant. In contrast, both S1443D and the double variant S1441E/S1443D had similar affinities to the wild type. The cancer-associated variant, M1231I, also had a similar affinity to wild type. However, in the case of this variant, both the association and dissociation rate constants were reduced approximately 10-fold. Molecular modelling of the M1231I variant, based on the published crystal structure of part of the C-terminal region, revealed no gross structural changes compared to wild type (root mean square deviation of 0.564 Å over 5556 equivalent atoms). However, predictions of the flexibility of the polypeptide backbone suggested that some regions of the variant protein had greatly increased rigidity compared to wild type. One such region is a loop linking the proposed CDC42 binding site with the helix containing the altered residue. It is suggested that this increase in rigidity is responsible for the observed changes in association and dissociation rate constants.
CONCLUSION: The consequences of introducing negative charge at Ser-1441 or Ser-1443 in IQGAP1 are different. The cancer-associated variant M1231I exerts its effects partly by rigidifying the protein.
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Affiliation(s)
- Sarah F Elliott
- Sarah F Elliott, George Allen, David J Timson, School of Biological Sciences, Queen's University Belfast, Medical Biology Centre, Belfast, BT9 7BL, United Kingdom
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14
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Moser E, Kargl J, Whistler JL, Waldhoer M, Tschische P. G protein-coupled receptor-associated sorting protein 1 regulates the postendocytic sorting of seven-transmembrane-spanning G protein-coupled receptors. Pharmacology 2010; 86:22-9. [PMID: 20693822 DOI: 10.1159/000314161] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2010] [Accepted: 04/23/2010] [Indexed: 11/19/2022]
Abstract
The largest superfamily of membrane proteins that translate extracellular signals into intracellular messages are the 7-transmembrane-spanning (7TM) G protein-coupled receptors (GPCR). One of the ways in which their activity is controlled is by the process of desensitization and endocytosis, whereby agonist-activated receptors are rapidly and often reversibly silenced through removal from the cell surface. Indeed, following endocytosis, individual receptors can be sorted differentially between recycling endosomes and lysosomes, which controls the reversibility of the silencing. Thus, endocytosis can either serve as a mechanism for receptor resensitization by delivering receptors back to the plasma membrane or facilitate receptor downregulation by serving as the first step towards targeting the receptors to lysosomes for degradation. The sorting of receptors to the lysosomal pathway can be facilitated by interaction with an array of accessory proteins. One of these proteins is the GPCR-associated sorting protein 1 (GASP-1), which specifically targets several 7TM-GPCR to the lysosomal pathway after endocytosis. Furthermore, GASP-1 was recently found to directly affect the signaling capacity of a 7TM-GPCR. Importantly, the in vivo relevance of GASP-1-dependent receptor sorting has also begun to be verified in animal models. Here, we summarize the recent advances in elucidating GASP-1-dependent receptor sorting functions and their potential implications in vivo.
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Affiliation(s)
- Elisabeth Moser
- Institute of Experimental and Clinical Pharmacology, Medical University of Graz, Graz, Austria
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15
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Martini L, Waldhoer M, Pusch M, Kharazia V, Fong J, Lee JH, Freissmuth C, Whistler JL. Ligand-induced down-regulation of the cannabinoid 1 receptor is mediated by the G-protein-coupled receptor-associated sorting protein GASP1. FASEB J 2006; 21:802-11. [PMID: 17197383 DOI: 10.1096/fj.06-7132com] [Citation(s) in RCA: 116] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The cannabinoid 1 receptor (CB1R) is one of the most abundant seven transmembrane (7TM) spanning/G-protein-coupled receptors in the central nervous system and plays an important role in pain transmission, feeding, and the rewarding effects of cannabis. Tolerance to cannabinoids has been widely observed after long-term use, with concomitant receptor desensitization and/or down-regulation depending on the brain region studied. Several CB1R agonists promote receptor internalization after activation, but the postendocytic sorting of the receptor has not been studied in detail. Utilizing human embryonic kidney (HEK293) cells stably expressing the CB1R and primary cultured neurons expressing endogenous CB1R, we show that treatment with cannabinoid agonists results in CB1R degradation after endocytosis and that the G-protein-coupled receptor-associated sorting protein GASP1 plays a major role in the postendocytic sorting process. Thus, these results may identify a molecular mechanism underlying tolerance and receptor down-regulation after long-term use of cannabinoids.
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Affiliation(s)
- Lene Martini
- Ernest Gallo Clinic and Research Center, University of California, San Francisco, CA, USA
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16
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Jagadish N, Rana R, Selvi R, Mishra D, Garg M, Yadav S, Herr J, Okumura K, Hasegawa A, Koyama K, Suri A. Characterization of a novel human sperm-associated antigen 9 (SPAG9) having structural homology with c-Jun N-terminal kinase-interacting protein. Biochem J 2005; 389:73-82. [PMID: 15693750 PMCID: PMC1184539 DOI: 10.1042/bj20041577] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
We report a novel SPAG9 (sperm-associated antigen 9) protein having structural homology with JNK (c-Jun N-terminal kinase)-interacting protein 3. SPAG9, a single copy gene mapped to the human chromosome 17q21.33 syntenic with location of mouse chromosome 11, was earlier shown to be expressed exclusively in testis [Shankar, Mohapatra and Suri (1998) Biochem. Biophys. Res. Commun. 243, 561-565]. The SPAG9 amino acid sequence analysis revealed identity with the JNK-binding domain and predicted coiled-coil, leucine zipper and transmembrane domains. The secondary structure analysis predicted an alpha-helical structure for SPAG9 that was confirmed by CD spectra. Microsequencing of higher-order aggregates of recombinant SPAG9 by tandem MS confirmed the amino acid sequence and mono atomic mass of 83.9 kDa. Transient expression of SPAG9 and its deletion mutants revealed that both leucine zipper with extended coiled-coil domains and transmembrane domain of SPAG9 were essential for dimerization and proper localization. Studies of MAPK (mitogenactivated protein kinase) interactions demonstrated that SPAG9 interacted with higher binding affinity to JNK3 and JNK2 compared with JNK1. No interaction was observed with p38alpha or extracellular-signal-regulated kinase pathways. Polyclonal antibodies raised against recombinant SPAG9 recognized native protein in human sperm extracts and localized specifically on the acrosomal compartment of intact human spermatozoa. Acrosome-reacted spermatozoa demonstrated SPAG9 immunofluorescence, indicating its retention on the equatorial segment after the acrosome reaction. Further, anti-SPAG9 antibodies inhibited the binding of human spermatozoa to intact human oocytes as well as to matched hemizona. This is the first report of sperm-associated JNK-binding protein that may have a role in spermatozoa-egg interaction.
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Affiliation(s)
- Nirmala Jagadish
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Ritu Rana
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Ramasamy Selvi
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Deepshikha Mishra
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Manoj Garg
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Shikha Yadav
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - John C. Herr
- †Department of Cell Biology, Center for Research in Contraceptive and Reproductive Health, University of Virginia, Charlottesville, VA 22908, U.S.A
| | - Katsuzumi Okumura
- ‡Laboratory of Biological Chemistry, Mie University, Tsu, Mie 514-8507, Japan
| | - Akiko Hasegawa
- §Laboratory of Developmental Biology and Reproduction, Institute of Advanced Medical Sciences, Hyogo College of Medicine, Nishinomiya, Hyogo, Japan
| | - Koji Koyama
- §Laboratory of Developmental Biology and Reproduction, Institute of Advanced Medical Sciences, Hyogo College of Medicine, Nishinomiya, Hyogo, Japan
- ∥Department of Obstetrics and Gynecology, Hyogo College of Medicine, Nishinomiya, Hyogo, Japan
| | - Anil Suri
- *Genes and Proteins Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India
- To whom correspondence should be addressed (email )
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17
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Roepman R, Letteboer SJF, Arts HH, van Beersum SEC, Lu X, Krieger E, Ferreira PA, Cremers FPM. Interaction of nephrocystin-4 and RPGRIP1 is disrupted by nephronophthisis or Leber congenital amaurosis-associated mutations. Proc Natl Acad Sci U S A 2005; 102:18520-5. [PMID: 16339905 PMCID: PMC1317916 DOI: 10.1073/pnas.0505774102] [Citation(s) in RCA: 101] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
RPGR-interacting protein 1 (RPGRIP1) is a key component of cone and rod photoreceptor cells, where it interacts with RPGR (retinitis pigmentosa GTPase regulator). Mutations in RPGRIP1 lead to autosomal recessive congenital blindness [Leber congenital amaurosis (LCA)]. Most LCA-associated missense mutations in RPGRIP1 are located in a segment that encodes two C2 domains. Based on the C2 domain of novel protein kinase C epsilon (PKC epsilon), we built a 3D-homology model for the C-terminal C2 domain of RPGRIP1. This model revealed a potential Ca2+-binding site that was predicted to be disrupted by a missense mutation in RPGRIP1, which was previously identified in an LCA patient. Through yeast two-hybrid screening of a retinal cDNA library, we found this C2 domain to specifically bind to nephrocystin-4, encoded by NPHP4. Mutations in NPHP4 are associated with nephronophthisis and a combination of nephronophthisis and retinitis pigmentosa called Senior-Løken syndrome (SLSN). We show that RPGRIP1 and nephrocystin-4 interact strongly in vitro and in vivo, and that they colocalize in the retina, matching the panretinal localization pattern of specific RPGRIP1 isoforms. Their interaction is disrupted by either mutations in RPGRIP1, found in patients with LCA, or by mutations in NPHP4, found in patients with nephronophthisis or SLSN. Thus, we provide evidence for the involvement of this disrupted interaction in the retinal dystrophy of both SLSN and LCA patients.
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Affiliation(s)
- Ronald Roepman
- Department of Human Genetics, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
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18
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Jagadish N, Rana R, Mishra D, Kumar M, Suri A. Sperm associated antigen 9 (SPAG9): a new member of c-Jun NH2 -terminal kinase (JNK) interacting protein exclusively expressed in testis. Keio J Med 2005; 54:66-71. [PMID: 16077255 DOI: 10.2302/kjm.54.66] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Previously, we cloned and sequenced a novel human sperm associated antigen 9 (SPAG9). Northern blot analysis and RNA in situ hybridization experiments revealed testis- and stage-specific expression of SPAG9 mRNA, mainly confined to round spermatid suggesting haploid germ cell expression Studies on the human and non-human primates (macaque and baboon) have shown a homology of 84.9% and 90.6% at amino acid level and 94% and 96.8% at DNA level, respectively. The presence of high level of homology at amino acid and DNA level indicates that SPAG9 is conserved in human, baboon and macaque sharing common function and common origin in the biological past. In addition, SPAG9 protein revealed structural homology with c-Jun NH2-terminal kinase (JNK) interacting protein (JIP). The amino acid sequence analysis of SPAG9 predicted coiled coil, leucine zipper and transmembrane domain, speculating the involvement of SPAG9 mediated signal transduction pathways in reproductive processes.
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Affiliation(s)
- Nirmala Jagadish
- Genes and Proteins Laboratory, National Institute of Immunology, New Delhi, India
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19
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Imanishi T, Itoh T, Suzuki Y, O'Donovan C, Fukuchi S, Koyanagi KO, Barrero RA, Tamura T, Yamaguchi-Kabata Y, Tanino M, Yura K, Miyazaki S, Ikeo K, Homma K, Kasprzyk A, Nishikawa T, Hirakawa M, Thierry-Mieg J, Thierry-Mieg D, Ashurst J, Jia L, Nakao M, Thomas MA, Mulder N, Karavidopoulou Y, Jin L, Kim S, Yasuda T, Lenhard B, Eveno E, Suzuki Y, Yamasaki C, Takeda JI, Gough C, Hilton P, Fujii Y, Sakai H, Tanaka S, Amid C, Bellgard M, Bonaldo MDF, Bono H, Bromberg SK, Brookes AJ, Bruford E, Carninci P, Chelala C, Couillault C, de Souza SJ, Debily MA, Devignes MD, Dubchak I, Endo T, Estreicher A, Eyras E, Fukami-Kobayashi K, R. Gopinath G, Graudens E, Hahn Y, Han M, Han ZG, Hanada K, Hanaoka H, Harada E, Hashimoto K, Hinz U, Hirai M, Hishiki T, Hopkinson I, Imbeaud S, Inoko H, Kanapin A, Kaneko Y, Kasukawa T, Kelso J, Kersey P, Kikuno R, Kimura K, Korn B, Kuryshev V, Makalowska I, Makino T, Mano S, Mariage-Samson R, Mashima J, Matsuda H, Mewes HW, Minoshima S, Nagai K, Nagasaki H, Nagata N, Nigam R, Ogasawara O, Ohara O, Ohtsubo M, Okada N, Okido T, Oota S, Ota M, Ota T, Otsuki T, Piatier-Tonneau D, Poustka A, Ren SX, Saitou N, Sakai K, Sakamoto S, Sakate R, Schupp I, Servant F, Sherry S, Shiba R, Shimizu N, Shimoyama M, Simpson AJ, Soares B, Steward C, Suwa M, Suzuki M, Takahashi A, Tamiya G, Tanaka H, Taylor T, Terwilliger JD, Unneberg P, Veeramachaneni V, Watanabe S, Wilming L, Yasuda N, Yoo HS, Stodolsky M, Makalowski W, Go M, Nakai K, Takagi T, Kanehisa M, Sakaki Y, Quackenbush J, Okazaki Y, Hayashizaki Y, Hide W, Chakraborty R, Nishikawa K, Sugawara H, Tateno Y, Chen Z, Oishi M, Tonellato P, Apweiler R, Okubo K, Wagner L, Wiemann S, Strausberg RL, Isogai T, Auffray C, Nomura N, Gojobori T, Sugano S. Integrative annotation of 21,037 human genes validated by full-length cDNA clones. PLoS Biol 2004; 2:e162. [PMID: 15103394 PMCID: PMC393292 DOI: 10.1371/journal.pbio.0020162] [Citation(s) in RCA: 267] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2003] [Accepted: 04/01/2004] [Indexed: 01/08/2023] Open
Abstract
The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology.
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Affiliation(s)
- Tadashi Imanishi
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Takeshi Itoh
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 2Bioinformatics Laboratory, Genome Research Department, National Institute of Agrobiological SciencesIbarakiJapan
| | - Yutaka Suzuki
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 68Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of TokyoTokyoJapan
| | - Claire O'Donovan
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Satoshi Fukuchi
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | | | - Roberto A Barrero
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Takuro Tamura
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 8BITS CompanyShizuokaJapan
| | - Yumi Yamaguchi-Kabata
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Motohiko Tanino
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Kei Yura
- 9Quantum Bioinformatics Group, Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research InstituteKyotoJapan
| | - Satoru Miyazaki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Kazuho Ikeo
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Keiichi Homma
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Arek Kasprzyk
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Tetsuo Nishikawa
- 10Reverse Proteomics Research InstituteChibaJapan
- 11Central Research Laboratory, HitachiTokyoJapan
| | - Mika Hirakawa
- 12Bioinformatics Center, Institute for Chemical Research, Kyoto UniversityKyotoJapan
| | - Jean Thierry-Mieg
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
- 14Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique MathematiqueMontpellierFrance
| | - Danielle Thierry-Mieg
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
- 14Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique MathematiqueMontpellierFrance
| | - Jennifer Ashurst
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Libin Jia
- 16National Cancer Institute, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Mitsuteru Nakao
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Michael A Thomas
- 17Department of Biological Sciences, Idaho State UniversityPocatello, IdahoUnited States of America
| | - Nicola Mulder
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Youla Karavidopoulou
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Lihua Jin
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Sangsoo Kim
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | | | - Boris Lenhard
- 19Center for Genomics and Bioinformatics, Karolinska InstitutetStockholmSweden
| | - Eric Eveno
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Yoshiyuki Suzuki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Chisato Yamasaki
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Jun-ichi Takeda
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Craig Gough
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Phillip Hilton
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Yasuyuki Fujii
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Hiroaki Sakai
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 22Tokyo Research Laboratories, Kyowa Hakko Kogyo CompanyTokyoJapan
| | - Susumu Tanaka
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Clara Amid
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Matthew Bellgard
- 24Centre for Bioinformatics and Biological Computing, School of Information Technology, Murdoch UniversityMurdoch, Western AustraliaAustralia
| | - Maria de Fatima Bonaldo
- 25Medical Education and Biomedical Research Facility, University of IowaIowa City, IowaUnited States of America
| | - Hidemasa Bono
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Susan K Bromberg
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | - Anthony J Brookes
- 19Center for Genomics and Bioinformatics, Karolinska InstitutetStockholmSweden
| | - Elspeth Bruford
- 28HUGO Gene Nomenclature Committee, University College LondonLondonUnited Kingdom
| | | | - Claude Chelala
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | - Christine Couillault
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | | | - Marie-Anne Debily
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | | | - Inna Dubchak
- 32Lawrence Berkeley National Laboratory, BerkeleyCaliforniaUnited States of America
| | - Toshinori Endo
- 33Department of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental UniversityTokyoJapan
| | | | - Eduardo Eyras
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Kaoru Fukami-Kobayashi
- 35Bioresource Information Division, RIKEN BioResource Center, RIKEN Tsukuba InstituteIbarakiJapan
| | - Gopal R. Gopinath
- 36Genome Knowledgebase, Cold Spring Harbor LaboratoryCold Spring Harbor, New YorkUnited States of America
| | - Esther Graudens
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Yoonsoo Hahn
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | - Michael Han
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Ze-Guang Han
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
| | - Kousuke Hanada
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideki Hanaoka
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Erimi Harada
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Katsuyuki Hashimoto
- 38Division of Genetic Resources, National Institute of Infectious DiseasesTokyoJapan
| | - Ursula Hinz
- 34Swiss Institute of BioinformaticsGenevaSwitzerland
| | - Momoki Hirai
- 39Graduate School of Frontier Sciences, Department of Integrated Biosciences, University of TokyoChibaJapan
| | - Teruyoshi Hishiki
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Ian Hopkinson
- 41Department of Primary Care and Population Sciences, Royal Free University College Medical School, University College LondonLondonUnited Kingdom
- 42Clinical and Molecular Genetics Unit, The Institute of Child HealthLondonUnited Kingdom
| | - Sandrine Imbeaud
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Hidetoshi Inoko
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Alexander Kanapin
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Yayoi Kaneko
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Takeya Kasukawa
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Janet Kelso
- 44South African National Bioinformatics Institute, University of the Western CapeBellvilleSouth Africa
| | - Paul Kersey
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | | | | | - Bernhard Korn
- 46RZPD Resource Center for Genome ResearchHeidelbergGermany
| | - Vladimir Kuryshev
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Izabela Makalowska
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Takashi Makino
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Shuhei Mano
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Regine Mariage-Samson
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | - Jun Mashima
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideo Matsuda
- 49Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka UniversityOsakaJapan
| | - Hans-Werner Mewes
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Shinsei Minoshima
- 50Medical Photobiology Department, Photon Medical Research Center, Hamamatsu University School of MedicineShizuokaJapan
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | | | - Hideki Nagasaki
- 51Computational Biology Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Naoki Nagata
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Rajni Nigam
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | - Osamu Ogasawara
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | | | - Masafumi Ohtsubo
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | - Norihiro Okada
- 53Department of Biological Sciences, Graduate School of Bioscience and Biotechnology, Tokyo Institute of TechnologyKanagawaJapan
| | - Toshihisa Okido
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Satoshi Oota
- 35Bioresource Information Division, RIKEN BioResource Center, RIKEN Tsukuba InstituteIbarakiJapan
| | - Motonori Ota
- 54Global Scientific Information and Computing Center, Tokyo Institute of TechnologyTokyoJapan
| | - Toshio Ota
- 22Tokyo Research Laboratories, Kyowa Hakko Kogyo CompanyTokyoJapan
| | - Tetsuji Otsuki
- 55Molecular Biology Laboratory, Medicinal Research Laboratories, Taisho Pharmaceutical CompanySaitamaJapan
| | | | - Annemarie Poustka
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Shuang-Xi Ren
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
| | - Naruya Saitou
- 56Department of Population Genetics, National Institute of GeneticsShizuokaJapan
| | - Katsunaga Sakai
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Shigetaka Sakamoto
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Ryuichi Sakate
- 39Graduate School of Frontier Sciences, Department of Integrated Biosciences, University of TokyoChibaJapan
| | - Ingo Schupp
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Florence Servant
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Stephen Sherry
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Rie Shiba
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Nobuyoshi Shimizu
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | - Mary Shimoyama
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | | | - Bento Soares
- 25Medical Education and Biomedical Research Facility, University of IowaIowa City, IowaUnited States of America
| | - Charles Steward
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Makiko Suwa
- 51Computational Biology Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Mami Suzuki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Aiko Takahashi
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Gen Tamiya
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Hiroshi Tanaka
- 33Department of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental UniversityTokyoJapan
| | - Todd Taylor
- 57Human Genome Research Group, Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Joseph D Terwilliger
- 58Columbia University and Columbia Genome CenterNew York, New YorkUnited States of America
| | - Per Unneberg
- 59Department of Biotechnology, Royal Institute of TechnologyStockholmSweden
| | - Vamsi Veeramachaneni
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Shinya Watanabe
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Laurens Wilming
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Norikazu Yasuda
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Hyang-Sook Yoo
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | - Marvin Stodolsky
- 60Biology Division and Genome Task Group, Office of Biological and Environmental Research, United States Department of EnergyWashington, D.CUnited States of America
| | - Wojciech Makalowski
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Mitiko Go
- 61Faculty of Bio-Science, Nagahama Institute of Bio-Science and TechnologyShigaJapan
| | - Kenta Nakai
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Toshihisa Takagi
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Minoru Kanehisa
- 12Bioinformatics Center, Institute for Chemical Research, Kyoto UniversityKyotoJapan
| | - Yoshiyuki Sakaki
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 57Human Genome Research Group, Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - John Quackenbush
- 62Institute for Genomic ResearchRockville, MarylandUnited States of America
| | - Yasushi Okazaki
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Yoshihide Hayashizaki
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Winston Hide
- 44South African National Bioinformatics Institute, University of the Western CapeBellvilleSouth Africa
| | - Ranajit Chakraborty
- 63Center for Genome Information, Department of Environmental Health, University of CincinnatiCincinnati, OhioUnited States of America
| | - Ken Nishikawa
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideaki Sugawara
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Yoshio Tateno
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Zhu Chen
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
- 64State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui-Jin Hospital, Shanghai Second Medical UniversityShanghaiChina
| | | | - Peter Tonellato
- 65PointOne SystemsWauwatosa, WisconsinUnited States of America
| | - Rolf Apweiler
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Kousaku Okubo
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Lukas Wagner
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Stefan Wiemann
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Robert L Strausberg
- 16National Cancer Institute, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Takao Isogai
- 10Reverse Proteomics Research InstituteChibaJapan
- 66Graduate School of Life and Environmental Sciences, University of TsukubaIbarakiJapan
| | - Charles Auffray
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Nobuo Nomura
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Takashi Gojobori
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
- 67Department of Genetics, Graduate University for Advanced StudiesShizuokaJapan
| | - Sumio Sugano
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 68Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of TokyoTokyoJapan
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20
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Vitour D, Lindenbaum P, Vende P, Becker MM, Poncet D. RoXaN, a novel cellular protein containing TPR, LD, and zinc finger motifs, forms a ternary complex with eukaryotic initiation factor 4G and rotavirus NSP3. J Virol 2004; 78:3851-62. [PMID: 15047801 PMCID: PMC374268 DOI: 10.1128/jvi.78.8.3851-3862.2004] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2003] [Accepted: 12/23/2003] [Indexed: 11/20/2022] Open
Abstract
Rotavirus mRNAs are capped but not polyadenylated, and viral proteins are translated by the cellular translation machinery. This is accomplished through the action of the viral nonstructural protein NSP3, which specifically binds the 3' consensus sequence of viral mRNAs and interacts with the eukaryotic translation initiation factor eIF4G I. To further our understanding of the role of NSP3 in rotavirus replication, we looked for other cellular proteins capable of interacting with this viral protein. Using the yeast two-hybrid assay, we identified a novel cellular protein-binding partner for rotavirus NSP3. This 110-kDa cellular protein, named RoXaN (rotavirus X protein associated with NSP3), contains a minimum of three regions predicted to be involved in protein-protein or nucleic acid-protein interactions. A tetratricopeptide repeat region, a protein-protein interaction domain most often found in multiprotein complexes, is present in the amino-terminal region. In the carboxy terminus, at least five zinc finger motifs are observed, further suggesting the capacity of RoXaN to bind other proteins or nucleic acids. Between these two regions exists a paxillin leucine-aspartate repeat (LD) motif which is involved in protein-protein interactions. RoXaN is capable of interacting with NSP3 in vivo and during rotavirus infection. Domains of interaction were mapped and correspond to the dimerization domain of NSP3 (amino acids 163 to 237) and the LD domain of RoXaN (amino acids 244 to 341). The interaction between NSP3 and RoXaN does not impair the interaction between NSP3 and eIF4G I, and a ternary complex made of NSP3, RoXaN, and eIF4G I can be detected in rotavirus-infected cells, implicating RoXaN in translation regulation.
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Affiliation(s)
- Damien Vitour
- Virologie Moléculaire et Structurale, Unité Mixte de Recherche, CNRS-INRA, 91198 Gif-sur-Yvette, France
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21
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Kikuno R, Nagase T, Nakayama M, Koga H, Okazaki N, Nakajima D, Ohara O. HUGE: a database for human KIAA proteins, a 2004 update integrating HUGEppi and ROUGE. Nucleic Acids Res 2004; 32:D502-4. [PMID: 14681467 PMCID: PMC308769 DOI: 10.1093/nar/gkh035] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
We have been developing a Human Unidentified Gene-Encoded (HUGE) protein database (http://www.kazusa.or.jp/huge) to summarize results from sequence analysis of human novel large (>4 kb) cDNAs identified in the Kazusa cDNA sequencing project. At present, HUGE contains 2031 cDNA entries (KIAA cDNAs), for each of which a gene/protein characteristic table has been prepared. Since we have been shifting our research attention from the identification and cloning of novel cDNAs to the functional analysis of the proteins encoded by these cDNAs (KIAA proteins), we have not substantially increased the number of cDNA entries in HUGE for some time. Instead, we have manually curated 451 KIAA cDNAs in order to prepare a set of genetic resources to facilitate the functional analysis of KIAA proteins. In addition, we have updated the contents of the corresponding gene/protein characteristic tables in HUGE and have constructed two subsidiary databases, HUGEppi (http://www. kazusa.or.jp/huge/ppi) and ROUGE (http://www. kazusa.or.jp/rouge), to make available the results from our study of KIAA protein function. HUGEppi shows detailed information on protein-protein interactions detected between 84 pairs of KIAA proteins by yeast two-hybrid screening. ROUGE summarizes the results of computer-assisted analyses of approximately 1000 mouse homologues of human large cDNAs that we identified.
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Affiliation(s)
- Reiko Kikuno
- Kazusa DNA Research Institute, 2-6-7 Kazusa-Kamatari, Kisarazu, Chiba, 292-0818, Japan.
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22
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Quilliam LA, Rebhun JF, Castro AF. A growing family of guanine nucleotide exchange factors is responsible for activation of Ras-family GTPases. PROGRESS IN NUCLEIC ACID RESEARCH AND MOLECULAR BIOLOGY 2003; 71:391-444. [PMID: 12102558 DOI: 10.1016/s0079-6603(02)71047-7] [Citation(s) in RCA: 222] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
GTPases of the Ras subfamily regulate a diverse array of cellular-signaling pathways, coupling extracellular signals to the intracellular response machinery. Guanine nucleotide exchange factors (GEFs) are primarily responsible for linking cell-surface receptors to Ras protein activation. They do this by catalyzing the dissociation of GDP from the inactive Ras proteins. GTP can then bind and induce a conformational change that permits interaction with downstream effectors. Over the past 5 years, approximately 20 novel Ras-family GEFs have been identified and characterized. These data indicate that a variety of different signaling mechanisms can be induced to activate Ras, enabling tyrosine kinases, G-protein-coupled receptors, adhesion molecules, second messengers, and various protein-interaction modules to relocate and/or activate GEFs and elevate intracellular Ras-GTP levels. This review discusses the structure and function of the catalytic or CDC25 homology domain common to almost all Ras-family GEFs. It also details our current knowledge about the regulation and function of this rapidly growing family of enzymes that include Sos1 and 2, GRF1 and 2, CalDAG-GEF/GRP1-4, C3G, cAMP-GEF/Epac 1 and 2, PDZ-GEFs, MR-GEF, RalGDS family members, RalGPS, BCAR3, Smg GDS, and phospholipase C(epsilon).
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Affiliation(s)
- Lawrence A Quilliam
- Department of Biochemistry and Molecular, Biology and Walther Oncology Center, Indiana University School of Medicine, Indianapolis 46202, USA
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23
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Whistler JL, Enquist J, Marley A, Fong J, Gladher F, Tsuruda P, Murray SR, Von Zastrow M. Modulation of postendocytic sorting of G protein-coupled receptors. Science 2002; 297:615-20. [PMID: 12142540 DOI: 10.1126/science.1073308] [Citation(s) in RCA: 252] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Recycling of the mu opioid receptor to the plasma membrane after endocytosis promotes rapid resensitization of signal transduction, whereas targeting of the delta opioid receptor (DOR) to lysosomes causes proteolytic down-regulation. We identified a protein that binds preferentially to the cytoplasmic tail of the DOR as a candidate heterotrimeric GTP-binding protein (G protein)-coupled receptor-associated sorting protein (GASP). Disruption of the DOR-GASP interaction through receptor mutation or overexpression of a dominant negative fragment of GASP inhibited receptor trafficking to lysosomes and promoted recycling. The GASP family of proteins may modulate lysosomal sorting and functional down-regulation of a variety of G protein-coupled receptors.
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Affiliation(s)
- Jennifer L Whistler
- Department of Neurology, Ernest Gallo Clinic and Research Center, University of California, San Francisco, Emeryville, CA 94608, USA.
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24
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Cao W, Mattagajasingh SN, Xu H, Kim K, Fierlbeck W, Deng J, Lowenstein CJ, Ballermann BJ. TIMAP, a novel CAAX box protein regulated by TGF-beta1 and expressed in endothelial cells. Am J Physiol Cell Physiol 2002; 283:C327-37. [PMID: 12055102 DOI: 10.1152/ajpcell.00442.2001] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Representational difference analysis of the glomerular endothelial cell response to transforming growth factor-beta1 (TGF-beta1) revealed a novel gene, TIMAP (TGF-beta-inhibited membrane-associated protein), which contains 10 exons and maps to human chromosome 20.q11.22. By Northern blot, TIMAP mRNA is highly expressed in all cultured endothelial and hematopoietic cells. The frequency of the TIMAP SAGE tag is much greater in endothelial cell SAGE databases than in nonendothelial cells. Immunofluorescence studies of rat tissues show that anti-TIMAP antibodies localize to vascular endothelium. TGF-beta1 represses TIMAP through a protein synthesis- and histone deacetylase-dependent process. The TIMAP protein contains five ankyrin repeats, a protein phosphatase-1 (PP1)-interacting domain, a COOH-terminal CAAX box, a domain arrangement similar to that of MYPT3, and a PP1 inhibitor. A green fluorescent protein-TIMAP fusion protein localized to the plasma membrane in a CAAX box-dependent fashion. Hence, TIMAP is a novel gene highly expressed in endothelial and hematopoietic cells and regulated by TGF-beta1. On the basis of its domain structure, TIMAP may serve a signaling function, potentially through interaction with PP1.
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Affiliation(s)
- Wangsen Cao
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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25
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Abstract
Protein tyrosine phosphatases (PTPs) are a diverse group of enzymes that contain a highly conserved active site motif, Cys-x5-Arg (Cx5R). The PTP superfamily enzymes, which include tyrosine-specific, dual specificity, low-molecular-weight, and Cdc25 phosphatases, are key mediators of a wide variety of cellular processes, including growth, metabolism, differentiation, motility, and programmed cell death. The PTEN/MMAC1/TEP1 gene was originally identified as a candidate tumor suppressor gene located on human chromosome 10q23; it encodes a protein with sequence similarity to PTPs and tensin. Recent studies have demonstrated that PTEN plays an essential role in regulating signaling pathways involved in cell growth and apoptosis, and mutations in the PTEN gene are now known to cause tumorigenesis in a number of human tissues. In addition, germ line mutations in the PTEN gene also play a major role in the development of Cowden and Bannayan-Zonana syndromes, in which patients often suffer from increased risk of breast and thyroid cancers. Biochemical studies of the PTEN phosphatase have revealed a molecular mechanism by which tumorigenesis may be caused in individuals with PTEN mutations. Unlike most members of the PTP superfamily, PTEN utilizes the phosphoinositide second messenger, phosphatidylinositol 3,4,5-trisphosphate (PIP3), as its physiologic substrate. This inositol lipid is an important regulator of cell growth and survival signaling through the Ser/Thr protein kinases PDK1 and Akt. By specifically dephosphorylating the D3 position of PIP3, the PTEN tumor suppressor functions as a negative regulator of signaling processes downstream of this lipid second messenger. Mutations that impair PTEN function result in a marked increase in cellular levels of PIP3 and constitutive activation of Akt survival signaling pathways, leading to inhibition of apoptosis, hyperplasia, and tumor formation. Certain structural features of PTEN contribute to its specificity for PIP3, as well as its role(s) in regulating cellular proliferation and apoptosis. Recently, myotubularin, a second PTP superfamily enzyme associated with human disease, has also been shown to utilize a phosphoinositide as its physiologic substrate.
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Affiliation(s)
- T Maehama
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, Michigan 48109-0606, USA.
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26
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De Toledo M, Colombo K, Nagase T, Ohara O, Fort P, Blangy A. The yeast exchange assay, a new complementary method to screen for Dbl-like protein specificity: identification of a novel RhoA exchange factor. FEBS Lett 2000; 480:287-92. [PMID: 11034346 DOI: 10.1016/s0014-5793(00)01953-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The target Rho GTPases of many guanine nucleotide exchange factors (GEFs) of the Dbl family remain to be identified. Here we report a new method: the yeast exchange assay (YEA), a rapid qualitative test to perform a wide range screen for GEF specificity. In this assay based on the two-hybrid system, a wild type GTPase binds to its effector only after activation by a specific GEF. We validated the YEA by activating GTPases by previously reported GEFs. We further established that a novel GEF, GEF337, activates RhoA in the YEA. GEF337 promoted nucleotide exchange on RhoA in vitro and promoted F-actin stress fiber assembly in fibroblasts, characteristic of RhoA activation.
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Affiliation(s)
- M De Toledo
- Centre de Recherches en Biochimie Macromoléculaire, CNRS UPR 1086, Montpellier, France
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27
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Taylor GS, Maehama T, Dixon JE. Myotubularin, a protein tyrosine phosphatase mutated in myotubular myopathy, dephosphorylates the lipid second messenger, phosphatidylinositol 3-phosphate. Proc Natl Acad Sci U S A 2000; 97:8910-5. [PMID: 10900271 PMCID: PMC16795 DOI: 10.1073/pnas.160255697] [Citation(s) in RCA: 260] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The lipid second messenger phosphatidylinositol 3-phosphate [PI(3)P] plays a crucial role in intracellular membrane trafficking. We report here that myotubularin, a protein tyrosine phosphatase required for muscle cell differentiation, is a potent PI(3)P phosphatase. Recombinant human myotubularin specifically dephosphorylates PI(3)P in vitro. Overexpression of a catalytically inactive substrate-trapping myotubularin mutant (C375S) in human 293 cells increases PI(3)P levels relative to that of cells overexpressing the wild-type enzyme, demonstrating that PI(3)P is a substrate for myotubularin in vivo. In addition, a Saccharomyces cerevisiae strain in which the myotubularin-like gene (YJR110w) is disrupted also exhibits increased PI(3)P levels. Both the recombinant yeast enzyme and a human myotubularin-related protein (KIAA0371) are able to dephosphorylate PI(3)P in vitro, suggesting that this activity is intrinsic to all myotubularin family members. Mutations in the MTM1 gene that cause human myotubular myopathy dramatically reduce the ability of the phosphatase to dephosphorylate PI(3)P. Our findings provide evidence that myotubularin exerts its effects during myogenesis by regulating cellular levels of the inositol lipid PI(3)P.
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Affiliation(s)
- G S Taylor
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI 48109-0606, USA
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Kelkar N, Gupta S, Dickens M, Davis RJ. Interaction of a mitogen-activated protein kinase signaling module with the neuronal protein JIP3. Mol Cell Biol 2000; 20:1030-43. [PMID: 10629060 PMCID: PMC85220 DOI: 10.1128/mcb.20.3.1030-1043.2000] [Citation(s) in RCA: 245] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The c-Jun NH(2)-terminal kinase (JNK) group of mitogen-activated protein kinases (MAPKs) is activated in response to the treatment of cells with inflammatory cytokines and by exposure to environmental stress. JNK activation is mediated by a protein kinase cascade composed of a MAPK kinase and a MAPK kinase kinase. Here we describe the molecular cloning of a putative molecular scaffold protein, JIP3, that binds the protein kinase components of a JNK signaling module and facilitates JNK activation in cultured cells. JIP3 is expressed in the brain and at lower levels in the heart and other tissues. Immunofluorescence analysis demonstrated that JIP3 was present in the cytoplasm and accumulated in the growth cones of developing neurites. JIP3 is a member of a novel class of putative MAPK scaffold proteins that may regulate signal transduction by the JNK pathway.
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Affiliation(s)
- N Kelkar
- Howard Hughes Medical Institute, Program in Molecular Medicine, Department of Biochemistry, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA
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Kikuno R, Nagase T, Suyama M, Waki M, Hirosawa M, Ohara O. HUGE: a database for human large proteins identified in the Kazusa cDNA sequencing project. Nucleic Acids Res 2000; 28:331-2. [PMID: 10592264 PMCID: PMC102416 DOI: 10.1093/nar/28.1.331] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
HUGE is a database for human large proteins newly identified in the Kazusa cDNA project, the aim of which is to predict the primary structure of proteins from the sequences of human large cDNAs (>4 kb). In particular, cDNA clones capable of coding for large proteins (>50 kDa) are the current targets of the project. HUGE contains >1100 cDNA sequences and detailed information obtained through analysis of the sequences of cDNAs and the predicted proteins. Besides an increase in the number of cDNA entries, the amount of experimental data for expression profiling has been largely increased and data on chromosomal locations have been newly added. All of the protein-coding regions were examined by GeneMark analysis, and the results of a motif/domain search of each predicted protein sequence against the Pfam database have been newly added. HUGE is available through the WWW at http://www.kazusa.or.jp/huge
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Affiliation(s)
- R Kikuno
- Kazusa DNA Research Institute, 1532-3 Yana, Kisarazu, Chiba 292-0812, Japan.
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