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Astrin-SKAP Complex Reconstitution Reveals Its Kinetochore
RESEARCH ARTICLE Astrin-SKAP complex reconstitution reveals its kinetochore interaction with microtubule-bound Ndc80 David M Kern1,2, Julie K Monda1,2†, Kuan-Chung Su1†, Elizabeth M Wilson-Kubalek3, Iain M Cheeseman1,2* 1Whitehead Institute for Biomedical Research, Cambridge, United States; 2Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; 3Department of Cell Biology, The Scripps Research Institute, La Jolla, United States Abstract Chromosome segregation requires robust interactions between the macromolecular kinetochore structure and dynamic microtubule polymers. A key outstanding question is how kinetochore-microtubule attachments are modulated to ensure that bi-oriented attachments are selectively stabilized and maintained. The Astrin-SKAP complex localizes preferentially to properly bi-oriented sister kinetochores, representing the final outer kinetochore component recruited prior to anaphase onset. Here, we reconstitute the 4-subunit Astrin-SKAP complex, including a novel MYCBP subunit. Our work demonstrates that the Astrin-SKAP complex contains separable kinetochore localization and microtubule binding domains. In addition, through cross-linking analysis in human cells and biochemical reconstitution, we show that the Astrin-SKAP complex binds synergistically to microtubules with the Ndc80 complex to form an integrated interface. We propose a model in which the Astrin-SKAP complex acts together with the Ndc80 complex to stabilize correctly formed kinetochore-microtubule interactions. *For correspondence: DOI: https://doi.org/10.7554/eLife.26866.001 [email protected] †These authors contributed equally to this work Introduction Competing interests: The The macromolecular kinetochore complex links chromosomes to dynamic microtubule polymers and authors declare that no harnesses the forces generated by microtubule growth and depolymerization to facilitate accurate competing interests exist. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Scaffolding During the Cell Cycle by A-Kinase Anchoring Proteins
Pflugers Arch - Eur J Physiol DOI 10.1007/s00424-015-1718-0 INVITED REVIEW Scaffolding during the cell cycle by A-kinase anchoring proteins B. Han1,2 & W. J. Poppinga1,2 & M. Schmidt1,2 Received: 12 May 2015 /Revised: 28 June 2015 /Accepted: 1 July 2015 # The Author(s) 2015. This article is published with open access at Springerlink.com Abstract Cell division relies on coordinated regulation of the specific AKAP subset in relation to diseases with focus on a cell cycle. A process including a well-defined series of strictly diverse subset of cancer. regulated molecular mechanisms involving cyclin-dependent kinases, retinoblastoma protein, and polo-like kinases. Dys- Keywords AKAPs . Scaffolding . Cell cycle . Proliferation . functions in cell cycle regulation are associated with disease Cancer such as cancer, diabetes, and neurodegeneration. Compart- mentalization of cellular signaling is a common strategy used to ensure the accuracy and efficiency of cellular responses. Introduction Compartmentalization of intracellular signaling is maintained by scaffolding proteins, such as A-kinase anchoring proteins The growth of organisms is driven by cell division which (AKAPs). AKAPs are characterized by their ability to anchor relies on coordinated regulation of phases in cell cycle [4]. the regulatory subunits of protein kinase A (PKA), and there- When the cell is quiescent, it remains in the G1 phase; how- by achieve guidance to different cellular locations via various ever, on initiation of cell division, it progresses into the S targeting domains. Next to PKA, AKAPs also associate with phase, during which DNA replication occurs, followed by a several other signaling elements including receptors, ion chan- separation of sister chromatids during the M phase, which in nels, protein kinases, phosphatases, small GTPases, and phos- turn is again separated in the pro-, meta-, ana-, and telophase, phodiesterases. -
A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug- Repurposing
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.22.002386; this version posted March 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug- Repurposing David E. Gordon1,2,3,4, Gwendolyn M. Jang1,2,3,4, Mehdi Bouhaddou1,2,3,4, Jiewei Xu1,2,3,4, Kirsten Obernier1,2,3,4, Matthew J. O'Meara5, Jeffrey Z. Guo1,2,3,4, Danielle L. Swaney1,2,3,4, Tia A. Tummino1,2,6, Ruth Huettenhain1,2,3,4, Robyn Kaake1,2,3,4, Alicia L. Richards1,2,3,4, Beril Tutuncuoglu1,2,3,4, Helene Foussard1,2,3,4, Jyoti Batra1,2,3,4, Kelsey Haas1,2,3,4, Maya Modak1,2,3,4, Minkyu Kim1,2,3,4, Paige Haas1,2,3,4, Benjamin J. Polacco1,2,3,4, Hannes Braberg1,2,3,4, Jacqueline M. Fabius1,2,3,4, Manon Eckhardt1,2,3,4, Margaret Soucheray1,2,3,4, Melanie J. Bennett1,2,3,4, Merve Cakir1,2,3,4, Michael J. McGregor1,2,3,4, Qiongyu Li1,2,3,4, Zun Zar Chi Naing1,2,3,4, Yuan Zhou1,2,3,4, Shiming Peng1,2,6, Ilsa T. Kirby1,4,7, James E. Melnyk1,4,7, John S. Chorba1,4,7, Kevin Lou1,4,7, ShiZhong A. Dai1,4,7, Wenqi Shen1,4,7, Ying Shi1,4,7, Ziyang Zhang1,4,7, Inigo Barrio-HernandeZ8, Danish Memon8, Claudia Hernandez-Armenta8, Christopher J.P. -
A SARS-Cov-2 Protein Interaction Map Reveals Targets for Drug Repurposing
Article A SARS-CoV-2 protein interaction map reveals targets for drug repurposing https://doi.org/10.1038/s41586-020-2286-9 A list of authors and affiliations appears at the end of the paper Received: 23 March 2020 Accepted: 22 April 2020 A newly described coronavirus named severe acute respiratory syndrome Published online: 30 April 2020 coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than Check for updates 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efcacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and eforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identifed the human proteins that physically associated with each of the SARS-CoV-2 proteins using afnity-purifcation mass spectrometry, identifying 332 high-confdence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. -
Dema and Faust Et Al., Suppl. Material 2020.02.03
Supplementary Materials Cyclin-dependent kinase 18 controls trafficking of aquaporin-2 and its abundance through ubiquitin ligase STUB1, which functions as an AKAP Dema Alessandro1,2¶, Dörte Faust1¶, Katina Lazarow3, Marc Wippich3, Martin Neuenschwander3, Kerstin Zühlke1, Andrea Geelhaar1, Tamara Pallien1, Eileen Hallscheidt1, Jenny Eichhorst3, Burkhard Wiesner3, Hana Černecká1, Oliver Popp1, Philipp Mertins1, Gunnar Dittmar1, Jens Peter von Kries3, Enno Klussmann1,4* ¶These authors contributed equally to this work 1Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert- Rössle-Strasse 10, 13125 Berlin, Germany 2current address: University of California, San Francisco, 513 Parnassus Avenue, CA 94122 USA 3Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Strasse 10, 13125 Berlin, Germany 4DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Oudenarder Strasse 16, 13347 Berlin, Germany *Corresponding author Enno Klussmann Max Delbrück Center for Molecular Medicine Berlin in the Helmholtz Association (MDC) Robert-Rössle-Str. 10, 13125 Berlin Germany Tel. +49-30-9406 2596 FAX +49-30-9406 2593 E-mail: [email protected] 1 Content 1. CELL-BASED SCREENING BY AUTOMATED IMMUNOFLUORESCENCE MICROSCOPY 3 1.1 Screening plates 3 1.2 Image analysis using CellProfiler 17 1.4 Identification of siRNA affecting cell viability 18 1.7 Hits 18 2. SUPPLEMENTARY TABLE S4, FIGURES S2-S4 20 2 1. Cell-based screening by automated immunofluorescence microscopy 1.1 Screening plates Table S1. Genes targeted with the Mouse Protein Kinases siRNA sub-library. Genes are sorted by plate and well. Accessions refer to National Center for Biotechnology Information (NCBI, BLA) entries. The siRNAs were arranged on three 384-well microtitre platres. -
Structural Analysis of SARS-Cov-2 and Predictions of the Human Interactome
A. Vandelli et al. Structure and interactions of SARS-CoV-2 Structural analysis of SARS-CoV-2 and predictions of the human interactome Andrea Vandelli1,2, Michele Monti1,3, Edoardo Milanetti4,5, Jakob Rupert 6, Elsa Zacco3, Elias Bechara1,3, Riccardo Delli Ponti 7,* and Gian Gaetano Tartaglia 1,3,6,8,* 1 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain 2 Systems Biology of Infection Lab, Department of Biochemistry and Molecular Biology, Biosciences Faculty, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain 3 Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genoa, Italy. 4 Department of Physics, Sapienza University, Piazzale Aldo Moro 5, 00185, Rome, Italy 5 Center for Life Nanoscience, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161, Rome, Italy 6 Department of Biology ‘Charles Darwin’, Sapienza University of Rome, P.le A. Moro 5, Rome 00185, Italy 7 School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore 8 Institucio Catalana de Recerca i Estudis Avançats (ICREA), 23 Passeig Lluis Companys, 08010 Barcelona, Spain *to whom correspondence should be addressed to: [email protected] (RDP) and [email protected] or [email protected] (GGT) ABSTRACT Specific elements of viral genomes regulate interactions within host cells. Here, we calculated the secondary structure content of >2500 coronaviruses and computed >100000 human protein interactions with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We found that the 3’ and 5’ are the most structured elements in the viral genome and the 5’ has the strongest propensity to associate with human proteins. -
Analysis of Genomic Regions of Increased Gene Expression (RIDGE)S in Immune Activation
Analysis of genomic Regions of IncreaseD Gene Expression (RIDGE)s in immune activation Lena Hansson Doctor of Philosophy Institute for Adaptive and Neural Computation School of Informatics and Division of Pathway Medicine Medical School University of Edinburgh 2009 Abstract A RIDGE (Region of IncreaseD Gene Expression), as defined by previous studies, is a con- secutive set of active genes on a chromosome that span a region around 110 kbp long. This study investigated RIDGE formation by focusing on the well-defined, immunological impor- tant MHC locus. Macrophages were assayed for gene expression levels using the Affymetrix MG-U74Av2 chip are were either 1) uninfected, 2) primed with IFN-g, 3) viral activated with mCMV, or 4) both primed and viral activated. Gene expression data from these conditions was studied using data structures and new software developed for the visualisation and handling of structured functional genomic data. Specifically, the data was used to study RIDGE structures and investigate whether physically linked genes were also functionally related, and exhibited co-expression and potentially co-regulation. A greater number of RIDGEs with a greater number of members than expected by chance were found. Observed RIDGEs featured functional associations between RIDGE members (mainly explored via GO, UniProt, and Ingenuity), shared upstream control elements (via PROMO, TRANSFAC, and ClustalW), and similar gene expression profiles. Furthermore RIDGE formation cannot be explained by sequence duplication events alone. When the analysis was extended to the entire mouse genome, it became apparent that known genomic loci (for example the protocadherin loci) were more likely to contain more and longer RIDGEs. -
The RNA-Binding Protein AKAP8 Suppresses Tumor Metastasis by Antagonizing EMT-Associated Alternative Splicing
ARTICLE https://doi.org/10.1038/s41467-020-14304-1 OPEN The RNA-binding protein AKAP8 suppresses tumor metastasis by antagonizing EMT-associated alternative splicing Xiaohui Hu1,2,4, Samuel E. Harvey1,2,4, Rong Zheng1,2, Jingyi Lyu1,2, Caitlin L. Grzeskowiak2, Emily Powell3, Helen Piwnica-Worms 3, Kenneth L. Scott2 & Chonghui Cheng 1,2* – 1234567890():,; Alternative splicing has been shown to causally contribute to the epithelial mesenchymal transition (EMT) and tumor metastasis. However, the scope of splicing factors that govern alternative splicing in these processes remains largely unexplored. Here we report the identification of A-Kinase Anchor Protein (AKAP8) as a splicing regulatory factor that impedes EMT and breast cancer metastasis. AKAP8 not only is capable of inhibiting splicing activity of the EMT-promoting splicing regulator hnRNPM through protein–protein interac- tion, it also directly binds to RNA and alters splicing outcomes. Genome-wide analysis shows that AKAP8 promotes an epithelial cell state splicing program. Experimental manipulation of an AKAP8 splicing target CLSTN1 revealed that splice isoform switching of CLSTN1 is crucial for EMT. Moreover, AKAP8 expression and the alternative splicing of CLSTN1 predict breast cancer patient survival. Together, our work demonstrates the essentiality of RNA metabolism that impinges on metastatic breast cancer. 1 Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA. 2 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA. 3 Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 4These authors contributed equally: Xiaohui Hu, Samuel E. -
Extensive Cargo Identification Reveals Distinct Biological Roles of the 12 Importin Pathways Makoto Kimura1,*, Yuriko Morinaka1
1 Extensive cargo identification reveals distinct biological roles of the 12 importin pathways 2 3 Makoto Kimura1,*, Yuriko Morinaka1, Kenichiro Imai2,3, Shingo Kose1, Paul Horton2,3, and Naoko 4 Imamoto1,* 5 6 1Cellular Dynamics Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan 7 2Artificial Intelligence Research Center, and 3Biotechnology Research Institute for Drug Discovery, 8 National Institute of Advanced Industrial Science and Technology (AIST), AIST Tokyo Waterfront 9 BIO-IT Research Building, 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan 10 11 *For correspondence: [email protected] (M.K.); [email protected] (N.I.) 12 13 Editorial correspondence: Naoko Imamoto 14 1 15 Abstract 16 Vast numbers of proteins are transported into and out of the nuclei by approximately 20 species of 17 importin-β family nucleocytoplasmic transport receptors. However, the significance of the multiple 18 parallel transport pathways that the receptors constitute is poorly understood because only limited 19 numbers of cargo proteins have been reported. Here, we identified cargo proteins specific to the 12 20 species of human import receptors with a high-throughput method that employs stable isotope 21 labeling with amino acids in cell culture, an in vitro reconstituted transport system, and quantitative 22 mass spectrometry. The identified cargoes illuminated the manner of cargo allocation to the 23 receptors. The redundancies of the receptors vary widely depending on the cargo protein. Cargoes 24 of the same receptor are functionally related to one another, and the predominant protein groups in 25 the cargo cohorts differ among the receptors. Thus, the receptors are linked to distinct biological 26 processes by the nature of their cargoes. -
Interactome Analyses Revealed That the U1 Snrnp Machinery Overlaps
www.nature.com/scientificreports OPEN Interactome analyses revealed that the U1 snRNP machinery overlaps extensively with the RNAP II Received: 12 April 2018 Accepted: 24 May 2018 machinery and contains multiple Published: xx xx xxxx ALS/SMA-causative proteins Binkai Chi1, Jeremy D. O’Connell1,2, Tomohiro Yamazaki1, Jaya Gangopadhyay1, Steven P. Gygi1 & Robin Reed1 Mutations in multiple RNA/DNA binding proteins cause Amyotrophic Lateral Sclerosis (ALS). Included among these are the three members of the FET family (FUS, EWSR1 and TAF15) and the structurally similar MATR3. Here, we characterized the interactomes of these four proteins, revealing that they largely have unique interactors, but share in common an association with U1 snRNP. The latter observation led us to analyze the interactome of the U1 snRNP machinery. Surprisingly, this analysis revealed the interactome contains ~220 components, and of these, >200 are shared with the RNA polymerase II (RNAP II) machinery. Among the shared components are multiple ALS and Spinal muscular Atrophy (SMA)-causative proteins and numerous discrete complexes, including the SMN complex, transcription factor complexes, and RNA processing complexes. Together, our data indicate that the RNAP II/U1 snRNP machinery functions in a wide variety of molecular pathways, and these pathways are candidates for playing roles in ALS/SMA pathogenesis. Te neurodegenerative disease Amyotrophic Lateral Sclerosis (ALS) has no known treatment, and elucidation of disease mechanisms is urgently needed. Tis problem has been especially daunting, as mutations in greater than 30 genes are ALS-causative, and these genes function in numerous cellular pathways1. Tese include mitophagy, autophagy, cytoskeletal dynamics, vesicle transport, DNA damage repair, RNA dysfunction, apoptosis, and pro- tein aggregation2–6.