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      Kelch Domain of Gigaxonin Interacts with Intermediate Filament Proteins Affected in Giant Axonal Neuropathy

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          Abstract

          Patients with giant axonal neuropathy (GAN) show progressive loss of motor and sensory function starting in childhood and typically live for less than 30 years. GAN is caused by autosomal recessive mutations leading to low levels of gigaxonin (GIG), a ubiquitously-expressed BTB/Kelch cytoplasmic protein believed to be an E3 ligase substrate adaptor. GAN pathology is characterized by aggregates of intermediate filaments (IFs) in multiple tissues. To delineate the molecular pathway between GIG deficiency and IF pathology, we undertook a proteomic screen to identify the normal binding partners of GIG. Prominent among them were several classes of IFs, including the neurofilament subunits whose accumulation leads to the axonal swellings for which GAN is named. We showed these interactions were dependent on the Kelch domain of GIG. Furthermore, we identified the E3 ligase MYCBP2 and the heat shock proteins HSP90AA1/AB1 as interactors with the BTB domain that may result in the ubiquitination and subsequent degradation of intermediate filaments. Our open-ended proteomic screen provides support to GIG’s role as an adaptor protein, linking IF proteins through its Kelch domain to the ubiquitin pathway proteins via its BTB domain, and points to future approaches for reversing the phenotype in human patients.

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          Most cited references27

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            The CRAPome: a Contaminant Repository for Affinity Purification Mass Spectrometry Data

            Affinity purification coupled with mass spectrometry (AP-MS) is now a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (e.g. proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. While the standard approach is to identify nonspecific interactions using one or more negative controls, most small-scale AP-MS studies do not capture a complete, accurate background protein set. Fortunately, negative controls are largely bait-independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the Contaminant Repository for Affinity Purification (the CRAPome) and describe the use of this resource to score protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely available online at www.crapome.org.
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              Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics.

              Dynamic reorganization of signaling systems frequently accompanies pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex absolute quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules, whereas only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. Copyright © 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 October 2015
                2015
                : 10
                : 10
                : e0140157
                Affiliations
                [1 ]Project A.L.S./Jenifer Estess Laboratory for Stem Cell Research, New York, New York, United States of America
                [2 ]Center for Motor Neuron Biology and Disease, Columbia University Medical Center, New York, New York, United States of America
                [3 ]Departments of Pathology and Cell Biology, Neurology, and Neuroscience, Columbia University Medical Center, New York, New York, United States of America
                [4 ]Columbia Stem Cell Initiative, Columbia University Medical Center, New York, New York, United States of America
                [5 ]Collaborations in Chemistry, Fuquay-Varina, North Carolina, United States of America
                University of Vienna, Max F. Perutz Laboratories, AUSTRIA
                Author notes

                Competing Interests: S.E. consults for Hannah’s Hope Fund. All other authors indicate no potential conflicts of interest. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: BJK HW. Performed the experiments: BJK AGD. Analyzed the data: BJK HW SE. Contributed reagents/materials/analysis tools: BJK AGD. Wrote the paper: BJK HW SE.

                Article
                PONE-D-15-28276
                10.1371/journal.pone.0140157
                4604155
                26460568
                4e38b229-1298-4f61-adc0-a94edc2aa6e2
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 28 June 2015
                : 22 September 2015
                Page count
                Figures: 4, Tables: 0, Pages: 12
                Funding
                This work was supported by Hannah’s Hope Fund, Project A.L.S, and New York Stem Cell Foundation NYSTEM (CO24415). B.J.K. is supported by an F31 grant from National Institute of Neurological Disorders and Stroke NINDS (NS077544-01A1) and a Hearst Scholarship.
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                Research Article
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                All relevant data are within the paper and its Supporting Information files.

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