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      Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance

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          Abstract

          Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. ‘Diversity Outbred in Australia (DOz)’ is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle’s contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            NIH Image to ImageJ: 25 years of image analysis

            For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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              The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences

              The PRoteomics IDEntifications (PRIDE) database ( https://www.ebi.ac.uk/pride/ ) is the world's largest data repository of mass spectrometry-based proteomics data. PRIDE is one of the founding members of the global ProteomeXchange (PX) consortium and an ELIXIR core data resource. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2019. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 500 datasets per month during 2021. In addition to continuous improvements in PRIDE Archive data pipelines and infrastructure, the PRIDE Spectra Archive has been developed to provide direct access to the submitted mass spectra using Universal Spectrum Identifiers. As a key point, the file format MAGE-TAB for proteomics has been developed to enable the improvement of sample metadata annotation. Additionally, the resource PRIDE Peptidome provides access to aggregated peptide/protein evidences across PRIDE Archive. Furthermore, we will describe how PRIDE has increased its efforts to reuse and disseminate high-quality proteomics data into other added-value resources such as UniProt, Ensembl and Expression Atlas.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                26 July 2023
                2023
                : 12
                : RP86961
                Affiliations
                [1 ] Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney ( https://ror.org/0384j8v12) Camperdown Australia
                [2 ] Australian Proteome Analysis Facility, Macquarie University ( https://ror.org/01sf06y89) Macquarie Park Australia
                [3 ] School of Medicine, Deakin University ( https://ror.org/02czsnj07) Geelong Australia
                [4 ] Centre for Diabetes Research, Harry Perkins Institute of Medical Research ( https://ror.org/02xz7d723) Murdoch Australia
                [5 ] School of Medical Sciences University of Sydney ( https://ror.org/0384j8v12) Sydney Australia
                Max Planck Institute for Biology Tübingen ( https://ror.org/0243gzr89) Germany
                Max Planck Institute for Biology Tübingen ( https://ror.org/0243gzr89) Germany
                Max Planck Institute for Biology Tübingen Germany
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                Macquarie University Sydney Australia
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                Deakin University Geelong Australia
                University of Sydney Sydney Australia
                Harry Perkins Institute of Medical Research Perth Australia
                University of Sydney Sydney Australia
                University of Sydney Sydney Australia
                Author information
                https://orcid.org/0000-0003-4514-7009
                https://orcid.org/0000-0002-2074-8599
                https://orcid.org/0000-0002-6758-4763
                https://orcid.org/0000-0003-0012-2529
                https://orcid.org/0000-0001-5946-5257
                Article
                86961
                10.7554/eLife.86961
                10371229
                37494090
                267ed175-c9e4-43a9-a639-c9d6a1360bd1
                © 2023, Masson et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 01 March 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000923, Australian Research Council;
                Award ID: Laureate Fellowship
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Computational and Systems Biology
                Custom metadata
                A pharmacological approach for the validation of systems genetics data in the context of insulin resistance.
                prc

                Life sciences
                skeletal muscle,insulin resistance,diversity outbred,thiostrepton,drug repurposing,mouse
                Life sciences
                skeletal muscle, insulin resistance, diversity outbred, thiostrepton, drug repurposing, mouse

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