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      A Comprehensive Subcellular Atlas of the Toxoplasma Proteome via hyperLOPIT Provides Spatial Context for Protein Functions

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          Summary

          Apicomplexan parasites cause major human disease and food insecurity. They owe their considerable success to highly specialized cell compartments and structures. These adaptations drive their recognition, nondestructive penetration, and elaborate reengineering of the host’s cells to promote their growth, dissemination, and the countering of host defenses. The evolution of unique apicomplexan cellular compartments is concomitant with vast proteomic novelty. Consequently, half of apicomplexan proteins are unique and uncharacterized. Here, we determine the steady-state subcellular location of thousands of proteins simultaneously within the globally prevalent apicomplexan parasite Toxoplasma gondii. This provides unprecedented comprehensive molecular definition of these unicellular eukaryotes and their specialized compartments, and these data reveal the spatial organizations of protein expression and function, adaptation to hosts, and the underlying evolutionary trajectories of these pathogens.

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          Highlights

          • Using hyperLOPIT, Toxoplasma proteins were assigned to their cell location

          • Complex proteomes associated with host interaction and adaptation are identified

          • The atlas reveals sites and chronology of cell evolution of apicomplexan parasitism

          • Cell spatial organization corelates with regulatory and biochemical programs

          Abstract

          Apicomplexan proteomes are substantially specific to these parasites, and many cellular compartments are highly specialized. Using spatial proteomic methods, Barylyuk et al. simultaneously map the locations of thousands of Toxoplasma proteins, resolving the genomic complexity of this pathogen within the context of its cell organelles, compartments, and structures.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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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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              Inference from Iterative Simulation Using Multiple Sequences

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                Author and article information

                Contributors
                Journal
                Cell Host Microbe
                Cell Host Microbe
                Cell Host & Microbe
                Cell Press
                1931-3128
                1934-6069
                11 November 2020
                11 November 2020
                : 28
                : 5
                : 752-766.e9
                Affiliations
                [1 ]Department of Biochemistry, University of Cambridge, Cambridge CB2 1QW, UK
                [2 ]Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB20 0AW, UK
                [3 ]MRC Biostatistics Unit, Cambridge Institute for Public Health, Cambridge CB2 0SR, UK
                [4 ]Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
                [5 ]MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
                [6 ]Global Station for Zoonosis Control, Gi-CoRE, Hokkaido University, Sapporo 060-0808, Japan
                [7 ]Nuffield Division of Clinical Laboratory Sciences (NDCLS), University of Oxford, Oxford OX3 9DU, UK
                Author notes
                []Corresponding author kb601@ 123456cam.ac.uk
                [∗∗ ]Corresponding author rfw26@ 123456cam.ac.uk
                [8]

                Lead Contact

                Article
                S1931-3128(20)30514-X
                10.1016/j.chom.2020.09.011
                7670262
                33053376
                2207f5ee-dedf-4a03-8c80-0d176da415d5
                © 2020 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 11 May 2020
                : 30 July 2020
                : 15 September 2020
                Categories
                Resource

                Microbiology & Virology
                apicomplexa,toxoplasma,plasmodium,proteomics,subcellular,organelle,parasitism,invasion,host-pathogen interaction,evolution

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