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      Identification of two pathways mediating protein targeting from ER to lipid droplets

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          Abstract

          Pathways localizing proteins to their sites of action are essential for eukaryotic cell organization and function. Although mechanisms of protein targeting to many organelles have been defined, how proteins, such as metabolic enzymes, target from the endoplasmic reticulum (ER) to cellular lipid droplets (LDs) is poorly understood. Here we identify two distinct pathways for ER-to-LD protein targeting: early targeting at LD formation sites during formation, and late targeting to mature LDs after their formation. Using systematic, unbiased approaches in Drosophila cells, we identified specific membrane-fusion machinery, including regulators, a tether and SNARE proteins, that are required for the late targeting pathway. Components of this fusion machinery localize to LD–ER interfaces and organize at ER exit sites. We identified multiple cargoes for early and late ER-to-LD targeting pathways. Our findings provide a model for how proteins target to LDs from the ER either during LD formation or by protein-catalysed formation of membrane bridges.

          Abstract

          Song et al. identify two protein-targeting pathways from the endoplasmic reticulum to (1) early lipid droplets (LDs) and (2) mature lipid droplets. They define key factors mediating the second, late pathway and its many cargoes.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

            Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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              Complex heatmaps reveal patterns and correlations in multidimensional genomic data.

              Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.
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                Author and article information

                Contributors
                robert@hsph.harvard.edu
                twalther@hsph.harvard.edu
                Journal
                Nat Cell Biol
                Nat Cell Biol
                Nature Cell Biology
                Nature Publishing Group UK (London )
                1465-7392
                1476-4679
                1 September 2022
                1 September 2022
                2022
                : 24
                : 9
                : 1364-1377
                Affiliations
                [1 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Molecular Metabolism, , Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [2 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Cell Biology, , Harvard Medical School, ; Boston, MA USA
                [3 ]GRID grid.38142.3c, ISNI 000000041936754X, Harvard Chan Advanced Multi-omics Platform, , Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [4 ]GRID grid.413575.1, ISNI 0000 0001 2167 1581, Howard Hughes Medical Institute, ; Boston, MA USA
                [5 ]GRID grid.38142.3c, ISNI 000000041936754X, Drosophila Research and Screening Center-Biomedical Technology Research Resource (DRSC-BTRR), Department of Genetics, , Harvard Medical School, ; Boston, MA USA
                [6 ]GRID grid.66859.34, ISNI 0000 0004 0546 1623, Broad Institute of Harvard and MIT, ; Cambridge, MA USA
                Author information
                http://orcid.org/0000-0002-4206-3291
                http://orcid.org/0000-0002-8925-7421
                http://orcid.org/0000-0001-8103-2239
                http://orcid.org/0000-0003-1442-1327
                Article
                974
                10.1038/s41556-022-00974-0
                9481466
                36050470
                7b31ff89-eb43-4449-954e-a2a71180a259
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 September 2021
                : 5 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000057, U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS);
                Award ID: T32GM007753
                Award ID: R01GM097194
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100006108, U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS);
                Award ID: 5TL1TR001101
                Award Recipient :
                Funded by: American Heart Association Predoctoral Fellowship Aramont Fund for Emerging Science Research
                Funded by: FundRef https://doi.org/10.13039/100005237, Helen Hay Whitney Foundation (HHWF);
                Award ID: Postdoctoral Fellow
                Award Recipient :
                Funded by: P41 GM132087
                Funded by: FundRef https://doi.org/10.13039/100000011, Howard Hughes Medical Institute (HHMI);
                Categories
                Article
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Cell biology
                protein transport,endoplasmic reticulum,lipids
                Cell biology
                protein transport, endoplasmic reticulum, lipids

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