Dataset Information

Sphingolipid metabolic flow controls phosphoinositide turnover at the trans-Golgi network.

ABSTRACT: Sphingolipids are membrane lipids globally required for eukaryotic life. The sphingolipid content varies among endomembranes with pre- and post-Golgi compartments being poor and rich in sphingolipids, respectively. Due to this different sphingolipid content, pre- and post-Golgi membranes serve different cellular functions. The basis for maintaining distinct subcellular sphingolipid levels in the presence of membrane trafficking and metabolic fluxes is only partially understood. Here, we describe a homeostatic regulatory circuit that controls sphingolipid levels at the trans-Golgi network (TGN). Specifically, we show that sphingomyelin production at the TGN triggers a signalling pathway leading to PtdIns(4)P dephosphorylation. Since PtdIns(4)P is required for cholesterol and sphingolipid transport to the trans-Golgi network, PtdIns(4)P consumption interrupts this transport in response to excessive sphingomyelin production. Based on this evidence, we envisage a model where this homeostatic circuit maintains a constant lipid composition in the trans-Golgi network and post-Golgi compartments, thus counteracting fluctuations in the sphingolipid biosynthetic flow.

SUBMITTER: Capasso S

PROVIDER: S-EPMC5470045 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Publications

Sphingolipid metabolic flow controls phosphoinositide turnover at the <i>trans</i>-Golgi network.

Capasso Serena S Sticco Lucia L Rizzo Riccardo R Pirozzi Marinella M Russo Domenico D Dathan Nina A NA Campelo Felix F van Galen Josse J Hölttä-Vuori Maarit M Turacchio Gabriele G Hausser Angelika A Malhotra Vivek V Riezman Isabelle I Riezman Howard H Ikonen Elina E Luberto Chiara C Parashuraman Seetharaman S Luini Alberto A D'Angelo Giovanni G

The EMBO journal 20170510 12

Sphingolipids are membrane lipids globally required for eukaryotic life. The sphingolipid content varies among endomembranes with pre- and post-Golgi compartments being poor and rich in sphingolipids, respectively. Due to this different sphingolipid content, pre- and post-Golgi membranes serve different cellular functions. The basis for maintaining distinct subcellular sphingolipid levels in the presence of membrane trafficking and metabolic fluxes is only partially understood. Here, we describe ...[more]

PMID: 28495678

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Project description:Knowledge of protein subcellular localization assists in the elucidation of protein function and understanding of different biological mechanisms that occur at discrete subcellular niches. Organelle-centric proteomics enables localization of thousands of proteins simultaneously. Although such techniques have successfully allowed organelle protein catalogues to be achieved, they rely on the purification or significant enrichment of the organelle of interest, which is not achievable for many organelles. Incomplete separation of organelles leads to false discoveries, with erroneous assignments. Proteomics methods that measure the distribution patterns of specific organelle markers along density gradients are able to assign proteins of unknown localization based on comigration with known organelle markers, without the need for organelle purification. These methods are greatly enhanced when coupled to sophisticated computational tools. Here we apply and compare multiple approaches to establish a high-confidence data set of Arabidopsis root tissue trans-Golgi network (TGN) proteins. The method employed involves immunoisolations of the TGN, coupled to probability-based organelle proteomics techniques. Specifically, the technique known as LOPIT (localization of organelle protein by isotope tagging), couples density centrifugation with quantitative mass-spectometry-based proteomics using isobaric labeling and targeted methods with semisupervised machine learning methods. We demonstrate that while the immunoisolation method gives rise to a significant data set, the approach is unable to distinguish cargo proteins and persistent contaminants from full-time residents of the TGN. The LOPIT approach, however, returns information about many subcellular niches simultaneously and the steady-state location of proteins. Importantly, therefore, it is able to dissect proteins present in more than one organelle and cargo proteins en route to other cellular destinations from proteins whose steady-state location favors the TGN. Using this approach, we present a robust list of Arabidopsis TGN proteins.

Dataset Information

Sphingolipid metabolic flow controls phosphoinositide turnover at the trans-Golgi network.

Publications

Sphingolipid metabolic flow controls phosphoinositide turnover at the <i>trans</i>-Golgi network.

Similar Datasets

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