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Identification, molecular characterization and immunolocalization of an isoform of the trans-Golgi-network (TGN)-specific integral membrane protein TGN38.

ABSTRACT: TGN38 is an integral membrane protein previously shown to be predominantly localized to the trans-Golgi network (TGN) of cells by virtue of a signal contained within its cytoplasmic 'tail' [Luzio, Brake, Banting, Howell, Braghetta & Stanley (1990) Biochem. J. 270, 97-102]. We now (i) describe the isolation of cDNA clones encoding an isoform of TGN38, (ii) present the sequence of that isoform and (iii) describe the production and use of antibodies which specifically recognize the new isoform. This isoform, designated TGN41, is also predominantly localized to the TGN. The only sequence differences between the protein coding regions of cDNA clones encoding TGN38 and those encoding TGN41 occur within the region specifying the cytoplasmic tails of the two proteins. The TGN localization signal is shown to be within the sequence common to both proteins.

SUBMITTER: Reaves B

PROVIDER: S-EPMC1131034 | biostudies-other | 1992 Apr

REPOSITORIES: biostudies-other

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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

Identification, molecular characterization and immunolocalization of an isoform of the trans-Golgi-network (TGN)-specific integral membrane protein TGN38.

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