Identification of Trans-Golgi Network Proteins in Arabidopsis thaliana Root Tissue

作者：Arnoud Groen, Gloria Sáncho-Andrés, Lisa M. Breckels, Laurent Gatto, Fernando Aniento, Kathryn S. Lilley · 发表于：Journal of Proteome Research · 年份：2013 · DOI：10.1021/pr4008464 · 被引用次数：73 · 研究领域：Cellular transport and secretion、Photosynthetic Processes and Mechanisms、Advanced Proteomics Techniques and Applications

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 demonstrat...