The cortical endoplasmic reticulum (ER) in tobacco (Nicotiana tabacum) epidermal cells is a network of tubules and cisternae undergoing dramatic rearrangements. Reticulons are integral membrane proteins involved in shaping ER tubules. Here, we characterized the localization, topology, effect, and interactions of five Arabidopsis thaliana reticulons (RTNs), isoforms 1-4 and 13, in the cortical ER. Our results indicate that RTNLB13 and RTNLB1-4 colocate to and constrict the tubular ER membrane. All five RTNs preferentially accumulate on ER tubules and are excluded from ER cisternae. All isoforms share the same transmembrane topology, with N and C termini facing the cytosol and four transmembrane domains. We show by Fö rster resonance energy transfer and fluorescence lifetime imaging microscopy that several RTNs have the capacity to interact with themselves and each other, and we suggest that oligomerization is responsible for their residence in the ER membrane. We also show that a complete reticulon homology domain is required for both RTN residence in high-curvature ER membranes and ER tubule constriction, yet it is not necessary for homotypic interactions.
Deep profiling of the transcriptome and proteome during leaf development reveals unexpected responses to water deficit, as well as a surprising lack of protein-level fluctuations during the day–night cycle, despite clear changes at the transcript level.
pep2pro is a comprehensive proteome analysis database specifically suitable for flexible proteome data analysis. The pep2pro database schema offers solutions to the various challenges of developing a proteome data analysis database and because data integrated in pep2pro are in relational format, it enables flexible and detailed data analysis. The information provided here will facilitate building proteome data analysis databases for other organisms or applications. The capacity of the pep2pro database for the integration and analysis of large proteome datasets was demonstrated by creating the pep2pro dataset, which is an organ-specific characterisation of the Arabidopsis thaliana proteome containing 14 522 identified proteins based on 2.6 million peptide spectrum assignments. This dataset provides evidence of protein expression and reveals organ-specific processes. The high coverage and density of the dataset are essential for protein quantification by normalised spectral counting and allowed us to extract information that is usually not accessible in low-coverage datasets. With this quantitative protein information we analysed organ- and organelle-specific sub-proteomes. In addition we matched spectra to regions in the genome that were not predicted to have protein coding capacity and provide PCR validation for selected revised gene models. Furthermore, we analysed the peptide features that distinguish detected from non-detected peptides and found substantial disagreement between predicted and detected proteotypic peptides, suggesting that large-scale proteomics data are essential for efficient selection of proteotypic peptides in targeted proteomics surveys. The pep2pro dataset is available as a resource for plant systems biology at www.pep2pro.ethz.ch.
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