Sorting Signals, N-Terminal Modifications and Abundance of the Chloroplast Proteome

By B. Zybailov, Heidi L. Rutschow, G. Friso, Andrea Rudella, Olof Emanuelsson, Qi Sun, K. V. van Wijk. PLoS ONE, 2008

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Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that ‘spectral counting’ can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/378640fff28c70075e93cf2d3917bd5f043b1968

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Citations in the corpus

Less label, more free: Approaches in label‐free quantitative mass spectrometry (2011, methodology): “Another method proposed for spectral counting was to weight the abundances of shared peptides based on the total SpC per protein [62], or alternatively distribute shared peptides based on the abundance of unique peptides for proteins with shared sequences [63, 64].”
Root-to-shoot Cd translocation via the xylem is the major process determining shoot and grain cadmium accumulation in rice (2009, neutral): “This does suggest that members of this cytosolic group of GSTs which are reported to associate with mitochondrial, chloroplastic, and vacuolar proteomes do so as a result of contamination of these organelles with these relatively abundant and hydrophobic proteins (Carter et al., 2004; Heazlewood et ”
Maize Metabolic Network Construction and Transcriptome Analysis (2013, methodology): “…ed by computational methods (Westerlund et al., 2003; Small et al., 2004; Emanuelsson et al., 2007), (iii) fi ndings from proteomics experiments (Zybailov et al., 2008; Majeran et al., 2011), (iv) references to the probe set identifi ers from various expression platforms developed for maize,…”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, neutral): “Recently, AtKEA2 was shown to be localized to the plastids and to mediate cation/H+ exchange, and rescue the Nhx1p mutant in yeast (Zybailov et al., 2008; Aranda-Sicilia et al., 2012).”
PPDB, the Plant Proteomics Database at Cornell (2008, background): “In a recent paper, we showed that ‘spectral counting’ can indeed provide large-scale protein quantification for Arabidopsis (9), if experiments are carefully designed with attention to reproducibility at every step of the process and if appropriate thresholds are applied for the minimum number of ma”