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


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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.

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          Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation.

          We report a method for large-scale absolute protein expression measurements (APEX) and apply it to estimate the relative contributions of transcriptional- and translational-level gene regulation in the yeast and Escherichia coli proteomes. APEX relies upon correcting each protein's mass spectrometry sampling depth (observed peptide count) by learned probabilities for identifying the peptides. APEX abundances agree with measurements from controls, western blotting, flow cytometry and two-dimensional gels, as well as known correlations with mRNA abundances and codon bias, providing absolute protein concentrations across approximately three to four orders of magnitude. Using APEX, we demonstrate that 73% of the variance in yeast protein abundance (47% in E. coli) is explained by mRNA abundance, with the number of proteins per mRNA log-normally distributed about approximately 5,600 ( approximately 540 in E. coli) protein molecules/mRNA. Therefore, levels of both eukaryotic and prokaryotic proteins are set per mRNA molecule and independently of overall protein concentration, with >70% of yeast gene expression regulation occurring through mRNA-directed mechanisms.
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            Comparison of label-free methods for quantifying human proteins by shotgun proteomics.

            Measurements of mass spectral peak intensities and spectral counts are promising methods for quantifying protein abundance changes in shotgun proteomic analyses. We describe Serac, software developed to evaluate the ability of each method to quantify relative changes in protein abundance. Dynamic range and linearity using a three-dimensional ion trap were tested using standard proteins spiked into a complex sample. Linearity and good agreement between observed versus expected protein ratios were obtained after normalization and background subtraction of peak area intensity measurements and correction of spectral counts to eliminate discontinuity in ratio estimates. Peak intensity values useful for protein quantitation ranged from 10(7) to 10(11) counts with no obvious saturation effect, and proteins in replicate samples showed variations of less than 2-fold within the 95% range (+/-2sigma) when >or=3 peptides/protein were shared between samples. Protein ratios were determined with high confidence from spectral counts when maximum spectral counts were >or=4 spectra/protein, and replicates showed equivalent measurements well within 95% confidence limits. In further tests, complex samples were separated by gel exclusion chromatography, quantifying changes in protein abundance between different fractions. Linear behavior of peak area intensity measurements was obtained for peptides from proteins in different fractions. Protein ratios determined by spectral counting agreed well with those determined from peak area intensity measurements, and both agreed with independent measurements based on gel staining intensities. Overall spectral counting proved to be a more sensitive method for detecting proteins that undergo changes in abundance, whereas peak area intensity measurements yielded more accurate estimates of protein ratios. Finally these methods were used to analyze differential changes in protein expression in human erythroleukemia K562 cells stimulated under conditions that promote cell differentiation by mitogen-activated protein kinase pathway activation. Protein changes identified with p<0.1 showed good correlations with parallel measurements of changes in mRNA expression.
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              Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome.

              Highly complex protein mixtures can be directly analyzed after proteolysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In this paper, we have utilized the combination of strong cation exchange (SCX) and reversed-phase (RP) chromatography to achieve two-dimensional separation prior to MS/MS. One milligram of whole yeast protein was proteolyzed and separated by SCX chromatography (2.1 mm i.d.) with fraction collection every minute during an 80-min elution. Eighty fractions were reduced in volume and then re-injected via an autosampler in an automated fashion using a vented-column (100 microm i.d.) approach for RP-LC-MS/MS analysis. More than 162,000 MS/MS spectra were collected with 26,815 matched to yeast peptides (7,537 unique peptides). A total of 1,504 yeast proteins were unambiguously identified in this single analysis. We present a comparison of this experiment with a previously published yeast proteome analysis by Yates and colleagues (Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242-7). In addition, we report an in-depth analysis of the false-positive rates associated with peptide identification using the Sequest algorithm and a reversed yeast protein database. New criteria are proposed to decrease false-positives to less than 1% and to greatly reduce the need for manual interpretation while permitting more proteins to be identified.

                Author and article information

                Role: Editor
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                23 April 2008
                : 3
                : 4
                [1 ]Department of Plant Biology, Cornell University, Ithaca, New York, United States of America
                [2 ]Stockholm Bioinformatics Center, AlbaNova, Stockholm University, Stockholm, Sweden
                [3 ]Computation Biology Service Unit, Cornell Theory Center, Cornell University, Ithaca, New York, United States of America
                University of Oldenburg, Germany
                Author notes
                * To whom correspondence should be addressed. E-mail: kv35@ 123456cornell.edu

                Conceived and designed the experiments: Kv BZ. Performed the experiments: BZ HR GF AR. Analyzed the data: QS OE Kv BZ. Contributed reagents/materials/analysis tools: QS. Wrote the paper: OE Kv BZ.


                Current address: Waters Co. EHQ Waters S.A.S., Guyancourt, France

                Zybailov et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 19
                Research Article
                Genetics and Genomics
                Plant Biology
                Biochemistry/Protein Chemistry



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