The use of heavy nitrogen in quantitative proteomics experiments in plants

Max Planck Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, 14476 Golm, Germany.
Trends in Plant Science (Impact Factor: 12.93). 12/2011; 17(2):102-12. DOI: 10.1016/j.tplants.2011.11.001
Source: PubMed


In the growing field of plant systems biology, there is an undisputed need for methods allowing accurate quantitation of proteins and metabolites. As autotrophic organisms, plants can easily metabolize different nitrogen isotopes, resulting in proteins and metabolites with distinct molecular mass that can be separated on a mass spectrometer. In comparative quantitative experiments, treated and untreated samples are differentially labeled by nitrogen isotopes and jointly processed, thereby minimizing sample-to-sample variation. In recent years, heavy nitrogen labeling has become a widely used strategy in quantitative proteomics and novel approaches have been developed for metabolite identification. Here, we present an overview of currently used experimental strategies in heavy nitrogen labeling in plants and provide background on the history and function of this quantitation technique.

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    • "The average labeling efficiency achieved using exogenous amino acid supply to Arabidopsis cell cultures was found to be only 70–80 % (Gruhler et al., 2005). Quantitative strategies with 15 N metabolic labeling have been described for plant proteome analysis, however care should be taken to ensure complete 15 N incorporation since even small amounts of 14 N in the labeled sample can have significant detrimental effect on the number of peptide identifications (Nelson et al., 2007; Guo and Li, 2011; Arsova et al., 2012). "
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    ABSTRACT: The proteomic composition of the Arabidopsis Golgi apparatus is currently reasonably well documented; however little is known about the relative abundances between different proteins within this compartment. Accurate quantitative information of Golgi resident proteins is of great importance: it facilitates a better understanding of the biochemical processes which take place within this organelle, especially those of different polysaccharide synthesis pathways. Golgi resident proteins are challenging to quantify since the abundance of this organelle is relatively low within the cell. In this study an organelle fractionation approach, targeting the Golgi apparatus, was combined with a label free quantitative mass spectrometry (MS), data-independent acquisition (DIA) method employing ion mobility separation known as LC-IMS-MSE (or HDMSE), to simultaneously localize proteins to the Golgi apparatus and assess their relative quantity. In total 102 Golgi localised proteins were quantified. These data provide new insight into Golgi apparatus organization and demonstrate that organelle fractionation in conjunction with label free quantitative MS is a powerful and relatively simple tool to access protein organelle localisation and their relative abundances. The findings presented open a unique view on the organization of the plant Golgi apparatus, leading towards novel hypotheses centered on the biochemical processes of this organelle.
    Plant physiology 08/2014; 166(2). DOI:10.1104/pp.114.245589 · 6.84 Impact Factor
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    • "Normalization and quantitation of peptide intensities can be done by introducing isotopically labeled peptides to a sample for which full scan spectra will be co-analyzed (Ong et al., 2002). The heavy and light peptide forms can be separated by their mass and one of the isotope species serves as a reference in quantitation (reference peptide; Arsova et al., 2012a,b). If supplied at known concentrations, the isotope-labeled reference peptides can also be used for determination of absolute protein concentrations (Kirkpatrick et al., 2005; Hanke et al., 2008). "
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    ABSTRACT: Quantitative comparative analyses of protein abundances using peptide ion intensities and their modifications have become a widely used technique in studying various biological questions. In the past years, several methods for quantitative proteomics were established using stable-isotope labeling and label-free approaches. We systematically evaluated the application of reference protein normalization (RPN) for proteomic experiments using a high mass accuracy LC-MS/MS platform. In RPN all sample peptide intensities were normalized to an average protein intensity of a spiked reference protein. The main advantage of this method is that it avoids fraction of total based relative analysis of proteomic data, which is often very much dependent on sample complexity. We could show that reference protein ion intensity sums are sufficiently reproducible to ensure a reliable normalization. We validated the RPN strategy by analyzing changes in protein abundances induced by nutrient starvation in . Beyond that, we provide a principle guideline for determining optimal combination of sample protein and reference protein load on individual LC-MS/MS systems.
    Frontiers in Plant Science 02/2013; 4:25. DOI:10.3389/fpls.2013.00025 · 3.95 Impact Factor
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    • "Recently, various quantitative proteomics strategies have been developed to gain insight into the phosphoprotein dynamics, including label-free, chemical or stable-isotope labeling and corresponding statistical assessment (Schulze and Usadel, 2010). In vivo metabolic incorporation of stable isotopes, particularly the heavy nitrogen (15N), is firstly described in 1999 (Oda et al., 1999) and has emerged as one of the favorite strategies given the autotrophic nature of plants (Dunkley et al., 2004; Gevaert et al., 2008; Gouw et al., 2010; Guo and Li, 2011; Arsova et al., 2012). Examples are the stable isotope labeling by/with amino acids in cell culture (SILAC; Ong et al., 2002) and the stable isotope labeling in planta (SILIP; Schaff et al., 2008). "
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    ABSTRACT: Protein phosphorylation is one of the most important post-translational modifications (PTMs) as it participates in regulating various cellular processes and biological functions. It is therefore crucial to identify phosphorylated proteins to construct a phosphor-relay network, and eventually to understand the underlying molecular regulatory mechanism in response to both internal and external stimuli. The changes in phosphorylation status at these novel phosphosites can be accurately measured using a (15)N-stable isotopic labeling in Arabidopsis (SILIA) quantitative proteomic approach in a high-throughput manner. One of the unique characteristics of the SILIA quantitative phosphoproteomic approach is the preservation of native PTM status on protein during the entire peptide preparation procedure. Evolved from SILIA is another quantitative PTM proteomic approach, AQUIP (absolute quantitation of isoforms of post-translationally modified proteins), which was developed by combining the advantages of targeted proteomics with SILIA. Bioinformatics-based phosphorylation site prediction coupled with an MS-based in vitro kinase assay is an additional way to extend the capability of phosphosite identification from the total cellular protein. The combined use of SILIA and AQUIP provides a novel strategy for molecular systems biological study and for investigation of in vivo biological functions of these phosphoprotein isoforms and combinatorial codes of PTMs.
    Frontiers in Plant Science 01/2012; 3:302. DOI:10.3389/fpls.2012.00302 · 3.95 Impact Factor
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