Hydroponic isotope labeling of entire plants and high-performance mass spectrometry for quantitative plant proteomics.

Hydroponic isotope labeling of entire plants (HILEP) combines hydroponic plant cultivation and metabolic labeling with stable isotopes using (15)N-containing inorganic salts to label whole and mature plants. Employing (15)N salts as the sole nitrogen source for HILEP leads to the production of healthy-looking plants which contain (15)N proteins labeled to nearly 100%. Therefore, HILEP is suitable for quantitative plant proteomic analysis, where plants are grown in either (14)N- or (15)N-hydroponic media and pooled when the biological samples are collected for relative proteome quantitation. The pooled (14)N-/(15)N-protein extracts can be fractionated in any suitable way and digested with a protease for shotgun proteomics, using typically reverse phase liquid chromatography nanoelectrospray ionization tandem mass spectrometry (RPLC-nESI-MS/MS). Best results were obtained with a hybrid ion trap/FT-MS mass spectrometer, combining high mass accuracy and sensitivity for the MS data acquisition with speed and high-throughput MS/MS data acquisition, increasing the number of proteins identified and quantified and improving protein quantitation. Peak processing and picking from raw MS data files, protein identification, and quantitation were performed in a highly automated way using integrated MS data analysis software with minimum manual intervention, thus easing the analytical workflow. In this methodology paper, we describe how to grow Arabidopsis plants hydroponically for isotope labeling using (15)N salts and how to quantitate the resulting proteomes using a convenient workflow that does not require extensive bioinformatics skills.

Analysis of protein networks in resting and collagen receptor (GPVI)-stimulated platelet sub-proteomes.

Proteomics approaches have made important contributions to the characterisation of platelet regulatory mechanisms. A common problem encountered with this method, however, is the masking of low-abundance (e.g. signalling) proteins in complex mixtures by highly abundant proteins. In this study, subcellular fractionation of washed human platelets either inactivated or stimulated with the glycoprotein (GP) VI collagen receptor agonist, collagen-related peptide, reduced the complexity of the platelet proteome. The majority of proteins identified by tandem mass spectrometry are involved in signalling. The effect of GPVI stimulation on levels of specific proteins in subcellular compartments was compared and analysed using in silico quantification, and protein associations were predicted using STRING (the search tool for recurring instances of neighbouring genes/proteins). Interestingly, we observed that some proteins that were previously unidentified in platelets including teneurin-1 and Van Gogh-like protein 1, translocated to the membrane upon GPVI stimulation. Newly identified proteins may be involved in GPVI signalling nodes of importance for haemostasis and thrombosis.

In planta proteomics and proteogenomics of the biotrophic barley fungal pathogen Blumeria graminis f. sp. hordei.

To further our understanding of powdery mildew biology during infection, we undertook a systematic shotgun proteomics analysis of the obligate biotroph Blumeria graminis f. sp. hordei at different stages of development in the host. Moreover we used a proteogenomics approach to feed information into the annotation of the newly sequenced genome. We analyzed and compared the proteomes from three stages of development representing different functions during the plant-dependent vegetative life cycle of this fungus. We identified 441 proteins in ungerminated spores, 775 proteins in epiphytic sporulating hyphae, and 47 proteins from haustoria inside barley leaf epidermal cells and used the data to aid annotation of the B. graminis f. sp. hordei genome. We also compared the differences in the protein complement of these key stages. Although confirming some of the previously reported findings and models derived from the analysis of transcriptome dynamics, our results also suggest that the intracellular haustoria are subject to stress possibly as a result of the plant defense strategy, including the production of reactive oxygen species. In addition, a number of small haustorial proteins with a predicted N-terminal signal peptide for secretion were identified in infected tissues: these represent candidate effector proteins that may play a role in controlling host metabolism and immunity.

Heat-shock response in Arabidopsis thaliana explored by multiplexed quantitative proteomics using differential metabolic labeling.

We have developed a general method for multiplexed quantitative proteomics using differential metabolic stable isotope labeling and mass spectrometry. The method was successfully used to study the dynamics of heat-shock response in Arabidopsis thaliana. A number of known heat-shock proteins were confirmed, and some proteins not previously associated with heat shock were discovered. The method is applicable in stable isotope labeling and allows for high degrees of multiplexing.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction.

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.