The integration of proteomics and systems approaches to map regulatory mechanisms underpinning platelet function.

Platelets in the circulation are triggered by vascular damage to activate, aggregate and form a thrombus that prevents excessive blood loss. Platelet activation is stringently regulated by intracellular signalling cascades, which when activated inappropriately lead to myocardial infarction and stroke. Strategies to address platelet dysfunction have included proteomics approaches which have lead to the discovery of a number of novel regulatory proteins of potential therapeutic value. Global analysis of platelet proteomes may enhance the outcome of these studies by arranging this information in a contextual manner that recapitulates established signalling complexes and predicts novel regulatory processes. Platelet signalling networks have already begun to be exploited with interrogation of protein datasets using in silico methodologies that locate functionally feasible protein clusters for subsequent biochemical validation. Characterization of these biological systems through analysis of spatial and temporal organization of component proteins is developing alongside advances in the proteomics field. This focused review highlights advances in platelet proteomics data mining approaches that complement the emerging systems biology field. We have also highlighted nucleated cell types as key examples that can inform platelet research. Therapeutic translation of these modern approaches to understanding platelet regulatory mechanisms will enable the development of novel anti-thrombotic strategies.

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. Molecular & Cellular Proteomics 8: 2368-2381, 2009.

Quantitative proteomics using uniform 15N-labeling, mascot and the trans-proteomic pipeline

Stable isotope labeling combined with MS is a powerful method for measuring relative protein abundances, for instance, by differential metabolic labeling of some or all amino acids with 14N and 15N in cell culture or hydroponic media. These and most other types of quantitative proteomics experiments using high-throughput technologies, such as LC-MS/MS, generate large amounts of raw MS data. This data needs to be processed efficiently and automatically, from the mass spectrometer to statistically evaluated protein identifications and abundance ratios. This paper describes in detail an approach to the automated analysis of uniformly 14N/15N-labeled proteins using MASCOT peptide identification in conjunction with the trans-proteomic pipeline (TPP) and a few scripts to integrate the analysis workflow. Two large proteomic datasets from uniformly labeled Arabidopsis thaliana were used to illustrate the analysis pipeline. The pipeline can be fully automated and uses only common or freely available software.

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. Molecular & Cellular Proteomics 8: 2368-2381, 2009.

Hydroponic isotope labelling of entire plants (HILEP) for quantitative plant proteomics; an oxidative stress case study

Hydroponic isotope labelling of entire plants (HILEP) is a cost-effective method enabling metabolic labelling of whole and mature plants with a stable isotope such as N-15. By utilising hydroponic media that contain N-15 inorganic salts as the sole nitrogen source, near to 100% N-15-labelling of proteins can be achieved. In this study, it is shown that HILEP, in combination with mass spectrometry, is suitable for relative protein quantitation of seven week-old Arabidopsis plants submitted to oxidative stress. Protein extracts from pooled N-14- and N-15-hydroponically grown plants were fractionated by SDS-PAGE, digested and analysed by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). Proteins were identified and the spectra of N-14/N-15 peptide pairs were extracted using their m/z chromatographic retention time, isotopic distributions, and the m/z difference between the N-14 and N-15 peptides. Relative amounts were calculated as the ratio of the sum of the peak areas of the two distinct N-14 and N-15 peptide isotope envelopes. Using Mascot and the open source trans-proteomic pipeline (TPP), the data processing was automated for global proteome quantitation down to the isoform level by extracting isoform specific peptides. With this combination of metabolic labelling and mass spectrometry it was possible to show differential protein expression in the apoplast of plants submitted to oxidative stress. Moreover, it was possible to discriminate between differentially expressed isoforms belonging to the same protein family, such as isoforms of xylanases and pathogen-related glucanases (PR 2). (C) 2008 Elsevier Ltd. All rights reserved.

Quantitative proteomics using uniform N-15-labeling, MASCOT, and the trans-proteomic pipeline

Stable isotope labeling combined with MS is a powerful method for measuring relative protein abundances, for instance, by differential metabolic labeling of some or all amino acids with N-14 and N-15 in cell culture or hydroponic media. These and most other types of quantitative proteomics experiments using high-throughput technologies, such as LC-MS/MS, generate large amounts of raw MS data. This data needs to be processed efficiently and automatically, from the mass spectrometer to statistically evaluated protein identifications and abundance ratios. This paper describes in detail an approach to the automated analysis of Uniformly N-14/N-15-labeled proteins using MASCOT peptide identification in conjunction with the trans-proteomic pipeline (TPP) and a few scripts to integrate the analysis workflow. Two large proteomic datasets from uniformly labeled Arabidopsis thaliana were used to illustrate the analysis pipeline. The pipeline can be fully automated and uses only common or freely available software.

Multiplexed quantitative proteomics using differential metabolic 15N-labeling

There are several advantages of using metabolic labeling in quantitative proteomics. The early pooling of samples compared to post-labeling methods eliminates errors from different sample processing, protein extraction and enzymatic digestion. Metabolic labeling is also highly efficient and relatively inexpensive compared to commercial labeling reagents. However, methods for multiplexed quantitation in the MS-domain (or ‘non-isobaric’ methods), suffer from signal dilution at higher degrees of multiplexing, as the MS/MS signal for peptide identification is lower given the same amount of peptide loaded onto the column or injected into the mass spectrometer. This may partly be overcome by mixing the samples at non-uniform ratios, for instance by increasing the fraction of unlabeled proteins. We have developed an algorithm for arbitrary degrees of nonisobaric multiplexing for relative protein abundance measurements. We have used metabolic labeling with different levels of 15N, but the algorithm is in principle applicable to any isotope or combination of isotopes. Ion trap mass spectrometers are fast and suitable for LC-MS/MS and peptide identification. However, they cannot resolve overlapping isotopic envelopes from different peptides, which makes them less suitable for MS-based quantitation. Fourier-transform ion cyclotron resonance (FTICR) mass spectrometry is less suitable for LC-MS/MS, but provides the resolving power required to resolve overlapping isotopic envelopes. We therefore combined ion trap LC-MS/MS for peptide identification with FTICR LC-MS for quantitation using chromatographic alignment. We applied the method in a heat shock study in a plant model system (A. thaliana) and compared the results with gene expression data from similar experiments in literature.

Proteomic analysis of the medicinal plant Artemisia annua: data from leaf and trichome extracts

This article contains raw and processed data related to research published by Bryant et al. [1]. Data was obtained by MS-based proteomics, analysing trichome-enriched, trichome-depleted and whole leaf samples taken from the medicinal plant Artemisia annua and searching the acquired MS/MS data against a recently published contig database [2] and other genomic and proteomic sequence databases for comparison. The processed data shows that an order-of-magnitude more proteins have been identified from trichome-enriched Artemisia annua samples in comparison to previously published data. Proteins known to have a role in the biosynthesis of artemisinin and other highly abundant proteins were found which imply additional enzymatically driven processes occurring within the trichomes that are significant for the biosynthesis of artemisinin.