Boosting the globalization of plant proteomics through INPPO: current developments and future prospects

The International Plant Proteomics Organization (INPPO) is a non-profit-organization consisting of people who are involved or interested in plant proteomics. INPPO is constantly growing in volume and activity, which is mostly due to the realization among plant proteomics researchers worldwide for the need of such a global platform. Their active participation resulted in the rapid growth within the first year of INPPO's official launch in 2011 via its website (www.inppo.com) and publication of the 'Viewpoint paper' in a special issue of PROTEOMICS (May 2011). Here, we will be highlighting the progress achieved in the year 2011 and the future targets for the year 2012 and onwards. INPPO has achieved a successful administrative structure, the Core Committee (CC; composed of President, Vice-President, and General Secretaries), Executive Council (EC), and General Body (GB) to achieve INPPO objectives. Various committees and subcommittees are in the process of being functionalized via discussion amongst scientists around the globe. INPPO's primary aim to popularize the plant proteomics research in biological sciences has also been recognized by PROTEOMICS where a section dedicated to plant proteomics has been introduced starting January 2012, following the very first issue of this journal devoted to plant proteomics in May 2011. To disseminate organizational activities to the scientific community, INPPO has launched a biannual (in January and July) newsletter entitled 'INPPO Express: News & Views' with the first issue published in January 2012. INPPO is also planning to have several activities in 2012, including programs within the Education Outreach committee in different countries, and the development of research ideas and proposals with priority on crop and horticultural plants, while keeping tight interactions with proteomics programs on model plants such as Arabidopsis thaliana, rice, and Medicago truncatula. Altogether, the INPPO progress and upcoming activities are because of immense support, dedication, and hard work of all members of the INPPO community, and also due to the wide encouragement and support from the communities (scientific and non-scientific).

Application of DIGE and mass spectrometry in the study of type 2 diabetes mellitus mouse models

Knowledge of the differences between the amounts and types of protein that are expressed in diseased compared to healthy subjects may give an understanding of the biological pathways that cause disease. This is the reasoning behind the presented protocol, which uses difference gel electrophoresis (DIGE) to discover up- or down-regulated proteins between mice of different genotypes, or of those fed on different diets, that may thus be prone to develop diabetes-like phenotypes. Subsequent analysis of these proteins by tandem mass spectrometry typically facilitates their identification with a high degree of confidence.

Mass spectrometry imaging of glucosinolates in Arabidopsis flowers and siliques

Glucosinolates are multi-functional plant secondary metabolites which play a vital role in plant defence and are, as dietary compounds, important to human health and livestock well-being. Knowledge of the tissue-specific regulation of their biosynthesis and accumulation is essential for plant breeding programs. Here, we report that in Arabidopsis thaliana, glucosinolates are accumulated differentially in specific cells of reproductive organs. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), distribution patterns of three selected compounds, 4-methylsulfinylbutyl (glucoraphanin), indol-3-ylmethyl (glucobrassicin), and 4-benzoyloxybutyl glucosinolates, were mapped in the tissues of whole flower buds, sepals and siliques. The results show that tissue localization patterns of aliphatic glucosinolate glucoraphanin and 4-benzoyloxybutyl glucosinolate were similar, but indole glucosinolate glucobrassicin had different localisation, indicating a possible difference in function. The high resolution images obtained by a complementary approach, cryo-SEM Energy Dispersive X-ray analysis (cryo-SEM-EDX), confirmed increased concentration of sulphur in areas with elevated amounts of glucosinolates, and allowed identifying the cell types implicated in accumulation of glucosinolates. High concentration of sulphur was found in S-cells adjacent to the phloem in pedicels and siliques, indicating the presence of glucosinolates. Moreover, both MALDI MSI and cryo-SEM-EDX analyses indicated accumulation of glucosinolates in cells on the outer surface of the sepals, suggesting that a layer of glucosinolate-accumulating epidermal cells protects the whole of the developing flower, in addition to the S-cells, which protect the phloem. This research demonstrates the high potential of MALDI MSI for understanding the cell-specific compartmentation of plant metabolites and its regulation.

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.

Early detection of ovarian cancer in samples pre-diagnosis using CA125 and MALDI-MS peaks

AIM

A nested case-control discovery study was undertaken to test whether information within the serum peptidome can improve on the utility of CA125 for early ovarian cancer detection.

MATERIALS AND METHODS

High-throughput matrix-assisted laser desorption ionisation mass spectrometry (MALDI-MS) was used to profile 295 serum samples from women pre-dating their ovarian cancer diagnosis and from 585 matched control samples. Classification rules incorporating CA125 and MS peak intensities were tested for discriminating ability.

RESULTS

Two peaks were found which in combination with CA125 discriminated cases from controls up to 15 and 11 months before diagnosis, respectively, and earlier than using CA125 alone. One peak was identified as connective tissue-activating peptide III (CTAPIII), whilst the other was putatively identified as platelet factor 4 (PF4). ELISA data supported the down-regulation of PF4 in early cancer cases.

CONCLUSION

Serum peptide information with CA125 improves lead time for early detection of ovarian cancer. The candidate markers are platelet-derived chemokines, suggesting a link between platelet function and tumour development.

Single-cell proteomic analysis of glucosinolate-rich S-cells in Arabidopsis thaliana

Single-cell analysis is essential for understanding the processes of cell differentiation and metabolic specialisation in rare cell types. The amount of single proteins in single cells can be as low as one copy per cell and is for most proteins in the attomole range or below; usually considered as insufficient for proteomic analysis. The development of modern mass spectrometers possessing increased sensitivity and mass accuracy in combination with nano-LC-MS/MS now enables the analysis of single-cell contents. In Arabidopsis thaliana, we have successfully identified nine unique proteins in a single-cell sample and 56 proteins from a pool of 15 single-cell samples from glucosinolate-rich S-cells by nanoLC-MS/MS proteomic analysis, thus establishing the proof-of-concept for true single-cell proteomic analysis. Dehydrin (ERD14_ARATH), two myrosinases (BGL37_ARATH and BGL38_ARATH), annexin (ANXD1_ARATH), vegetative storage proteins (VSP1_ARATH and VSP2_ARATH) and four proteins belonging to the S-adenosyl-l-methionine cycle (METE_ARATH, SAHH1_ARATH, METK4_ARATH and METK1/3_ARATH) with associated adenosine kinase (ADK1_ARATH), were amongst the proteins identified in these single-S-cell samples. Comparison of the functional groups of proteins identified in S-cells with epidermal/cortical cells and whole tissue provided a unique insight into the metabolism of S-cells. We conclude that S-cells are metabolically active and contain the machinery for de novo biosynthesis of methionine, a precursor for the most abundant glucosinolate glucoraphanine in these cells. Moreover, since abundant TGG2 and TGG1 peptides were consistently found in single-S-cell samples, previously shown to have high amounts of glucosinolates, we suggest that both myrosinases and glucosinolates can be localised in the same cells, but in separate subcellular compartments. The complex membrane structure of S-cells was reflected by the presence of a number of proteins involved in membrane maintenance and cellular organisation.

Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes

Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Background

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

Results

We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods.

Conclusions

The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author.

A well-characterised peak identification list of MALDI MS profile peaks for human blood serum

MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10 kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum.

Evaluation of peak-picking algorithms for protein mass spectrometry

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

Genome expansion and gene loss in powdery mildew fungi reveal tradeoffs in extreme parasitism

Powdery mildews are phytopathogens whose growth and reproduction are entirely dependent on living plant cells. The molecular basis of this life-style, obligate biotrophy, remains unknown. We present the genome analysis of barley powdery mildew, Blumeria graminis f.sp. hordei (Blumeria), as well as a comparison with the analysis of two powdery mildews pathogenic on dicotyledonous plants. These genomes display massive retrotransposon proliferation, genome-size expansion, and gene losses. The missing genes encode enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and transporters, probably reflecting their redundancy in an exclusively biotrophic life-style. Among the 248 candidate effectors of pathogenesis identified in the Blumeria genome, very few (less than 10) define a core set conserved in all three mildews, suggesting that most effectors represent species-specific adaptations.

Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

OBJECTIVES

Our objective was to test the performance of CA125 in classifying serum samples from a cohort of malignant and benign ovarian cancers and age-matched healthy controls and to assess whether combining information from matrix-assisted laser desorption/ionization (MALDI) time-of-flight profiling could improve diagnostic performance.

MATERIALS AND METHODS

Serum samples from women with ovarian neoplasms and healthy volunteers were subjected to CA125 assay and MALDI time-of-flight mass spectrometry (MS) profiling. Models were built from training data sets using discriminatory MALDI MS peaks in combination with CA125 values and tested their ability to classify blinded test samples. These were compared with models using CA125 threshold levels from 193 patients with ovarian cancer, 290 with benign neoplasm, and 2236 postmenopausal healthy controls.

RESULTS

Using a CA125 cutoff of 30 U/mL, an overall sensitivity of 94.8% (96.6% specificity) was obtained when comparing malignancies versus healthy postmenopausal controls, whereas a cutoff of 65 U/mL provided a sensitivity of 83.9% (99.6% specificity). High classification accuracies were obtained for early-stage cancers (93.5% sensitivity). Reasons for high accuracies include recruitment bias, restriction to postmenopausal women, and inclusion of only primary invasive epithelial ovarian cancer cases. The combination of MS profiling information with CA125 did not significantly improve the specificity/accuracy compared with classifications on the basis of CA125 alone.

CONCLUSIONS

We report unexpectedly good performance of serum CA125 using threshold classification in discriminating healthy controls and women with benign masses from those with invasive ovarian cancer. This highlights the dependence of diagnostic tests on the characteristics of the study population and the crucial need for authors to provide sufficient relevant details to allow comparison. Our study also shows that MS profiling information adds little to diagnostic accuracy. This finding is in contrast with other reports and shows the limitations of serum MS profiling for biomarker discovery and as a diagnostic tool.

Glucosinolate-accumulating S-cells in Arabidopsis leaves and flower stalks undergo programmed cell death at early stages of differentiation

The plant secondary metabolites glucosinolates (GSL) have important functions in plant resistance to herbivores and pathogens. We identified all major GSL that accumulated in S-cells in Arabidopsis by MALDI-TOF MS, and estimated by LC-MS that the total GSL concentration in these cells is >130 mM. The precise locations of the S-cells outside phloem bundles in rosette and cauline leaves and in flower stalks were visualised using sulphur mapping by cryo-SEM/energy-dispersive X-ray analysis. S-cells contain up to 40% of the total sulphur in flower stalk tissues. S-cells in emerging flower stalks and developing leaf tissues show typical signs of programmed cell death (PCD) or apoptosis, such as chromatin condensation in the nucleus and blebbing of the membranes. TUNEL staining for DNA double-strand breaks confirmed the occurrence of PCD in S-cells in post-meristematic tissues in the flower stalk as well as in the leaf. Our results indicate that S-cells in post-meristematic tissues show an extreme degree of metabolic specialisation in addition to PCD. Accumulation and maintenance of a high concentration of GSL in these cells are accompanied by degradation of a number of cell organelles. The substantial changes in cell composition during S-cell differentiation indicate the importance of this particular GSL-based phloem defence system. The specific anatomy of the S-cells and the ability to accumulate specialised secondary metabolites is similar to that of the non-articulated laticifer cells in latex plants, suggesting a common evolutionary origin.

S6K1 is acetylated at lysine 516 in response to growth factor stimulation

The 70kDa ribosomal protein S6 kinase 1 (S6K1) plays important roles in the regulation of protein synthesis, cell growth and metabolism. S6K1 is activated by the phosphorylation of multiple serine and threonine residues in response to stimulation by a variety of growth factors and cytokines. In addition to phosphorylation, we have recently shown that S6K1 is also targeted by lysine acetylation. Here, using tandem mass spectrometry we have mapped acetylation of S6K1 to lysine 516, a site close to the C-terminus of the kinase that is highly conserved amongst vertebrate S6K1 orthologues. Using acetyl-specific K516 antibodies, we show that acetylation of endogenous S6K1 at this site is potently induced upon growth factor stimulation. Although S6K1 acetylation and phosphorylation are both induced by growth factor stimulation, these events appear to be functionally independent. Indeed, experiments using inhibitors of S6K1 activation and exposure of cells to various stresses indicate that S6K1 acetylation can occur in the absence of phosphorylation and vice versa. We propose that K516 acetylation may serve to modulate important kinase-independent functions of S6K1 in response to growth factor signalling.

Peptides generated ex vivo from serum proteins by tumor-specific exopeptidases are not useful biomarkers in ovarian cancer

BACKGROUND

The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls.

METHODS

We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set.

RESULTS

Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set.

CONCLUSIONS

For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.

Purification and molecular cloning of antimicrobial peptides from Scots pine seedlings

A novel protocol for rapid and efficient purification of antimicrobial peptides from plant seedlings has been developed. Two peptides with antimicrobial activity, designated p1 and p2, were purified nearly to homogeneity from Scots pine seedlings by a combination of sulfuric acid extraction, ammonium sulfate precipitation, heat-inactivation and ion-exchange chromatography on phosphocellulose. Purified proteins had molecular masses of 11 kDa (p1) and 5.8 kDa (p2) and were identified by mass spectrometry as defensin and lipid-transfer protein, respectively. We demonstrated their growth inhibitory effects against a group of phytopathogenic fungi. Furthermore, we report for the first time molecular cloning and characterization of defensin 1 cDNA from Scots pine. A cDNA expression library from 7 days Scots pine seedlings was generated and used to isolate a cDNA clone corresponding to Scots pine defensin, termed PsDef1. The full-length coding sequence of PsDef1 is 252 bp in length and has an open reading frame capable to encode a protein of 83 amino residues. The deduced sequence has the typical features of plant defensins, including an endoplasmic reticulum signal sequence of 33aa, followed by a characteristic defensin domain of 50 amino acids representing its active form. The calculated molecular weight of the mature form of PsDef1 is 5601.6 Da, which correlates well with the results of SDS-PAGE analysis. Finally, the antimicrobial properties of PsDef1 against a panel of fungi and bacteria define it as a member of the morphogenic group of plant defensins.

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.

The NERC DataGrid services

This short paper outlines the key components of the NERC DataGrid: a discovery service, a vocabulary service and a software stack deployed both centrally to provide a data discovery portal, and at data providers to provide local portals and data and metadata services.