Classification of wheat varieties: Use of two-dimensional gel electrophoresis for varieties that can not be classified by matrix assisted laser desorption/ionization-time of flight-mass spectrometry and an artificial neural network

2-DE Separation and Identification of Oat (Avena sativa L.) Proteins and Their Prolamin Fractions

At present two-dimensional polyacrylamide gel electrophoresis (2-DE) is the most widely used proteomic tool, which enables simultaneous separation of even thousands of proteins with a high degree of resolution. The quality of 2-DE separation depends on the type of biological material used as a protein source. The presence of interfering compounds (e.g., phenols, as it is the fact in plant material including oat seeds) impedes 2-DE run. With the use of this technique it is possible to analyze the complex protein mixtures, characteristic protein fractions, as well as individual proteins.The purpose of this chapter is to describe the 2-DE technique (the separate stages of the first and the second dimension) for determining the oat protein composition (oat seed proteome), separation and preliminary identification of oat prolamin fractions. Electrophoretically separated proteins are identified on the basis of pI markers (identifying the location of both ends of an IPG strip) and on 2D SDS-PAGE standards. The gel images of oat proteins are analyzed with the help of ImageMaster 2D Platinum 6.0 program (Amersham Bioscience, part of GE Healthcare, Uppsala, Sweden). It allows finding unique spot identifiers for the occurrence of oat prolamin fractions in oat total proteins. The characteristic spots of similar shape and intensity (anchoring spots) and characteristic groups of spots can be searched for the purpose of identification.

Proteotyping of Holm oak (Quercus ilex subsp. ballota) provenances through proteomic analysis of acorn flour

Proteomics has become a powerful tool to characterize biodiversity and natural variability in plant species, as well as to catalogue and establish phylogenetic relationships and distances among populations, provenances or ecotypes. In this chapter, we describe the standard proteomics workflow that we currently use in cataloguing Holm oak (Quercus ilex subsp. ballota [Desf.] Samp.) populations. Proteins are extracted from acorn flour or pollen by TCA/acetone or TCA/acetone-phenol methods, resolved by one- or two-dimensional gel electrophoresis, and gel images are captured and analyzed by appropriate software and statistical packages. Quantitative or qualitative variable bands or spots are subjected to MS analysis in order to identify them and correlate differences in the protein profile with the phenotypes or environmental conditions.

Studies of variability in Holm oak (Quercus ilex subsp. ballota [Desf.] Samp.) through acorn protein profile analysis

Studies of variability in Holm oak (Quercus ilex subsp. ballota [Desf.] Samp.), the dominant tree species in the typical Mediterranean forest, have been carried out by using electrophoresis-based proteomic analysis of acorns. Ten populations distributed throughout the Andalusia region have been surveyed. Acorns were sampled from individual trees and proteins extracted from seed flour by using the TCA-acetone precipitation protocol. Extracts were subjected to SDS-PAGE and 2-DE for protein separation, gel images captured, spot or bands quantified, and subjected to statistical analysis (ANOVA, SOM and clustering). Variable bands or spots among populations were subjected to MALDI-TOF/TOF and LC-MS/MS for identification. The protein yield of the used protocol varied among populations, and it was in the 2.92-5.92 mg/g dry weight range. A total of 23 bands were resolved by SDS-PAGE in the 3-35 kDa Mr range, with 8 and 12, out of the total, showing respectively qualitative and quantitative statistically significant differences among populations. Data allowed grouping populations, with groups being correlated according to geographical location and climate conditions, to northern and southern, as well as the discrimination of both mesic and xeric groups. Acorn flour extracts from the most distant populations were analyzed by 2-DE, and 56 differential spots were proposed as markers of variability. Identified proteins were classified into two principal categories; storage and stress/defense protein. Besides providing the first reference map of mature acorn seeds, the use of SDS-PAGE and proteomics in characterizing natural biodiversity in forest trees will be discussed.

Implications of high-temperature events and water deficits on protein profiles in wheat (Triticum aestivum L. cv. Vinjett) grain

Increased climatic variability is resulting in an increase of both the frequency and the magnitude of extreme climate events. Therefore, cereals may be exposed to more than one stress event in the growing season, which may ultimately affect crop yield and quality. Here, effects are reported of interaction of water deficits and/or a high-temperature event (32°C) during vegetative growth (terminal spikelet) with either of these stress events applied during generative growth (anthesis) in wheat. Influence of combinations of stress on protein fractions (albumins, globulins, gliadins and glutenins) in grains and stress-induced changes on the albumin and gliadin proteomes were investigated by 2-DE and MS. The synthesis of individual protein fractions was shown to be affected by both the type and time of the applied stresses. Identified drought or high-temperature-responsive proteins included proteins involved in primary metabolism, storage and stress response such as late embryogenesis abundant proteins, peroxiredoxins and α-amylase/trypsin inhibitors. Several proteins, e.g. heat shock protein and 14-3-3 protein changed in abundance only under multiple high temperatures.

Clonal reproduction and natural variation of Populus canescens patches

Trees growing in their natural habitat represent a valuable resource for elucidating mechanisms of adaptation to environmental constraints. Along the Erqis river, there are various Populus forests, which provide 'natural laboratories' for studying tree ecophysiological responses to their habitat. Reproduction strategies and natural variation of the 'mosaic' distributed Populus canescens patches were studied using a proteomic approach and nuclear microsatellite markers. Clonal reproduction was the primary reproduction strategy of these P. canescens patches. Forty-eight percent of the locations represented in one or two P. canescens patches were identified. In total, 83 different proteins were identified in 118 of 119 protein spots, most of them involved in metabolism. Distinct proteomes and post-translational modifications were found in different P. canescens patches. The differences in the proteomes originate both from the expression of different protein isoforms with the same function and from the differential expression of proteins with different functions, suggesting that different patches might have a functional basis for their adaptation to their environments. Our studies provide a good example of applying proteomics to measure natural variation between patches and will provide a basis for understanding how trees survive through their responses to natural conditions.

Investigation of the effect of nitrogen on severity of Fusarium head blight in barley

The effect of nitrogen on Fusarium Head Blight (FHB) in a susceptible barley cultivar was investigated using gel-based proteomics. Barley grown with either 15 or 100kgha(-1)N fertilizer was inoculated with Fusarium graminearum (Fg). The storage protein fraction did not change significantly in response either to N level or Fg, whereas eighty protein spots in the water-soluble albumin fraction increased and 108 spots decreased more than two-fold in intensity in response to Fg. Spots with greater intensity in infected plants contained fungal proteins (9 spots) and proteolytic fragments of plant proteins (65 spots). Identified fungal proteins included two superoxide dismutases, L-xylulose reductase in two spots, peptidyl prolyl cis-trans isomerase and triosephosphate isomerase, and proteins of unknown function. Spots decreasing in intensity in response to Fg contained plant proteins possibly degraded by fungal proteases. Greater spot volume changes occurred in response to Fg in plants grown with low nitrogen, although proteomes of uninfected plants were similar for both treatments. Correlation of proteome changes with measurement of Fusarium-damaged kernels, fungal biomass and mycotoxin levels indicated that increased Fusarium infection occurred in barley with low N and suggests control of N fertilization as a possible way to minimise FHB in barley.

Protein polymorphism between 2 Picea abies populations revealed by 2-dimensional gel electrophoresis and tandem mass spectrometry

In species with high gene flow and consequent low interpopulation differentiation over wide geographic ranges, differential gene expression along ecological gradients often reveals adaptive significance. We investigated potential differences in protein expression between Picea abies ecotypes adapted to contrasting altitude conditions. Protein expression patterns were compared between needles and roots of 2-month-old P. abies seedlings by means of 2-dimensional electrophoresis. Proteins exhibiting differential expression between the 2 ecotypes were analyzed by tandem mass spectrometry. A total of 19 proteins exhibited qualitative or quantitative polymorphism between the 2 populations. These proteins exhibited organ-specific expression, and the level of interpopulation protein polymorphism was organ dependent. Among differentially expressed proteins, we identified proteins involved in photosynthesis, photorespiration, root tracheary element differentiation, and transmitochondrial membrane transport. Our results show that P. abies seedlings from locally adapted ecotypes exhibit consistent differences in protein expression. The expression polymorphism of some of these proteins has potential adaptive significance.

Mass spectrometry analysis of gliadins in celiac disease

In recent years, scientific research on wheat gluten proteins has followed three main directions aimed at (1) finding relationships between individual genetic alleles coding for gliadins, high or low molecular weight glutenin subunits, and the viscoelastic dough properties of flour-derived products such as pasta and bread; (2) identifying prolamins and derived peptides involved in celiac disease, a pathological condition in which the small intestine of genetically predisposed individuals is reversibly damaged; and (3) developing and validating sensitive and specific methods for detecting trace amounts of gluten proteins in gluten-free foods for celiac disease patients. In this review, the main aspects of current and perspective applications of mass spectrometry and proteomic technologies to the structural characterization of gliadins are presented, with focus on issues related to detection, identification, and quantification of intact gliadins, as well as gliadin-derived peptides relevant to the biochemical, immunological, and toxicological aspects of celiac disease.

Biosystematics and plant proteomics: role of proteomics in plant phylogenetic analysis

Since time immemorial, systematics has played significant role in every sphere of life. Biosystematics has evolved from folk taxonomy towards natural classification system and then culminated into homology based classification system. A good systematic approach is practical and predictive of phylogenetics of taxa incorporating different data. The morphological, chemical and molecular (genomics and proteomics) informations are used to explore the exact inter-relationship among the organisms. Proteomics is an essential and inevitable aspect in plant biology which can help in deciphering the functions of the genes that are or will be sequenced. Proteomics has proved to be a good tool in characterisation of individual lines and genetic distances among the genera, species, subspecies, verities and populations describing their phylogenetic interrelationships. Two-dimensional electrophoresis (2-DE) is the major technique being applied for polypeptide characterization of each taxon for exploring phylogenetic or physiological relationships among organs, tissues or organisms. Moreover, proteomics can lead to unraveling the natural phenomena of plants development and their response to changing environment. These proteomic derived informations and their application in phylogenetic studies can be useful in agro-biotechnology development for better yield and safe use of food and medicines.

Multivariate analysis of 2-DE protein patterns--practical approaches

Practical approaches to the use of multivariate data analysis of 2-DE protein patterns are demonstrated by three independent strategies for the image analysis and the multivariate analysis on the same set of 2-DE data. Four wheat varieties were selected on the basis of their baking quality. Two of the varieties were of strong baking quality and hard wheat kernel and two were of weak baking quality and soft kernel. Gliadins at different stages of grain development were analyzed by the application of multivariate data analysis on images of 2-DEs. Patterns related to the wheat varieties, harvest times and quality were detected on images of 2-DE protein patterns for all the three strategies. The use of the multivariate methods was evaluated in the alignment and matching procedures of 2-DE gels. All the three strategies were able to discriminate the samples according to quality, harvest time and variety, although different subsets of protein spots were selected. The explorative approach of using multivariate data analysis and variable selection in the analyses of 2-DEs seems to be promising as a fast, reliable and convenient way of screening and transforming many gel images into spot quantities.

Changes in cod muscle proteins during frozen storage revealed by proteome analysis and multivariate data analysis

Multivariate data analysis has been combined with proteomics to enhance the recovery of information from 2-DE of cod muscle proteins during different storage conditions. Proteins were extracted according to 11 different storage conditions and samples were resolved by 2-DE. Data generated by 2-DE was subjected to principal component analysis (PCA) and discriminant partial least squares regression (DPLSR). Applying PCA to 2-DE data revealed the samples to form groups according to frozen storage time, whereas differences due to different storage temperatures or chilled storage in modified atmosphere packing did not lead to distinct changes in protein pattern. Applying DPLSR to the 2-DE data enabled the selection of protein spots critical for differentiation between 3 and 6 months frozen storage with 12 months frozen storage. Some of these protein spots have been identified by MS/MS, revealing myosin light chain 1, 2 and 3, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, aldolase A and two alpha-actin fragments, and a nuclease diphosphate kinase B fragment to change in concentration, during frozen storage. Application of proteomics, multivariate data analysis and MS/MS to analyse protein changes in cod muscle proteins during storage has revealed new knowledge on the issue and enables a better understanding of biochemical processes occurring.

Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of genetically modified crops. 2. Assessing natural variability

Proteomics is currently tested as a complementary tool for the safety assessment of genetically modified (GM) crops. Understanding the natural variability of the proteome is crucial for the interpretation of biological differences between transgenic and nontransgenic parental lines. The natural variation of seed protein profiles among a set of 12 Arabidopsis thaliana ecotypes was determined by utilizing two-dimensional electrophoresis (2DE). The total number of different resolved protein spots found among the 12 ecotypes was 931 with a range of 573 (Mt-0) to 653 (Condara) in any one ecotype. Although the ecotypes were grown side-by-side in an environmentally controlled growth chamber, almost half of the resolved spots varied with respect to their presence/absence, and 95% of the spots present in all ecotypes varied in spot quantity (2-53-fold). In the evaluation of unintended effects of genetic modification, it is concluded that the experimental design must account for existing natural variability, which, in the case of the expressed proteome, can be substantial.

Rice proteomics: a cornerstone for cereal food crop proteomes

Proteomics-a systematic study of proteins present in a cell, tissue, organ, or organism at a particular moment during the life cycle-that began with classical two-dimensional electrophoresis and its advancement during the 1990s, has been revolutionized by a series of tremendous technological developments in mass spectrometry (MS), a core technology. Proteomics is exerting its influence on biological function of genes and genomes in the era (21st century) of functional genomics, and for this reason yeast, bacterial, and mammalian systems are the best examples. Although plant proteomics is still in its infancy, evolving proteomic technologies and the availability of the genome sequences of Arabidopsis thaliana (L.) Heyhn, and rice (Oryza sativa L.), model dicotyledoneous and monocotyledoneous (monocot) species, respectively, are propelling it towards new heights, as evidenced by the rapid spurt in worldwide plant proteome research. Rice, with an immense socio-economic impact on human civilization, is a representative model of cereal food crops, and we consider it as a cornerstone for functional genomics of cereal plants. In this review, we look at the history and the current state of monocot proteomes, including barley, maize, and wheat, with a central focus on rice, which has the most extensive proteomic coverage to date. On one side, we highlight advances in technologies that have generated enormous amount of interest in plant proteomics, and the other side summarizes the achievements made towards establishing proteomes during plant growth & development and challenge to environmental factors, including disease, and for studying genetic relationships. In light of what we have learned from the proteomic journey in rice and other monocots, we finally reveal and assess their impact in our continuous strive towards completion of their full proteomes.

Extraction methods for analysis of citrus leaf proteins by two-dimensional gel electrophoresis

General procedures for the extraction of Citrus leaf proteins for analysis by two-dimensional electrophoresis (2-DE) were developed through the evaluation and modification of existing methods. Among the methods evaluated, the best results were obtained when Tris-HCl, KCl, and phenol extractions were followed by precipitation with organic solvents to purify and concentrate the samples. The utility of the Tris-HCl extraction method was demonstrated on the leaves of six genetically different Citrus varieties. The methods described are versatile and result in high resolution 2-DE gels of Citrus leaf proteins.

Determination of wheat quality by mass spectrometry and multivariate data analysis

Multivariate analysis has been applied as support to proteome analysis in order to implement an easier and faster way of data handling based on separation by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry. The characterisation phase in proteome analysis by means of simple visual inspection is a demanding process and also insecure because subjectivity is the controlling element. Multivariate analysis offers, to a considerable extent, objectivity and must therefore be regarded as a neutral way to evaluate results obtained by proteome analysis. Proteome analysis of storage proteins from the wheat gluten complex based on two-dimensional electrophoresis and analysis of the N-terminal sequence has revealed a protein homologous to gamma-gliadins, tentatively associated with quality and within the molecular weight range 27-35 kDa. Further examinations of gliadin data based on mass spectrometry revealed that quality among wheat varieties could be determined by means of principal component analysis. Further examinations by interval partial least squares made it possible to encircle an overall optimal molecular weight interval from 31.5 to 33.7 kDa. The use of multivariate analysis on data from mass spectrometry has thus shown to be a promising technique to minimize the number of two-dimensional gels within the field of proteome analysis.

Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis

The performance of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks in wheat variety classification is further evaluated.1 Two principal issues were studied: (a) the number of varieties that could be classified correctly; and (b) various means of pre-processing mass spectrometric data. The number of wheat varieties tested was increased from 10 to 30. The main pre-processing method investigated was based on Gaussian smoothing of the spectra, but other methods based on normalisation procedures and multiplicative scatter correction of data were also used. With the final method, it was possible to classify 30 wheat varieties with 87% correctly classified mass spectra and a correlation coefficient of 0.90.