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PubMed2006

Proteomic responses of rice young panicles to salinity.

Rice (Oryza sativa) is most sensitive to salinity during the reproductive stage. We employed a proteomic approach to further understand the mechanism of plant responses to salinity at an early reproductive stage. Plants were grown in culture solution and salt stress imposed at panicle initiation. After 12 days of stress, young panicles were collected from control and salt stressed plants. The Na+ and K+ content of panicle and several yield components changed significantly in response to short-term salt stress. The collected panicles were sorted into three different sizes (7 +/- 1, 11 +/- 1, and 15 +/- 1 mm) and their proteome patterns were analyzed using 2-DE in triplicates. The expression pattern of 13 proteins significantly changed in all panicle sizes in response to stress. MS analysis of salt responsive proteins and 16 other highly abundant proteins of panicle led to the identification of proteins involved in several salt responsive mechanisms which may increase plant adaptation to salt stress including higher constitutive expression level and up-regulation of antioxidants, up-regulation of proteins involved in translation, transcription, signal transduction, and ATP generation. To the best of our knowledge, this is the first proteome analysis of plant young panicle which may enhance our understanding of plant molecular responses to salinity. Proteome reference map of rice young panicle is available at http://www.proteome.ir.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2004

Isotope-coded N-terminal sulfonation of peptides allows quantitative proteomic analysis with increased de novo peptide sequencing capability.

Recently various methods for the N-terminal sulfonation of peptides have been developed for the mass spectrometric analyses of proteomic samples to facilitate de novo sequencing of the peptides produced. This paper describes the isotope-coded N-terminal sulfonation (ICenS) of peptides; this procedure allows both de novo peptide sequencing and quantitative proteomics to be studied simultaneously. As N-terminal sulfonation reagents, 13C-labeled 4-sulfophenyl[13C6]isothiocyanate (13C-SPITC) and unlabeled 4-sulfophenyl isothiocyanate (12C-SPITC) were synthesized. The experimental and reference peptide mixtures were derivatized independently using 13C-SPITC and 12C-SPITC and then combined to generate an isotopically labeled peptide mixture in which each isotopic pair differs in mass by 6 Da. Capillary reverse-phase liquid chromatography/tandem mass spectrometry experiments on the resulting peptide mixtures revealed several immediate advantages of ICenS in addition to the de novo sequencing capability of N-terminal sulfonation, namely, differentiation between N-terminal sulfonated peptides and unmodified peptides in mass spectra, differentiation between N- and C-terminal fragments in tandem mass spectra of multiply protonated peptides by comparing fragmentations of the isotopic pairs, and relative peptide quantification between proteome samples. We demonstrate that the combination of N-terminal sulfonation and isotope coding in the mass spectrometric analysis of proteomic samples is a viable method that overcomes many problems associated with current N-terminal sulfonation methods.

Amino Acid Sequence↗

PubMed2000

A method for global analysis of complex proteomes using sample prefractionation by solution isoelectrofocusing prior to two-dimensional electrophoresis.

Two-dimensional electrophoresis is a critical technique for proteome research, but currently available methods are not capable of resolving the >10,000 protein components in most eukaryotic proteomes. We have developed and demonstrated the utility of a novel solution isoelectrofocusing device and method that can reproducibly prefractionate cell extracts into well-defined pools prior to 2D PAGE on a scale directly compatible with the high sensitivity of proteome studies. A prototype device was used to separate metabolically radiolabeled Escherichia coli extracts in method optimization and proof-of-principle experiments. Samples were loaded into separation chambers divided by thin polyacrylamide gels containing immobilines at specific pH values and isoelectrically focused for several hours, which resulted in well-resolved fractions. Total recoveries in the fractionated samples were greater than 80% and most protein spots in the original sample were recovered after this prefractionation step. Nonideal behavior (precipitation/aggregation), typically encountered when unfractionated samples at high protein loads were applied directly to either narrow- or broad-range IPG gels, was dramatically reduced. Hence this approach allows increases in overall protein loads, resolution, and dynamic detection range compared with either alternative prefractionation methods or direct use of parallel narrow pH range gels without sample prefractionation. The pH ranges and number of fractions can be readily adapted to the requirements of specific types of samples and projects. This method should allow quantitative comparisons of at least 10,000 protein components on a series of narrow pH range gels, and protein detection limits are estimated to be 1000 molecules per cell when mammalian proteomes are fractionated into five or more pools.

Cell Extracts↗

PubMed2006

Proteomic analysis in cancer research: potential application in clinical use.

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. The novel technologies allows researchers to facilitate the comprehensive analyses of genomes, transcriptomes, and proteomes in health and disease. The information that is expected from such technologies may soon exert a dramatic change in cancer research and impact dramatically on the care of cancer patients. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The localization of gene products, which is often difficult to deduce from the sequence, can be determined experimentally. Mechanisms, such as regulation of protein function by proteolysis, recycling, and isolation in cell compartments, affect gene products, not genes. Finally, protein-protein interactions and the molecular composition of cellular structures can be determined only at the protein level. The biological variability among patient samples as well as the great dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we have tried to offer a wide perspective about the current possibilities.

Antibodies, Neoplasm↗

PubMed2006

The analysis of proteome changes in sunflower seeds induced by N+ implantation.

In this work, the proteomic changes induced by N+ ion implantation were investigated using a sunflower seed model by a two-dimensional electrophoretic analysis. To further understand the changes of total protein irradiated with N+ ion, a proteomic analysis of N+ ion implantation seeds was developed. Among approximately 369 total protein spots displayed in 2-D gels, eight specific proteins were found in non-implanted seeds while four proteins were found in implanted seeds. Six proteins were used for MALDI-TOF MS analysis, of which only two had been reported before. The proteins designated as No.29 showed 23.4% homology to MADS-box transcriptional factor HAM59, while No. 279 protein had 23.20% identity to homeobox-leucine zipper protein HAHB-4. The analysis of proteome changes induced by N+ implantation could provide a new clue to studying mutation mechanism of ion implantation. To our knowledge, this is the first report about the analysis of proteome changes induced by N+ implantation in sunflower seeds.

Amino Acid Sequence↗

PubMed2000

Laser capture microdissection: beyond functional genomics to proteomics.

Proteomics will drive biology and medicine beyond genomics, and can have a profound impact on molecular diagnostics. The posttranslational modifications of cellular proteins that govern physiology and become deranged in disease cannot be accurately portrayed by gene expression alone. Consequently, new technology is being developed to discover, and quantitatively monitor, proteomic changes that are associated with disease etiology and progression. In the past, proteomic technologies were restricted to tumor cell lines or homogenized bulk tissue specimens. This source material may not accurately reflect molecular events taking place in the specific cells of the tissue itself. This article describes a completely new class of proteomic-based approaches aimed at the identification and investigation of protein markers in the actual histologically defined cell populations that are immersed in heterogeneous diseased tissue. It is envisioned that these investigations will eventually lead to novel diagnostic, prognostic, or therapeutic markers that can be applied to monitor therapeutic toxicity or efficacy.

DNA, Complementary↗

PubMed2006

[Proteome analysis--basis for individualized pancreatic carcinoma therapy?].

Ductal pancreatic adenocarcinoma is a dismal disease, having the worst prognosis of all solid tumors. While genomics and transcriptomics have provided a wealth of data, no contribution has been made to clinical medicine in terms of diagnostic or prognostic markers. Hope lies in yet another novel technology, proteomics. Conceptually, proteomics bears the advantage of incorporating both posttranslational modifications as well as host factors. This is thought to be important in factors influencing survival such as chemoresistance. This tutorial review discusses the state of the art in pancreatic cancer proteomics in light of technical developments. At this moment, proteomics is still at the beginning in clinical application. First results, however, suggest some hope for the development of a new understanding of the molecular biology in pancreatic cancer yielding into very specific markers of disease or allowing a rational and individualized therapy.

Adenocarcinoma↗

PubMed2003

Interpretation of mass spectrometry data for high-throughput proteomics.

Recent developments in proteomics have revealed a bottleneck in bioinformatics: high-quality interpretation of acquired MS data. The ability to generate thousands of MS spectra per day, and the demand for this, makes manual methods inadequate for analysis and underlines the need to transfer the advanced capabilities of an expert human user into sophisticated MS interpretation algorithms. The identification rate in current high-throughput proteomics studies is not only a matter of instrumentation. We present software for high-throughput PMF identification, which enables robust and confident protein identification at higher rates. This has been achieved by automated calibration, peak rejection, and use of a meta search approach which employs various PMF search engines. The automatic calibration consists of a dynamic, spectral information-dependent algorithm, which combines various known calibration methods and iteratively establishes an optimised calibration. The peak rejection algorithm filters signals that are unrelated to the analysed protein by use of automatically generated and dataset-dependent exclusion lists. In the "meta search" several known PMF search engines are triggered and their results are merged by use of a meta score. The significance of the meta score was assessed by simulation of PMF identification with 10,000 artificial spectra resembling a data situation close to the measured dataset. By means of this simulation the meta score is linked to expectation values as a statistical measure. The presented software is part of the proteome database ProteinScape which links the information derived from MS data to other relevant proteomics data. We demonstrate the performance of the presented system with MS data from 1891 PMF spectra. As a result of automatic calibration and peak rejection the identification rate increased from 6% to 44%.

Algorithms↗

PubMed2026

Integrated analysis of amide proton transfer weighted MRI and proteomics uncovers altered protein dynamics in glioblastoma.

PURPOSE: Elevated amide proton transfer-weighted (APTw) MRI signals in glioblastoma (GBM) are often linked to increased intracellular mobile proteins, but the associated molecular patterns in human tissue remain unclear. We examined the relationship between regional APTw features and cellular protein composition and profiled proteomic differences between tumor and peritumoral tissue. METHODS: In this single-center prospective study, preoperative MRI data were integrated with intraoperative neuronavigation for 12 image-guided tissue samples (8 tumor and 4 peritumoral). Total, cytoplasmic, and nuclear proteins were quantified using bicinchoninic acid (BCA) assay. Data-independent acquisition (DIA) proteomics identified exploratory differentially expressed proteins (DEPs), followed by functional enrichment and protein-protein interaction (PPI) network analyses. Transcript-level expression patterns and survival associations were queried in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets to provide indirect external clinical context. RESULTS: Tumor regions showed higher APTw signals than peritumoral regions (p < 0.001) and increased cytoplasmic protein concentration (p < 0.05), without a corresponding increase in total or nuclear protein levels. DIA identified 654 DEPs. Further analysis highlighted 36 higher-significance DEPs, and prioritized 12 hub proteins in the PPI network. In public transcriptomic datasets, ERBB2, RUNX1, and SHC1 showed higher expression in GBM and were associated with poorer overall survival. CONCLUSION: These findings suggest that elevated APTw signal in GBM may be associated with increased cytoplasmic protein content and distinct proteomic alterations. This imaging-proteomic framework provides exploratory regional context for future mechanistic and follow-up studies, but larger, spatially matched and independently validated cohorts are required to confirm the molecular contributors to APTw contrast.

Humans↗

PubMed2005

Proteome analysis of the medicinal plant Catharanthus roseus.

A proteomic approach is undertaken aiming at the identification of novel proteins involved in the alkaloid biosynthesis of Catharanthus roseus. The C. roseus cell suspension culture A11 accumulates the terpenoid indole alkaloids strictosidine, ajmalicine and vindolinine. Cells were grown for 21 days, and alkaloid accumulation was monitored during this period. After a rapid increase between day 3 and day 6, the alkaloid content reached a maximum on day 16. Systematic analysis of the proteome was performed by two-dimensional polyacrylamide gel electrophoresis. After day 3, the proteome started to change with an increasing number of protein spots. On day 13, the proteome changed back to roughly the same as at the start of the growth cycle. 88 protein spots were selected for identification by mass spectrometry (MALDI-MS/MS). Of these, 58 were identified, including two isoforms of strictosidine synthase (EC 4.3.3.2), which catalyzes the formation of strictosidine in the alkaloid biosynthesis; tryptophan synthase (EC 4.1.1.28), which is needed for the supply of the alkaloid precursor tryptamine; 12-oxophytodienoate reductase, which is indirectly involved in the alkaloid biosynthesis as it catalyzes the last step in the biosynthesis of the regulator jasmonic acid. Unique sequences were found, which may also relate to unidentified biosynthetic proteins.

Alkaloids↗

PubMed2004

Proteomics of the rice cell: systematic identification of the protein populations in subcellular compartments.

Despite recent progress in sequencing the complete genome of rice ( Oryza sativa), the proteome of this species remains poorly understood. To extend our knowledge of the rice proteome, the subcellular compartments, which include plasma membranes (PM), vacuolar membranes (VM), Golgi membranes (GM), mitochondria (MT), and chloroplasts (CP), were purified from rice seedlings and cultured suspension cells. The proteins of each of these compartments were then systematically analyzed using two-dimensional (2D) electrophoresis, mass spectrometry, and Edman sequencing, followed by database searching. In all, 58 of the 464 spots detected by 2D electrophoresis in PM, 43 of the 141 spots in VM, 46 of the 361 spots in GM, 146 in the 672 spots in MT, and 89 of the 252 spots in CP could be identified by this procedure. The characterized proteins were found to be involved in various processes, such as respiration and the citric acid cycle in MT; photosynthesis and ATP synthesis in CP; and antifungal defense and signal systems in the membranes. Edman degradation revealed that 60-98% of N-terminal sequences were blocked, and the ratios of blocked to unblocked proteins in the proteomes of the various subcellular compartments differed. The data on the proteomes of subcellular compartments in rice will be valuable for resolving questions in functional genomics as well as for genome-wide exploration of plant function.

Cell Membrane↗

PubMed2003

Proteomics for the identification of specifically oxidized proteins in brain: technology and application to the study of neurodegenerative disorders.

Proteomics offers the opportunity elucidate the complex protein interactions of cellular systems by studying the products of genes, i.e., proteins, and their structure, function and localization. The purpose of proteomics is to explain the information contained in the genome sequences in order to provide clues on cellular events, especially related to disease. Our proteomic approach has made possible the identification of specifically oxidized proteins in Alzheimer's disease (AD) brain, providing for the first time evidence on how oxidative stress plays a crucial role in AD-related neurodegeneration. This represents an example of the use of proteomics to solve biological problems related to disease. The field, which is still in its infancy, represents a very promising way to elucidate mechanism of disease at a protein level. However, the techniques that support its development present several limitations and require introduction of new tools and innovation in order to achieve a fast, reliable and sensitive method to understand normal biological processes and their regulation as well as these cellular properties in disease.

Alzheimer Disease↗

PubMed2006

Integrating synapse proteomics with transcriptional regulation.

The mammalian postsynaptic proteome (PSP) comprises a highly interconnected set of approximately 1,000 proteins. The PSP is organized into macromolecular complexes that have a modular architecture defined by protein interactions and function. Signals initiated by neurotransmitter receptors are integrated by these complexes and their constituent enzymes to orchestrate multiple downstream cellular changes, including transcriptional regulation of genes at the nucleus. Genome wide transcriptome studies are beginning to map the sets of genes regulated by the synapse proteome. Conversely, understanding the transcriptional regulation of genes encoding the synapse proteome will shed light on synapse formation. Mutations that disrupt synapse signalling complexes result in cognitive impairments in mice and humans, and recent evidence indicates that these mutation change gene expression profiles. We discuss the need for global approaches combining genetics, transcriptomics and proteomics in order to understand cognitive function and disruption in diseases.

Animals↗

PubMed2004

Proteomic studies of human and other vertebrate muscle proteins.

This review summarizes results of some systemic studies of muscle proteins of humans and some other vertebrates. The studies, started after introduction of two-dimensional gel electrophoresis of O'Farrell, were significantly extended during development of proteomics, a special branch of functional genomics. Special attention is paid to analysis of characteristic features of strategy for practical realization of the systemic approach during three main stages of these studies: pre-genomic, genomic (with organizational registration of proteomics), and post-genomic characterized by active use of structural genomics data. Proteomic technologies play an important role in detection of changes in isoforms of various muscle proteins (myosins, troponins, etc.). These changes possibly reflecting tissue specificity of gene expression may underline functional state of muscle tissues under normal and pathological conditions, and such proteomic analysis is now used in various fields of medicine.

Animals↗

PubMed2004

Lateral roots affect the proteome of the primary root of maize (Zea mays L.).

Lateral roots are initiated from the pericycle cells of other types of roots and remain in contact with these roots throughout their life span. Although this physical contact has the potential to permit the exchange of signals, little is known about the flow of information from the lateral roots to the primary root. To begin to study these interactions the proteome of the primary root system of the maize (Zea mays L.) lrt1 mutant, which does not initiate lateral roots, was compared with the corresponding proteome of wild-type seedlings 9 days after germination. Approximately 150 soluble root proteins were resolved by two-dimensional electrophoresis and analyzed by MALDI-ToF mass spectrometry and database searching. The 96 most abundant proteins from a pH 4-7 gradient were analyzed; 67 proteins representing 47 different Genbank accessions were identified. Interestingly, 10 (15/150) of the detected proteins were preferentially expressed in lrt1 roots that lack lateral roots. Eight of these lrt1-specific proteins were identified and four are involved in lignin metabolism. This study demonstrates for the first time the influence of lateral roots on the proteome of the primary root system. To our knowledge this is the first study to demonstrate an interaction between two plant organs (viz., lateral and primary roots) at the level of the proteome.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2004

Proteomics in cancer screening and management in gynecologic cancer.

Biomarkers are used routinely for population screening, disease diagnosis and prognosis, monitoring of therapy, and prediction of therapeutic response. Unfortunately, most biomarkers have low sensitivity and specificity and little predictive value. Novel techniques for better screening and early diagnosis of ovarian cancer are urgently needed. Proteomics, the study of the cellular proteins and their activation states, integrates some fundamental techniques, including high-throughput protein purification and profiling, genomic and proteomic databases, and mass spectrometry. In oncology, proteomics will contribute greatly to our understanding of gene functions in tumor development and provide information in clinical applications. This article reviews proteomic techniques and their potential applications in gynecologic cancer screening and management.

Biomarkers, Tumor↗

PubMed2004

Applications of affinity chromatography in proteomics.

Affinity chromatography is a powerful protein separation method that is based on the specific interaction between immobilized ligands and target proteins. Peptides can also be separated effectively by affinity chromatography through the use of peptide-specific ligands. Both two-dimensional electrophoresis (2-DE)- and non-2-DE-based proteomic approaches benefit from the application of affinity chromatography. Before protein separation by 2-DE, affinity separation is used primarily for preconcentration and pretreatment of samples. Those applications entail the removal of one protein or a class of proteins that might interfere with 2-DE resolution, the concentration of low-abundance proteins to enable them to be visualized in the gel, and the classification of total protein into two or more groups for further separation by gel electrophoresis. Non-2-DE-based approaches have extensively employed affinity chromatography to reduce the complexity of protein and peptide mixtures. Prior to mass spectrometry (MS), preconcentration and capture of specific proteins or peptides to enhance sensitivity can be accomplished by using affinity adsorption. Affinity purification of protein complexes followed by identification of proteins by MS serves as a powerful tool for generating a map of protein-protein interactions and cellular locations of complexes. Affinity chromatography of peptide mixtures, coupled with mass spectrometry, provides a tool for the study of protein posttranslational modification (PTM) sites and quantitative proteomics. Quantitation of proteomes is possible via the use of isotope-coded affinity tags and isolation of proteolytic peptides by affinity chromatography. An emerging area of proteomics technology development is miniaturization. Affinity chromatography is becoming more widely used for exploring PTM and protein-protein interactions, especially with a view toward developing new general tag systems and strategies of chemical derivatization on peptides for affinity selection. More applications of affinity-based purification can be expected, including increasing the resolution in 2-DE, improving the sensitivity of MS quantification, and incorporating purification as part of multidimensional liquid chromatography experiments.

Chromatography, Affinity↗

PubMed2005

Detection of intra-amniotic infection in a rabbit model by proteomics-based amniotic fluid analysis.

OBJECTIVE: This study was undertaken to identify intra-amniotic infection caused by several different organisms in a rabbit model by using proteomics. STUDY DESIGN: Twenty infected and 18 uninfected amniotic fluid samples were subjected to proteomic analysis by surface-enhanced laser desorption ionization (SELDI-TOF, Ciphergen Biosystems, Fremont, Calif), 1- and 2-dimensional gel electrophoresis, and tandem mass spectrometry (MS/MS). RESULTS: Detailed SELDI-TOF spectra revealed a constitutive 4.0 kd peak in all animals. Infected samples also displayed a signature double peak at 3.6 kd. A SELDI-TOF signature profile for intra-amniotic infection predicted positive amniotic fluid and/or fetal cultures with a sensitivity of 90% and specificity of 83%. Similar proteomic profiles were obtained regardless of the infecting organism. The 3.6 kd peak appeared to contain rabbit calgranulin C and rabbit calcyclin, members of the S100 family of calcium binding proteins. CONCLUSION: Amniotic fluid proteomic analysis was able to detect intra-amniotic infection in this experimental rabbit model. S100 proteins may be involved in the host inflammatory response to intra-amniotic infection.

Amniotic Fluid↗