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Update and challenges on proteomics in rice.

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.

Cluster Analysis↗

Integrating forward and reverse proteomics to unravel protein function.

To date, proteomics approaches have aimed to either identify novel proteins or change in protein expression/modification in various organisms under normal or disease conditions. One major aspect of functional proteomics is to identify protein biological properties in a given context, however, forward proteomics approaches alone cannot complete this goal. Indeed, with the increasing successes of such proteomics-based research strategies and the subsequent increasing amounts of proteins identified with unknown molecular functions, approaches allowing for systematic analyses of protein functions are desired. In this review, we propose to depict the complementarities of forward and reverse proteomics approaches in the definite understanding of protein functions. This dual strategy requires a data integration loop which allows for systematic characterization of protein function(s). The details of the integrative process combining both in silico and experimental resources and tools are presented. Altogether, we believe that the integration of forward and reverse proteomics approaches supported by bioinformatics will provide an efficient path towards systems biology.

Animals↗

Minimum reporting requirements for proteomics: a MIAPE primer.

Amongst other functions, the Human Proteome Organization's Proteomics Standards Initiative (HUPO PSI) facilitates the generation by the proteomics community of guidelines that specify the appropriate level of detail to provide when describing the various components of a proteomics experiment. These guidelines are codified as the MIAPE (Minimum Information About a Proteomics Experiment) specification, the first modules of which are now finalized. This primer describes the structure and scope of MIAPE, places it in context amongst reporting specifications for other domains, briefly discusses related informatics resources and closes by considering the ramifications for the proteomics community.

Databases, Protein↗

Proteomic patterns as a diagnostic tool for early-stage cancer: a review of its progress to a clinically relevant tool.

The pace of development in novel technologies that promise improvements in the early diagnosis of disease is truly impressive. One such technology at the forefront of this revolution is mass spectrometry. New capabilities in mass spectrometry have provided the means for the development of proteomics, and the race is on to find innovative ways to apply this powerful technology to solving the problems faced in clinical medicine. One area that has garnered much attention over the past few years is the use of mass spectral patterns for cancer diagnostics. The use of these so-called 'proteomic patterns' for disease diagnosis relies fundamentally on the pattern of signals observed within a mass spectrum rather than the more conventional identification and quantitation of a biomarker such as in the case of cancer antigen-125- or prostate-specific antigen. The inherent throughput of proteomic pattern technology enables the analysis of hundreds of clinical samples per day. Currently, there are two primary means by which proteomic patterns can be acquired, surface-enhanced laser desorption/ionization (SELDI) and an electrospray ionization (ESI) method that has been popularized under the name, OvaCheck. In this review, an historical perspective on the development of proteomic patterns for the diagnosis of early-stage cancers is described. In addition, a critical assessment of the overall technology is presented with an emphasis on the steps required to enable proteomic pattern analysis to become a viable clinical tool for diagnosing early-stage cancers.

Early Diagnosis↗

Nanoscale proteomics.

Efforts to develop a liquid chromatography (LC)/mass spectrometry (MS) technology for ultra-sensitive proteomics studies (i.e., nanoscale proteomics) are described. The approach combines high-efficiency nanoscale LC (separation peak capacity of approximately 10(3); 15-microm-i.d. packed capillaries with flow rates of 20 nL min(-1), the optimal separation linear velocity) with advanced MS, including high-sensitivity and high-resolution Fourier transform ion cyclotron resonance MS, to perform both single-stage MS and tandem MS (MS/MS) proteomic analyses. The technology enables broad protein identification from nanogram-size proteomics samples and allows the characterization of more abundant proteins from sub-picogram-size samples. Protein identification in such studies using MS is demonstrated from <75 zeptomole of a protein. The average proteome measurement throughput is approximately 50 proteins h(-1) using MS/MS during separations, presently requiring approximately 3 h sample(-1). Greater throughput (approximately 300 proteins h(-1)) and improved detection limits providing more comprehensive proteome coverage can be obtained by using the "accurate mass and time" tag approach developed in our laboratory. This approach provides a dynamic range of at least 10(6) for protein relative abundances and an improved basis for quantitation. These capabilities lay the foundation for studies from single or limited numbers of cells.

Amino Acid Sequence↗

Proteomics. Concepts and perspectives.

Within the last five years the field of proteomics has changed the understanding of molecular biology. Proteins manifest physiological as well as pathophysiological processes in a cell or an organism, and proteomics describes the complete protein inventory in dependence on in vivo parameters. Disease mechanism or drug effects both affect a protein profile and, vice versa, characterising protein profiles reveals information for the understanding of disease and therapy. Analytical methods for proteomics are based on conventional tools for protein characterisation. The technical challenge is the complete coverage of physico-chemical properties for thousands of proteins. Nucleic acids display a relative chemical homogeneity and therefore genomics was considered more promising in the past than proteomics. Further improvements in proteomics technologies will likely change this course with proteomics complementing genomics as a tool to study life sciences.

Animals↗

Mitochondrial proteomics. Undercover in the lipid bilayer.

Alteration of the mitochondrial proteome and altered mitochondrial function has been implicated in a variety of degenerative diseases, heart disease, aging and cancer. Based upon the human genome there is estimated to be approximately 1000 to 2000 proteins constituting the mitochondrial proteome. Despite the ability of a traditional proteomic approach involving two-dimensional gel electrophoresis (2-DE) to resolve and identify thousands of proteins in a single gel, just over 600 mitochondrial proteins have been identified and characterized at the molecular level. The limitations and recent advances of 2-DE in its ability to study mitochondrial proteins and create a database of the mitochondrial proteome is discussed, as well as the alternative methods that are being employed, including different mass spectrometry based approaches following both one-dimensional SDS-PAGE and gel-free approaches, blue native gel electrophoresis (BN-PAGE), proteome simplification by submitochondrial fractionation, and affinity chromatography. In addition, the successful application of proteomics to the investigation of some specific mitochondrial cardiomyopathies is discussed.

Animals↗

Interaction proteomics.

The term proteome is traditionally associated with the identification of a large number of proteins within complex mixtures originating from a given organelle, cell or even organism. Current proteome investigations are basically focused on two major areas, expression proteomics and functional proteomics. Both approaches rely on the fractionation of protein mixtures essentially by two-dimensional polyacrylamide gel electrophoresis (2D-gel) and the identification of individual protein bands by mass spectrometric techniques (2D-MS). Functional proteomics approaches are basically addressing two main targets, the elucidation of the biological function of unknown proteins and the definition of cellular mechanisms at the molecular level. In the cell many processes are governed not only by the relative abundance of proteins but also by rapid and transient regulation of activity, association and localization of proteins and protein complexes. The association of an unknown protein with partners belonging to a specific protein complex involved in a particular process would then be strongly suggestive of its biological function. The identification of interacting proteins in stable complexes in a cellular system is essentially achieved by affinity-based procedures. Different strategies relying on this simple concept have been developed and a brief overview of the main approaches presently used in functional proteomics studies is described.

Chromatography, Affinity↗

Discriminatory proteomic biomarker analysis identifies free hemoglobin in the cerebrospinal fluid of women with severe preeclampsia.

OBJECTIVE: Preeclampsia is an idiopathic multisystem disorder specific to human pregnancy. This study used proteomic analysis of cerebrospinal fluid (CSF) to identify protein biomarkers characteristic of preeclampsia and related to its severity. STUDY DESIGN: CSF was collected from women diagnosed clinically with severe preeclampsia (sPE: n = 7), mild preeclampsia (mPE: n = 8), and normotensive controls (CRL: n = 8). Samples were subjected to proteomic analysis using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy. A discriminative proteomic biomarker profile was extracted by applying Mass Restricted analysis, and a Preeclampsia Proteomic Biomarker (PPB) score developed based on the presence or absence of four discriminatory protein peaks in individual CSF SELDI tracings. In-gel tryptic digests, Western blot analysis, on-chip immunoassays, ELISA, and spectral analysis were used to identify the biomarkers composing the PPB score. RESULTS: PPB score distinguished patients with a clinical diagnosis of sPE from mPE and CRLs. (PPB median [range]: sPE: 4 [0-4] vs mPE: 1 [0-1] vs CRL: 0 [0-0]; P < 0.001). PPB scores were unaffected by parity, magnesium seizure prophylaxis, CSF leukocyte counts, and total protein content. Proteomic identification techniques matched the discriminatory protein peaks to the alpha- and beta-hemoglobin chains. ELISA confirmed that women diagnosed clinically with sPE had significantly higher CSF hemoglobin concentrations than women with mPE or CRL (median [range]: sPE: 6.6 [0.0-10.3] microg/mL vs mPE: 0 [0-1.3] microg/mL vs CRL: 0 [0-0] microg/mL; P < 0.001). CONCLUSION: Proteomic analysis of CSF can accurately distinguish sPE from both mPE and CRL. Patients with sPE have nanomolar amounts of free hemoglobin in their CSF. Further studies are needed to confirm these observations and determine their physiologic implications.

Biomarkers↗

Proteome analysis of signaling cascades in human platelets.

During the last 15 years, advances in mass spectrometry (MS) instrumentation and techniques have revolutionized the emerging field of proteomics. Proteomics technology allows a comprehensive and efficient analysis of the protein content (i.e., the proteome) of any cell, tissue or biological fluid and has become an indispensable tool in biomedical research, complementing the powerful field of genomics. Proteomics is based on the huge analytical power offered by mass spectrometry in combination with several separation techniques, such as two-dimensional gel electrophoresis (2-DE) or multidimensional liquid chromatography. The technology is particularly suitable for platelets because of the absence of a nucleus. In the recent years, there has been success in mapping the proteome of the platelet in a basal state. Furthermore, a handful of research groups have also applied this technology to the study of signaling cascades in human platelets, allowing the identification of novel platelet signaling proteins and phosphorylation events. Those studies provide new insights into the mechanisms of platelet activation and build the basis for the development of therapeutic agents for thrombotic disease. This article focus on the application of 2-DE-based proteomics to the study of signaling cascades in human platelets.

Blood Platelets↗

Limitations of current proteomics technologies.

Application of proteomics technologies in the investigation of biological systems creates new possibilities in the elucidation of biopathomechanisms and the discovery of novel drug targets and early disease markers. A proteomic analysis involves protein separation and protein identification as well as characterization of the post-translational modifications. Proteomics has been applied in the investigation of various disorders, like neurological diseases, and the application has resulted in the detection of a large number of differences in the levels and the modifications of proteins between healthy and diseased states. However, the current proteomics technologies are still under development and show certain limitations. In this article, we discuss the major drawbacks and pitfalls of proteomics we have observed in our laboratory and in particular during the application of proteomics technologies in the investigation of the brain.

Chromatography, Liquid↗

Proteomic approaches in brain research and neuropharmacology.

Numerous applications of genomic technologies have enabled the assembly of unprecedented inventories of genes, expressed in cells under specific physiological and pathophysiological conditions. Complementing the valuable information generated through functional genomics with the integrative knowledge of protein expression and function should enable the development of more efficient diagnostic tools and therapeutic agents. Proteomic analyses are particularly suitable to elucidate posttranslational modifications, expression levels and protein-protein interactions of thousands of proteins at a time. In this review, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) investigations of brain tissues in neurodegenerative diseases such as Alzheimer's disease, Down syndrome and schizophrenia, and the construction of 2D-PAGE proteome maps of the brain are discussed. The role of the Human Proteome Organization (HUPO) as an international coordinating organization for proteomic efforts, as well as challenges for proteomic technologies and data analysis are also addressed. It is expected that the use of proteomic strategies will have significant impact in neuropharmacology over the coming decade.

Alzheimer Disease↗

Accurate diagnosis of acute graft-versus-host disease using serum proteomic pattern analysis.

OBJECTIVE: The rapid diagnosis of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (HCT) is important for optimizing the management of this life-threatening complication. Current diagnostic techniques are time-consuming and require invasive tissue sampling. We investigated serum protein pattern analysis using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry as a tool to diagnose GVHD. PATIENTS AND METHODS: Eighty-eight serum samples were obtained from 34 patients undergoing HCT either pretransplant (n = 28 samples) or at various time points posttransplant (n = 60 samples), including 22 samples obtained on the day of onset of acute GVHD symptoms. Serum proteomic spectra generated from a "training set" of known samples were used to identify distinct proteomic patterns that best categorized a sample as either pretransplant, posttransplant non-GVHD, or GVHD; these distinct proteomic signatures were subsequently used to classify samples from a masked "test" sample set into the appropriate diagnostic category. RESULTS: Proteomic pattern analysis accurately distinguished GVHD samples from both posttransplant non-GVHD samples and pretransplant samples (100% specificity and 100% sensitivity in both cases). Furthermore, distinct serum proteomic signatures were identified that distinguished pretransplant from posttransplant non-GVHD samples (100% specificity and 94% sensitivity). CONCLUSION: These preliminary data suggest a potential application of SELDI-TOF-based proteomic analysis as a rapid and accurate method to diagnose acute GVHD.

Adult↗

Proteomics of breast carcinoma.

Beast cancer is the most diagnosed cancer in women, accounting for approximately 40,000 deaths annually in the USA. Significant advances have been made in the areas of detection and treatment, but a significant number of breast cancers are detected late. The advent of proteomics provides the hope of discovering novel biological markers that can be used for early detection, disease diagnosis, prognostication and prediction of response to therapy. Several proteomics technologies including 2D-PAGE, 2D-DIGE, ICAT, SELDI-TOF, MudPIT and protein arrays have been used to uncover molecular mechanisms associated with breast carcinoma at the global level, and a number of these technologies, particularly the SELDI-TOF hold promise as a proteomic approach that can be applied at the bedside for discovering protein patterns that distinguish disease and disease-free states with high sensitivity and specificity. Laser microdissection, a method for selection of homogenous cell populations, coupled to 2D-DIGE or MudPIT constitute a new proteomics-based paradigm for detecting disease in pathology specimens and monitoring disease response to therapy. This review describes proteomics technologies, and their application in the proteomic analysis of breast carcinoma.

Biomarkers, Tumor↗

Mitochondrial proteomic characterization of human normal articular chondrocytes.

OBJECTIVE: Mitochondrial dysfunctions have been associated with apoptosis, aging and osteoarthritis (OA). Chondrocyte mitochondrial proteins are attractive targets for the study of the metabolism of cartilage degradation. The copurification of "contaminating" proteins has been the major problem in all phases of mitochondrial proteome research. Therefore, we set up a procedure for the proteomic analysis of human chondrocyte mitochondrial proteins. METHOD: Four types of protein extracts were obtained from primary cultured chondrocytes isolated from healthy donors: (1) initial total chondrocyte extract (CE), (2) cytosol-enriched supernatant fraction (CY), (3) crude mitochondria fraction (CM), and (4) pure mitochondria fraction (PM). Mitochondria were purified by density gradient ultracentrifugation. Mitochondrial proteins were separated by means of two-dimensional gel electrophoresis (2-DE) and silver stained. Protein spots were then identified by mass spectrometry using MALDI-TOF/TOF technology. RESULTS: The best 2-DE reference map of mitochondrial proteome was constructed employing PM fraction. Thirty-nine percent of the identified proteins were functionally distributed in the mitochondria, 14% in the endoplasmic reticulum and 36% in the cytoplasm. Examining their biological function, 22% are involved in protein targeting, 12% in signaling, 12% in glycolysis, 10% in RNA, DNA or protein synthesis, 10% in oxidative phosphorylation and 4% in redox. The analysis of mitochondrial Mn-superoxide dismutase (SODM) revealed an age-dependent decrease of this protein. CONCLUSION: PM fraction allowed the obtention of a high quality proteomic map for the study of mitochondrial proteins in human articular chondrocytes. This proteomic approach may be also efficient to analyze both quantitative and qualitative modulations of the mitochondrial proteome in human chondrocytes during aging and pathological conditions such as OA.

Adolescent↗

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics↗

Abundance of intrinsically unstructured proteins in P. falciparum and other apicomplexan parasite proteomes.

Preliminary sequence analysis of Plasmodium falciparum has shown that the proteome of this organism is enriched in intrinsically unstructured proteins (IUPs), which are either completely disordered or contain large disordered regions. IUPs have been characterized as a unique class of proteins that plays an important role in biology and disease. In this study, the IUP contents in the proteomes of apicomplexan parasites, especially the proteome of P. falciparum and its various life cycle stages, have been evaluated with DisEMBL-1.4. Compared with other proteomes, apicomplexan species are extremely abundant in proteins containing long disordered regions, and the IUP contents in mammalian Plasmodium species are higher than in most other apicomplexan parasites. The proteome of the P. falciparum sporozoite appears to be distinct from the other life cycle stages in having an even higher content of disordered proteins. The abundance of IUPs in the P. falciparum proteome correlates with its enrichment in repetitive sequences. The structural plasticity of IUPs, which allows promiscuous binding interactions, may favour parasite survival both by inhibiting the generation of effective high affinity antibody responses and by facilitating the interactions with host molecules necessary for attachment and invasion of host cells.

Animals↗

Proteomic analysis of anti-cancer effects by paclitaxel treatment in cervical cancer cells.

OBJECTIVES: Paclitaxel (Taxol), a potent drug of natural origin isolated from the bark of the Pacific yew, is widely used in the treatment of ovarian, lung and breast cancer. At present, there is little information regarding the anti-cancer mechanism of paclitaxel against cervical carcinoma cells. We thus tried to show the anti-cancer effect of paclitaxel on cervical carcinoma cell line carrying HPV by using a proteomic analysis and to investigate the mechanism of actions. METHODS: We treated paclitaxel to cervical carcinoma cells and then carried out MTT assay to observe the anti-proliferate activity. Using proteomics analysis including two-dimensional (2-DE) gel electrophoresis and MALDI-TOF-MS, we tried to find the anti-proliferate activity-related proteins. Among them, paclitaxel treatment suppressed the expression of the mitotic checkpoint protein BUB3. Functional proteomic analysis by small interfering RNA (siRNA) targeting was tried to illuminate a role of mitotic checkpoint protein BUB3 in cell cycle progression. RESULTS: The cytotoxicity effects of paclitaxel were determined in HPV-16 positive CaSki, HPV-18 positive HeLa and HPV-negative C33A cervical carcinoma cell lines. Using efficient proteomics methods including 2-DE/MALDI-TOF-MS, we identified several cellular proteins that are responsive to paclitaxel treatment in HeLa cells. Paclitaxel treatment elevated mainly apoptosis-related, immune response-related and cell cycle check point-related proteins. On the other hand, paclitaxel treatment diminished growth factor/oncogene-related proteins and transcription regulation-related proteins. Paclitaxel showed anti-proliferate activity through the membrane death receptor (DR)-mediated apoptotic pathway involving activation of caspase-8 with a TRAIL-dependent fashion as well as the mitochondrial-mediated pathway involving down-regulation of bcl-2 by cytochrome c release. Furthermore, we found siRNA-induced BUB3 knock down on cell cycle progression blocked by cell cycle arrest after paclitaxel treatment. CONCLUSIONS: The proteome profiling technique provided a broad-base and effective approach for the identification of protein changes induced by paclitaxel and showed anti-proliferate activity through the membrane death receptor-mediated apoptotic pathway, the mitochondrial-mediated pathway. This study shows the power of proteomic profiling with functional analysis using RNAi technology for the discovery of novel molecular targets and a better understanding of the actions of paclitaxel at the molecular level in cervical carcinoma cells.

Antineoplastic Agents, Phytogenic↗