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PubMed2003

The proteome: anno Domini 2002.

We present some current definitions related to functional and structural proteomics and the human proteome, and we review the following aspects of proteome analysis: Classical 2-D map analysis (isoelectric focusing (IEF) followed by SDS-PAGE); Quantitative proteomics (isotope-coded affinity tag (ICAT), fluorescent stains) and their use in e.g., tumor analysis and identification of new target proteins for drug development; Electrophoretic pre-fractionation (how to see the hidden proteome!); Multidimensional separations, such as: (a) coupled size-exclusion and reverse-phase (RP)-HPLC; (b) coupled ion-exchange and RP-HPLC; (c) coupled RP-HPLC and RP-HPLC at 25/60 degrees C; (d) coupled RP-HPLC and capillary electrophoresis (CE); (e) metal affinity chromatography coupled with CE; Protein chips. Some general conclusions are drawn on proteome analysis and we end this review by trying to decode the glass ball of the aruspex and answer the question: "Quo vadis, proteome"?

Animals↗
PubMed2002

Defining the mandate of proteomics in the post-genomics era: workshop report.

Research in proteomics is the next step after genomics in understanding life processes at the molecular level. In the largest sense proteomics encompasses knowledge of the structure, function and expression of all proteins in the biochemical or biological contexts of all organisms. Since that is an impossible goal to achieve, at least in our lifetimes, it is appropriate to set more realistic, achievable goals for the field. Up to now, primarily for reasons of feasibility, scientists have tended to concentrate on accumulating information about the nature of proteins and their absolute and relative levels of expression in cells (the primary tools for this have been 2D gel electrophoresis and mass spectrometry). Although these data have been useful and will continue to be so, the information inherent in the broader definition of proteomics must also be obtained if the true promise of the growing field is to be realized. Acquiring this knowledge is the challenge for researchers in proteomics and the means to support these endeavors need to be provided. An attempt has been made to present the major issues confronting the field of proteomics and two clear messages come through in this report. The first is that the mandate of proteomics is and should be much broader than is frequently recognized. The second is that proteomics is much more complicated than sequencing genomes. This will require new technologies but it is highly likely that many of these will be developed. Looking back 10 to 20 years from now, the question is: Will we have done the job wisely or wastefully? This report summarizes the presentations made at a symposium at the National Academy of Sciences on February 25, 2002.

Computational Biology↗
PubMed2004

Proteomics in platelet science.

Proteomics, the rapid large-scale analysis of cellular proteins, is becoming an important tool in the study of human platelet biology. A number of investigators have used proteomics techniques to study platelets including two-dimensional gel electrophoresis, protein separation, and mass spectrometry protein identification. Most efforts have focused on: 1) cataloging the spectrum of proteins that comprise the normal platelet "proteome", 2) characterizing proteins released from activated platelets, and 3) identifying phosphoproteins generated upon platelet stimulation. The incorporation of modern proteomics technology to platelet studies will further our understanding of platelet activation, adhesion, and aggregation at the protein level. Moreover, proteomics offers hope that novel biomarkers can be discovered that diagnose inherited and/or acquired platelet disorders, or predict the susceptibility of such individuals to bleeding or thrombosis. Finally, proteomics could lead to identification of novel agents that have therapeutic value. This review discusses the current status and future opportunities of proteomics technologies in platelet science.

Blood Platelets↗
PubMed2004

Clusters of proteins in archaeal and bacterial proteomes using compositional analysis.

In silico proteomics complements computational genomics in characterizing genome evolution. Here we examine cluster patterns in archaeal and bacterial proteomes using compositional properties of protein sequences in contrast to the traditionally used sequence alignment procedures. Application of standard Principal Component Analysis to the multi-dimensional data identified cluster patterns. Two types of cluster patterns exist in bacterial proteomes. Proteomes of type I have one major cluster with few isolated points in space revealing an underlying largely homogeneous compositional structure. In type II proteomes two clusters of protein distribution were discernible. The two clusters differ in size and were separated from each other although the boundary was somewhat fuzzy. Proteins falling in the major cluster were labeled as 'typical' and proteins of the minor cluster were called 'atypical'. The atypical proteins were mapped to Cluster of Orthologous Groups. Species distribution in COGs maps with respect to atypical proteins illuminated the biological relationships of extreme diversity among the archaeal members and of diversity among bacteria in relation to their niche. Amino acids that were over-represented in the atypical proteins had higher biosynthetic cost compared to 'typical' ribosomal proteins. However, archaea and bacteria economize by preferring the less costly amino acid to others closely related in chemical structure. Further, over-representation of serine in atypical proteins of archaeal members suggests re-examining these proteomes for the presence of Serine/Threonine phosphatases and kinases in Archaea. Our computational procedure can serve as a useful addition to the existing tools for carrying out in silico proteomics.

Archaeal Proteins↗
PubMed2025

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Single-Cell Analysis↗
PubMed2000

Proteomics in medical microbiology.

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.

Bacterial Proteins↗
PubMed2006

Knowledge-based proteome profiling: considering identified proteins to evaluate separation efficiency by 2-D PAGE.

Proteome profiling techniques rely on the separation of proteins or peptides and their subsequent quantification. The reliability of this technique is still limited because a proteome profiling result does not necessarily represent the true protein composition of the analysed sample, thus seriously hampering proper data interpretation. Many experimentally observed proteome alterations are biologically not significant. It was the aim of this study to use the knowledge of the biological context of proteins in order to establish optimised proteome profiling protocols. While 2-D spot patterns of total cell protein fractions were found to poorly represent the true protein composition, purified subcellular protein fractions were found to better represent the protein composition of the analysed sample. The application of a standardised protocol to different kinds of cells revealed several striking observations. Firstly, the protein composition of cultured cells of various origins is very similar. Secondly, proteome alterations observed with the described protocols do make sense from a biologic point of view and may thus be considered as truly representative for the analysed samples. Thirdly, primary white blood cells isolated from different donors were found to show minor, but reproducible and significant individual differences. We designate the consideration of known properties of identified proteins in proteome profiles as a knowledge-based approach. The present data suggest that this approach may tremendously help to improve the applied techniques and assess the results. We demonstrate that the fulfilment of well-defined criteria of proteome profiles eventually results in reliable and biologically relevant data.

Amino Acid Sequence↗
PubMed2006

SPLASH: systematic proteomics laboratory analysis and storage hub.

In the field of proteomics, the increasing difficulty to unify the data format, due to the different platforms/instrumentation and laboratory documentation systems, greatly hinders experimental data verification, exchange, and comparison. Therefore, it is essential to establish standard formats for every necessary aspect of proteomics data. One of the recently published data models is the proteomics experiment data repository [Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D. et al., Nat. Biotechnol. 2003, 21, 247-254]. Compliant with this format, we developed the systematic proteomics laboratory analysis and storage hub (SPLASH) database system as an informatics infrastructure to support proteomics studies. It consists of three modules and provides proteomics researchers a common platform to store, manage, search, analyze, and exchange their data. (i) Data maintenance includes experimental data entry and update, uploading of experimental results in batch mode, and data exchange in the original PEDRo format. (ii) The data search module provides several means to search the database, to view either the protein information or the differential expression display by clicking on a gel image. (iii) The data mining module contains tools that perform biochemical pathway, statistics-associated gene ontology, and other comparative analyses for all the sample sets to interpret its biological meaning. These features make SPLASH a practical and powerful tool for the proteomics community.

Database Management Systems↗
PubMed2006

Systematical evaluation of the effects of sample collection procedures on low-molecular-weight serum/plasma proteome profiling.

Blood is an ideal source for biomarker discovery. However, little has been done to address the effects of sampling, handling and storage procedures on serum/plasma proteomes. We used magnetic bead-based MALDI-TOF MS to systematically evaluate the influence of each procedure on low-molecular-weight serum/plasma proteome profiling on the basis of the whole spectra. We found that sampling procedures, including the selection of blood collection tubes and anticoagulants, variations in clotting time or time lag before centrifugation, and hemolysis, displayed significant effects on the proteomes. Moreover, serum and plasma were mutually incompatible for proteome comparison. By contrast, overnight fasting, handling procedures, including centrifugation speeds (1500 x g vs. 3000 x g) or time (15 min vs. 30 min), and storage conditions, such as at 4 degrees C or 25 degrees C for up to 24 h or at -80 degrees C for up to 3 months, and repeated freeze/thaw of up to ten cycles, had relatively minor effects on the proteomes based upon our analysis of about 100 peaks. We concluded that low-molecular-weight serum/plasma proteomes were diversely affected by sampling, handling and storage with most change from variations of sampling procedures. We therefore suggest the necessity of standardizing sampling procedure for proteome comparison and biomarker discovery.

Adult↗
PubMed2006

Proteomic dissection of plant development.

Plant development is controlled by complex endogenous genetic programs and responses to environmental cues. Proteome analyses have recently been introduced to plant biology to identify proteins instrumental in these developmental processes. To date most plant proteome studies have been employed to generate reference maps of the most abundant soluble proteins of plant organs at a defined developmental stage. However, proteomics is now also utilized for genetic studies comparing the proteomes of different plant genotypes, for physiological studies analyzing the influences of exogenous signals on a particular plant organ, and developmental studies investigating proteome changes during development. Technical advances are now beginning to allow a proteomic dissection of individual cell types, thus greatly increasing the information revealed by proteome analyses.

Plant Development↗
PubMed2006

Two-dimensional gel electrophoresis as tool for proteomics studies in combination with protein identification by mass spectrometry.

The proteome analysis by 2-DE is one of the most potent methods of analyzing the complete proteome of cells, cell lines, organs and tissues in proteomics studies. It allows a fast overview of changes in cell processes by analysis of the entire protein extracts in any biological and medical research projects. New instrumentation and advanced technologies provide proteomics studies in a wide variety of biological and biomedical questions. Proteomics work is being applied to study antibiotics-resistant strains and human tissues of various brain, lung, and heart diseases. It cumulated in the identification of antigens for the design of new vaccines. These advances in proteomics have been possible through the development of advanced high-resolution 2-DE systems allowing resolution of up to 10 000 protein spots of entire cell lysates in combination with protein identification by new highly sensitive mass spectrometric techniques. The present technological achievements are suited for a high throughput screening of different cell situations. Proteomics may be used to investigate the health effects of radiation and electromagnetic field to clarify possible dangerous alterations in human beings.

Animals↗
PubMed2006

Urinary proteomics.

Protein measurement in urine has been used for many years for the diagnosis and monitoring of renal disease. The pattern of urinary protein excretion can be used to identify the cause of the disease and to classify proteinuria. In recent years, proteomics has proven to be a powerful tool in investigation and clinical medicine. Proteomics employs a protein separation method and the identification of proteins using mass spectrometry. One of the objectives of clinical proteomics is the identification of biological markers of disease. To accomplish this, it is necessary to have a normal proteome of the medium in question, which in our case is urine. Comparison of the normal urinary proteome with the urinary proteome from patients with a defined disease can detect proteins expressed differentially from one another. The aim of this review is to present the situation of urinary proteomics, putting special emphasis on its application in the diagnosis of glomerular diseases, renal allograft rejection, urological cancers and urolithiasis.

Biomarkers↗
PubMed2005

The clinical application of proteomics.

BACKGROUND: Proteomics is defined as a scientific approach used to elucidate all protein species within a cell or tissue, and many researchers are taking advantage of proteomic technology to elucidate protein changes between healthy and diseased states. METHODS: The application of proteomic techniques and strategies to the field of medicine is slowly transforming the way biomarker discovery is conducted. However, the complexity of serum is the source of both its promise to clinical applications and its challenge to proteomic analysis. Like any new technology when it is first introduced, proteomics has been touted with much hope and promise. RESULTS AND CONCLUSIONS: We provide a review of the clinical application of proteomics with the emphasis on current practical issues and challenges facing proteomic research.

Humans↗
PubMed2005

Asthma, the ugly duckling of lung disease proteomics?

The human respiratory system represents a vital but vulnerable system. It is a major target for many diseases such as cancer and asthma. The incidence of these diseases has increased dramatically in the last 40-50 years. In the search for possible new therapies, many experimental tools and methods have been developed to study these diseases, ranging from animal models to in vitro studies. In the last decades, genomic and proteomic approaches have gained a lot of attention. After the major scientific breakthroughs in the field of genomics, it is now widely accepted that to understand biological processes, large-scale protein studies through proteomics techniques are required. In the battle against lung cancer, the proteomics approach has already been successfully implemented. Surprisingly, only a few proteomics studies on the ever-increasing global asthma problem have been published so far. And although proteomics also has its limitations and experimental difficulties, in our opinion, proteomics can definitely contribute to the understanding of a complex disease such as asthma. Therefore, the additional values and possibilities of proteomics in asthma research should be thoroughly investigated. A close collaboration between the different scientific disciplines may eventually lead to the development of new therapeutic strategies against asthma.

Asthma↗
PubMedDate not supplied

Proteomics in developmental toxicology.

The objective of this presentation is to review the major proteomic technologies available to developmental toxicologists and, when possible, to provide examples of how various proteomic technologies have been used in developmental toxicology or toxicology in general. The field of proteomics is too broad for us to go into great depth about each technology, so we have attempted to provide brief overviews supplemented with many references that cover the subjects in more detail. Proteomics tools produce a global view of complex biological systems by examining complex protein mixtures using large-scale, high-throughput technologies. These technologies speed up the process of protein separation, quantification, and identification. As an important complement to genomics, proteomics allows for the examination of the entire complement of proteins in an organism, tissue, or cell-type. Current proteomics technologies not only identify protein expression, but also post-translational modifications and protein interactions. The field of proteomics is expanding rapidly to provide greater volume and quality of protein information to help understand the multifaceted nature of biological systems.

Animals↗
PubMedDate not supplied

Proteomics for the identification of new prostate cancer biomarkers.

Molecular profiling studies of human prostate cancer provide great opportunities to identify new prostate cancer biomarkers to improve prostate cancer detection and treatment. Proteomics has distinct advantages over genomic and ribonucleic acid expression studies because it is the proteins that are ultimately responsible for the malignant phenotype. The goal of traditional proteomic studies is to identify disease-specific biomarkers. Two-dimensional (2-D) gel electrophoresis (polyacrylamide gel electrophoresis; PAGE) coupled with mass spectrometry is the most widely used experimental strategy and, to date, has yielded several potentially relevant prostate cancer biomarkers. A promising prostate cancer biomarker identified by 2-D PAGE and mass spectrometry is annexin I. Studies have already confirmed that annexin I is underexpressed in a majority of early stage prostate cancers. Other non-gel-based proteomic technologies that may have improved sensitivity as compared to 2-D PAGE have recently been developed. An example of this is the ProteomeLab PF 2-D (Beckman Coulter, Inc., Fullerton, CA). The goal of most proteomic studies is to identify biomarkers that can be measured by enzyme-linked immunosorbent assay or immunohistochemistry. Improvements in proteomic technology may be changing this paradigm because there are now efforts to develop proteomic technologies directly into clinical diagnostic tests. An example of this technology is surface-enhanced laser desorption ionization time-of-flight mass spectrometry. Using this technology combined with a pattern recognition based bioinformatics tool, discriminatory spectrum proteomic profiles were generated that could help discriminate men with prostate cancer from those with benign prostates. If several technologic hurdles can be overcome, it is possible that methodology will improve the specificity and sensitivity of prostate cancer detection.

Biomarkers, Tumor↗
PubMed2005

Proteomics.

Proteomics is the measurement of one or more protein populations or proteomes, preferably in a quantitative manner. A protein population may be the set of proteins found in an organism, in a tissue or biofluid, in a cell, or in a subcellular compartment. A population also may be the set of proteins with a common characteristic, for example, those that interact with each other in molecular complexes, those involved in the same process such as signal transduction or cell cycle control, or those that share a common posttranslational modification such as phosphorylation or glycosylation. Proteomics experiments that involve mass spectrometry are divided into five categories: (1) protein identification, (2) protein quantitation or differential analysis, (3) protein-protein interactions, (4) post-translational modifications, and (5) structural proteomics. Each of these proteomics categories is reviewed. Examples are given for quantitative experiments involving two-dimensional gel electrophoresis, and for gel-free analysis using isotope-coded affinity tags. The impact of proteomics on biological research and on drug development is discussed. Challenges for further development in proteomics are presented, including sample preparation, sensitivity, dynamic range, and automation.

Animals↗
PubMed2004

Ultrasensitive proteomics using high-efficiency on-line micro-SPE-nanoLC-nanoESI MS and MS/MS.

Ultrasensitive nanoscale proteomics approaches for characterizing proteins from complex proteomic samples of <50 ng of total mass are described. Protein identifications from 0.5 pg of whole proteome extracts were enabled by ultrahigh sensitivity (<75 zmol for individual proteins) achieved using high-efficiency (peak capacities of approximately 10(3)) 15-microm-i.d. capillary liquid chromatography separations (i.e., using nanoLC, approximately 20 nL/min mobile-phase flow rate at the optimal linear velocity of approximately 0.2 cm/s) coupled on-line with a micro-solid-phase sample extraction and a nanoscale electrospray ionization interface to a 11.4-T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer (MS). Proteome measurement coverage improved as sample size was increased from as little as 0.5 pg of sample. It was found that a 2.5-ng sample provided 14% coverage of all annotated open reading frames for the microorganism Deinococcus radiodurans, consistent with previous results for a specific culture condition. The estimated detection dynamic range for detected proteins was 10(5)-10(6). An improved accurate mass and LC elution time two-dimensional data analysis methodology, used to both speed and increase the confidence of peptide/protein identifications, enabled identification of 872 proteins/run from a single 3-h nanoLC/FTICR MS analysis. The low-zeptomole-level sensitivity provides a basis for extending proteomics studies to smaller cell populations and potentially to a single mammalian cell. Application with ion trap MS/MS instrumentation allowed protein identification from 50 pg (total mass) of proteomic samples (i.e., approximately 100 times larger than FTICR MS), corresponding to a sensitivity of approximately 7 amol for individual proteins. Compared with single-stage FTICR measurements, ion trap MS/MS provided a much lower proteome measurement coverage and dynamic range for a given analysis time and sample quantity.

Amino Acid Sequence↗