蛋白质双向电泳图像分析

随着人类基因组计划的接近完成,蛋白质组（proteome）研究成为新的热点.其中高分辨率的双向电泳（two-dimensional gel electrophoresis, 2-DE）技术使对组织或细胞的整个蛋白质组的综合分析成为可能.近年来这一技术有了很大的改进和提高,特别是图像分析系统,算法更为先进,功能日益强大,操作也更简便,为大规模研究提供了良好的工具.使用新一代的2D图像分析系统,对离体培养的雪旺氏细胞的蛋白质样品双向电泳结果进行了初步分析,探讨了在图像扫描、点检测、背景消除、匹配、结果报告和数据分析各步中的技术问题,并报告了进行2D图像分析的体会.     

Web-accessible proteome databases for microbial research

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.     

Construction of a two-dimensional gel electrophoresis protein database for the Nicotiana tabacum cv. Bright Yellow-2 cell suspension culture

Using two-dimensional gel electrophoresis (2-DE) and electrospray-tandem mass spectrometry (ESI-MS/MS), we have started the proteome analysis of the cell line Nicotiana tabacum cv. Bright Yellow-2 (tobacco BY-2). The BY-2 cell suspension culture is widely used as a model system to study the growth and development of plant cells. We present a protocol describing the sample preparation and 2-DE, enabling us to separate and display more than 1000 proteins from this cell culture. A reference gel was generated, using immobilized pH gradient isoelectric focusing in a linear gradient from pH 3 to 10 and 12% Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Although the tobacco genome is not sequenced yet, a range of protein spots from this reference map was identified by means of a semi-automated liquid chromatography-ESI-quadrupole time of flight-tandem MS (LC-ESI-QTOF-MS-MS) setup and cross-species matching. These data were integrated in a database, which can be accessed at http://tby2-www.uia.ac.be/tby2/. On the on-line reference map, the identified protein spots are hyperlinked to individual protein entries. Each protein entry contains all identification information, as well as links to relevant entries in other on-line databases. Comprehensive search functions are implemented. Especially for an unsequenced but widespread model organism like tobacco BY-2, such a reference database is a convenient source for protein information that brings protein identification within reach without the need for extensive MS. This publicly accessible database provides a solid basis for tobacco BY-2 proteomics in the future.     

Visualisation and analysis of proteomic data from the procyclic form of Trypanosoma brucei

We have undertaken a large scale study of the proteins expressed in the procyclic form of the parasite Trypanosoma brucei, which causes African sleeping sickness, using 2-DE and MS. The complete data set encompasses over 2000 identifications, of which 770 are distinct proteins. We have discovered that multiple protein isoforms appear to be common in T. brucei, as most proteins have been matched to more than one gel spot. We have developed visualisation software to investigate the differences between isoforms, based on the information from the results of database searches with MS data. We are able to highlight instances where PTMs are the most likely cause of variant forms. In other cases, spots that appear reproducibly across replicates contain fragments of proteins, arising either as experimental artefacts or as part of protein degradation. We are also able to classify clusters of gel spots into different groups based on the pattern of peptides that have been matched from MS data. The entire data set is stored within a relational database system that allows complex queries ( http://www.gla.ac.uk/functionalgenomics). Using specific proteins as examples, we demonstrate how the visualisation software and the database query facilities can be used.     

Age-related proteome analysis of the mouse brain: a 2-DE study

2-DE remains the most popular and versatile protein separation method among a rapidly growing array of various proteomics technologies. However, variability in sample processing, experimental design and data analyses results in a limited cross-validation between studies performed in different laboratories. One of the goals of the Human Proteome Organization (HUPO) is to establish standards and guidelines for proteomics studies. We contributed to the HUPO Brain Proteome Project by analyzing brains from neonatal and adult mice using 2-DE. Here we propose a standard workflow to analyze 2-DE images and extract statistically significant differences. After differential analysis and identification by MALDI-TOF/TOF, dihydropyrimidinase-related proteins, brain FABP, stathmin, isocitrate dehydrogenase, gamma enolase, annexin V, glutamine synthetase, creatine kinase B chain, triosephosphate dehydrogenase, and malate dehydrogenase were found differentially expressed between the two groups. The functions and potential mechanisms underlying the variation observed for these proteins are discussed.     

An iterative calibration method with prediction of post-translational modifications for the construction of a two-dimensional electrophoresis database of mouse mammary gland proteins

Protein databases serve as general reference resources providing an orientation on two-dimensional electrophoresis (2-DE) patterns of interest. The intention behind constructing a 2-DE database of the water soluble proteins from wild-type mouse mammary gland tissue was to create a reference before going on to investigate cancer-associated protein variations. This database shall be deemed to be a model system for mouse tissue, which is open for transgenic or knockout experiments. Proteins were separated and characterized in terms of their molecular weight (M(r)) and isoelectric point (pI) by high resolution 2-DE. The proteins were identified using prevalent proteomics methods. One method was peptide mass fingerprinting by matrix-assisted laser desorption/ionization-mass spectrometry. Another method was N-terminal sequencing by Edman degradation. By N-terminal sequencing M(r) and pI values were specified more accurately and so the calibration of the master gel was obtained more systematically and exactly. This permits the prediction of possible post-translational modifications of some proteins. The mouse mammary gland 2-DE protein database created presently contains 66 identified protein spots, which are clickable on the gel pattern. This relational database is accessible on the WWW under the URL: http://www.mpiib-berlin.mpg.de/2D-PAGE.     

ProteomeGRID: towards a high-throughput proteomics pipeline through opportunistic cluster image computing for two-dimensional gel electrophoresis

The quest for high-throughput proteomics has revealed a number of critical issues. Whilst improved two-dimensional gel electrophoresis (2-DE) sample preparation, staining and imaging issues are being actively pursued by industry, reliable high-throughput spot matching and quantification remains a significant bottleneck in the bioinformatics pipeline, thus restricting the flow of data to mass spectrometry through robotic spot excision and protein digestion. To this end, it is important to establish a full multi-site Grid infrastructure for the processing, archival, standardisation and retrieval of proteomic data and metadata. Particular emphasis needs to be placed on large-scale image mining and statistical cross-validation for reliable, fully automated differential expression analysis, and the development of a statistical 2-DE object model and ontology that underpins the emerging HUPO PSI GPS (Human Proteome Organization Proteomics Standards Initiative General Proteomics Standards). The first step towards this goal is to overcome the computational and communications burden entailed by the image analysis of 2-DE gels with Grid enabled cluster computing. This paper presents the proTurbo framework as part of the ProteomeGRID, which utilises Condor cluster management combined with CORBA communications and JPEG-LS lossless image compression for task farming. A novel probabilistic eager scheduler has been developed to minimise make-span, where tasks are duplicated in response to the likelihood of the Condor machines' owners evicting them. A 60 gel experiment was pair-wise image registered (3540 tasks) on a 40 machine Linux cluster. Real-world performance and network overhead was gauged, and Poisson distributed worker evictions were simulated. Our results show a 4:1 lossless and 9:1 near lossless image compression ratio and so network overhead did not affect other users. With 40 workers a 32x speed-up was seen (80% resource efficiency), and the eager scheduler reduced the impact of evictions by 58%.     

Characterisation of rice anther proteins expressed at the young microspore stage

In combination with two-dimensional polyacrylamide gel electrophoresis (2-DE) protein mapping and mass spectrometry analysis, the pattern of gene expression in specific tissues at a specific stage can be displayed and characterised. We used this approach for rice (Oryza sativa L. cultivar Doongara) to display and assign identity to proteins in the anthers at the young microspore stage. Over 4000 anther proteins in the pI range of 4-11 and molecular mass range of 6-122 kDa were reproducibly resolved after silver staining, representing about 10% of the estimated total genomic output of rice. Two hundred and seventy-three protein spots have been extracted either from polyninylidene diffluoride membrane blots or from colloidal Coomassie blue stained 2-DE gels and analysed by N-terminal sequencing, Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MS) analysis or tandem MS sequencing. This enabled identification of 53 anther protein spots representing 43 different proteins. Using the publicly available rice expressed sequence tag (EST) database at the National Centre for Biotechnology Information, a further 37 protein spots were matched to ESTs. After BLAST searching with these ESTs, we were able to predict the identity of 22 of these protein spots. Proteome reference maps of rice anthers have been constructed according to the SWISS-2DPAGE standards and are available for public access at http://semele.anu.edu.au/2d/2d.html.     

Proteome analysis of hepatocellular carcinoma by laser capture microdissection

Hepatocellular carcinoma (HCC) is one of the most frequent visceral neoplasia worldwide and is a multifactorial and multistage pathogenesis that finally leads to the deregulation of cell homeostasis. Laser capture microdissection (LCM) may allow a more ready identification of differences in protein expression in selected cell types or areas of tissue, and microscopic regions as small as 3-5 microm in diameter can be sampled. Here we applied the LCM to the proteomic study of hepatitis B-related HCC and surrounding non-tumor tissues. Proteome alterations were observed using 2-DE and ESI-MS/MS, and alterations in the proteome were examined. Twenty protein spots were selected, of which 11 proteins were significantly altered in the HCC compared with the surrounding non-tumor tissues. Of the proteins that were selected, peroxiredoxin 2, apolipoprotein A-I precursor, 3-hydroxyacyl-CoA dehydrogenase type II, and 14.5-kDa translational inhibitor protein appear to be novel candidates as useful hepatitis B-related HCC markers. This study indicates that LCM is a useful technological method in the proteomic study of cancer tissue. The proteins revealed in this experiment can be used in the future for studies pertaining to hepatocarcinogenesis, or as diagnostic markers and therapeutic targets for HCC associated with hepatitis B virus infection.     

Two-dimensional electrophoretic profiling of normal human kidney glomerulus proteome and construction of an extensible markup language (XML)-based database

To contribute to physiology and pathophysiology of the glomerulus of human kidney, we have launched a proteomic study of human glomerulus, and compiled a profile of proteins expressed in the glomerulus of normal human kidney by two-dimensional gel electrophoresis (2-DE) and identification with matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and/or liquid chromatography-tandem mass spectrometry (LC-MS/MS). Kidney cortices with normal appearance were obtained from patients under surgical nephrectomy due to renal tumor, and glomeruli were highly purified by a standard sieving method followed by picking-up under a phase-contrast microscope. The glomerular proteins were separated by 2-DE with 24 cm immobilized pH gradient strips in the 3-10 range in the first dimension and 26 x 20 cm sodium dodecyl sulfate polyacrylamide electrophoresis gels of 12.5% in the second dimension. Gels were silver-stained, and valid spots were processed for identification through an integrated robotic system that consisted of a spot picker, an in-gel digester, and a MALDI-TOF MS and / or a LC-MS/MS. From 2-DE gel images of glomeruli of four subjects with no apparent pathologic manifestations, a synthetic gel image of normal glomerular proteins was created. The synthetic gel image contained 1713 valid spots, of which 1559 spots were commonly observed in the respective 2-DE gels. Among the 1559 spots, 347 protein spots, representing 212 proteins, have so far been identified, and used for the construction of an extensible markup language (XML)-based database. The database is deposited on a web site (http://www.sw.nec.co.jp/bio/rd/hgldb/index.html) in a form accessible to researchers to contribute to proteomic studies of human glomerulus in health and disease.     

Evaluation of 2-DE protein patterns from pre- and postnatal stages of the mouse brain

Brains of the mouse from three developmental stages, embryo day 16 (Ed16), postnatal stage one week (1W) and eight weeks (8W), were distributed to different laboratories for a collaborative proteome analysis (The Human Brain Proteome Project). As one of the laboratories involved in this project, we separated total protein extracts of the brains by large gel 2-DE. From the 2-DE protein patterns a section was evaluated for each of the three stages according to resolution, reproducibility and quantitative changes using an image analysis software. The evaluated pattern section was selected to allow comparisons of 2-DE patterns between different laboratories on the basis of optimum separation. Changes in protein expression were analysed within two phases of development: Stage Ed16 versus stage 1W and stage 1W versus stage 8W. Out of the 200 protein spots evaluated 5-6% showed quantitative changes in the range of > or = 30% between two stages. The relationship in the frequency of up- and down-regulated protein spots differed between the two investigated phases. Most of the protein spots which showed altered expression between two stages were identified by MS. High quality in protein separation and evaluation is demonstrated.     

Gaining knowledge from previously unexplained spectra-application of the PTM-Explorer software to detect PTM in HUPO BPP MS/MS data

A novel software tool named PTM-Explorer has been applied to LC-MS/MS datasets acquired within the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP). PTM-Explorer enables automatic identification of peptide MS/MS spectra that were not explained in typical sequence database searches. The main focus was detection of PTMs, but PTM-Explorer detects also unspecific peptide cleavage, mass measurement errors, experimental modifications, amino acid substitutions, transpeptidation products and unknown mass shifts. To avoid a combinatorial problem the search is restricted to a set of selected protein sequences, which stem from previous protein identifications using a common sequence database search. Prior to application to the HUPO BPP data, PTM-Explorer was evaluated on excellently manually characterized and evaluated LC-MS/MS data sets from Alpha-A-Crystallin gel spots obtained from mouse eye lens. Besides various PTMs including phosphorylation, a wealth of experimental modifications and unspecific cleavage products were successfully detected, completing the primary structure information of the measured proteins. Our results indicate that a large amount of MS/MS spectra that currently remain unidentified in standard database searches contain valuable information that can only be elucidated using suitable software tools.     

Geometric algorithms for the analysis of 2D-electrophoresis gels.

In proteomics, two-dimensional gel electrophoresis (2-DE) is a separation technique for proteins. The resulting protein spots can be identified either by using picking robots and subsequent mass spectrometry or by visual cross inspection of a new gel image with an already analyzed master gel. Difficulties especially arise from inherent noise and irregular geometric distortions in 2-DE images. Aiming at the automated analysis of large series of 2-DE images, or at the even more difficult interlaboratory gel comparisons, the bottleneck is to solve the two most basic algorithmic problems with high quality: Identifying protein spots and computing a matching between two images. For the development of the analysis software CAROl at Freie Universit?t Berlin, we have reconsidered these two problems and obtained new solutions which rely on methods from computational geometry. Their novelties are: 1. Spot detection is also possible for complex regions formed by several "merged" (usually saturated) spots; 2. User-defined landmarks are not necessary for the matching. Furthermore, images for comparison are allowed to represent different parts of the entire protein pattern, which only partially "overlap." The implementation is done in a client server architecture to allow queries via the internet. We also discuss and point at related theoretical questions in computational geometry.     

PROTICdb: a web-based application to store, track, query, and compare plant proteome data

PROTICdb is a web-based application, mainly designed to store and analyze plant proteome data obtained by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS). The purposes of PROTICdb are (i) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements, and (ii) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of post-translational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs of image analysis and MS identification software, or by filling web forms. 2-D PAGE annotated maps can be displayed, queried, and compared through a graphical interface. Links to external databases are also available. Quantitative data can be easily exported in a tabulated format for statistical analyses. PROTICdb is based on the Oracle or the PostgreSQL Database Management System and is freely available upon request at the following URL: http://moulon.inra.fr/ bioinfo/PROTICdb.     

Development and optimization of two-dimensional-electrophoresis protocol ofLeptospirillum ferriphilum

Leptospirillum ferriphilum is important in bioleaching, in which process it is often under heavy stresses of heavy metal ions and high oxidation reduction potential (ORP). Two-dimensional-electrophoresis (2-DE) and comparative proteomic analysis are useful to investigate the responses ofL. ferriphilum to environmental stresses. But, 2-DE analysis forL. ferriphilum is not successful as the samples ofL. ferriphilum contain low protein concentration, complex composition, high salt concentration, and many other interfering components, which make it difficult for 2-DE analysis. In this research, optimizations on the sample preparation and purification methods, sample volume, sample loading methods for isoelectric focusing (IEF), and gel visualization methods were made. More than 629 Coomassie stained spots in single gel were obtained. The image quality and protein concentration in most of the spots met the requirements for both differential spots analysis and mass-spectrum analysis. The 2-DE protocol forL. ferriphilum was successfully developed for the first time.     

Proteomic approach to identify acute phase response-related proteins with low molecular weight in loach skin following injury

Proteome analysis by two-dimensional gel electrophoresis (2-DE) together with mass spectrometry was applied to screen acute phase response (APR)-related proteins with low molecular weight in loach skin following injury. Furthermore, Western blotting and function tests were applied to confirm the results obtained from the proteomic study. Fifteen APR-related proteins with sixteen spots (PLA with two spots) on a 2-DE map were identified in this study. Furthermore, six were known acute phase proteins including galactose-binding lectin (GBL), lysozyme, C3, CD59, double PLA and 50s ribosomal protein; while ATP kinase, zinc finger protein 183, alpha-neurotoxin homology, angiostatin, serine/threonine kinase, metalloproteinase inhibitor, regulator of G-protein 4, cryptdin-9 and disintegrin trigranin were found by our lab to be APR-related proteins. In addition, our results suggest that proteomes with low molecular weight can be characterized by 2-DE with a Tris-tricine system followed by mass spectrometry.     

Protein spot detection and quantification in 2-DE gel images using machine-learning methods

Two-dimensional gel electrophoresis (2-DE) is the most established protein separation method used in expression proteomics. Despite the existence of sophisticated software tools, 2-DE gel image analysis still remains a serious bottleneck. The low accuracies of commercial software packages and the extensive manual calibration that they often require for acceptable results show that we are far from achieving the goal of a fully automated and reliable, high-throughput gel processing system. We present a novel spot detection and quantification methodology which draws heavily from unsupervised machine-learning methods. Using the proposed hierarchical machine learning-based segmentation methodology reduces both the number of faint spots missed (improves sensitivity) and the number of extraneous spots introduced (improves precision). The detection and quantification performance has been thoroughly evaluated and is shown to compare favorably (higher F-measure) to a commercially available software package (PDQuest). The whole image analysis pipeline that we have developed is fully automated and can be used for high-throughput proteomics analysis since it does not require any manual intervention for recalibration every time a new 2-DE gel image is to be analyzed. Furthermore, it can be easily parallelized for high performance and also applied without any modification to prealigned group average gels.     

PPMdb: a plant plasma membrane database

PPMdb is a proteome database dedicated to proteins from plant plasma membranes. It provides comprehensive two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) maps, partial amino acid sequences and expression data. All this information is gathered and structured in a relational database, after being analyzed and annotated. PPMdb includes active links to related biological databases (EMBL, GenBank, GenPep, and SWISS-PROT and TrEMBL) as well as to MEDLINE abstracts. Information on specific protein spots can be displayed by clicking on the 2-D maps. In addition, users can query the database by accession number, protein name, pI and MW, and cellular location. Access to PPMdb is available at the following URL: http://sphinx.rug. ac.be:8080.