The SWISS-2DPAGE database of two-dimensional polyacrylamide gel electrophoresis, its status in 1995

2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments

Background

The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed.

Results

In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application.

Conclusion

We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage.

Proteome analysis of non-model plants: a challenging but powerful approach

Biological research has focused in the past on model organisms and most of the functional genomics studies in the field of plant sciences are still performed on model species or species that are characterized to a great extent. However, numerous non-model plants are essential as food, feed, or energy resource. Some features and processes are unique to these plant species or families and cannot be approached via a model plant. The power of all proteomic and transcriptomic methods, that is, high-throughput identification of candidate gene products, tends to be lost in non-model species due to the lack of genomic information or due to the sequence divergence to a related model organism. Nevertheless, a proteomics approach has a great potential to study non-model species. This work reviews non-model plants from a proteomic angle and provides an outline of the problems encountered when initiating the proteome analysis of a non-model organism. The review tackles problems associated with (i) sample preparation, (ii) the analysis and interpretation of a complex data set, (iii) the protein identification via MS, and (iv) data management and integration. We will illustrate the power of 2DE for non-model plants in combination with multivariate data analysis and MS/MS identification and will evaluate possible alternatives.

The Escherichia coli proteome: past, present, and future prospects

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects.

Proteome and proteomics for the research on protein alterations in aging

Functional decline of tissues in aged animals is a result of cellular aging. Though any process of somatic cell aging basically depends on genomic instructions, phenotypes of aged cells are expressed in a given internal environment of each cell type that was made with translated proteins and post-translationally modified products. Therefore, research on age-dependent protein alterations in each cell type is very important in clarifying mechanisms of aging. The novel term "proteome" is a compound of "protein" and "genome," which means constitutive whole proteins including post-translationally modified products in a cell type. Proteomics is a novel strategy for analyzing proteomes. In proteomics, high resolution two-dimensional electrophoresis is exclusively performed for isolation of proteins followed by mass spectrometry for identification of proteins and determination of modifications. Thus, proteomics is becoming appreciated as a powerful tool to find out proteins responsible for cellular aging, symptoms of senility and geriatric diseases.

The BPP (protein biochemistry and proteomics) two-dimensional electrophoresis database

The BPP (protein biochemistry and proteomics) two-dimensional electrophoresis (2-DE) database (http://www-smbh.univ-paris13.fr/lbtp/Biochemistry/Biochimie/bque.htm) was established in 1998. The current release contains 11 reference maps from human hematopoietic and lymphoid cell line samples. These reference maps have now 255 identified spots, corresponding to 84 protein entries. The World Wide Web (WWW) presentation is designed to allow public access to the available 2-DE data together with logical connections to databases providing complementary information.

Solubilization of delipidated macrophage membrane proteins for analysis by two-dimensional electrophoresis

Two-dimensional electrophoresis of proteins is often precluded due to the lack of solubilization of cell membrane extracts in an aqueous medium. Various additives and detergents have been used to circumvent the problem, but their efficacy may not be satisfactory. In this study, the removal of lipidic components of the cell membrane extract with chloroform-methanol was used to achieve solubilization. Optimal delipidation was obtained with acetone washings. This procedure increased solubilization of membrane proteins from a murine macrophage cell line, thus showing a substantial improvement in gel resolution. The two-dimensional gels loaded with delipidated extract proved to be free of smearing and horizontal streaking. In addition, other protein spots were revealed that were not detected in the gels loaded with undelipidated cell membrane extract.

Two-dimensional gel electrophoresis analyses identify nucleophosmin as an estrogen regulated protein associated with acquired estrogen-independence in human breast cancer cells

We have used two-dimensional gel electrophoresis to identify proteins associated with estrogen-induced proliferation in MCF-7 breast cancer cells and their progression to estrogen-independent proliferation. We compared the total cellular proteins from MCF-7 cells and an estrogen independent derivative of the MCF-7 cells MCF-7/LCC1 (Brünner et al. Cancer Research 1993, 53, 283-290), each grown with and without estradiol. These comparisons reveal seven estrogen-regulated proteins. Three of these proteins (HI-1: 36 kDa/pI 4.5, HI-10: 40 kDa/pI 5.5 and HI-19: 62 kDa/pI 5.0) exhibit a 'progression-like' pattern, being induced by estradiol in MCF-7 cells and constitutively present/upregulated in the MCF-7/LCC1 growing without estradiol. HI-11 (65 kDa/pI 5.5) is strongly induced by estradiol in MCF-7 cells but constitutively downregulated and unresponsive to estradiol in the MCF-7/LCC1 cells. Two proteins exhibit a suppressor pattern and are downregulated by estradiol in the estrogen-dependent MCF-7 cells (HI-3: 44 kDa/pI 4.4 and HI-4: 56 kDa/ pI 5.2) and present in MCF-7/LCC1 cells growing without estradiol at levels comparable to that seen in estrogen-treated MCF-7 cells. One protein (HI-9: 68 kDa/pI 5.5) exhibits a marked estrogen regulated pI shift, rather than changes in abundance. We purified and sequenced the HI-10 protein, which we identified as the nucleolar protein, nucleophosmin (NPM). One- and two-dimensional Western blot analyses of MCF-7/LCC1 cell lysates confirmed that HI-10 is immunoreactive with an antinucleophosmin antibody. Western blotting also confirmed the estrogenic regulation of NPM seen in the initial two-dimensional gel electrophoresis studies. Thus, NPM is induced by estradiol in the MCF-7 cells and upregulated in the MCF-7/LCC1 cells growing without estrogen, clearly associating its expression with an acquired estrogen-independent phenotype. NPM has several potentially important roles in regulating cell function and signaling. It is a substrate for phosphorylation by p34cdc2 kinase, protein kinase C and nuclear kinase II, and a repressor of the transcriptional regulating activities of both the IRF-1 tumor suppressor protein and the YY1 transcription factor. Studies are currently underway to determine which of these NPM functions may be involved in the hormonal progression of breast cancer.

Integrated access to genomic and other bioinformation: an essential ingredient of the drug discovery process

Due to the high rate of data production and the need of researchers to have rapid access to new data, public databases have become the major medium through which genome mapping and sequencing data as well as macromolecular structural data are published. There are now more than 250 databases of biomolecular, structural, genetic, or phenotypic data, many of which are doubling in size annually. These databases, many of which were created and are maintained by experimentalists for their own research use, provide valuable collections of organized, validated data. However, the very number and diversity of databases now make efficient data resource discovery as important as effective data resource use. Existing autonomous biological databases contain related data which are more valuable when interconnected than when isolated. Political and scientific realities dictate that these databases will be built by different teams, in different locations, for different purposes, and using different data models and supporting DBMSs. As a consequence, connecting the related data they contain is not straightforward. Experience with existing biological databases indicates that it is possible to form useful queries across these databases, but that doing so usually requires expertise in the semantic structure of each source database. Advancing to the next level of integration among biological information resources poses significant technical and sociological challenges.

Make2ddb: a simple package to set up a two-dimensional electrophoresis database for the World Wide Web

Two-dimensional electrophoresis (2-DE) has become a highly reproducible protein separation technique that currently serves as the main basis for proteome research and in particular for protein identification. Also, the Internet provides large utilities for exchanging data, and we can observe increased interest among scientists to build remote 2-DE databases, since many members of the concerned community are now able to access the data. By preparing the data and programs that are required to create a federated 2-DE database, the Make2ddb package, described here, helps to build such a database on the user own World Wide Web site.

Rapid access to biomedical knowledge with GeneCards and HotMolecBase: implications for the electrophoretic analysis of large sets of gene products

Rapid access to well-organized information about gene products is important for many studies that simultaneously monitor large sets of those factors, for example with electrophoretic methods. HotMolecBase and GeneCards, Internet resources that may be accessed from our Bioinformatics homepage at http://bioinfo.weizmann.ac.il/, have been designed to address similar problems. GeneCards presents semi-automatically collected information about all approved human genes and their products (with a focus on cellular functions and medical aspects), and offers a new kind of knowledge navigation guidance system that interactively guides the information-seeking scientist to relevant information. On the other hand, HotMolecBase is a collection of more extensive hypertext fact sheets about a small set of medically interesting molecules (mainly proteins) that are regarded as especially promising targets for drug development. Together, both resources may help scientists world-wide to find their way in the growing labyrinth of biomedical information on the World Wide Web. In the present article, we want to explain how these resources may be used by researchers who want to access information related to particular spots on two-dimensional electrophoresis gels.

Towards a proteome project of cyanobacterium Synechocystis sp. strain PCC6803: linking 130 protein spots with their respective genes

Following the complete sequencing of the genome of the univellular cyanobacterium, Synechocystis sp. strain PCC6803 within our institute, a protein-gene linkage map of this photosynthetic microorganism was successfully constructed for 130 high abundance proteins present on two-dimensional gels. An additional six proteins were analyzed, but were probably encoded extrachromosomally. In order to demonstrate the usefulness of this protein-gene linkage map, we analyzed the changes that occur in cellular proteins after illumination of PCC6803 cells. The results indicate that this protein-gene linkage map greatly simplifies the identification process of such modulated genes. After illumination, at least three distinctive spots with reduced intensity were detected on two-dimensional gels and the corresponding genes of two of these were successfully identified as chaperonin 2 and a Tortula ruralis rehydrin-related gene. Thus, the combination of the protein-gene linkage map and two-dimensional gel electrophoresis should permit a comprehensive analyses of the proteins encoded by the genome (i.e., "proteome") of this photosynthetic autotroph. This post-genome project represents a productive way of exploiting the information obtained from the sequencing of the cyanobacterium genome.

Bioinformatics--principles and potential of a new multidisciplinary tool

The materials of bioinformatics are biological data, and its methods are derived from a wide variety of computational techniques. Recent years have seen an explosive growth in biological data, and the development of novel computational methods. These methods have become essential to research progress in structural biology, genomics, structure-based drug design and molecular evolution. The development and maintenance of a robust infrastructure of biological data is of equal importance if biotechnology is to take maximum advantage of research advances in a wide variety of fields. While bioinformatics has already made important contributions, it faces significant challenges as it matures.