Biomedical subjects

D F Hochstrasser

Publications and source records attributed to D F Hochstrasser.

118 records · Page 7Linked to original sources

PubMedDate not supplied

Improved and simplified in-gel sample application using reswelling of dry immobilized pH gradients.

A simple and inexpensive methacrylate rehydration chamber was built to accommodate ten immobilized pH gradient (IPG) strips. In the chamber, entire IPG gels were used for sample application, with the protein entering the gels during their rehydration. For rehydration, commercially available or laboratory-made strips were positioned in the grooves with the gel in contact with 500 microL of sample for 6 h or overnight. This avoided the use of sample cups, eliminated precipitation at the sample application site, thus improving resolution over the entire pH range of the gels. It also allowed precise control of protein amounts and sample volumes loaded into the IPG gels, and also lowered costs of reagents during rehydration and equilibration owing to the reduced volumes. Up to 5 mg of protein can be loaded on wide IPG gels and up to 15 mg of some samples on narrow pH range gels.

Electrophoresis, Gel, Two-Dimensional↗

PubMedDate not supplied

Detailed peptide characterization using PEPTIDEMASS--a World-Wide-Web-accessible tool.

In peptide mass fingerprinting, there are frequently peptides whose masses cannot be explained. These are usually attributed to either a missed cleavage site during the chemical or enzymatic cutting process, the lack of reduction and alkylation of a protein, protein modifications like the oxidation of methionine, or the presence of protein post-translational modifications. However, they could equally be due to database errors, unusual splicing events, variants of a protein in a population, or artifactual protein modifications. Unfortunately the verification of each of these possibilities can be tedious and time-consuming. To better utilize annotated protein databases for the understanding of peptide mass fingerprinting data, we have written the program "PEPTIDEMASS". This program generates the theoretical peptide masses of any protein in the SWISS-PROT database, or of any sequence specified by the user. If the sequence is derived from the SWISS-PROT database, the program takes into account any annotations for that protein in order to generate the peptide masses. In this manner, the user can obtain the predicted masses of peptides from proteins which are known to have signal sequences, propeptides, transit peptides, simple post-translational modifications, and disulfide bonds. Users are also warned if any peptide masses are subject to change from protein isoforms, database conflicts, or an mRNA splicing variation. The program is freely accessible to the scientific community via the ExPASy World Wide Web server, at the URL address: http://www.expasy.ch/www/tools.html.

Amino Acid Sequence↗

PubMedDate not supplied

The Dictyostelium discoideum proteome--the SWISS-2DPAGE database of the multicellular aggregate (slug).

The cellular slime mold Dictyostelium discoideum is a eukaryotic microorganism which has developmental life stages attractive to the cell and molecular biologist. By displaying the two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) protein map of different developmental stages, the key molecules can be identified and characterised, allowing a detailed understanding of the D. discoideum proteome. Here we describe the preparation of reference gel of the D. discoideum multicellular aggregate, the slug. Proteins were separated by 2-D PAGE with immobilised pH gradients (pH 3.5-10) in the first dimension and sodium dodecyl sulfate (SDS)-PAGE in the second dimension. Micropreparative gels were electroblotted onto polyvinylidene difluoride (PVDF) membranes and 150 spots were visualised by amido black staining. Protein spots were excised and 31 were putatively identified by matching their amino acid composition, estimated isoelectric point (pI) and molecular weight (M(r)) against the SWISS-PROT database with the ExPASy AAcompID tool (http:// expasy.hcuge.ch/ch2d/aacompi.html). A total of 25 proteins were identified by matching against database entries for D. discoideum, and another six by cross-species matching against database entries for Saccharomyces cerevisiae proteins. This map will be available in the SWISS-2DPAGE database.

Animals↗

PubMedDate not supplied

Large-scale protein modelling and integration with the SWISS-PROT and SWISS-2DPAGE databases: the example of Escherichia coli.

Knowledge-based molecular modelling of proteins has proven useful in many instances, including the rational design of mutagenesis experiments, but it has generally been limited by the availability of expensive computer hardware and software. To overcome these limitations, we developed the SWISS-MODEL server for automated knowledge-based protein modelling. The SWISS-MODEL server uses the Brookhaven Protein Data Bank as a source of structural information and automatically generates protein models for sequences which share significant similarities with at least one protein of known three-dimensional structure. We have now used the software framework of the server to generate large collections of protein models, and established the SWISS-MODEL Repository, a new database for automatically generated and theoretical protein models. This repository is directly integrated with the SWISS-PROT and SWISS-2DPAGE databases through the ExPASy World Wide Web server (URL is http://expasy.hcuge.ch). Here we present an illustration of this process by an application to the Escherichia coli sequences.

Bacterial Proteins↗

PubMedDate not supplied

Spermatocytes and round spermatids of rat testis: the difference between in vivo and in vitro protein patterns.

During mammalian spermatogenesis meiotic cell division and spermiogenesis occurs. Gene expression during this process is temporally regulated at the transcriptional and translational levels but the mechanisms are not well understood. In this publication we have investigated the synthesis of proteins in vitro to detect the proteins with a high metabolic turnover and to compare them with the in vivo protein map. RNA of spermatocytes and round spermatid cell populations, purified by centrifugal elutriation, and total testis was isolated. The poly A+ mRNA fraction was translated using a rabbit reticulocyte lysate. The translation products were separated by two-dimensional (2-D) gel electrophoresis using nonlinear 3.5-10 immobilized pH gradients for the first-dimensional separation. The gels with 35S-translated proteins were transferred onto polyvinylidene difluoride (PVDF) membranes and scanned using a phosphorimager. A highly reproducible and complex protein pattern was obtained using this methodology. Only rat testis messages were translated. Using Melanie 2 software we could compare and detect more than 1000 proteins on 2-D radioactive images. Some changes could be observed in protein expression between the different cell types but they were not statistically significant. The comparison between the 2-D rat testis map and the in vitro translated patterns show no matching between any spots. This result suggests that the post-transcriptional modifications occurring in the reticulocyte system are not the same as those that occur in vivo in the testis. Rabbit reticulocyte proteins were detected by staining PVDF membranes with colloidal gold. Rat testis and reticulocyte patterns were completely different.

Animals↗

PubMedDate not supplied

Renal cell carcinoma and normal kidney protein expression.

Renal cell carcinoma (RCC), a human kidney cancer from the proximal tubular epithelium, accounts for about 3% of adult malignancies. Molecular and cytogenetic analysis have highlighted deletions, translocations, or loss of heterozygosity in the 3p21-p26, a putative RCC locus, as well as in 6q, 8p, 9pq, and 14pq. Studies on phenotypic expression of human kidney tissue and on post-translational modifications in RCC have not yet provided a marker for early renal cell carcinoma diagnosis. Current diagnostic methods do not help to detect the tumor before advanced stages. We therefore used two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) to study normal and tumor kidney tissues in ten patients suffering from RCC. A human kidney protein map in the SWISS-2DPAGE database accessible through the ExPASy WWW Molecular Biology Server was established. Of 2789 separated polypeptides, 43 were identified by gel comparison, amino acid analysis, N-terminal sequencing, and/or immunodetection. The comparison between normal and tumor kidney tissues showed four polypeptides to be absent in RCC. One of them was identified as ubiquinol cytochrome c reductase (UQCR), whose locus has elsewhere been tentatively assigned to chromosome 19p12 or chromosome 22. A second polypeptide was identified as mitochondrial NADH-ubiquinone oxido-reductase complex I whose locus is located on chromosome 18p11.2 and chromosome 19q13.3. These result suggest that the lack of UQCR and of mitochondrial NADH-ubiquinone oxidoreductase complex I expression in RCC may be caused by unknown deletions, or by changes in gene transcription or translation. It might indicate that mitochondrial disfunction plays a major role in RCC genesis or evolution.

Amino Acid Sequence↗

PubMedDate not supplied

Specific sample preparation in colorectal cancer.

Large tissue samples from ten patients operated for colorectal cancer were prepared in the operating room in iced phosphate buffered saline, containing ethylene diaminetetraacetic acid and protease inhibitors. After cutting the specimens into small fragments, the tissues were gently pressed through a steel mesh. Membranes were permeabilized in chilled ethanol 70% to allow cytosolic fluoresceine isothiocyanate labeling, performed with anti-cytokeratin (CAM 5.2) antibodies. Samples were quantitatively sorted with a fluorescence activated cell sorter (FACS) and denatured before processing separation by two-dimensional electrophoresis on polyacrylamide gels. This procedure made it possible to sample about 4 x 10(7) viable normal and tumoral cells before fixation, and up to 4 x 10(6) cells after FACS. The gels run before and after fixation showed no major differences. The rate of cytokeratin-positive cells in the samples was the following (mean, CI 5-95%): mucosa 29.5% (8.9-66.7%), tumor 44.3% (6.6-94.8%). The epithelial cell content in colorectal cancer and normal mucosa shows important intersample variations. This is important for any comparison of fresh samples, whether at DNA, RNA, or at the protein level. We propose a method allowing the preparation of pure epithelial cell samples from normal and tumoral colonic fresh mucosa.

Colorectal Neoplasms↗

PubMedDate not supplied

Simultaneous analysis of cyclin and oncogene expression using multiple monoclonal antibody immunoblots.

Cell dysfunction or dysregulation in cancer generally results from complex gene interactions, numerous cellular events and environmental influences which modify gene expression or post-translational protein modifications. Genetic analysis in itself cannot always predict or diagnose multigenic diseases. The major technical difficulty is thus to detect, identify and measure simultaneously the expression of several genes and the post-translational modifications of their products. In order to progress to this direction, this paper describes a simple immunoblot method using several monoclonal anti-bodies to simultaneously analyze oncogene expression and cell cycle specific checkpoints in patient solid biopsies and transformed cell lines. One mg of normal human liver biopsy and HEPG2 (hepatoblastoma-derived cell line) protein samples have been separated by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and transferred onto polyvinylidene difluoride (PVDF) membranes. The membranes were stained with amido black, scanned and tested separately with the nine monoclonal antibodies p53, c-myc, PCNA, MEK1, pan-ras, Cip1, Cdc2, Kip1, and TCTP. The nine antibodies of interest were then combined to form a mixture, and simultaneously used as the primary antibodies. This antibody mixture simultaneously detected the nine proteins of interest on both samples and it demonstrated the extensive expression changes and the presence of various isoforms most likely due to post-translational modifications of gene products.

Antibodies, Monoclonal↗

PubMedDate not supplied

Automatic learning strategies and their application to electrophoresis analysis.

Automatic learning plays an important role in image analysis and pattern recognition. A taxonomy of automatic learning strategies is presented; this categorization is based on the amount of inferences the learning element must perform to bridge the gap between environmental and system knowledge representation level. Four main categories are identified and described: rote learning, learning by deduction, learning by induction, and learning by analogy. An application of learning by induction to medical image analysis is then exposed. It consists in the classification of two-dimensional gel electrophoretograms into meaningful distinct classes, as well in their conceptual description.

Electrophoresis, Gel, Two-Dimensional↗

PubMedDate not supplied

A clinical molecular scanner: the Melanie project.

We developed an expert system to analyze and interpret protein maps. This system, Melanie (medical electrophoresis analysis interactive expert), can distinguish between normal and cirrhotic liver and identify various types of cancer on the basis of protein patterns in biopsy specimens. Our findings suggest that some diseases associated with toxic compounds or modifications of the human genome can be diagnosed by expert systems that analyze protein maps. The combination of protein mapping and computer analysis could result in a clinically useful "molecular scanner". The massive amount of information analyzed and stored in such studies requires new strategies, including centralized databases and image transmission over networks. Increased understanding of protein expression and regulation will enhance the importance of the human genome project in medicine and biology.

Computer Systems↗