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PubMed2003

Open architecture expression profiling of plant transcriptomes and gene discovery using GeneCalling technology.

The recent rapid developments in genomics tools, technologies, and bioinformatics have revolutionized gene expression analysis. It is now routine to measure gene expression modulation at the genomic level. GeneCalling technology is an open architecture system capable of assaying more than 95% of genes expressed in a tissue. Unlike the closed systems, GeneCalling is not dependent upon an existing sequence or clone database. GeneCalling uses as low as 50 pg of the cDNA from samples and identifies cDNA fragments that are differentially modulated within a set of samples. With the use of 96 pairs of restriction enzymes, more than 30,000 cDNA fragments are routinely assayed to identify those that are differentially modulated. Specific processes, such as SeqCalling, Trace Poisoning, and GeneCall Poisoning, are set up to not only confirm the known genes, but also to clone and analyze unknown and novel genes that have an interesting expression profile. GeneCalling has been successfully applied to expression profiling of several plant and fungal species, and resulted in identification and characterization of genes that are useful in commercial applications towards improving agriculturally important traits in plants.

DNA, Complementary↗
PubMed2006

Gene profiling and bioinformatic analysis of Schwann cell embryonic development and myelination.

To elucidate the molecular mechanisms involved in Schwann cell development, we profiled gene expression in the developing and injured rat sciatic nerve. The genes that showed significant changes in expression in developing and dedifferentiated nerve were validated with RT-PCR, in situ hybridisation, Western blot and immunofluorescence. A comprehensive approach to annotating micro-array probes and their associated transcripts was performed using Biopendium, a database of sequence and structural annotation. This approach significantly increased the number of genes for which a functional insight could be found. The analysis implicates agrin and two members of the collapsin response-mediated protein (CRMP) family in the switch from precursors to Schwann cells, and synuclein-1 and alphaB-crystallin in peripheral nerve myelination. We also identified a group of genes typically related to chondrogenesis and cartilage/bone development, including type II collagen, that were expressed in a manner similar to that of myelin-associated genes. The comprehensive function annotation also identified, among the genes regulated during nerve development or after nerve injury, proteins belonging to high-interest families, such as cytokines and kinases, and should therefore provide a uniquely valuable resource for future research.

Agrin↗
PubMed2005

MOLE: a data management application based on a protein production data model.

MOLE (mining, organizing, and logging experiments) has been developed to meet the growing data management and target tracking needs of molecular biologists and protein crystallographers. The prototype reported here will become a Laboratory Information Management System (LIMS) to help protein scientists manage the large amounts of laboratory data being generated due to the acceleration in proteome research and will furthermore facilitate collaborations between groups based at different sites. To achieve this, MOLE is based on the data model for protein production devised at the European Bioinformatics Institute (Pajon A, et al., Proteins in press).

Algorithms↗
PubMed2003

Bioinformatics Resources for In Silico Proteome Analysis.

In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species-mainly the human-have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.

Journal Article↗
PubMed1997

Health On the Net automated database of health and medical information.

With the number of World Wide Web sites growing every day, the problem is not just to find information, but to locate the right piece of information. Current World Wide Web search engines have not resolved this problem as they most often return a long list of documents. The search result is then unusable because of the large number of answers from different domains and topics. Only complex queries may, in a given situation, produce a limited number of potentially relevant documents. To make searches more efficient and usable by common users, we now need intelligent and specialised search engines on the Net [1,2]. Health On the Net Foundation and the Molecular Imaging and Bioinformatics Laboratory at Geneva University Hospital have developed Multi-Agent Retrieval Vagabond on Information Networks (MARVIN), a robot that searches sites and documents specifically related to a given specialised field. One such robot has already been implemented and used for the medical and the 2D electrophoresis domains. Health On the Net Foundation has implemented the corresponding search engines, MedHunt (http://www.hon.ch/cgi-bin/find) for the medical field and 2DHunt (http://www.hon.ch/cgi-bin/2DHunt/find) for the 2D electrophoresis field.

Computer Communication Networks↗
PubMed1999

A new liquid chromatography/tandem mass spectrometric approach for the identification of class I major histocompatibility complex associated peptides that eliminates the need for bioassays.

Cell-surface class I major histocompatibility complex (MHC) molecules present processed self- and nonself-peptides to thymus-derived (T) lymphocytes, allowing the intracellular compartment of cells to be sampled in order to detect infection. Since the class I MHC-peptide complex plays a critical role in cell-mediated immunity, it is important to obtain sequence information on the MHC-associated peptides unique to infected cells as a prelude to the development of vaccines. Here, we outline and test an alternative strategy for identifying the proteins that are processed through the MHC pathway. This new strategy eliminates the necessity of developing and maintaining cytotoxic T lymphocyte (CTL) lines for peptide identification. In this new approach genome sequences from the infecting agent are scanned for stretches of amino acids that match a particular MHC binding motif. Molecular masses from these putative MHC-binding peptide sequences are calculated and compared to those found for peptides isolated from pathogen-infected host cells using liquid chromatography/mass spectrometry (LC/MS). Peptides with masses matching those in the database are then analyzed by tandem mass spectrometry (MS/MS) to determine their identity. Using this approach we were able to confirm the processing and presentation of two Trypanosoma cruzi proteins by the MHC class I pathway. These data suggest that a rigorous approach employing two-dimensional separations in conjunction with MS/MS and bioinformatics is a feasible means of identifying pathogen gene products of immunological interest when a CTL assay is unavailable or unsuccessful.

Animals↗
PubMed1999

Hepatitis C virus encodes a selenium-dependent glutathione peroxidase gene. Implications for oxidative stress as a risk factor in progression to hepatocellular carcinoma.

AIM: Using structural bioinformatics methods, the aim is to assess the hypothesis that hepatitis C virus (HCV) encodes a glutathione peroxidase (GPx) gene in an overlapping reading frame, linking HCV expression and pathogenesis to the Se status and dietary oxidant/Antioxidant balance of the host. METHODS: The putative HCV GPx gene was identified by searching viral sequence databases, using conserved GPx active site sequences as probes, giving particular weight to the UGA (selenocysteine) codon. Multiple sequence alignments were generated and analyzed to validate the sequence similarity, and to establish the degree of conservation of the identified genomic features in HCV. Molecular modeling was used to assess the structural feasibility of the proposed homology. RESULTS: The GPx homology region overlaps the NS4 gene, and is well conserved in HCV. The sequence similarity of the conserved active site regions to a set of known GPx is high (4 to 6 SD greater than expected for similar random sequences). The computed strain energy of a molecular model of the HCV GPx is energetically favorable, comparable to the bovine GPx structure. CONCLUSIONS: By linking HCV replication and pathogenesis to the Se status and dietary oxidant/antioxidant balance of the host, the existence of a viral GPx gene could help to explain why HCV disease progression is accelerated by oxidant stresses such as alcoholism and iron overload.

Amino Acid Sequence↗
PubMed2004

A genomic perspective on protein tyrosine phosphatases: gene structure, pseudogenes, and genetic disease linkage.

The protein tyrosine phosphatases (PTPs) are now recognized as critical regulators of signal transduction under normal and pathophysiological conditions. In this analysis we have explored the sequence of the human genome to define the composition of the PTP family. Using public and proprietary sequence databases, we discovered one novel human PTP gene and defined chromosomal loci and exon structure of the additional 37 genes encoding known PTP transcripts. Direct orthologs were present in the mouse genome for all 38 human PTP genes. In addition, we identified 12 PTP pseudogenes unique to humans that have probably contaminated previous bioinformatics analysis of this gene family. PCR amplification and transcript sequencing indicate that some PTP pseudogenes are expressed, but their function (if any) is unknown. Furthermore, we analyzed the enhanced diversity generated by alternative splicing and provide predicted amino acid sequences for four human PTPs that are currently defined by fragments only. Finally, we correlated each PTP locus with genetic disease markers and identified 4 PTPs that map to known susceptibility loci for type 2 diabetes and 19 PTPs that map to regions frequently deleted in human cancers. We have made our analysis available at http://ptp.cshl.edu or http://science.novonordisk.com/ptp and we hope this resource will facilitate the functional characterization of these key enzymes.

Amino Acid Sequence↗
PubMed2025

Visualization using NIPTviewer support the clinical interpretation of noninvasive prenatal testing results.

BACKGROUND: Noninvasive prenatal testing (NIPT) is increasingly used to screen for fetal chromosomal aneuploidy by analyzing cell-free DNA (cfDNA) in peripheral maternal blood. The method provides an opportunity for early detection of large genetic abnormalities without an increased risk of miscarriage due to invasive procedures. Commercial applications for use at clinical laboratories often take advantage of DNA sequencing technologies and include the bioinformatic workup of the sequence data. The interpretation of the test results and the clinical report writing, however, remains the responsibility of the diagnostic laboratory. In order to facilitate this step, we developed NIPTviewer, a web-based application to visualize and guide the interpretation of NIPT data results. RESULTS: NIPTviewer has a database functionality to store the NIPT results and a web interface for user interaction and visualization. The application has been implemented as part of a novel analysis pipeline for NIPT in a diagnostic laboratory at Uppsala University Hospital. The validation data set included 84 previously analyzed plasma samples with known results regarding chromosomes 13, 18, 21, X and Y. They were sequenced in six different experiments, uploaded to NIPTviewer and assigned to a clinical laboratory geneticist for interpretation. The results of all previously analyzed samples were replicated. CONCLUSION: NIPTviewer facilitates NIPT results interpretation and has been implemented as part of a NIPT analysis routine that was accredited by the national accreditation body for Sweden (Swedac).

Humans↗
PubMed2001

A bioinformatical approach suggests the function of the autoimmune hepatitis target antigen soluble liver antigen/liver pancreas.

Antibodies to a soluble liver antigen/liver pancreas (SLA/LP) appear to be highly specific for the diagnosis of autoimmune hepatitis. The SLA/LP target antigen was recently identified as a hitherto unknown gene encoding 474 amino acid residues. The function of this antigen remains unclear, because it does not share sequence homology with proteins of known function stored in any of the publicly accessible databases. Therefore we used a new theoretical method called fold recognition and could show that the SLA/LP sequence is compatible with the architecture of the superfamily of pyridoxal phosphate (PLP; vitamin B6)-dependent transferases. Its function is likely to be that of a serine hydroxymethyltransferase and may be an important enzyme in the thus far poorly understood selenocysteine pathway.

Amino Acid Sequence↗
PubMed2006

A multi-step approach to time series analysis and gene expression clustering.

MOTIVATION: The huge growth in gene expression data calls for the implementation of automatic tools for data processing and interpretation. RESULTS: We present a new and comprehensive machine learning data mining framework consisting in a non-linear PCA neural network for feature extraction, and probabilistic principal surfaces combined with an agglomerative approach based on Negentropy aimed at clustering gene microarray data. The method, which provides a user-friendly visualization interface, can work on noisy data with missing points and represents an automatic procedure to get, with no a priori assumptions, the number of clusters present in the data. Cell-cycle dataset and a detailed analysis confirm the biological nature of the most significant clusters. AVAILABILITY: The software described here is a subpackage part of the ASTRONEURAL package and is available upon request from the corresponding author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Artificial Intelligence↗
PubMed2003

Mapping by sequencing the Pneumocystis genome using the ordering DNA sequences V3 tool.

A bioinformatics tool called ODS3 has been created for mapping by sequencing. The tool allows the creation of integrated genomic maps from genetic, physical mapping, and sequencing data and permits an integrated genome map to be stored, retrieved, viewed, and queried in a stand-alone capacity, in a client/server relationship with the Fungal Genome Database (FGDB), and as a web-browsing tool for the FGDB. In that ODS3 is programmed in Java, the tool promotes platform independence and supports export of integrated genome-mapping data in the extensible markup language (XML) for data interchange with other genome information systems. The tool ODS3 is used to create an initial integrated genome map of the AIDS-related fungal pathogen, Pneumocystis carinii. Contig dynamics would indicate that this physical map is approximately 50% complete with approximately 200 contigs. A total of 10 putative multigene families were found. Two of these putative families were previously characterized in P. carinii, namely the major surface glycoproteins (MSGs) and HSP70 proteins; three of these putative families (not previously characterized in P. carinii) were found to be similar to families encoding the HSP60 in Schizosaccharomyces pombe, the heat-shock psi protein in S. pombe, and the RNA synthetase family (i.e., MES1) in Saccharomyces cerevisiae. Physical mapping data are consistent with the 16S, 5.8S, and 26S rDNA genes being single copy in P. carinii. No other fungus outside this genus is known to have the rDNA genes in single copy.

Computational Biology↗
PubMedDate not supplied

Correlation between gene expression and GO semantic similarity.

This research analyzes some aspects of the relationship between gene expression, gene function, and gene annotation. Many recent studies are implicitly based on the assumption that gene products that are biologically and functionally related would maintain this similarity both in their expression profiles as well as in their Gene Ontology (GO) annotation. We analyze how accurate this assumption proves to be using real publicly available data. We also aim to validate a measure of semantic similarity for GO annotation. We use the Pearson correlation coefficient and its absolute value as a measure of similarity between expression profiles of gene products. We explore a number of semantic similarity measures (Resnik, Jiang, and Lin) and compute the similarity between gene products annotated using the GO. Finally, we compute correlation coefficients to compare gene expression similarity against GO semantic similarity. Our results suggest that the Resnik similarity measure outperforms the others and seems better suited for use in Gene Ontology. We also deduce that there seems to be correlation between semantic similarity in the GO annotation and gene expression for the three GO ontologies. We show that this correlation is negligible up to a certain semantic similarity value; then, for higher similarity values, the relationship trend becomes almost linear. These results can be used to augment the knowledge provided by clustering algorithms and in the development of bioinformatic tools for finding and characterizing gene products.

Algorithms↗
PubMed2006

An interactive visualization tool to explore the biophysical properties of amino acids and their contribution to substitution matrices.

BACKGROUND: Quantitative descriptions of amino acid similarity, expressed as probabilistic models of evolutionary interchangeability, are central to many mainstream bioinformatic procedures such as sequence alignment, homology searching, and protein structural prediction. Here we present a web-based, user-friendly analysis tool that allows any researcher to quickly and easily visualize relationships between these bioinformatic metrics and to explore their relationships to underlying indices of amino acid molecular descriptors. RESULTS: We demonstrate the three fundamental types of question that our software can address by taking as a specific example the connections between 49 measures of amino acid biophysical properties (e.g., size, charge and hydrophobicity), a generalized model of amino acid substitution (as represented by the PAM74-100 matrix), and the mutational distance that separates amino acids within the standard genetic code (i.e., the number of point mutations required for interconversion during protein evolution). We show that our software allows a user to recapture the insights from several key publications on these topics in just a few minutes. CONCLUSION: Our software facilitates rapid, interactive exploration of three interconnected topics: (i) the multidimensional molecular descriptors of the twenty proteinaceous amino acids, (ii) the correlation of these biophysical measurements with observed patterns of amino acid substitution, and (iii) the causal basis for differences between any two observed patterns of amino acid substitution. This software acts as an intuitive bioinformatic exploration tool that can guide more comprehensive statistical analyses relating to a diverse array of specific research questions.

Amino Acid Sequence↗
PubMed2005

Oral cancer plasma tumor marker identified with bead-based affinity-fractionated proteomic technology.

BACKGROUND: There is no plasma marker for detecting oral cancer, one of the most frequent cancers worldwide. We developed a bead-based affinity-fractionated proteomic method to discover a novel plasma marker for oral cancer. METHODS: Affinity purification of heparinized plasma with magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis were used to screen potential oral cancer markers. We compiled MS protein profiles for 57 patients with oral cancer and compared them with profiles from 29 healthy controls. The spectra were analyzed statistically using flexAnalysis and ClinProt bioinformatic software. In each MS analysis, the peak intensities of interest were normalized with an internal standard (adrenocorticotropic hormone 18-39). For identification, affinity bead-purified plasma protein was subjected to MALDI TOF/TOF analysis followed by Mascot identification of the peptide sequences and a search of the National Center for Biotechnology Information protein database. RESULTS: To optimize MALDI-TOF analysis based on the best discriminator of the cancer and control spectra, copper-chelated beads were used for plasma protein profiling. The within- and between-run CVs for assays were <4% and 7%, respectively. Six markers that differentiated between cancer and control spectra were found, with mean (SD) molecular masses of 2664 (1), 2850 (1), 3250 (1), 7735 (2), 7927 (2), and 9240 (2) Da. The 2664-Da marker, identified as a fragment of the fibrinogen alpha-chain, had the highest sensitivity (100%) and specificity (97%) for cancer. CONCLUSION: The high specificity and sensitivity of the fibrinogen alpha-chain fragment suggest that it may be a clinical useful tumor marker.

Adult↗
PubMed2003

Beyond the genome--SMi Conference 27-28 January 2003, London, UK.

Over a decade of astonishing developments, genomics and proteomics have promised a fundamentally new approach to drug discovery. Although there has been an undeniable increase in the range of potential targets available, this has not led to an increased output of the drug discovery pipeline into the clinic. With tighter markets and increasing competition, the major pharmaceutical companies are under intense pressure to achieve rapid, concrete delivery of those early promises, but there remain acute problems in the genes-to-drugs pipeline. This meeting showcased a range of novel approaches from proteomics and bioinformatics to address these problems. A common theme in the range of proteomics offerings was the prioritization of potential novel targets on the basis of their accessibility to drugs and their functional link to disease phenotypes. Informatics and in silico offerings also concentrated on fast, accurate, drug-focused workflows built on large integrative databases and novel data-mined algorithms.

Animals↗
PubMed2003

A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology.

Based on the recent development in the gene ontology and functional domain databases, a new hybridization approach is developed for predicting protein subcellular location by combining the gene product, functional domain, and quasi-sequence-order effects. As a showcase, the same prokaryotic and eukaryotic datasets, which were studied by many previous investigators, are used for demonstration. The overall success rate by the jackknife test for the prokaryotic set is 94.7% and that for the eukaryotic set 92.9%. These are so far the highest success rates achieved for the two datasets by following a rigorous cross-validation test procedure, suggesting that such a hybrid approach may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology. The very high success rates also reflect the fact that the subcellular localization of a protein is closely correlated with: (1). the biological objective to which the gene or gene product contributes, (2). the biochemical activity of a gene product, and (3). the place in the cell where a gene product is active.

Algorithms↗