Search PubMed⌕ Search

Biomedical subjects

Stephen G Oliver

Publications and source records attributed to Stephen G Oliver.

17 recordsLinked to original sources
PubMed2003

A model-based analysis of microarray experimental error and normalisation.

A statistical model is proposed for the analysis of errors in microarray experiments and is employed in the analysis and development of a combined normalisation regime. Through analysis of the model and two-dye microarray data sets, this study found the following. The systematic error introduced by microarray experiments mainly involves spot intensity-dependent, feature-specific and spot position-dependent contributions. It is difficult to remove all these errors effectively without a suitable combined normalisation operation. Adaptive normalisation using a suitable regression technique is more effective in removing spot intensity-related dye bias than self-normalisation, while regional normalisation (block normalisation) is an effective way to correct spot position-dependent errors. However, dye-flip replicates are necessary to remove feature-specific errors, and also allow the analyst to identify the experimentally introduced dye bias contained in non-self-self data sets. In this case, the bias present in the data sets may include both experimentally introduced dye bias and the biological difference between two samples. Self-normalisation is capable of removing dye bias without identifying the nature of that bias. The performance of adaptive normalisation, on the other hand, depends on its ability to correctly identify the dye bias. If adaptive normalisation is combined with an effective dye bias identification method then there is no systematic difference between the outcomes of the two methods.

Algorithms↗
PubMed2003

SiteSeer: Visualisation and analysis of transcription factor binding sites in nucleotide sequences.

The regulation of gene expression is a fundamental process within every living cell, which allows organisms to manage the precise levels of functional gene products with high sensitivity. It is well established that specific DNA sequences located upstream of the transcriptional start site are important in facilitating the binding of regulatory proteins that control the transcription of the gene. Indeed, microarray-based studies have successfully mined the upstream regions of co-expressed genes and discovered over-represented sequences corresponding to known promoter sites. Here we describe a tool for the visualisation of mapped transcription factor binding sites in the upstream regions of either single or grouped eukaryotic genes, which allows users to examine the positions of known and user-defined sites (http://rocky.bms.umist.ac.uk/SiteSeer/). SiteSeer allows the user to map different sections of the TRANSFAC and SCPD databases (or a set of user-defined sites) onto nucleotide sequences. Additionally, users may restrict the analysis by expectation values for certain DNA words as well as by known binding sites specific to a given organism. We believe this tool will prove particularly valuable for biologists who wish to examine sets of co-expressed or functionally-related genes and those who wish to visualise the positions of promoter sequences and generate displays for publications.

5' Flanking Region↗
PubMed2003

High-throughput classification of yeast mutants for functional genomics using metabolic footprinting.

Many technologies have been developed to help explain the function of genes discovered by systematic genome sequencing. At present, transcriptome and proteome studies dominate large-scale functional analysis strategies. Yet the metabolome, because it is 'downstream', should show greater effects of genetic or physiological changes and thus should be much closer to the phenotype of the organism. We earlier presented a functional analysis strategy that used metabolic fingerprinting to reveal the phenotype of silent mutations of yeast genes. However, this is difficult to scale up for high-throughput screening. Here we present an alternative that has the required throughput (2 min per sample). This 'metabolic footprinting' approach recognizes the significance of 'overflow metabolism' in appropriate media. Measuring intracellular metabolites is time-consuming and subject to technical difficulties caused by the rapid turnover of intracellular metabolites and the need to quench metabolism and separate metabolites from the extracellular space. We therefore focused instead on direct, noninvasive, mass spectrometric monitoring of extracellular metabolites in spent culture medium. Metabolic footprinting can distinguish between different physiological states of wild-type yeast and between yeast single-gene deletion mutants even from related areas of metabolism. By using appropriate clustering and machine learning techniques, the latter based on genetic programming, we show that metabolic footprinting is an effective method to classify 'unknown' mutants by genetic defect.

Cells, Cultured↗
PubMed2003

Engineering evolution to study speciation in yeasts.

The Saccharomyces 'sensu stricto' yeasts are a group of species that will mate with one another, but interspecific pairings produce sterile hybrids. A retrospective analysis of their genomes revealed that translocations between the chromosomes of these species do not correlate with the group's sequence-based phylogeny (that is, translocations do not drive the process of speciation). However, that analysis was unable to infer what contribution such rearrangements make to reproductive isolation between these organisms. Here, we report experiments that take an interventionist, rather than a retrospective approach to studying speciation, by reconfiguring the Saccharomyces cerevisiae genome so that it is collinear with that of Saccharomyces mikatae. We demonstrate that this imposed genomic collinearity allows the generation of interspecific hybrids that produce a large proportion of spores that are viable, but extensively aneuploid. We obtained similar results in crosses between wild-type S. cerevisiae and the naturally collinear species Saccharomyces paradoxus, but not with non-collinear crosses. This controlled comparison of the effect of chromosomal translocation on species barriers suggests a mechanism for the generation of redundancy in the S. cerevisiae genome.

Aneuploidy↗
PubMed2003

Using yeast to place human genes in functional categories.

The availability of the draft sequence of the human genome has created a pressing need to assign functions to each of the 35,000 or so genes that it defines. One useful approach for this purpose is to use model organisms for both bioinformatic and functional comparisons. We have developed a complementation system, based on the model eukaryote Saccharomyces cerevisiae, to clone human cDNAs that can functionally complement yeast essential genes. The system employs two regulatable promoters. One promoter, tetO (determining doxycycline-repressible expression), is used to control essential S. cerevisiae genes. The other, pMET3 (which is switched off in the presence of methionine), is employed to regulate the expression of mammalian cDNAs in yeast. We have demonstrated that this system is effective for both individual cDNA clones and for cDNA libraries, permitting the direct selection of functionally complementing clones. Three human cDNA libraries have been constructed and screened for clones that can complement specific essential yeast genes whose expression is switched off by the addition of doxycycline to the culture medium. The validity of each complementation was checked by showing that the yeast cells stop their growth in the presence of doxycycline and methionine, which represses the expression of the yeast and mammalian coding sequence, respectively. Using this system, we have screened 25 tetO replacement strains and succeeded in isolating human cDNAs complementing six essential yeast genes. In this way, we have uncovered a novel human ubiquitin-conjugating enzyme, have isolated a human cDNA clone that may function as a signal peptidase and have demonstrated that the functional segment of the human Psmd12 proteosome sub-unit contains a PINT domain.

Cerebellum↗
PubMed2003

An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry.

A method for the global analysis of yeast intracellular metabolites, based on electrospray mass spectrometry (ES-MS), has been developed. This has involved the optimization of methods for quenching metabolism in Saccharomyces cerevisiae and extracting the metabolites for analysis by positive-ion electrospray mass spectrometry. The influence of cultivation conditions, sampling, quenching and extraction conditions, concentration step, and storage have all been studied and adapted to allow direct infusion of samples into the mass spectrometer and the acquisition of metabolic profiles with simultaneous detection of more than 25 intracellular metabolites. The method, which can be applied to other micro-organisms and biological systems, may be used for comparative analysis and screening of metabolite profiles of yeast strains and mutants under controlled conditions in order to elucidate gene function via metabolomics. Examples of the application of this analytical strategy to specific yeast strains and single-ORF yeast deletion mutants generated through the EUROFAN programme are presented.

Buffers↗
PubMed2003

A systematic approach to modeling, capturing, and disseminating proteomics experimental data.

Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.

Database Management Systems↗
PubMed2003

Mcm1p-induced DNA bending regulates the formation of ternary transcription factor complexes.

The yeast MADS-box transcription factor Mcm1p plays an important regulatory role in several diverse cellular processes. In common with a subset of other MADS-box transcription factors, Mcm1p elicits substantial DNA bending. However, the role of protein-induced bending by MADS-box proteins in eukaryotic gene regulation is not understood. Here, we demonstrate an important role for Mcm1p-mediated DNA bending in determining local promoter architecture and permitting the formation of ternary transcription factor complexes. We constructed mutant mcm1 alleles that are defective in protein-induced bending. Defects in nuclear division, cell growth or viability, transcription, and gene expression were observed in these mutants. We identified one likely cause of the cell growth defects as the aberrant formation of the cell cycle-regulatory Fkh2p-Mcm1p complex. Microarray analysis confirmed the importance of Mcm1p-mediated DNA bending in maintaining correct gene expression profiles and revealed defects in Mcm1p-mediated repression of Ty elements and in the expression of the cell cycle-regulated YFR and CHS1 genes. Thus, we discovered an important role for DNA bending by MADS-box proteins in the formation and function of eukaryotic transcription factor complexes.

Alleles↗
PubMed2002

Comparative assessment of large-scale data sets of protein-protein interactions.

Comprehensive protein protein interaction maps promise to reveal many aspects of the complex regulatory network underlying cellular function. Recently, large-scale approaches have predicted many new protein interactions in yeast. To measure their accuracy and potential as well as to identify biases, strengths and weaknesses, we compare the methods with each other and with a reference set of previously reported protein interactions.

Bias↗
PubMed2002

Tools for the study of genome rearrangements in laboratory and industrial yeast strains.

In order to investigate the extent of genome rearrangements in laboratory and industrial yeast strains, a set of plasmids, containing ca. 300 bp fragments from highly conserved genes from S. cerevisiae, has been constructed. We chose three unique PCR products, each from a single gene, per chromosome: one from close to the centromere, and one from each chromosome end. Using these plasmids as probes to hybridize a Southern blot from a pulsed-field gel electrophoresis separation of the 16 yeast chromosomes, it is possible to identify large chromosomal rearrangements such as reciprocal translocations.

Blotting, Southern↗
PubMed2002

Functional genomics: lessons from yeast.

Functional genomics represents a systematic approach to elucidating the function of the novel genes revealed by complete genome sequences. Such an approach should adopt a hierarchical strategy since this will both limit the number of experiments to be performed and permit a closer and closer approximation to the function of any individual gene to be achieved. Moreover, hierarchical analyses have, in their early stages, tremendous integrative power and functional genomics aims at a comprehensive and integrative view of the workings of living cells. The first draft of the human genome sequence has just been produced, and the complete genome sequences of a number of eukaryotic human pathogens (including the parasitic protozoa Plasmodium, Leishmania, and Trypanosoma) will soon be available. However, the most rapid progress in the elucidation of gene function will initially be made using model organisms. Yeast is an excellent eukaryotic model and at least 40% of single-gene determinants of human heritable diseases find homologues in yeast. We have adopted a systematic approach to the functional analysis of the Saccharomyces cerevisiae genome. A number of the approaches for the functional analysis of novel yeast genes are discussed. The different approaches are grouped into four domains: genome, transcriptome, proteome, and metabolome. The utility of genetic, biochemical, and physico-chemical methods for the analysis of these domains is discussed, and the importance of framing precise biological questions, when using these comprehensive analytical methods, is emphasized. Finally, the prospects for elucidating the function of protozoan genes by using the methods pioneered with yeast, and even exploiting Saccharomyces itself, as a surrogate, are explored.

Fungal Proteins↗
PubMed2002

Stable isotope labelling in vivo as an aid to protein identification in peptide mass fingerprinting.

Peptide mass fingerprinting (PMF) is a powerful technique for identification of proteins derived from in-gel digests by virtue of their matrix-assisted laser desorption/ionization-time of flight mass spectra. However, there are circumstances where the under-representation of peptides in the mass spectrum and the complexity of the source proteome mean that PMF is inadequate as an identification tool. In this paper, we show that identification is substantially enhanced by inclusion of composition data for a single amino acid. Labelling in vivo with a stable isotope labelled amino acid (in this paper, decadeuterated leucine) identifies the number of such amino acids in each digest fragment, and show a considerable gain in the ability of PMF to identify the parent protein. The method is tolerant to the extent of labelling, and as such, may be applicable to a range of single cell systems.

Deuterium↗
PubMed2002

Hybridization array technology coupled with chemostat culture: Tools to interrogate gene expression in Saccharomyces cerevisiae.

Hybridization array technology is increasingly being used for the analysis of gene expression in the yeast Saccharomyces cerevisiae. It is a powerful technique in which the relative abundance of all the mRNA molecules transcribed under a particular condition may be simultaneously measured. However, most studies performed using this technique are carried out in batch culture where the growth rate and environment are continuously changing. Often, the experimental condition being studied also impacts on the growth rate of the cells. Changes in growth rate affect the pattern of gene expression. Consequently, the analysis and interpretation of experimental results obtained in this way are inherently problematic due to the difficulty in discriminating between effects due to the experimental condition per se and concomitant growth rate-related effects. Here, we present a method that addresses this problem by exploiting chemostat culture, in which the cells can be grown at a fixed growth rate, in combination with hybridization array technology. We use two experimental examples to illustrate the advantages of using this approach and then describe a specific application of this approach to investigate the effect of carbon and nitrogen limitation at the transcriptome level.

Cell Culture Techniques↗
PubMed2002

Dynamics of protein turnover, a missing dimension in proteomics.

Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucose-limited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.

Amino Acids↗
PubMed2000

Suppression of sorbitol dependence in a strain bearing a mutation in the SRB1/PSA1/VIG9 gene encoding GDP-mannose pyrophosphorylase by PDE2 overexpression suggests a role for the Ras/cAMP signal-transduction pathway in the control of yeast cell-wall biogenesis.

Complementation studies and allele replacement in Saccharomyces cerevisiae revealed that PSA1/VIG9, an essential gene that encodes GDP-mannose pyrophosphorylase, is the wild-type SRB1 gene. Cloning and sequencing of the srb1-1 allele showed that it determines a single amino acid change from glycine to aspartic acid at residue 276 (srb1(D276)). Genetic evidence is presented showing that at least one further mutation is required for the sorbitol dependence of srb1(D276). A previously reported complementing gene, which this study has now identified as PDE2, is a multi-copy suppressor of sorbitol dependence and is not, as was previously suggested, the SRB1 gene. srb and pde2 mutants share a number of phenotypes, including lysis upon hypotonic shock and enhanced transformability. These data are consistent with the idea that the Ras/cAMP pathway might modulate cell-wall construction.

Amino Acid Sequence↗
PubMed1999

Down-regulation of the expression of PKC1 and SRB1/PSA1/VIG9, two genes involved in cell wall integrity in Saccharomyces cerevisiae, causes flocculation.

The cell wall integrity determinants PKC1 and SRB1/PSA1/VIG9 of Saccharomyces cerevisiae were expressed under the control of the tightly regulated promoter pMET3. Substitution of the cell-cycle-regulated SRB1/PSA1 native promoter with pMET3 led to faster cell growth, larger cell volumes, and a twofold reduction of the steady-state SRB1/PSA1 mRNA level. In addition, the new pattern of expression of SRB1/PSA1 resulted in a dominant flocculation phenotype at all phases of batch growth. By contrast, expression of PKC1 from pMET3 increased the flocculation capacity of cells only at stationary phase. Methionine-mediated repression of either PSA1/SRB1 or PKC1 resulted in enhanced cell clumping. Cells in which both these genes had been replaced with their respective pMET3-regulated cassettes were highly flocculent under both expression and repression conditions. These results suggest that greater exposure of flocculin on the cell surface, caused by either cell wall distortion (through depletion of Pkc1p) or aberrant regulation of mannosylation (through constitutive production of Srb1p), results in an increased flocculation ability.

Cell Wall↗