Biomedical subjects

Andrew Hayes

Publications and source records attributed to Andrew Hayes.

13 recordsLinked to original sources

PubMed2006

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Algorithms↗

PubMed2006

Annotation of unknown yeast ORFs by correlation analysis of microarray data and extensive literature searches.

Changes in the expression of genes were used to elucidate the metabolic pathways and regulatory mechanisms that respond to environmental or genetic modifications. Results from previously published chemostat datasets were merged with novel data generated in the present study. ORFs displaying significant changes in expression that correlated with those of other ORFs were analysed using GO mapping tools and supplemented by literature information. The strategy developed was used to propose annotations for ORFs of unknown function. The following ORFs were assigned functions as a result of this study: YMR090w, YGL157w, YGR243w, YLR327c, YER121w, YFR017c, YGR067c, YKL187c, YGR236c (SPG1), YMR107w (SPG4), YMR206w, YER067w, YJL103c, YNL175C (NOP13) YJL200C, YDL070C (FMP16) and YGR173W.

Algorithms↗

PubMed2006

Identification of changes in gene expression in dorsal root ganglia in diabetic neuropathy: correlation with functional deficits.

This study aimed to correlate the onset of functional deficits in diabetic neuropathy with changes in gene expression in rat dorsal root ganglia (DRG). After 1, 4, or 8 weeks of streptozotocin-induced diabetes, sensory and motor nerve conduction velocities (NCV) were measured as an indicator of neuropathy and changes in gene expression were measured using Affymetrix oligonucleotide microarrays. No significant changes in NCV were found after 1 week of diabetes, but after 4 and 8 weeks, there was a significant reduction in both sensory and motor NCV. Global gene expression changes in diabetic rat DRG were evident from principal component analysis of microarray data after 1, 4, and 8 weeks. Expression changes in individual genes were relatively small in line with a gradual degenerative neuropathy indirectly resulting from diabetes. Sets of differentially expressed genes have been identified and quantitative reverse transcriptase-polymerase chain reaction has been used to confirm the microarray data for several genes. Gene ontology overrepresentation analysis was performed on the microarray data to identify biologic processes altered in diabetic DRG. The genes identified in this study may be responsible for causing the functional deficits and suggest pathways/processes that require further investigation as possible targets for therapeutic intervention.

Animals↗

PubMed2005

maxdLoad2 and maxdBrowse: standards-compliant tools for microarray experimental annotation, data management and dissemination.

BACKGROUND: maxdLoad2 is a relational database schema and Java application for microarray experimental annotation and storage. It is compliant with all standards for microarray meta-data capture; including the specification of what data should be recorded, extensive use of standard ontologies and support for data exchange formats. The output from maxdLoad2 is of a form acceptable for submission to the ArrayExpress microarray repository at the European Bioinformatics Institute. maxdBrowse is a PHP web-application that makes contents of maxdLoad2 databases accessible via web-browser, the command-line and web-service environments. It thus acts as both a dissemination and data-mining tool. RESULTS: maxdLoad2 presents an easy-to-use interface to an underlying relational database and provides a full complement of facilities for browsing, searching and editing. There is a tree-based visualization of data connectivity and the ability to explore the links between any pair of data elements, irrespective of how many intermediate links lie between them. Its principle novel features are: the flexibility of the meta-data that can be captured, the tools provided for importing data from spreadsheets and other tabular representations, the tools provided for the automatic creation of structured documents, the ability to browse and access the data via web and web-services interfaces. Within maxdLoad2 it is very straightforward to customise the meta-data that is being captured or change the definitions of the meta-data. These meta-data definitions are stored within the database itself allowing client software to connect properly to a modified database without having to be specially configured. The meta-data definitions (configuration file) can also be centralized allowing changes made in response to revisions of standards or terminologies to be propagated to clients without user intervention.maxdBrowse is hosted on a web-server and presents multiple interfaces to the contents of maxd databases. maxdBrowse emulates many of the browse and search features available in the maxdLoad2 application via a web-browser. This allows users who are not familiar with maxdLoad2 to browse and export microarray data from the database for their own analysis. The same browse and search features are also available via command-line and SOAP server interfaces. This both enables scripting of data export for use embedded in data repositories and analysis environments, and allows access to the maxd databases via web-service architectures. CONCLUSION: maxdLoad2 http://www.bioinf.man.ac.uk/microarray/maxd/ and maxdBrowse http://dbk.ch.umist.ac.uk/maxdBrowse are portable and compatible with all common operating systems and major database servers. They provide a powerful, flexible package for annotation of microarray experiments and a convenient dissemination environment. They are available for download and open sourced under the Artistic License.

Data Interpretation, Statistical↗

PubMed2005

Doxycycline, the drug used to control the tet-regulatable promoter system, has no effect on global gene expression in Saccharomyces cerevisiae.

The tet-regulatable promoter system is commonly used for genetic studies in many eukaryotic organisms. The promoter is regulated using doxycycline. There are no obvious phenotypic effects observed when doxycycline is added to the growth medium of yeast to control expression from the promoter. It is widely accepted that doxycycline is innocuous to yeast. Global genetic studies are now commonplace and the tetO-system is being used in transcriptome studies. Hence, we wanted to ensure that the absence of phenotypic effects, on addition of doxycycline to the growth medium, is mirrored in transcriptome data. We have demonstrated that doxycycline has no significant effect on global transcription levels and will continue to use the tetO-regulatable promoter system for genetic studies.

Culture Media↗

PubMed2004

Global analysis of nutrient control of gene expression in Saccharomyces cerevisiae during growth and starvation.

Global gene expression in yeast was examined in five different nutrient-limited steady states and in their corresponding starvation-induced stationary phases. The use of chemostats, with their ability to generate defined and reproducible physiological conditions, permitted the exclusion of the confounding variables that frequently complicate transcriptome analyses. This approach allowed us to dissect out effects on gene expression that are specific to particular physiological states. Thus, we discovered that a large number of ORFs involved in protein synthesis were activated under ammonium limitation, whereas the expression of ORFs concerned with energy and metabolism was enhanced by carbon limitation. Elevated transcription of genes in high-affinity glucose uptake, the trichloroacetic acid cycle, and oxidative phosphorylation were observed in glucose-limiting, but not glucose-abundant, conditions. In contrast, genes involved in gluconeogenesis and, interestingly, genes subject to nitrogen catabolite repression increased their transcription when ethanol was the carbon source, even though ammonium was in excess. This result suggests that up-regulation of genes sensitive to nitrogen catabolite repression may contribute anapleurotic intermediates in ethanol-grown cells. The different starvation conditions produced two general types of transcription profiles, with carbon-starved cells transcribing far fewer genes than cells starved for any of the other macronutrients. Nonetheless, each starvation condition induced its own peculiar set of genes, and only 17 genes were induced >5-fold by all five starvations. In all cases, analysis of the upstream sequences of clusters of coregulated genes identified motifs that may be recognized by transcription factors specific for controlling gene expression in each of the physiological conditions examined.

Cell Division↗

PubMed2004

Comparative genomic hybridization provides new insights into the molecular taxonomy of the Saccharomyces sensu stricto complex.

The science of taxonomy is constantly improving as new techniques are developed. Current practice is to construct phylogenetic trees based on the analysis of the DNA sequence of single genes, or parts of single genes. However, this approach has recently been brought into question as several tree topologies may be produced for the same clade when the sequences for various different genes are used. The availability of complete genome sequences for several organisms has seen the adoption of microarray technology to construct molecular phylogenies of bacteria, based on all of the genes. Similar techniques have been used to reveal the relationships between different strains of the yeast Saccharomyces cerevisiae. We have exploited microarray technology to construct a molecular phylogeny for the Saccharomyces sensu stricto complex of yeast species, which is based on all of the protein-encoding genes revealed by the complete genome sequence of the paradigmatic species, S. cerevisiae. We also analyze different strains of S. cerevisiae itself, as well as the putative species S. boulardii. We show that in addition to the phylogeny produced, we can identify and analyze individual ORF traits and interpret the results to give a detailed explanation of evolutionary events underlying the phylogeny.

Classification↗

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

GIMS: an integrated data storage and analysis environment for genomic and functional data.

Effective analyses in functional genomics require access to many kinds of biological data. For example, the analysis of upregulated genes in a microarray experiment might be aided by information concerning protein interactions or proteins' cellular locations. However, such information is often stored in different formats at different sites, in ways that may not be amenable to integrated analysis. The Genome Information Management System (GIMS) is an object database that integrates genomic data with data on the transcriptome, protein-protein interactions, metabolic pathways and annotations, such as gene ontology terms and identifiers. The resulting system supports the running of analyses over this integrated data resource, and provides comprehensive facilities for handling and interrelating the results of these analyses. GIMS has been used to store Saccharomyces cerevisiae data, and we demonstrate how the integrated storage of diverse types of data can be beneficial for analysis, using combinations of complex queries. As an example, we describe how GIMS has been used to analyse a collection of aryl alcohol dehydrogenase gene deletion mutants. The GIMS database can be accessed remotely using a Java application that can be downloaded from http://img.cs.man.ac.uk/gims.

Computational Biology↗

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

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

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↗