Andrew Hayes

Bio: Andrew Hayes is an academic researcher from University of Manchester. The author has contributed to research in topics: Saccharomyces cerevisiae & Gene. The author has an hindex of 35, co-authored 61 publications receiving 4331 citations. Previous affiliations of Andrew Hayes include Georgetown University & National Institute for Medical Research.

A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

Abstract: A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are "silent," that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing "metabolic snapshots," can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY—an abbreviation for functional analysis by co-responses in yeast.

The Syk tyrosine kinase suppresses malignant growth of human breast cancer cells

Abstract: Syk is a protein tyrosine kinase that is widely expressed in haematopoietic cells It is involved in coupling activated immunoreceptors to downstream signalling events that mediate diverse cellular responses including proliferation, differentiation and phagocytosis1,2,3,4 Syk expression has been reported in cell lines of epithelial origin5, but its function in these cells remains unknown Here we show that Syk is commonly expressed in normal human breast tissue, benign breast lesions and low-tumorigenic breast cancer cell lines Syk messenger RNA and protein, however, are low or undetectable in invasive breast carcinoma tissue and cell lines Transfection of wild-type Syk into a Syk-negative breast cancer cell line markedly inhibited its tumour growth and metastasis formation in athymic mice Conversely, overexpression of a kinase-deficient Syk in a Syk-positive breast cancer cell line significantly increased its tumour incidence and growth Suppression of tumour growth by the reintroduction of Syk appeared to be the result of aberrant mitosis and cytokinesis We propose that Syk is a potent modulator of epithelial cell growth and a potential tumour suppressor in human breast carcinomas

Growth control of the eukaryote cell: a systems biology study in yeast

Abstract: Background: Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Results: Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rateassociated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Functional Characterization of the S. cerevisiae Genome by Gene Deletion and Parallel Analysis

Abstract: The functions of many open reading frames (ORFs) identified in genome-sequencing projects are unknown. New, whole-genome approaches are required to systematically determine their function. A total of 6925 Saccharomyces cerevisiae strains were constructed, by a high-throughput strategy, each with a precise deletion of one of 2026 ORFs (more than one-third of the ORFs in the genome). Of the deleted ORFs, 17 percent were essential for viability in rich medium. The phenotypes of more than 500 deletion strains were assayed in parallel. Of the deletion strains, 40 percent showed quantitative growth defects in either rich or minimal medium.

Metabolomics - the link between genotypes and phenotypes

Abstract: Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms ‘transcriptome’ and ‘proteome’, the set of metabolites synthesized by a biological system constitute its ‘metabolome’. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.

Self-assembly and mineralization of peptide-amphiphile nanofibers

Abstract: We have used the pH-induced self-assembly of a peptide-amphiphile to make a nanostructured fibrous scaffold reminiscent of extracellular matrix. The design of this peptide-amphiphile allows the nanofibers to be reversibly cross-linked to enhance or decrease their structural integrity. After cross-linking, the fibers are able to direct mineralization of hydroxyapatite to form a composite material in which the crystallographic c axes of hydroxyapatite are aligned with the long axes of the fibers. This alignment is the same as that observed between collagen fibrils and hydroxyapatite crystals in bone.

The druggable genome

Abstract: An assessment of the number of molecular targets that represent an opportunity for therapeutic intervention is crucial to the development of post-genomic research strategies within the pharmaceutical industry. Now that we know the size of the human genome, it is interesting to consider just how many molecular targets this opportunity represents. We start from the position that we understand the properties that are required for a good drug, and therefore must be able to understand what makes a good drug target.