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Background: Haploinsufficient (HI) genes are those for which a reduction in copy number in a diploid from two to one results in significantly reduced fitness. Haploinsufficiency is increasingly implicated in human disease, and so predicting this phenotype could provide insights into the genetic mechanisms behind many human diseases, including some cancers. Results: In the present work we show that orthologues of Saccharomyces cerevisiae HI genes are preferentially retained across the kingdom Fungi, and that the HI genes of S. cerevisiae can be used to predict haploinsufficiency in humans. Our HI gene predictions confirm known associations between haploinsufficiency and genetic disease, and predict several further disorders in which the phenotype may be relevant. Haploinsufficiency is also clearly relevant to the gene-dosage imbalances inherent in eukaryotic sex-determination systems. In S. cerevisiae, HI genes are over-represented on chromosome III, the chromosome that determines yeast's mating type. This may be a device to select against the loss of one copy of chromosome III from a diploid. We found that orthologues of S. cerevisiae HI genes are also over-represented on the mating-type chromosomes of other yeasts and filamentous fungi. In animals with heterogametic sex determination, accumulation of HI genes on the sex chromosomes would compromise fitness in both sexes, given X chromosome inactivation in females. We found that orthologues of S. cerevisiae HI genes are significantly under-represented on the X chromosomes of mammals and of Caenorhabditis elegans. There is no X inactivation in Drosophila melanogaster (increased expression of X in the male is used instead) and, in this species, we found no depletion of orthologues to yeast HI genes on the sex chromosomes. Conclusion: A special relationship between HI genes and the sex/mating-type chromosome extends from S. cerevisiae to Homo sapiens, with the microbe being a useful model for species throughout the evolutionary range. Furthermore, haploinsufficiency in yeast can predict the phenotype in higher organisms. [ABSTRACT FROM AUTHOR]

Background: To elucidate the biological processes affected by changes in growth rate and nutrient availability, we have performed a comprehensive analysis of the transcriptome, proteome and metabolome responses of chemostat cultures of the yeast, Saccharomyces cerevisiae, growing at a range of growth rates and in four different nutrient-limiting conditions. Results: We find significant changes in expression for many genes in each of the four nutrient-limited conditions tested. We also observe several processes that respond differently to changes in growth rate and are specific to each nutrient-limiting condition. These include carbohydrate storage, mitochondrial function, ribosome synthesis, and phosphate transport. Integrating transcriptome data with proteome measurements allows us to identify previously unrecognized examples of post-transcriptional regulation in response to both nutrient and growth-rate signals. Conclusions: Our results emphasize the unique properties of carbon metabolism and the carbon substrate, the limitation of which induces significant changes in gene regulation at the transcriptional and post-transcriptional level, as well as altering how many genes respond to growth rate. By comparison, the responses to growth limitation by other nutrients involve a smaller set of genes that participate in specific pathways. See associated commentary http://www.biomedcentral.com/1741-7007/8/62 [ABSTRACT FROM AUTHOR]

Background: To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity. Results: We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions. Conclusions: We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sysbio. org/yeastnet/. [ABSTRACT FROM AUTHOR]

Background: A microorganism is able to adapt to changes in its physicochemical or nutritional environment and this is crucial for its survival. The yeast, Saccharomyces cerevisiae, has developed mechanisms to respond to such environmental changes in a rapid and effective manner; such responses may demand a widespread re-programming of gene activity. The dynamics of the re-organization of the cellular activities of S. cerevisiae in response to the sudden and transient removal of either carbon or nitrogen limitation has been studied by following both the short- and long-term changes in yeast's transcriptomic profiles., Results: The study, which spans timescales from seconds to hours, has revealed the hierarchy of metabolic and genetic regulatory switches that allow yeast to adapt to, and recover from, a pulse of a previously limiting nutrient. At the transcriptome level, a glucose impulse evoked significant changes in the expression of genes concerned with glycolysis, carboxylic acid metabolism, oxidative phosphorylation, and nucleic acid and sulphur metabolism. In ammonium-limited cultures, an ammonium impulse resulted in the significant changes in the expression of genes involved in nitrogen metabolism and ion transport. Although both perturbations evoked significant changes in the expression of genes involved in the machinery and process of protein synthesis, the transcriptomic response was delayed and less complex in the case of an ammonium impulse. Analysis of the regulatory events by two different system-level, network-based approaches provided further information about dynamic organization of yeast cells as a response to a nutritional change., Conclusions: The study provided important information on the temporal organization of transcriptomic organization and underlying regulatory events as a response to both carbon and nitrogen impulse. It has also revealed the importance of a long-term dynamic analysis of the response to the relaxation of a nutritional limitation to understand the molecular basis of the cells' dynamic behaviour.

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.