A systems biology strategy for understanding the genome-wide control of growth rate and metabolic flux in yeast.
Lead Research Organisation:
University of Cambridge
Department Name: Biochemistry
Abstract
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Technical Summary
We shall develop both top-down and bottom-up genome-wide models for the control of the maximum specific grown rate in baker¿s yeast. Genes with high flux-control coefficients will be identified via haploinsufficiency measurements in turbidostats. Genome-wide metabolite binding and flux/transformation/enzyme kinetic measurements will be carried out mass spectrometrically using protein microarrays obtained from M. Snyder. Intra- and extra-cellular metabolome transcriptome and proteome measurements in selected genetically defined strains will be used, iteratively, to validate the model. Flux-balance modelling will also be used to define specific modulations likely to be most discriminatory between competing models. The result will be the first example in which the controls on growth rate and metabolic fluxes are established on a genome-wide scale.
Organisations
People |
ORCID iD |
| Stephen Oliver (Principal Investigator) |
Publications
Alcasabas AA
(2013)
Control analysis of the eukaryotic cell cycle using gene copy-number series in yeast tetraploids.
in BMC genomics
Amoutzias GD
(2012)
Evaluation and properties of the budding yeast phosphoproteome.
in Molecular & cellular proteomics : MCP
Barton MD
(2010)
Evolutionary systems biology of amino acid biosynthetic cost in yeast.
in PloS one
Bonzanni N
(2011)
The role of proteosome-mediated proteolysis in modulating potentially harmful transcription factor activity in Saccharomyces cerevisiae.
in Bioinformatics (Oxford, England)
Castrillo J
(2014)
Fungal Genomics
Castrillo JI
(2016)
Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks.
in Methods in molecular biology (Clifton, N.J.)
Castrillo JI
(2011)
Yeast systems biology: the challenge of eukaryotic complexity.
in Methods in molecular biology (Clifton, N.J.)
Davey HM
(2012)
Genome-wide analysis of longevity in nutrient-deprived Saccharomyces cerevisiae reveals importance of recycling in maintaining cell viability.
in Environmental microbiology
De Clare M
(2013)
Copy-number variation of cancer-gene orthologs is sufficient to induce cancer-like symptoms in Saccharomyces cerevisiae.
in BMC biology
De Clare M
(2011)
Haploinsufficiency and the sex chromosomes from yeasts to humans.
in BMC biology
| Description | 1. Identification and characterisation of high flux control (HFC) genes in the yeast Saccharomyces cerevisiae. 2. Discovery of the phenomenon of haploproficiency, which has profound implications for the treatment of cancer. 3. Demonstration, on both the bioinformatic and experimental levels, that yeast haplo-insufficiency and -proficiency phenotypes are predictive of similar phenotypes of human genes. 4. Construction of a Boolean model of the yeast cell cycle, its use to predict the biphasic nature control by the key cell-cycle gene CDC28, and experimental validation of that prediction. 5. Elucidation of both nutrient and growth rate control of gene expression in yeast at both the mRNA and protein levels. 6. Construction of a consensus metabolic model for S. cerevisiae and its use to predict epistatic interactions between metabolic genes. 7. Improvement and refinement of the metabolic model using empirical epistasis data. 8. Elucidation of the role of the transcription factor Gis1p in the transition into stationary phase (quiescence). 9 Discovery that Gis1p is processed (not degraded) by the proteosome and that this processing reduces its transcriptional activation ability. 10. Construction of a logical (computer) model of the regulatory circuitry in which Gis1p is involved and prediction that proteolytic processing of Gis1p enables fast escape from quiescence once nutrients become available. This prediction was confirmed experimentally. |
| Exploitation Route | Our findings on haploproficient genes suggest that low or intermediate doses of anticancer drugs may actually promote growth of the tumour, while higher doses will retard it. We have confirmed these predictions with a colon cancer cell line, but these findings need to be followed up by cancer specialists. |
| Sectors | Energy,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
| Description | Our approach to metabolic modelling and the prediction of the phenotypic impact of the recruitment of foreign genes into yeast and the deletion of endogenous genes have been exploited by the biotech SME, BioSyntha. They have resulted in a valuable patent in the biofuels area. A post-doc employed on this grant, Dr Annette Alcasabas, is now employed by BioSyntha. |
| First Year Of Impact | 2010 |
| Sector | Aerospace, Defence and Marine,Energy,Manufacturing, including Industrial Biotechology |
| Impact Types | Economic |