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Using a logical model to predict the growth of yeast.

ABSTRACT: BACKGROUND: A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement. RESULTS: Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings. CONCLUSION: ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.

SUBMITTER: Whelan KE

PROVIDER: S-EPMC2335308 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Using a logical model to predict the growth of yeast.

Whelan K E KE King R D RD

BMC bioinformatics 20080212

<h4>Background</h4>A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.<h4>Results</h4>Compared to t ...[more]

PMID: 18269749

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Project description:Pseudohyphal growth is a nutrient-regulated program in which budding yeast form multicellular filaments of elongated and connected cells. Filamentous growth is required for virulence in pathogenic fungi and provides an informative model of stress-responsive signaling. The genetics and regulatory networks modulating pseudohyphal growth have been studied extensively, but little is known regarding the changes in metabolites that enable pseudohyphal filament formation. Inositol signaling molecules are an important class of metabolite messengers encompassing highly phosphorylated and diffusible inositol polyphosphates (InsPs). We report here that the InsP biosynthesis pathway is required for wild-type pseudohyphal growth. Under nitrogen-limiting conditions that can induce filamentation, InsPs exhibit characteristic profiles, distinguishing the InsP7 pyrophosphate isoforms 1PP-InsP5 and 5PP-InsP5. Deletion and overexpression analyses of InsP kinases identify elevated levels of 5PP-InsP5 relative to 1PP-InsP5 in mutants exhibiting hyper-filamentous growth. Overexpression of KCS1, which promotes formation of inositol pyrophosphates, is sufficient to drive pseudohyphal filamentation on medium with normal nitrogen levels. We find that the kinases Snf1p (AMPK), Kss1p, and Fus3p (MAPKs), required for wild-type pseudohyphal growth, are also required for wild-type InsP levels. Deletion analyses of the corresponding kinase genes indicate elevated InsP3 levels and an absence of exaggerated 5PP-InsP5 peaks in trace profiles from snf1Δ/Δ and kss1Δ/Δ mutants exhibiting decreased pseudohyphal filamentation. Elevated 5PP-InsP5:1PP-InsP5 ratios are present in the hyperfilamentous fus3 deletion mutant. Collectively, the data identify the presence of elevated 5PP-InsP5 levels relative to other inositol pyrophosphates as an in vivo marker of hyper-filamentous growth, while providing initial evidence for the regulation of InsP signaling by pseudohyphal growth kinases.

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Using a logical model to predict the growth of yeast.

Publications

Using a logical model to predict the growth of yeast.

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