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Non-Mendelian determinant [ISP+] in yeast is a nuclear-residing prion form of the global transcriptional regulator Sfp1.

ABSTRACT: Four protein-based genetic determinants or prions-[SWI(+)], [MCA], [OCT(+)], and [MOT3(+)]-are recent additions to the list of well-known Saccharomyces cerevisiae prions, [PSI(+)], [URE3], and [PIN(+)]. A rapid expansion of this list may indicate that many yeast proteins can convert into heritable prion forms and underscores a problem of prion input into cellular physiology. Here, we prove that the global transcriptional regulator Sfp1 can become a prion corresponding to the prion-like determinant [ISP(+)] described earlier. We show that SFP1 deletion causes an irreversible [ISP(+)] loss, whereas increased SFP1 expression induces [ISP(+)] appearance. Cells that display the [ISP(+)] phenotype contain the aggregated form of Sfp1. Indeed, these aggregates demonstrate a nuclear location. We also show that the phenotypic manifestation of Sfp1 prionization differs from the manifestation of SFP1 deletion. These properties and others distinguish [ISP(+)] from yeast prions described to date.

SUBMITTER: Rogoza T

PROVIDER: S-EPMC2890785 | biostudies-other | 2010 Jun

REPOSITORIES: biostudies-other

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Project description:Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein-protein interactions and transcription factor binding revealed critical insights into cellular behavior. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate mRNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental (13)C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. Although mRNA expression alone did not directly predict metabolic response, this correlation improved through incorporating a network-based model of amino acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow-on transcriptional regulators that were experimentally validated with additional (13)C-based flux measurements. As a first step in linking metabolic control and genetic regulatory networks, this model underscores the importance of integrating diverse data types in large-scale cellular models. We anticipate that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications.

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Non-Mendelian determinant [ISP+] in yeast is a nuclear-residing prion form of the global transcriptional regulator Sfp1.

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