Influence of specific HSP70 domains on fibril formation of the yeast prion protein Ure2.

Ure2p is the protein determinant of the Saccharomyces cerevisiae prion state [URE3]. Constitutive overexpression of the HSP70 family member SSA1 cures cells of [URE3]. Here, we show that Ssa1p increases the lag time of Ure2p fibril formation in vitro in the presence or absence of nucleotide. The presence of the HSP40 co-chaperone Ydj1p has an additive effect on the inhibition of Ure2p fibril formation, whereas the Ydj1p H34Q mutant shows reduced inhibition alone and in combination with Ssa1p. In order to investigate the structural basis of these effects, we constructed and tested an Ssa1p mutant lacking the ATPase domain, as well as a series of C-terminal truncation mutants. The results indicate that Ssa1p can bind to Ure2p and delay fibril formation even in the absence of the ATPase domain, but interaction of Ure2p with the substrate-binding domain is strongly influenced by the C-terminal lid region. Dynamic light scattering, quartz crystal microbalance assays, pull-down assays and kinetic analysis indicate that Ssa1p interacts with both native Ure2p and fibril seeds, and reduces the rate of Ure2p fibril elongation in a concentration-dependent manner. These results provide new insights into the structural and mechanistic basis for inhibition of Ure2p fibril formation by Ssa1p and Ydj1p.

Influence of specific HSP70 domains on fibril formation of the yeast prion protein Ure2.

Ure2p is the protein determinant of the Saccharomyces cerevisiae prion state [URE3]. Constitutive overexpression of the HSP70 family member SSA1 cures cells of [URE3]. Here, we show that Ssa1p increases the lag time of Ure2p fibril formation in vitro in the presence or absence of nucleotide. The presence of the HSP40 co-chaperone Ydj1p has an additive effect on the inhibition of Ure2p fibril formation, whereas the Ydj1p H34Q mutant shows reduced inhibition alone and in combination with Ssa1p. In order to investigate the structural basis of these effects, we constructed and tested an Ssa1p mutant lacking the ATPase domain, as well as a series of C-terminal truncation mutants. The results indicate that Ssa1p can bind to Ure2p and delay fibril formation even in the absence of the ATPase domain, but interaction of Ure2p with the substrate-binding domain is strongly influenced by the C-terminal lid region. Dynamic light scattering, quartz crystal microbalance assays, pull-down assays and kinetic analysis indicate that Ssa1p interacts with both native Ure2p and fibril seeds, and reduces the rate of Ure2p fibril elongation in a concentration-dependent manner. These results provide new insights into the structural and mechanistic basis for inhibition of Ure2p fibril formation by Ssa1p and Ydj1p.

Relationship between prion propensity and the rates of individual molecular steps of fibril assembly.

Peptides and proteins possess an inherent propensity to self-assemble into generic fibrillar nanostructures known as amyloid fibrils, some of which are involved in medical conditions such as Alzheimer disease. In certain cases, such structures can self-propagate in living systems as prions and transmit characteristic traits to the host organism. The mechanisms that allow certain amyloid species but not others to function as prions are not fully understood. Much progress in understanding the prion phenomenon has been achieved through the study of prions in yeast as this system has proved to be experimentally highly tractable; but quantitative understanding of the biophysics and kinetics of the assembly process has remained challenging. Here, we explore the assembly of two closely related homologues of the Ure2p protein from Saccharomyces cerevisiae and Saccharomyces paradoxus, and by using a combination of kinetic theory with solution and biosensor assays, we are able to compare the rates of the individual microscopic steps of prion fibril assembly. We find that for these proteins the fragmentation rate is encoded in the structure of the seed fibrils, whereas the elongation rate is principally determined by the nature of the soluble precursor protein. Our results further reveal that fibrils that elongate faster but fracture less frequently can lose their ability to propagate as prions. These findings illuminate the connections between the in vitro aggregation of proteins and the in vivo proliferation of prions, and provide a framework for the quantitative understanding of the parameters governing the behavior of amyloid fibrils in normal and aberrant biological pathways.

FY is an RNA 3' end-processing factor that interacts with FCA to control the Arabidopsis floral transition

The nuclear RNA binding protein, FCA, promotes Arabidopsis reproductive development. FCA contains a WW protein interaction domain that is essential for FCA function. We have identified FY as a protein partner for this domain. FY belongs to a highly conserved group of eukaryotic proteins represented in Saccharomyces cerevisiae by the RNA 3' end-processing factor, Pfs2p. FY regulates RNA 3' end processing in Arabidopsis as evidenced through its role in FCA regulation. FCA expression is autoregulated through the use of different polyadenylation sites within the FCA pre-mRNA, and the FCA/FY interaction is required for efficient selection of the promoter-proximal polyadenylation site. The FCA/FY interaction is also required for the downregulation of the floral repressor FLC. We propose that FCA controls 3' end formation of specific transcripts and that in higher eukaryotes, proteins homologous to FY may have evolved as sites of association for regulators of RNA 3' end processing.

Bayesian correlated clustering to integrate multiple datasets.

MOTIVATION: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct-but often complementary-information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets. RESULTS: Using a set of six artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real Saccharomyces cerevisiae datasets. In the two-dataset case, we show that MDI's performance is comparable with the present state-of-the-art. We then move beyond the capabilities of current approaches and integrate gene expression, chromatin immunoprecipitation-chip and protein-protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques-as well as to non-integrative approaches-demonstrate that MDI is competitive, while also providing information that would be difficult or impossible to extract using other methods.