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Chernoff, Yury O.

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Polyglutamine toxicity is controlled by prion composition and gene dosage in yeast

2012-04-19 , Gong, He , Romanova, Nina V. , Allen, Kim D. , Chandramowlishwaran, Pavithra , Gokhale, Kavita , Newnam, Gary P. , Mieczkowski, Piotr , Sherman, Michael Y. , Chernoff, Yury O.

Polyglutamine expansion causes diseases in humans and other mammals. One example is Huntington’s disease. Fragments of human huntingtin protein having an expanded polyglutamine stretch form aggregates and cause cytotoxicity in yeast cells bearing endogenous QN-rich proteins in the aggregated (prion) form. Attachment of the proline(P)-rich region targets polyglutamines to the large perinuclear deposit (aggresome). Aggresome formation ameliorates polyglutamine cytotoxicity in cells containing only the prion form of Rnq1 protein. Here we show that expanded polyglutamines both with (poly-QP) or without (poly-Q) a P-rich stretch remain toxic in the presence of the prion form of translation termination (release) factor Sup35 (eRF3). A Sup35 derivative that lacks the QN-rich domain and is unable to be incorporated into aggregates counteracts cytotoxicity, suggesting that toxicity is due to Sup35 sequestration. Increase in the levels of another release factor, Sup45 (eRF1), due to either disomy by chromosome II containing the SUP45 gene or to introduction of the SUP45- bearing plasmid counteracts poly-Q or poly-QP toxicity in the presence of the Sup35 prion. Protein analysis confirms that polyglutamines alter aggregation patterns of Sup35 and promote aggregation of Sup45, while excess Sup45 counteracts these effects. Our data show that one and the same mode of polyglutamine aggregation could be cytoprotective or cytotoxic, depending on the composition of other aggregates in a eukaryotic cell, and demonstrate that other aggregates expand the range of proteins that are susceptible to sequestration by polyglutamines.

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Arra: genetic study of the yeast prion-interacting proteins

2011-02-28 , Chernoff, Yury O.

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Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training

2008-12 , Ter-Hovhannisyan,Vardges , Lomsadze, Alexandre , Chernoff, Yury O. , Borodovsky, Mark

We describe a new ab initio algorithm, GeneMark-ES version 2, that identifies protein-coding genes in fungal genomes. The algorithm does not require a predetermined training set to estimate parameters of the underlying hidden Markov model (HMM). Instead, the anonymous genomic sequence in question is used as an input for iterative unsupervised training. The algorithm extends our previously developed method tested on genomes of Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. To better reflect features of fungal gene organization, we enhanced the intron submodel to accommodate sequences with and without branch point sites. This design enables the algorithm to work equally well for species with the kinds of variations in splicing mechanisms seen in the fungal phyla Ascomycota, Basidiomycota, and Zygomycota. Upon self-training, the intron submodel switches on in several steps to reach its full complexity. We demonstrate that the algorithm accuracy, both at the exon and the whole gene level, is favorably compared to the accuracy of gene finders that employ supervised training. Application of the new method to known fungal genomes indicates substantial improvement over existing annotations. By eliminating the effort necessary to build comprehensive training sets, the new algorithm can streamline and accelerate the process of annotation in a large number of fungal genome sequencing projects

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Huntingtin toxicity in yeast model depends on polyglutamine aggregation mediated by a prion-like protein Rnq1

2002-06-10 , Meriin, Anatoli B. , Zhang, Xiaoqian , He, Xiangwei , Newnam, Gary P. , Chernoff, Yury O. , Sherman, Michael Y.

The cause of Huntington’s disease is expansion of polyglutamine (polyQ) domain in huntingtin, which makes this protein both neurotoxic and aggregation prone. Here we developed the first yeast model, which establishes a direct link between aggregation of expanded polyQ domain and its cytotoxicity. Our data indicated that deficiencies in molecular chaperones Sis1 and Hsp104 inhibited seeding of polyQ aggregates, whereas ssa1 , ssa2 , and ydj1–151 mutations inhibited expansion of aggregates. The latter three mutants strongly suppressed the polyQ toxicity. Spontaneous mutants with suppressed aggregation appeared with high frequency, and in all of them the toxicity was relieved. Aggregation defects in these mutants and in T sis1–85 were not complemented in the cross to the hsp104 mutant, demonstrating an unusual type of inheritance. Since Hsp104 is required for prion maintenance in yeast, this suggested a role for prions in polyQ aggregation and toxicity. We screened a set of deletions of nonessential genes coding for known prions and related proteins and found that deletion of the RNQ1 gene specifically suppressed aggregation and toxicity of polyQ. Curing of the prion form of Rnq1 from wild-type cells dramatically suppressed both aggregation and toxicity of polyQ. We concluded that aggregation of polyQ is critical for its toxicity and that Rnq1 in its prion conformation plays an essential role in polyQ aggregation leading to the toxicity.

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Yeast model for studying heritable mammalian prion disease

2011-12-01 , Chernoff, Yury O.

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Identification of genes influencing synthetic lethality of genetic and epigenetic alterations in translation termination factors in yeast

2011 , Kiktev, D. A. , Chernoff, Yury O. , Archipenko, A. V. , Zhouravleva, G. A.

Translation termination in eukaryotic cells is determined by proteins Sup35 (eRF3) and Sup45 (eRF1) [1], which interact with a large number of partners [2]. In yeast Saccharomyces cerevisiae, protein Sup35 can form an aggregating epigenetically inherited conformer (prion) [PSI+] [3]. This prion is carried through the cytoplasm and causes disturbances in translation termination, which are phenotypically identified as the dominant omnipotent nonsense suppression. [PSI+] variants with different properties (nonsense suppression efficiency and transmission stability in mitosis) can be obtained in the same yeast strain. The presence of prion [PSI+] leads to lethality in the haploid yeast strain carrying mutations in the gene encoding another termination factor, Sup45 [4]. We have shown that the combination in the diploid strain of some mutant alleles of the SUP45 gene in the heterozygous state with prion [PSI+] entails the death of the hybrid [5]. The synthetic lethality of prion [PSI+] and mutant allele of the sup45 gene depends both on the type of mutant allele and the prion variant. Variant [PSI+], which is a strong suppressor (“strong” [PSI+], or [PSI+]S), causes synthetic lethality with all nonsense mutations and some missense mutations sup45 in the heterozygote. Our data indicate that the lethality of hybrids is correlated with a decreased activity of the Sup45 protein in the cell in case of sup45 mutations. This paper describes a test system that allows identification of proteins that affect the stability of prion [PSI+] and/or the efficiency of translation termination by their effect on the synthetic lethality of the prion conformer Sup35 and mutant alleles of SUP45. This test system is suitable to search for proteins that affect the translation termination efficiency and/ or prion maintenance in yeast cells. Gene library screening using this test system allowed us to identify the CUR1 gene, whose influence on another prion, [URE3], was shown earlier but the effect on translation termination factors was not known.

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Phenotypic detection of mouse PrP aggregation in yeast

2008-03-31 , Chernoff, Yury O.

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Destabilization and recovery of a yeast prion after mild heat shock

2011-05-06 , Newnam, Gary P. , Birchmore, Jennifer L. , Chernoff, Yury O.

Yeast prion [PSI+] is a self-perpetuating amyloid of the translational termination factor Sup35. Although [PSI+] propagation is modulated by heat shock proteins (Hsps), high temperature was previously reported to have little or no effect on [PSI+]. Our results show that short-term exposure of exponentially growing yeast culture to mild heat shock, followed by immediate resumption of growth, leads to [PSI+] destabilization, sometimes persisting for several cell divisions after heat shock. Prion loss occurring in the first division after heat shock is preferentially detected in a daughter cell, indicating the impairment of prion segregation that results in asymmetric prion distribution between a mother cell and a bud. Longer heat shock or prolonged incubation in the absence of nutrients after heat shock lead to [PSI+] recovery. Both prion destabilization and recovery during heat shock depend on protein synthesis. Maximal prion destabilization coincides with maximal imbalance between Hsp104 and other Hsps such as Hsp70-Ssa. Deletions of individual SSA genes increase prion destabilization and/or counteract recovery. Dynamics of prion aggregation during destabilization and recovery is consistent with the notion that efficient prion fragmentation and segregation require a proper balance between Hsp104 and other (e. g. Hsp70- Ssa) chaperones. In contrast to heat shock, [PSI+] destabilization by osmotic stressors does not always depend on cell proliferation and/or protein synthesis, indicating that different stresses may impact the prion via different mechanisms. Our data demonstrate that heat stress causes asymmetric prion distribution in a cell division, and confirm that effects of Hsps on prions are physiologically relevant.

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Pathogenic Polyglutamine Tracts Are Potent Inducers of Spontaneous Sup35 and Rnq1 Amyloidogenesis

2010-03-10 , Goehler, Heike , Dröge, Anja , Lurz, Rudi , Schnoegl, Sigrid , Chernoff, Yury O. , Wanker, Erich E.

The glutamine/asparagine (Q/N)-rich yeast prion protein Sup35 has a low intrinsic propensity to spontaneously self-assemble into ordered, β-sheet-rich amyloid fibrils. In yeast cells, de novo formation of Sup35 aggregates is greatly facilitated by high protein concentrations and the presence of preformed Q/N-rich protein aggregates that template Sup35 polymerization. Here, we have investigated whether aggregation-promoting polyglutamine (polyQ) tracts can stimulate the de novo formation of ordered Sup35 protein aggregates in the absence of Q/N-rich yeast prions. Fusion proteins with polyQ tracts of different lengths were produced and their ability to spontaneously self-assemble into amlyloid structures was analyzed using in vitro and in vivo model systems. We found that Sup35 fusions with pathogenic (≥54 glutamines), as opposed to non-pathogenic (19 glutamines) polyQ tracts efficiently form seeding-competent protein aggregates. Strikingly, polyQ-mediated de novo assembly of Sup35 protein aggregates in yeast cells was independent of pre-existing Q/N-rich protein aggregates. This indicates that increasing the content of aggregation-promoting sequences enhances the tendency of Sup35 to spontaneously self-assemble into insoluble protein aggregates. A similar result was obtained when pathogenic polyQ tracts were linked to the yeast prion protein Rnq1, demonstrating that polyQ sequences are generic inducers of amyloidogenesis. In conclusion, long polyQ sequences are powerful molecular tools that allow the efficient production of seeding-competent amyloid structures.

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Gene identification in novel eukaryotic genomes by self-training algorithm

2005 , Lomsadze, Alexandre , Ter-Hovhannisyan, Vardges , Chernoff, Yury O. , Borodovsky, Mark

Finding new protein-coding genes is one of the most important goals of eukaryotic genome sequencing projects. However, genomic organization of novel eukaryotic genomes is diverse and ab initio gene finding tools tuned up for previously studied species are rarely suitable for efficacious gene hunting inDNA sequences of a new genome. Gene identification methods based on cDNA and expressed sequence tag (EST) mapping to genomic DNA or those using alignments to closely related genomes rely either on existence of abundant cDNA and EST data and/ or availability on reference genomes. Conventional statistical ab initio methods require large training sets of validated genes for estimating gene model parameters. In practice, neither one of these types of data may be available in sufficient amount until rather late stages of the novel genome sequencing. Nevertheless, we have shown that gene finding in eukaryotic genomes could be carried out in parallel with statistical models estimation directly from yet anonymous genomic DNA. The suggested method of parallelization of gene prediction with the model parameters estimation follows the path of the iterative Viterbi training. Rounds of genomic sequence labeling into coding and non-coding regions are followed by the rounds of model parameters estimation. Several dynamically changing restrictions on the possible range of model parameters are added to filter out fluctuations in the initial steps of the algorithm that could redirect the iteration process away from the biologically relevant point in parameter space. Tests on well-studied eukaryotic genomes have shown that the new method performs comparably or better than conventional methods where the supervised model training precedes the gene prediction step. Several novel genomes have been analyzed and biologically interesting findings are discussed. Thus, a self-training algorithm that had been assumed feasible only for prokaryotic genomes has now been developed for ab initio eukaryotic gene identification.

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