The Stress Response Factors Yap6, Cin5, Phd1, and Skn7 Direct Targeting of the Conserved Co-Repressor Tup1-Ssn6 in S. cerevisiae

Maintaining the proper expression of the transcriptome during development or in response to a changing environment requires a delicate balance between transcriptional regulators with activating and repressing functions. The budding yeast transcriptional co-repressor Tup1-Ssn6 is a model for studying similar repressor complexes in multicellular eukaryotes. Tup1-Ssn6 does not bind DNA directly, but is directed to individual promoters by one or more DNA-binding proteins, referred to as Tup1 recruiters. This functional architecture allows the Tup1-Ssn6 to modulate the expression of genes required for the response to a variety of cellular stresses. To understand the targeting or the Tup1-Ssn6 complex, we determined the genomic distribution of Tup1 and Ssn6 by ChIP-chip. We found that most loci bound by Tup1-Ssn6 could not be explained by co-occupancy with a known recruiting cofactor and that deletion of individual known Tup1 recruiters did not significantly alter the Tup1 binding profile. These observations suggest that new Tup1 recruiting proteins remain to be discovered and that Tup1 recruitment typically depends on multiple recruiting cofactors. To identify new recruiting proteins, we computationally screened for factors with binding patterns similar to the observed Tup1-Ssn6 genomic distribution. Four top candidates, Cin5, Skn7, Phd1, and Yap6, all known to be associated with stress response gene regulation, were experimentally confirmed to physically interact with Tup1 and/or Ssn6. Incorporating these new recruitment cofactors with previously characterized cofactors now explains the majority of Tup1 targeting across the genome, and expands our understanding of the mechanism by which Tup1-Ssn6 is directed to its targets

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p

Flocculation in ale brewing strains of Saccharomyces cerevisiae : re-evaluation of the role of cell surface charge and hydrophobicity

Flocculation is an eco-friendly process of cell separation, which has been traditionally exploited by the brewing industry. Cell surface charge (CSC), cell surface hydrophobicity (CSH) and the presence of active flocculins, during the growth of two (NCYC 1195 and NCYC 1214) ale brewing flocculent strains, belonging to the NewFlo phenotype, were examined. Ale strains, in exponential phase of growth, were not flocculent and did not present active flocculent lectins on the cell surface; in contrast, the same strains, in stationary phase of growth, were highly flocculent (>98%) and presented a hydrophobicity of approximately three to seven times higher than in exponential phase. No relationship between growth phase, flocculation and CSC was observed. For comparative purposes, a constitutively flocculent strain (S646-1B) and its isogenic non-flocculent strain (S646-8D) were also used. The treatment of ale brewing and S646-1B strains with pronase E originated a loss of flocculation and a strong reduction of CSH; S646-1B pronase E-treated cells displayed a similar CSH as the non-treated S646-8D cells. The treatment of the S646-8D strain with protease did not reduce CSH. In conclusion, the increase of CSH observed at the onset of flocculation of ale strains is a consequence of the presence of flocculins on the yeast cell surface and not the cause of yeast flocculation. CSH and CSC play a minor role in the auto-aggregation of the ale strains since the degree of flocculation is defined, primarily, by the presence of active flocculins on the yeast cell wall.Manuela D. Machado gratefully acknowledges the post-doctoral grant from Fundacao para a Ciencia e a Tecnologia (FCT) from Portuguese Government (SFRH/BPD/72816/2010)

Substrate-Specific Gene Expression in Batrachochytrium dendrobatidis, the Chytrid Pathogen of Amphibians

Determining the mechanisms of host-pathogen interaction is critical for understanding and mitigating infectious disease. Mechanisms of fungal pathogenicity are of particular interest given the recent outbreaks of fungal diseases in wildlife populations. Our study focuses on Batrachochytrium dendrobatidis (Bd), the chytrid pathogen responsible for amphibian declines around the world. Previous studies have hypothesized a role for several specific families of secreted proteases as pathogenicity factors in Bd, but the expression of these genes has only been evaluated in laboratory growth conditions. Here we conduct a genome-wide study of Bd gene expression under two different nutrient conditions. We compare Bd gene expression profiles in standard laboratory growth media and in pulverized host tissue (i.e., frog skin). A large proportion of genes in the Bd genome show increased expression when grown in host tissue, indicating the importance of studying pathogens on host substrate. A number of gene classes show particularly high levels of expression in host tissue, including three families of secreted proteases (metallo-, serine- and aspartyl-proteases), adhesion genes, lipase-3 encoding genes, and a group of phylogenetically unusual crinkler-like effectors. We discuss the roles of these different genes as putative pathogenicity factors and discuss what they can teach us about Bd’s metabolic targets, host invasion, and pathogenesis