278 research outputs found

    A Bayesian Network Driven Approach to Model the Transcriptional Response to Nitric Oxide in Saccharomyces cerevisiae

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    The transcriptional response to exogenously supplied nitric oxide in Saccharomyces cerevisiae was modeled using an integrated framework of Bayesian network learning and experimental feedback. A Bayesian network learning algorithm was used to generate network models of transcriptional output, followed by model verification and revision through experimentation. Using this framework, we generated a network model of the yeast transcriptional response to nitric oxide and a panel of other environmental signals. We discovered two environmental triggers, the diauxic shift and glucose repression, that affected the observed transcriptional profile. The computational method predicted the transcriptional control of yeast flavohemoglobin YHB1 by glucose repression, which was subsequently experimentally verified. A freely available software application, ExpressionNet, was developed to derive Bayesian network models from a combination of gene expression profile clusters, genetic information and experimental conditions

    Exome sequencing implicates genetic disruption of prenatal neuro-gliogenesis in sporadic congenital hydrocephalus

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    Congenital hydrocephalus (CH), characterized by enlarged brain ventricles, is considered a disease of excessive cerebrospinal fluid (CSF) accumulation and thereby treated with neurosurgical CSF diversion with high morbidity and failure rates. The poor neurodevelopmental outcomes and persistence of ventriculomegaly in some post-surgical patients highlight our limited knowledge of disease mechanisms. Through whole-exome sequencing of 381 patients (232 trios) with sporadic, neurosurgically treated CH, we found that damaging de novo mutations account for >17% of cases, with five different genes exhibiting a significant de novo mutation burden. In all, rare, damaging mutations with large effect contributed to ~22% of sporadic CH cases. Multiple CH genes are key regulators of neural stem cell biology and converge in human transcriptional networks and cell types pertinent for fetal neuro-gliogenesis. These data implicate genetic disruption of early brain development, not impaired CSF dynamics, as the primary pathomechanism of a significant number of patients with sporadic CH

    Predicting Cellular Growth from Gene Expression Signatures

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    Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate

    Deletion of the Pichia pastoris KU70 Homologue Facilitates Platform Strain Generation for Gene Expression and Synthetic Biology

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    Targeted gene replacement to generate knock-outs and knock-ins is a commonly used method to study the function of unknown genes. In the methylotrophic yeast Pichia pastoris, the importance of specific gene targeting has increased since the genome sequencing projects of the most commonly used strains have been accomplished, but rapid progress in the field has been impeded by inefficient mechanisms for accurate integration. To improve gene targeting efficiency in P. pastoris, we identified and deleted the P. pastoris KU70 homologue. We observed a substantial increase in the targeting efficiency using the two commonly known and used integration loci HIS4 and ADE1, reaching over 90% targeting efficiencies with only 250-bp flanking homologous DNA. Although the ku70 deletion strain was noted to be more sensitive to UV rays than the corresponding wild-type strain, no lethality, severe growth retardation or loss of gene copy numbers could be detected during repetitive rounds of cultivation and induction of heterologous protein production. Furthermore, we demonstrated the use of the ku70 deletion strain for fast and simple screening of genes in the search of new auxotrophic markers by targeting dihydroxyacetone synthase and glycerol kinase genes. Precise knock-out strains for the well-known P. pastoris AOX1, ARG4 and HIS4 genes and a whole series of expression vectors were generated based on the wild-type platform strain, providing a broad spectrum of precise tools for both intracellular and secreted production of heterologous proteins utilizing various selection markers and integration strategies for targeted or random integration of single and multiple genes. The simplicity of targeted integration in the ku70 deletion strain will further support protein production strain generation and synthetic biology using P. pastoris strains as platform hosts

    The Origin Recognition Complex Interacts with a Subset of Metabolic Genes Tightly Linked to Origins of Replication

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    The origin recognition complex (ORC) marks chromosomal sites as replication origins and is essential for replication initiation. In yeast, ORC also binds to DNA elements called silencers, where its primary function is to recruit silent information regulator (SIR) proteins to establish transcriptional silencing. Indeed, silencers function poorly as chromosomal origins. Several genetic, molecular, and biochemical studies of HMR-E have led to a model proposing that when ORC becomes limiting in the cell (such as in the orc2-1 mutant) only sites that bind ORC tightly (such as HMR-E) remain fully occupied by ORC, while lower affinity sites, including many origins, lose ORC occupancy. Since HMR-E possessed a unique non-replication function, we reasoned that other tight sites might reveal novel functions for ORC on chromosomes. Therefore, we comprehensively determined ORC “affinity” genome-wide by performing an ORC ChIP–on–chip in ORC2 and orc2-1 strains. Here we describe a novel group of orc2-1–resistant ORC–interacting chromosomal sites (ORF–ORC sites) that did not function as replication origins or silencers. Instead, ORF–ORC sites were comprised of protein-coding regions of highly transcribed metabolic genes. In contrast to the ORC–silencer paradigm, transcriptional activation promoted ORC association with these genes. Remarkably, ORF–ORC genes were enriched in proximity to origins of replication and, in several instances, were transcriptionally regulated by these origins. Taken together, these results suggest a surprising connection among ORC, replication origins, and cellular metabolism

    Global Transcriptome and Deletome Profiles of Yeast Exposed to Transition Metals

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    A variety of pathologies are associated with exposure to supraphysiological concentrations of essential metals and to non-essential metals and metalloids. The molecular mechanisms linking metal exposure to human pathologies have not been clearly defined. To address these gaps in our understanding of the molecular biology of transition metals, the genomic effects of exposure to Group IB (copper, silver), IIB (zinc, cadmium, mercury), VIA (chromium), and VB (arsenic) elements on the yeast Saccharomyces cerevisiae were examined. Two comprehensive sets of metal-responsive genomic profiles were generated following exposure to equi-toxic concentrations of metal: one that provides information on the transcriptional changes associated with metal exposure (transcriptome), and a second that provides information on the relationship between the expression of ∼4,700 non-essential genes and sensitivity to metal exposure (deletome). Approximately 22% of the genome was affected by exposure to at least one metal. Principal component and cluster analyses suggest that the chemical properties of the metal are major determinants in defining the expression profile. Furthermore, cells may have developed common or convergent regulatory mechanisms to accommodate metal exposure. The transcriptome and deletome had 22 genes in common, however, comparison between Gene Ontology biological processes for the two gene sets revealed that metal stress adaptation and detoxification categories were commonly enriched. Analysis of the transcriptome and deletome identified several evolutionarily conserved, signal transduction pathways that may be involved in regulating the responses to metal exposure. In this study, we identified genes and cognate signaling pathways that respond to exposure to essential and non-essential metals. In addition, genes that are essential for survival in the presence of these metals were identified. This information will contribute to our understanding of the molecular mechanism by which organisms respond to metal stress, and could lead to an understanding of the connection between environmental stress and signal transduction pathways

    Nuclear Mitochondrial DNA Activates Replication in Saccharomyces cerevisiae

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    The nuclear genome of eukaryotes is colonized by DNA fragments of mitochondrial origin, called NUMTs. These insertions have been associated with a variety of germ-line diseases in humans. The significance of this uptake of potentially dangerous sequences into the nuclear genome is unclear. Here we provide functional evidence that sequences of mitochondrial origin promote nuclear DNA replication in Saccharomyces cerevisiae. We show that NUMTs are rich in key autonomously replicating sequence (ARS) consensus motifs, whose mutation results in the reduction or loss of DNA replication activity. Furthermore, 2D-gel analysis of the mrc1 mutant exposed to hydroxyurea shows that several NUMTs function as late chromosomal origins. We also show that NUMTs located close to or within ARS provide key sequence elements for replication. Thus NUMTs can act as independent origins, when inserted in an appropriate genomic context or affect the efficiency of pre-existing origins. These findings show that migratory mitochondrial DNAs can impact on the replication of the nuclear region they are inserted in

    The concept of "compartment allergy": prilocaine injected into different skin layers

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    We herein present a patient with delayed-type allergic hypersensitivity against prilocaine leading to spreading eczematous dermatitis after subcutaneous injections for local anesthesia with prilocaine. Prilocaine allergy was proven by positive skin testing and subcutaneous provocation, whereas the evaluation of other local anesthetics - among them lidocaine, articaine and mepivacaine - did not exhibit any evidence for cross-reactivity

    Extensions of MADM (Mosaic Analysis with Double Markers) in Mice

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    Mosaic Analysis with Double Markers (MADM) is a method for generating genetically mosaic mice, in which sibling mutant and wild-type cells are labeled with different fluorescent markers. It is a powerful tool that enables analysis of gene function at the single cell level in vivo. It requires transgenic cassettes to be located between the centromere and the mutation in the gene of interest on the same chromosome. Here we compare procedures for introduction of MADM cassettes into new loci in the mouse genome, and describe new approaches for expanding the utility of MADM. We show that: 1) Targeted homologous recombination outperforms random transgenesis in generation of reliably expressed MADM cassettes, 2) MADM cassettes in new genomic loci need to be validated for biallelic and ubiquitous expression, 3) Recombination between MADM cassettes on different chromosomes can be used to study reciprocal chromosomal deletions/duplications, and 4) MADM can be modified to permit transgene expression by combining it with a binary expression system. The advances described in this study expand current, and enable new and more versatile applications of MADM

    Comparative transcriptomic analysis reveals similarities and dissimilarities in saccharomyces cerevisiae wine strains response to nitrogen availability

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    Nitrogen levels in grape-juices are of major importance in winemaking ensuring adequate yeast growth and fermentation performance. Here we used a comparative transcriptome analysis to uncover wine yeasts responses to nitrogen availability during fermentation. Gene expression was assessed in three genetically and phenotypically divergent commercial wine strains (CEG, VL1 and QA23), under low (67 mg/L) and high nitrogen (670 mg/L) regimes, at three time points during fermentation (12h, 24h and 96h). Two-way ANOVA analysis of each fermentation condition led to the identification of genes whose expression was dependent on strain, fermentation stage and on the interaction of both factors. The high fermenter yeast strain QA23 was more clearly distinct from the other two strains, by differential expression of genes involved in flocculation, mitochondrial functions, energy generation and protein folding and stabilization. For all strains, higher transcriptional variability due to fermentation stage was seen in the high nitrogen fermentations. A positive correlation between maximum fermentation rate and the expression of genes involved in stress response was observed. The finding of common genes correlated with both fermentation activity and nitrogen up-take underlies the role of nitrogen on yeast fermentative fitness. The comparative analysis of genes differentially expressed between both fermentation conditions at 12h, where the main difference was the level of nitrogen available, showed the highest variability amongst strains revealing strain-specific responses. Nevertheless, we were able to identify a small set of genes whose expression profiles can quantitatively assess the common response of the yeast strains to varying nitrogen conditions. The use of three contrasting yeast strains in gene expression analysis prompts the identification of more reliable, accurate and reproducible biomarkers that will facilitate the diagnosis of deficiency of this nutrient in the grape-musts and the development of strategies to optimize yeast performance in industrial fermentations
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