500 research outputs found

    Fission yeast SWI/SNF and RSC complexes show compositional and functional differences from budding yeast.

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    SWI/SNF chromatin-remodeling complexes have crucial roles in transcription and other chromatin-related processes. The analysis of the two members of this class in Saccharomyces cerevisiae, SWI/SNF and RSC, has heavily contributed to our understanding of these complexes. To understand the in vivo functions of SWI/SNF and RSC in an evolutionarily distant organism, we have characterized these complexes in Schizosaccharomyces pombe. Although core components are conserved between the two yeasts, the compositions of S. pombe SWI/SNF and RSC differ from their S. cerevisiae counterparts and in some ways are more similar to metazoan complexes. Furthermore, several of the conserved proteins, including actin-like proteins, are markedly different between the two yeasts with respect to their requirement for viability. Finally, phenotypic and microarray analyses identified widespread requirements for SWI/SNF and RSC on transcription including strong evidence that SWI/SNF directly represses iron-transport genes

    Large-scale proteomic analysis of T. spiralis muscle-stage ESPs identifies a novel upstream motif for in silico prediction of secreted products

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    The Trichinella genus contains parasitic nematodes capable of infecting a wide range of hosts including mammals, birds and reptiles. Like other helminths, T. spiralis secretes a complex mixture of bioactive molecules capable of modulating its immediate surroundings and creating a hospitable environment for growth, survival and ultimately transmission. The constitution of these excretory-secretory products (ESPs) changes depending on the tissue niche and the specific stage of parasite development. Unique to T. spiralis is a true intracellular stage wherein larvae develop inside striated myotubes. Remarkably, the parasite larvae do not destroy the host cell but rather reprogram it to support their presence and growth. This transformation is largely mediated through stage-specific secretions released into the host cell cytoplasm. In this study, we apply state of the art proteomics and computational approaches to elucidate the composition and functions of muscle-stage T. spiralis ESPs. Moreover, we define a recurring, upstream motif associated with the stichosome, the main secretory organ of this worm, and can be used to predict secreted proteins across experimentally less tractable T. spiralis life cycle stages

    Shotgun Mass Spectrometry Workflow Combining IEF and LC-MALDI-TOF/TOF

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    We present a high throughput shotgun mass spectrometry workflow using a bidimensional peptide fractionation procedure consisting of isoelectric focusing and RP-HPLC prior to mass spectrometric analysis, with the aim of optimizing peptide separation and protein identification. As part of the workflow we used the ‘Isotope-Coded Protein Labeling’ (ICPL) method for accurate relative quantitation of protein expression. Such workflow was successfully applied to a comparative proteome analysis of schizophrenia versus healthy control brain tissues and can be an alternative to proteome researches

    Plasmodium falciparum CRK4 directs continuous rounds of DNA replication during schizogony.

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    : Plasmodium parasites, the causative agents of malaria, have evolved a unique cell division cycle in the clinically relevant asexual blood stage of infection(1). DNA replication commences approximately halfway through the intracellular development following invasion and parasite growth. The schizont stage is associated with multiple rounds of DNA replication and nuclear division without cytokinesis, resulting in a multinucleated cell. Nuclei divide asynchronously through schizogony, with only the final round of DNA replication and segregation being synchronous and coordinated with daughter cell assembly(2,3). However, the control mechanisms for this divergent mode of replication are unknown. Here, we show that the Plasmodium-specific kinase PfCRK4 is a key cell-cycle regulator that orchestrates multiple rounds of DNA replication throughout schizogony in Plasmodium falciparum. PfCRK4 depletion led to a complete block in nuclear division and profoundly inhibited DNA replication. Quantitative phosphoproteomic profiling identified a set of PfCRK4-regulated phosphoproteins with greatest functional similarity to CDK2 substrates, particularly proteins involved in the origin of replication firing. PfCRK4 was required for initial and subsequent rounds of DNA replication during schizogony and, in addition, was essential for development in the mosquito vector. Our results identified an essential S-phase promoting factor of the unconventional P. falciparum cell cycle. PfCRK4 is required for both a prolonged period of the intraerythrocytic stage of Plasmodium infection, as well as for transmission, revealing a broad window for PfCRK4-targeted chemotherapeutics.<br/

    C-STrap Sample Preparation Method—In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format

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    Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method’s use in qualitative and semi-quantitative proteomics experiments

    In vivo incorporation of fenfluramine and norfenfluramine into pigmented and nonpigmented hair of rats measured by HPLC-fluorescence detection

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    The incorporation profiles for fenfluramine (Fen) and its metabolite norfenfluramine (Norf) into black hair and white hair of Zucker rats and into white hair of Wistar rats after intraperitoneal (i.p.) administration of Fen or N-nitrosofenfluramine (N-Fen) were studied in great detail. The target compounds were determined by high-performance liquid chromatography with fluorescence detection using 4-(4,5-diphenyl-1 H-imidazol-2-yl)benzoyl chloride as a derivatization reagent. After repeated i.p. administration of Fen (5 mg/kg) for 4 days to Zucker rats, shaft and root samples of black and white hair were obtained 1 week after the first administration. It was surprising that Fen and Norf levels in root samples of white hair were much higher than those in shaft or root samples of black hair, strongly suggesting that unknown mechanisms other than the action of melanin take place in the white hair root. Time course profiles for Fen and Norf after administration of a single i.p. dose of Fen or N-Fen were constructed for Zucker and Wistar rats. The percent level of Fen or Norf in white hair was 15-50% of that in black hair at any interval within 600 min after a single administration of Fen in Zucker rats. Even with Wistar rats having only white hair, we could demonstrate the time courses for incorporation of Fen and Norf into white hair. Finally, time course profiles for Fen and Norf were also followed after a single i.p. administration of N-Fen; this experiment showed that the levels of Norf were much higher than those of Fen for both black and white hair samples of Zucker rats at any interval tested

    A genome-wide association study identifies protein quantitative trait loci (pQTLs)

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    There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10 -57), CCL4L1 (p = 3.9×10-21), IL18 (p = 6.8×10-13), LPA (p = 4.4×10-10), GGT1 (p = 1.5×10-7), SHBG (p = 3.1×10-7), CRP (p = 6.4×10-6) and IL1RN (p = 7.3×10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. © 2008 Melzer et al

    ProtQuant: a tool for the label-free quantification of MudPIT proteomics data

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    <p>Abstract</p> <p>Background</p> <p>Effective and economical methods for quantitative analysis of high throughput mass spectrometry data are essential to meet the goals of directly identifying, characterizing, and quantifying proteins from a particular cell state. Multidimensional Protein Identification Technology (MudPIT) is a common approach used in protein identification. Two types of methods are used to detect differential protein expression in MudPIT experiments: those involving stable isotope labelling and the so-called label-free methods. Label-free methods are based on the relationship between protein abundance and sampling statistics such as peptide count, spectral count, probabilistic peptide identification scores, and sum of peptide Sequest XCorr scores (ΣXCorr). Although a number of label-free methods for protein quantification have been described in the literature, there are few publicly available tools that implement these methods. We describe ProtQuant, a Java-based tool for label-free protein quantification that uses the previously published ΣXCorr method for quantification and includes an improved method for handling missing data.</p> <p>Results</p> <p><it>ProtQuant </it>was designed for ease of use and portability for the bench scientist. It implements the ΣXCorr method for label free protein quantification from MudPIT datasets. <it>ProtQuant </it>has a graphical user interface, accepts multiple file formats, is not limited by the size of the input files, and can process any number of replicates and any number of treatments. In addition,<it>ProtQuant </it>implements a new method for dealing with missing values for peptide scores used for quantification. The new algorithm, called ΣXCorr*, uses "below threshold" peptide scores to provide meaningful non-zero values for missing data points. We demonstrate that ΣXCorr* produces an average reduction in false positive identifications of differential expression of 25% compared to ΣXCorr.</p> <p>Conclusion</p> <p><it>ProtQuant </it>is a tool for protein quantification built for multi-platform use with an intuitive user interface. <it>ProtQuant </it>efficiently and uniquely performs label-free quantification of protein datasets produced with Sequest and provides the user with facilities for data management and analysis. Importantly, <it>ProtQuant </it>is available as a self-installing executable for the Windows environment used by many bench scientists.</p
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