19 research outputs found

    Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa

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    Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s)

    A Novel C1q Domain-Containing Protein Isolated from the Mollusk Modiolus kurilensis Recognizing Glycans Enriched with Acidic Galactans and Mannans

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    C1q domain-containing (C1qDC) proteins are a group of biopolymers involved in immune response as pattern recognition receptors (PRRs) in a lectin-like manner. A new protein MkC1qDC from the hemolymph plasma of Modiolus kurilensis bivalve mollusk widespread in the Northwest Pacific was purified. The isolation procedure included ammonium sulfate precipitation followed by affinity chromatography on pectin-Sepharose. The full-length MkC1qDC sequence was assembled using de novo mass-spectrometry peptide sequencing complemented with N-terminal Edman’s degradation, and included 176 amino acid residues with molecular mass of 19 kDa displaying high homology to bivalve C1qDC proteins. MkC1qDC demonstrated antibacterial properties against Gram-negative and Gram-positive strains. MkC1qDC binds to a number of saccharides in Ca(2+)-dependent manner which characterized by structural meta-similarity in acidic group enrichment of galactose and mannose derivatives incorporated in diversified molecular species of glycans. Alginate, κ-carrageenan, fucoidan, and pectin were found to be highly effective inhibitors of MkC1qDC activity. Yeast mannan, lipopolysaccharide (LPS), peptidoglycan (PGN) and mucin showed an inhibitory effect at concentrations three orders of magnitude greater than for the most effective saccharides. MkC1qDC localized to the mussel hemal system and interstitial compartment. Intriguingly, MkC1qDC was found to suppress proliferation of human adenocarcinoma HeLa cells in a dose-dependent manner, indicating to the biomedical potential of MkC1qDC protein

    The National Center for Biotechnology Information's Protein Clusters Database

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    Rapid increases in DNA sequencing capabilities have led to a vast increase in the data generated from prokaryotic genomic studies, which has been a boon to scientists studying micro-organism evolution and to those who wish to understand the biological underpinnings of microbial systems. The NCBI Protein Clusters Database (ProtClustDB) has been created to efficiently maintain and keep the deluge of data up to date. ProtClustDB contains both curated and uncurated clusters of proteins grouped by sequence similarity. The May 2008 release contains a total of 285 386 clusters derived from over 1.7 million proteins encoded by 3806 nt sequences from the RefSeq collection of complete chromosomes and plasmids from four major groups: prokaryotes, bacteriophages and the mitochondrial and chloroplast organelles. There are 7180 clusters containing 376 513 proteins with curated gene and protein functional annotation. PubMed identifiers and external cross references are collected for all clusters and provide additional information resources. A suite of web tools is available to explore more detailed information, such as multiple alignments, phylogenetic trees and genomic neighborhoods. ProtClustDB provides an efficient method to aggregate gene and protein annotation for researchers and is available at http://www.ncbi.nlm.nih.gov/sites/entrez?db=proteinclusters

    Shewanella knowledgebase: integration of the experimental data and computational predictions suggests a biological role for transcription of intergenic regions

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    Shewanellae are facultative γ-proteobacteria whose remarkable respiratory versatility has resulted in interest in their utility for bioremediation of heavy metals and radionuclides and for energy generation in microbial fuel cells. Extensive experimental efforts over the last several years and the availability of 21 sequenced Shewanella genomes made it possible to collect and integrate a wealth of information on the genus into one public resource providing new avenues for making biological discoveries and for developing a system level understanding of the cellular processes. The Shewanella knowledgebase was established in 2005 to provide a framework for integrated genome-based studies on Shewanella ecophysiology. The present version of the knowledgebase provides access to a diverse set of experimental and genomic data along with tools for curation of genome annotations and visualization and integration of genomic data with experimental data. As a demonstration of the utility of this resource, we examined a single microarray data set from Shewanella oneidensis MR-1 for new insights into regulatory processes. The integrated analysis of the data predicted a new type of bacterial transcriptional regulation involving co-transcription of the intergenic region with the downstream gene and suggested a biological role for co-transcription that likely prevents the binding of a regulator of the upstream gene to the regulator binding site located in the intergenic region

    Phenotype Fingerprinting Suggests the Involvement of Single-Genotype Consortia in Degradation of Aromatic Compounds by Rhodopseudomonas palustris

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    Anaerobic degradation of complex organic compounds by microorganisms is crucial for development of innovative biotechnologies for bioethanol production and for efficient degradation of environmental pollutants. In natural environments, the degradation is usually accomplished by syntrophic consortia comprised of different bacterial species. This strategy allows consortium organisms to reduce efforts required for maintenance of the redox homeostasis at each syntrophic level. Cellular mechanisms that maintain the redox homeostasis during the degradation of aromatic compounds by one organism are not fully understood. Here we present a hypothesis that the metabolically versatile phototrophic bacterium Rhodopseudomonas palustris forms its own syntrophic consortia, when it grows anaerobically on p-coumarate or benzoate as a sole carbon source. We have revealed the consortia from large-scale measurements of mRNA and protein expressions under p-coumarate, benzoate and succinate degrading conditions using a novel computational approach referred as phenotype fingerprinting. In this approach, marker genes for known R. palustris phenotypes are employed to determine the relative expression levels of genes and proteins in aromatics versus non-aromatics degrading condition. Subpopulations of the consortia are inferred from the expression of phenotypes and known metabolic modes of the R. palustris growth. We find that p-coumarate degrading conditions may lead to at least three R. palustris subpopulations utilizing p-coumarate, benzoate, and CO2 and H2. Benzoate degrading conditions may also produce at least three subpopulations utilizing benzoate, CO2 and H2, and N2 and formate. Communication among syntrophs and inter-syntrophic dynamics in each consortium are indicated by up-regulation of transporters and genes involved in the curli formation and chemotaxis. The N2-fixing subpopulation in the benzoate degrading consortium has preferential activation of the vanadium nitrogenase over the molybdenum nitrogenase. This subpopulation in the consortium was confirmed in an independent experiment by consumption of dissolved nitrogen gas under the benzoate degrading conditions

    Whole-genome sequencing of 1,171 elderly admixed individuals from Brazil

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    As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS

    EXPORTS Measurements and Protocols for the NE Pacific Campaign

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    EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led and NSF co-funded field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite information and state of the art technology
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