57 research outputs found

    The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium: community development of new Gene Ontology terms describing biological processes involved in microbe-host interactions

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    All microbes that form beneficial, neutral, or pathogenic associations with hosts face similar challenges. They must physically adhere to and/or gain entry to host tissues; they must avoid, suppress, or tolerate host defenses; they must acquire nutrients from the host and successfully multiply. Microbes that associate with hosts come from many kingdoms of life and include bacteria, fungi, oomycetes, and nematodes. The increasing numbers of full genome sequences from these diverse microbes provide the opportunity to discover common mechanisms by which the microbes forge and maintain intimate associations with host organisms. However, cross-genome analyses have been hindered by lack of a universal vocabulary for describing biological processes involved in the interplay between microbes and their hosts. The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has been working for three years as an official interest group of the Gene Ontology (GO) Consortium to develop well-defined GO terms that describe many of the biological processes common to diverse plant- and animal-associated microbes. Creating these terms, over 700 at this time, has required a synthesis of diverse points of view from many research communities. The use of these terms in genome annotation will allow cross-genome searches for genes with common function (without demand for sequence similarity) and also improve the interpretation of data from high-throughput microarray and proteomic analyses. This article, and the more focused mini-reviews that make up this supplement to BMC Microbiology, describe the development and use of these terms

    TIGRFAMs and Genome Properties: tools for the assignment of molecular function and biological process in prokaryotic genomes

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    TIGRFAMs is a collection of protein family definitions built to aid in high-throughput annotation of specific protein functions. Each family is based on a hidden Markov model (HMM), where both cutoff scores and membership in the seed alignment are chosen so that the HMMs can classify numerous proteins according to their specific molecular functions. Most TIGRFAMs models describe ‘equivalog’ families, where both orthology and lateral gene transfer may be part of the evolutionary history, but where a single molecular function has been conserved. The Genome Properties system contains a queriable set of metabolic reconstructions, genome metrics and extractions of information from the scientific literature. Its genome-by-genome assertions of whether or not specific structures, pathways or systems are present provide high-level conceptual descriptions of genomic content. These assertions enable comparative genomics, provide a meaningful biological context to aid in manual annotation, support assignments of Gene Ontology (GO) biological process terms and help validate HMM-based predictions of protein function. The Genome Properties system is particularly useful as a generator of phylogenetic profiles, through which new protein family functions may be discovered. The TIGRFAMs and Genome Properties systems can be accessed at and

    Programmed cell death in host-symbiont associations, viewed through the Gene Ontology

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    Manipulation of programmed cell death (PCD) is central to many host microbe interactions. Both plant and animal cells use PCD as a powerful weapon against biotrophic pathogens, including viruses, which draw their nutrition from living tissue. Thus, diverse biotrophic pathogens have evolved many mechanisms to suppress programmed cell death, and mutualistic and commensal microbes may employ similar mechanisms. Necrotrophic pathogens derive their nutrition from dead tissue, and many produce toxins specifically to trigger programmed cell death in their hosts. Hemibiotrophic pathogens manipulate PCD in a most exquisite way, suppressing PCD during the biotrophic phase and stimulating it during the necrotrophic phase. This mini-review will summarize the mechanisms that have evolved in diverse microbes and hosts for controlling PCD and the Gene Ontology terms developed by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium for describing those mechanisms

    Genomewide identification of \u3ci\u3ePseudomonas syringae\u3c/i\u3e pv.\u3ci\u3etomato\u3c/i\u3e DC3000 promoters controlled by the HrpL alternative sigma factor

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    The ability of Pseudomonas syringae pv. tomato DC3000 to parasitize tomato and Arabidopsis thaliana depends on genes activated by the HrpL alternative sigma factor. To support various functional genomic analyses of DC3000, and specifically, to identify genes involved in pathogenesis, we developed a draft sequence of DC3000 and used an iterative process involving computational and gene expression techniques to identify virulence-implicated genes downstream of HrpLresponsive promoters. Hypersensitive response and pathogenicity (Hrp) promoters are known to control genes encoding the Hrp (type III protein secretion) machinery and a few type III effector proteins in DC3000. This process involved (i) identification of 9 new virulenceimplicated genes in the Hrp regulon by miniTn5gus mutagenesis, (ii) development of a hidden Markov model (HMM) trained with known and transposon-identified Hrp promoter sequences, (iii) HMM identification of promoters upstream of 12 additional virulence-implicated genes, and (iv) microarray and RNA blot analyses of the HrpLdependent expression of a representative subset of these DC3000 genes. We found that the Hrp regulon encodes candidates for 4 additional type III secretion machinery accessory factors, homologs of the effector proteins HopPsyA, AvrPpiB1 (2 copies), AvrPpiC2, AvrPphD (2 copies), AvrPphE, AvrPphF, and AvrXv3, and genes associated with the production or metabolism of virulence factors unrelated to the Hrp type III secretion system, including syringomycin synthetase (SyrE), N-(indole-3-acetyl)-L-lysine synthetase (IaaL), and a subsidiary regulon controlling coronatine production. Additional candidate effector genes, hopPtoA2, hopPtoB2, and an avrRps4 homolog, were preceded by Hrp promoter-like sequences, but these had HMM expectation values of relatively low significance and were not detectably activated by HrpL

    Comparative Genomics of Emerging Human Ehrlichiosis Agents

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    Anaplasma (formerly Ehrlichia) phagocytophilum, Ehrlichia chaffeensis, and Neorickettsia (formerly Ehrlichia) sennetsu are intracellular vector-borne pathogens that cause human ehrlichiosis, an emerging infectious disease. We present the complete genome sequences of these organisms along with comparisons to other organisms in the Rickettsiales order. Ehrlichia spp. and Anaplasma spp. display a unique large expansion of immunodominant outer membrane proteins facilitating antigenic variation. All Rickettsiales have a diminished ability to synthesize amino acids compared to their closest free-living relatives. Unlike members of the Rickettsiaceae family, these pathogenic Anaplasmataceae are capable of making all major vitamins, cofactors, and nucleotides, which could confer a beneficial role in the invertebrate vector or the vertebrate host. Further analysis identified proteins potentially involved in vacuole confinement of the Anaplasmataceae, a life cycle involving a hematophagous vector, vertebrate pathogenesis, human pathogenesis, and lack of transovarial transmission. These discoveries provide significant insights into the biology of these obligate intracellular pathogens

    BioCreative III interactive task: an overview

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    The BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of biomedical literature, provides a diverse and engaged end user group for text mining tools. Earlier BioCreative challenges involved many text mining teams in developing basic capabilities relevant to biological curation, but they did not address the issues of system usage, insertion into the workflow and adoption by curators. Thus in BioCreative III (BC-III), the InterActive Task (IAT) was introduced to address the utility and usability of text mining tools for real-life biocuration tasks. To support the aims of the IAT in BC-III, involvement of both developers and end users was solicited, and the development of a user interface to address the tasks interactively was requested

    Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

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    AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec
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