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

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

BioCreative III interactive task: an overview

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

The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://nar.oxfordjournals.org/

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

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

Disparities in Use of Virtual Primary Care During the Early COVID-19 Pandemic

Background: The COVID-19 pandemic increased the use of virtual health care. However, certain factors may disparately affect some patients\u27 utilization of virtual care. Associations between age, racial categories (White or Black), and socioeconomic disadvantage were evaluated during the early COVID-19 pandemic. Methods: This cross-sectional retrospective study included adult patients with virtual or in-person primary care encounters at a large, midwestern hospital system with widespread urban and suburban offices between March 1, 2020, and June 30, 2020. Virtual visits included synchronous video and telephone visits and asynchronous patient portal E-visits. Chi-squared tests and multivariable logistic analysis assessed the associations between ages and racial categories, and area deprivation index with the use of virtual versus in-person primary care. Results: Of 72,153 patient encounters, 43.0% were virtual visits, 54.6% were White patients, and 45.4% were Black. Across equivalent age ranges, black patients were slightly less likely to utilize virtual care than similarly aged White patients, but not consistently across virtual modalities. Women were more likely to use virtual care across all modalities, and individuals \u3e65 years were more likely to use telephone visits and less likely to use video and E-visits, regardless of race. Patients residing in areas with the greatest socioeconomic advantage were more likely to utilize video and E-visits. Conclusions: Differential patterns of utilization emerged across racial categories and age ranges, suggesting that racial disparities are exacerbated depending upon patient age and mode of utilization

The “Minimum Information about an ENvironmental Sequence” (MIENS) specification

We present the Genomic Standards Consortium’s (GSC) “Minimum Information about an ENvironmental Sequence” (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biospher

The complete genome sequence of the \u3ci\u3eArabidopsis\u3c/i\u3e and tomato pathogen \u3ci\u3ePseudomonas syringae\u3c/i\u3e pv. \u3ci\u3etomato\u3c/i\u3e DC3000

We report the complete genome sequence of the model bacterial pathogen Pseudomonas syringae pathovar tomato DC3000 (DC3000), which is pathogenic on tomato and Arabidopsis thaliana. The DC3000 genome (6.5 megabases) contains a circular chromosome and two plasmids, which collectively encode 5,763 ORFs. We identified 298 established and putative virulence genes, including several clusters of genes encoding 31 confirmed and 19 predicted type III secretion system effector proteins. Many of the virulence genes were members of paralogous families and also were proximal to mobile elements, which collectively comprise7%of the DC3000 genome. The bacterium possesses a large repertoire of transporters for the acquisition of nutrients, particularly sugars, as well as genes implicated in attachment to plant surfaces. Over 12% of the genes are dedicated to regulation, which may reflect the need for rapid adaptation to the diverse environments encountered during epiphytic growth and pathogenesis. Comparative analyses confirmed a high degree of similarity with two sequenced pseudomonads, Pseudomonas putida and Pseudomonas aeruginosa, yet revealed 1,159 genes unique to DC3000, of which 811 lack a known function. Includes published article and additional supporting materials

Complete Genome Sequence of the Oral Pathogenic Bacterium Porphyromonas gingivalis Strain W83

The complete 2,343,479-bp genome sequence of the gram-negative, pathogenic oral bacterium Porphyromonas gingivalis strain W83, a major contributor to periodontal disease, was determined. Whole-genome comparative analysis with other available complete genome sequences confirms the close relationship between the Cytophaga-Flavobacteria-Bacteroides (CFB) phylum and the green-sulfur bacteria. Within the CFB phyla, the genomes most similar to that of P. gingivalis are those of Bacteroides thetaiotaomicron and B. fragilis. Outside of the CFB phyla the most similar genome to P. gingivalis is that of Chlorobium tepidum, supporting the previous phylogenetic studies that indicated that the Chlorobia and CFB phyla are related, albeit distantly. Genome analysis of strain W83 reveals a range of pathways and virulence determinants that relate to the novel biology of this oral pathogen. Among these determinants are at least six putative hemagglutinin-like genes and 36 previously unidentified peptidases. Genome analysis also reveals that P. gingivalis can metabolize a range of amino acids and generate a number of metabolic end products that are toxic to the human host or human gingival tissue and contribute to the development of periodontal disease

The complete genome sequence of Chlorobium tepidum TLS, a photosynthetic, anaerobic, green-sulfur bacterium

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