924 resultados para Arnold Bode


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Pseudomonas syringae pv. phaseolicola is the seed borne causative agent of halo blight in the common bean Phaseolus vulgaris. Pseudomonas syringae pv. phaseolicola race 4 strain 1302A contains the avirulence gene hopAR1 (located on a 106-kb genomic island, PPHGI-1, and earlier named avrPphB), which matches resistance gene R3 in P. vulgaris cultivar Tendergreen (TG) and causes a rapid hypersensitive reaction (HR). Here, we have fluorescently labeled selected Pseudomonas syringae pv. phaseolicola 1302A and 1448A strains (with and without PPHGI-1) to enable confocal imaging of in-planta colony formation within the apoplast of resistant (TG) and susceptible (Canadian Wonder [CW]) P. vulgaris leaves. Temporal quantification of fluorescent Pseudomonas syringae pv. phaseolicola colony development correlated with in-planta bacterial multiplication (measured as CFU/ml) and is, therefore, an effective means of monitoring Pseudomonas syringae pv. phaseolicola endophytic colonization and survival in P. vulgaris. We present advances in the application of confocal microscopy for in-planta visualization of Pseudomonas syringae pv. phaseolicola colony development in the leaf mesophyll to show how the HR defense response greatly affects colony morphology and bacterial survival. Unexpectedly, the presence of PPHGI-1 was found to cause a reduction of colony development in susceptible P. vulgaris CW leaf tissue. We discuss the evolutionary consequences that the acquisition and retention of PPHGI-1 brings to Pseudomonas syringae pv. phaseolicola in planta.

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The immense social and economic impact of bacterial pathogens, from drug-resistant infections in hospitals to the devastation of agricultural resources, has resulted in major investment to understand the causes and conse- quences of pathogen evolution. Recent genome se- quencing projects have provided insight into the evolution of bacterial genome structures; revealing the impact of mobile DNA on genome restructuring and pathogenicity. Sequencing of multiple genomes of relat- ed strains has enabled the delineation of pathogen evo- lution and facilitated the tracking of bacterial pathogens globally. Other recent theoretical and empirical studies have shown that pathogen evolution is significantly influenced by ecological factors, such as the distribution of hosts within the environment and the effects of co- infection. We suggest that the time is ripe for experi- mentalists to use genomics in conjunction with evolu- tionary ecology experiments to further understanding of how bacterial pathogens evolve.

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The atmospheric component of the United Kingdom’s new High-resolution Global Environmental Model (HiGEM) has been run with interactive aerosol schemes that include biomass burning and mineral dust. Dust emission, transport, and deposition are parameterized within the model using six particle size divisions, which are treated independently. The biomass is modeled in three nonindependent modes, and emissions are prescribed from an external dataset. The model is shown to produce realistic horizontal and vertical distributions of these aerosols for each season when compared with available satellite- and ground-based observations and with other models. Combined aerosol optical depths off the coast of North Africa exceed 0.5 both in boreal winter, when biomass is the main contributor, and also in summer, when the dust dominates. The model is capable of resolving smaller-scale features, such as dust storms emanating from the Bode´ le´ and Saharan regions of North Africa and the wintertime Bode´ le´ low-level jet. This is illustrated by February and July case studies, in which the diurnal cycles of model variables in relation to dust emission and transport are examined. The top-of-atmosphere annual mean radiative forcing of the dust is calculated and found to be globally quite small but locally very large, exceeding 20 W m22 over the Sahara, where inclusion of dust aerosol is shown to improve the model radiative balance. This work extends previous aerosol studies by combining complexity with increased global resolution and represents a step toward the next generation of models to investigate aerosol–climate interactions. 1. Introduction Accurate modeling of mineral dust is known to be important because of its radiative impact in both numerical weather prediction models (Milton et al. 2008; Haywood et

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Uncertainties in sea-level projections for the 21st century have focused ice sheet modelling efforts to include the processes that are thought to be contributing to the recently observed rapid changes at ice sheet margins. This effort is still in its infancy, however, leaving us unable to make reliable predictions of ice sheet responses to a warming climate if such glacier accelerations were to increase in size and frequency. The geological record, however, has long identified examples of nonlinear ice sheet response to climate forcing (Shackleton NJ, Opdyke ND. 1973. Oxygen isotope and paleomagnetic stratigraphy of equatorial Pacific core V28–239, late Pliocene to latest Pleistocene. Geological Society of America Memoirs145: 449–464; Fairbanks RG. 1989. A 17,000 year glacio-eustatic sea level record: influence of glacial melting rates on the Younger Dryas event and deep ocean circulation. Nature342: 637–642; Bard E, Hamelin B, Arnold M, Montaggioni L, Cabioch G, Faure G, Rougerie F. 1996. Sea level record from Tahiti corals and the timing of deglacial meltwater discharge. Nature382: 241–244), thus suggesting an alternative strategy for constraining the rate and magnitude of sea-level change that we might expect by the end of this century. Copyright © 2009 John Wiley & Sons, Ltd.

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This article presents a case study of a comparison of an Eulerian chemical transport model (CTM) and Lagrangian chemical model with measurements taken by aircraft. High-resolution Eulerian integrations produce improved point-by-point comparisons between model results and measurements compared to low resolution. The Lagrangian model requires mixing to be introduced in order to model the measurements.

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The co-evolution of bacterial plant pathogens and their hosts is a complex and dynamic process. Plant resistance can impose stress on invading pathogens that can lead to, and select for, beneficial changes in the bacterial genome. The Pseudomonas syringae pv. phaseolicola (Pph) genomic island PPHGI-1 carries an effector gene, avrPphB (hopAR1), which triggers the hypersensitive reaction in bean plants carrying the R3 resistance gene. Interaction between avrPphB and R3 generates an antimicrobial environment within the plant, resulting in the excision of PPHGI-1 and its loss from the genome. The loss of PPHGI-1 leads to the generation of a Pph strain able to cause disease in the plant. In this study, we observed that lower bacterial densities inoculated into resistant bean (Phaseolus vulgaris) plants resulted in quicker PPHGI-1 loss from the population, and that loss of the island was strongly influenced by the type of plant resistance encountered by the bacteria. In addition, we found that a number of changes occurred in the bacterial genome during growth in the plant, whether or not PPHGI-1 was lost. We also present evidence that the circular PPHGI-1 episome is able to replicate autonomously when excised from the genome. These results shed more light onto the plasticity of the bacterial genome as it is influenced by in planta conditions.

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Pathogenicity islands (PAIs) were first described in uropathogenic E. coli. They are now defined as regions of DNA that contain virulence genes and are present in the genome of pathogenic strains, but absent from or only rarely present in non-pathogenic variants of the same or related strains. Other features include a variable G+C content, distinct boundaries from the rest of the genome and the presence of genes related to mobile elements such as insertion sequences, integrases and transposases. Although PAIs have now been described in a wide range of both plant and animal pathogens it has become evident that the general features of PAIs are displayed by a number of regions of DNA with functions other than pathogenicity, such as symbiosis and antibiotic resistance, and the general term genomic islands has been adopted. This review will describe a range of genomic islands in plant pathogenic bacteria including those that carry effector genes, phytotoxins and the type III protein secretion cluster. The review will also consider some medically important bacteria in order to discuss the range, acquisition and stabilization of genomic islands.

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Bacterial pathogens exhibit significant variation in their genomic content of virulence factors. This reflects the abundance of strategies pathogens evolved to infect host organisms by suppressing host immunity. Molecular arms-races have been a strong driving force for the evolution of pathogenicity, with pathogens often encoding overlapping or redundant functions, such as type III protein secretion effectors and hosts encoding ever more sophisticated immune systems. The pathogens’ frequent exposure to other microbes, either in their host or in the environment, provides opportunities for the acquisition or interchange of mobile genetic elements. These DNA elements accessorise the core genome and can play major roles in shaping genome structure and altering the complement of virulence factors. Here, we review the different mobile genetic elements focusing on the more recent discoveries and highlighting their role in shaping bacterial pathogen evolution.

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Pseudomonas syringae pv. phaseolicola causes halo blight of the common bean, Phaseolus vulgaris, worldwide and remains difficult to control. Races of the pathogen cause either disease symptoms or a resistant hypersensitive response on a series of differentially reacting bean cultivars. The molecular genetics of the interaction between P. syringae pv. phaseolicola and bean, and the evolution of bacterial virulence, have been investigated in depth and this research has led to important discoveries in the field of plant-microbe interactions. In this review, we discuss several of the areas of study that chart the rise of P. syringae pv. phaseolicola from a common pathogen of bean plants to a molecular plant-pathogen supermodel bacterium. Taxonomy: Bacteria; Proteobacteria, gamma subdivision; order Pseudomonadales; family Pseudomonadaceae; genus Pseudomonas; species Pseudomonas syringae; Genomospecies 2; pathogenic variety phaseolicola. Microbiological properties: Gram-negative, aerobic, motile, rod-shaped, 1.5 µm long, 0.7-1.2 µm in diameter, at least one polar flagellum, optimal temperatures for growth of 25-30 °C, oxidase negative, arginine dihydrolase negative, levan positive and elicits the hypersensitive response on tobacco. Host range: Major bacterial disease of common bean (Phaseolus vulgaris) in temperate regions and above medium altitudes in the tropics. Natural infections have been recorded on several other legume species, including all members of the tribe Phaseoleae with the exception of Desmodium spp. and Pisum sativum. Disease symptoms: Water-soaked lesions on leaves, pods, stems or petioles, that quickly develop greenish-yellow haloes on leaves at temperatures of less than 23 °C. Infected seeds may be symptomless, or have wrinkled or buttery-yellow patches on the seed coat. Seedling infection is recognized by general chlorosis, stunting and distortion of growth. Epidemiology: Seed borne and disseminated from exudation by water-splash and wind occurring during rainfall. Bacteria invade through wounds and natural openings (notably stomata). Weedy and cultivated alternative hosts may also harbour the bacterium. Disease control: Some measure of control is achieved with copper formulations and streptomycin. Pathogen-free seed and resistant cultivars are recommended. Useful websites: Pseudomonas-plant interaction http://www.pseudomonas-syringae.org/; PseudoDB http://xbase.bham.ac.uk/pseudodb/; Plant Associated and Environmental Microbes Database (PAMDB) http://genome.ppws.vt.edu/cgi-bin/MLST/home.pl; PseudoMLSA Database http://www.uib.es/microbiologiaBD/Welcome.html.

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