Exploring interactions of plant microbiomes

A plethora of microbial cells is present in every gram of soil, and microbes are found extensively in plant and animal tissues. The mechanisms governed by microorganisms in the regulation of physiological processes of their hosts have been extensively studied in the light of recent findings on microbiomes. In plants, the components of these microbiomes may form distinct communities, such as those inhabiting the plant rhizosphere, the endosphere and the phyllosphere. In each of these niches, the "microbial tissue" is established by, and responds to, specific selective pressures. Although there is no clear picture of the overall role of the plant microbiome, there is substantial evidence that these communities are involved in disease control, enhance nutrient acquisition, and affect stress tolerance. In this review, we first summarize features of microbial communities that compose the plant microbiome and further present a series of studies describing the underpinning factors that shape the phylogenetic and functional plant-associated communities. We advocate the idea that understanding the mechanisms by which plants select and interact with their microbiomes may have a direct effect on plant development and health, and further lead to the establishment of novel microbiome-driven strategies, that can cope with the development of a more sustainable agriculture

Sobrecarga de ferro transfusional em portadores de anemia falciforme: comparação entre ressonância magnética e ferritina sérica

OBJETIVO: Identificar variáveis preditoras de sobrecarga de ferro em portadores de anemia falciforme e correlacionar indicadores bioquímicos e imaginológicos. MATERIAiS E MÉTODOS: Foi realizado estudo transversal envolvendo 32 portadores de anemia falciforme, que foram submetidos a dosagem sérica de ferro, ferritina e a ressonância magnética do fígado. Foram realizadas cinco sequências gradiente-eco e uma spin-eco. A intensidade de sinal foi obtida em cada sequência pelas médias das regiões de interesse no fígado e musculatura paravertebral para obter a razão da intensidade de sinal (RIS) fígado/músculo. A partir da RIS foi obtida a concentração hepática estimada de ferro (CHEF) pela fórmula: e[5,808 - (0,877 × T2*) - (1,518 × PI)], onde T2* é a RIS na sequência com TE de 13 ms e PI é a RIS da sequência com ponderação intermediária. Os pacientes foram agrupados segundo o regime de transfusão de hemácias (regulares mensais versus esporádicas). RESULTADOS: Os grupos transfusionais foram comparados pelas variáveis clínico-laboratoriais, sendo significativas as diferenças entre RIS, CHEF e ferritina sérica: o grupo que recebeu transfusões regulares apresentou sobrecarga de ferro hepático mais intensa. CONCLUSÃO: A ressonância magnética foi ferramenta eficiente para avaliação de sobrecarga hepática de ferro em portadores de anemia falciforme

Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains

Ruiz JC, D'Afonseca V, Silva A, et al. Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains. PLoS ONE. 2011;6(4): e18551.Background: Corynebacterium pseudotuberculosis, a Gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity. Methodology and Findings: We characterized two C. pseudotuberculosis genomes (Cp1002, isolated from goats; and CpC231, isolated from sheep). Analysis of the predicted genomes showed high similarity in genomic architecture, gene content and genetic order. When C. pseudotuberculosis was compared with other Corynebacterium species, it became evident that this pathogenic species has lost numerous genes, resulting in one of the smallest genomes in the genus. Other differences that could be part of the adaptation to pathogenicity include a lower GC content, of about 52%, and a reduced gene repertoire. The C. pseudotuberculosis genome also includes seven putative pathogenicity islands, which contain several classical virulence factors, including genes for fimbrial subunits, adhesion factors, iron uptake and secreted toxins. Additionally, all of the virulence factors in the islands have characteristics that indicate horizontal transfer. Conclusions: These particular genome characteristics of C. pseudotuberculosis, as well as its acquired virulence factors in pathogenicity islands, provide evidence of its lifestyle and of the pathogenicity pathways used by this pathogen in the infection process. All genomes cited in this study are available in the NCBI Genbank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers CP001809 and CP001829

De pivete a funqueiro: genealogia de uma alteridade

Com base na teoria das representações sociais de Moscovici e a partir de contextualizações do fenômeno dos arrastões, esse texto se propõe a discutir elementos que respondam às questões: por que discursos criminalizantes, que afirmam a periculosidade do funkeiro, se fizeram tão presentes desde o início da década de noventa no Rio de Janeiro? Como esses discursos, que apontam para uma determinada construção social do funkeiro, interferiram na relação do funk com a sociedade? A discussão passa pela compreensão dos dispositivos criados na sociedade carioca daquele período para a solução de problemas com os quais ela se via confrontada. Trata-se de tentar compreender como, em certo momento, o funkeiro ganha um perfil amplamente difundido como problema que requer um tipo de intervenção específica

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio