2 resultados para Host defence

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Traditional cell culture models have limitations in extrapolating functional mechanisms that underlie strategies of microbial virulence. Indeed during the infection the pathogens adapt to different tissue-specific environmental factors. The development of in vitro models resembling human tissue physiology might allow the replacement of inaccurate or aberrant animal models. Three-dimensional (3D) cell culture systems are more reliable and more predictive models that can be used for the meaningful dissection of host–pathogen interactions. The lung and gut mucosae often represent the first site of exposure to pathogens and provide a physical barrier against their entry. Within this context, the tracheobronchial and small intestine tract were modelled by tissue engineering approach. The main work was focused on the development and the extensive characterization of a human organotypic airway model, based on a mechanically supported co-culture of normal primary cells. The regained morphological features, the retrieved environmental factors and the presence of specific epithelial subsets resembled the native tissue organization. In addition, the respiratory model enabled the modular insertion of interesting cell types, such as innate immune cells or multipotent stromal cells, showing a functional ability to release pertinent cytokines differentially. Furthermore this model responded imitating known events occurring during the infection by Non-typeable H. influenzae. Epithelial organoid models, mimicking the small intestine tract, were used for a different explorative analysis of tissue-toxicity. Further experiments led to detection of a cell population targeted by C. difficile Toxin A and suggested a role in the impairment of the epithelial homeostasis by the bacterial virulence machinery. The described cell-centered strategy can afford critical insights in the evaluation of the host defence and pathogenic mechanisms. The application of these two models may provide an informing step that more coherently defines relevant molecular interactions happening during the infection.

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Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management Bull’s eye rot (BER) caused by Neofabraea alba is one of the most frequent and damaging latent infection occurring in stored pome fruits worldwide. Fruit infection occurs in the orchard, but disease symptoms appear only 3 months after harvest, during refrigerated storage. In Italy BER is particularly serious for late harvest apple cultivar as ‘Pink Lady™’. The purposes of this thesis were: i) Evaluate the influence of ‘Pink Lady™’ apple primary metabolites in N. alba quiescence ii) Evaluate the influence of pH in five different apple cultivars on BER susceptibility iii) To find out not chemical method to control N. alba infection iv) Identify some fungal volatile compounds in order to use them as N. alba infections markers. Results regarding the role of primary metabolites showed that chlorogenic, quinic and malic acid inhibit N. alba development. The study based on the evaluation of cultivar susceptibility, showed that Granny Smith was the most resistant apple cultivar among the varieties analyzed. Moreover, Granny Smith showed the lowest pH value from harvest until the end of storage, supporting the thesis that ambient pH could be involved in the interaction between N. alba and apple. In order to find out new technologies able to improve lenticel rot management, the application of a non-destructive device for the determination of chlorophyll content was applied. Results showed that fruit with higher chlorophyll content are less susceptible to BER, and molecular analyses comforted this result. Fruits with higher chlorophyll content showed up-regulation of PGIP and HCT, genes involved in plant defence. Through the application of PTR-MS and SPME GC-MS, 25 volatile organic compounds emitted by N. alba were identified. Among them, 16 molecules were identified as potential biomarkers.