Modeling Klebsiella pneumoniae pathogenesis by infection of the wax moth Galleria mellonella

The implementation of infection models that approximate human disease is essential for understanding pathogenesis at the molecular level and for testing new therapies before they are entered into clinical stages. Insects are increasingly being used as surrogate hosts because they share, with mammals, essential aspects of the innate immune response to infections. We examined whether the larva of the wax moth Galleria mellonella could be used as a host model to conceptually approximate Klebsiella pneumoniae-triggered pneumonia. We report that the G. mellonella model is capable of distinguishing between pathogenic and nonpathogenic Klebsiella strains. Moreover, K. pneumoniae infection of G. mellonella models some of the known features of Klebsiella-induced pneumonia, i.e., cell death associated with bacterial replication, avoidance of phagocytosis by phagocytes, and the attenuation of host defense responses, chiefly the production of antimicrobial factors. Similar to the case for the mouse pneumonia model, activation of innate responses improved G. mellonella survival against subsequent Klebsiella challenge. Virulence factors necessary in the mouse pneumonia model were also implicated in the Galleria model. We found that mutants lacking capsule polysaccharide, lipid A decorations, or the outer membrane proteins OmpA and OmpK36 were attenuated in Galleria. All mutants activated G. mellonella defensive responses. The Galleria model also allowed us to monitor Klebsiella gene expression. The expression levels of cps and the loci implicated in lipid A remodeling peaked during the first hours postinfection, in a PhoPQ- and PmrAB-governed process. Taken together, these results support the utility of G. mellonella as a surrogate host for assessing infections with K. pneumoniae.

The distribution of Fasciola hepatica and Fasciola gigantica within southern Tanzania - constraints associated with the intermediate host

In East Africa, Fasciola gigantica is generally the causative agent of fasciolosis but there have been reports of F. hepatica in cattle from highland regions of Kenya, Ethiopia, Uganda and Zaire. The topography of the Southern Highlands of Tanzania provides an environment where the climatic conditions exist for the sustenance of lymnaeid species capable of Supporting both Fasciola hepatica and F. gigantica. Theoretically this would allow interaction between fasciolid species and the possible creation of hybrids. In this report we present molecular data confirming the existence of the snail, Lymnaea truncatula, at high altitude on the Kitulo Plateau of the Southern Highlands, Tanzania, along with morphometric and molecular data confirming the presence of F. hepatica in the corresponding area. At lower altitudes, where climatic conditions were unfavourable for the existence of L. truncatula, the presence of its sister species L. natalensis was confirmed by molecular data along with its preferred fasciolid parasite, F. gigantica. Analysis based on a 618 bp sequence of the 28S rRNA gene did not reveal the presence of hybrid fasciolids in our fluke samples.

Ecological impacts of the microsporidian parasite Pleistophora mulleri on its freshwater amphipod host Gammarus duebeni celticus

The microsporidian parasite, Pleistophora mulleri, infects the abdominal muscle of the freshwater amphipod Gammarus duebeni celticus. We recently showed that P. mulleri infection was associated with G. d. celticus hosts being more vulnerable to predation by the invasive amphipod Gammarus pulex. Parasitized G. d. celticus also had a reduced ability to prey upon other co-occurring amphipods. We suggested the parasite may have pervasive influences on host ecology and behaviour. Here, we examine the association between P. mulleri parasitism and parameters influencing individual host fitness, behaviour and interspecific interactions. We also investigate the relationship between parasite prevalence and host population structure in the field. In our G. d. celticus study population, P. mulleri prevalence was strongly seasonal, ranging from 8.5% in summer to 44.9% in winter. The relative abundance of hosts with the heaviest parasite burden increased during summer, which coincided with high host mortality, suggesting that parasitism may regulate host abundance to some degree. Females were more likely to be parasitized than males and parasitized males were paired with smaller females than unparasitized males. Parasitism was associated with reduction in the host's activity level and reduced both its predation on the isopod Asellus aquaticus and aggression towards precopula pairs of the invasive G. pulex. We discuss the pervasive influence of this parasite on the ecology of its host.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

Foot-and-mouth disease virus, but not bovine enterovirus, targets the host cell cytoskeleton via the nonstructural protein 3Cpro.

Foot-and-mouth disease virus (FMDV), a member of the Picornaviridae, is a pathogen of cloven-hoofed animals and causes a disease of major economic importance. Picornavirus-infected cells show changes in cell morphology and rearrangement of cytoplasmic membranes, which are a consequence of virus replication. We show here, by confocal immunofluorescence and electron microscopy, that the changes in morphology of FMDV-infected cells involve changes in the distribution of microtubule and intermediate filament components during infection. Despite the continued presence of centrosomes in infected cells, there is a loss of tethering of microtubules to the microtubule organizing center (MTOC) region. Loss of labeling for -tubulin, but not pericentrin, from the MTOC suggests a targeting of -tubulin (or associated proteins) rather than a total breakdown in MTOC structure. The identity of the FMDV protein(s) responsible was determined by the expression of individual viral nonstructural proteins and their precursors in uninfected cells. We report that the only viral nonstructural protein able to reproduce the loss of -tubulin from the MTOC and the loss of integrity of the microtubule system is FMDV 3Cpro. In contrast, infection of cells with another picornavirus, bovine enterovirus, did not affect -tubulin distribution, and the microtubule network remained relatively unaffected.

Host-based P2P flow identification and use in real-time

Data identification is a key task for any Internet Service Provider (ISP) or network administrator. As port fluctuation and encryption become more common in P2P traffic wishing to avoid identification, new strategies must be developed to detect and classify such flows. This paper introduces a new method of separating P2P and standard web traffic that can be applied as part of a data mining process, based on the activity of the hosts on the network. Unlike other research, our method is aimed at classifying individual flows rather than just identifying P2P hosts or ports. Heuristics are analysed and a classification system proposed. The accuracy of the system is then tested using real network traffic from a core internet router showing over 99% accuracy in some cases. We expand on this proposed strategy to investigate its application to real-time, early classification problems. New proposals are made and the results of real-time experiments compared to those obtained in the data mining research. To the best of our knowledge this is the first research to use host based flow identification to determine a flows application within the early stages of the connection.