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      Gene expression profiling of Spodoptera frugiperda hemocytes and fat body using cDNA microarray reveals polydnavirus-associated variations in lepidopteran host genes transcript levels

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          Abstract

          Background

          Genomic approaches provide unique opportunities to study interactions of insects with their pathogens. We developed a cDNA microarray to analyze the gene transcription profile of the lepidopteran pest Spodoptera frugiperda in response to injection of the polydnavirus HdIV associated with the ichneumonid wasp Hyposoter didymator. Polydnaviruses are associated with parasitic ichneumonoid wasps and are required for their development within the lepidopteran host, in which they act as potent immunosuppressive pathogens. In this study, we analyzed transcriptional variations in the two main effectors of the insect immune response, the hemocytes and the fat body, after injection of filter-purified HdIV.

          Results

          Results show that 24 hours post-injection, about 4% of the 1750 arrayed host genes display changes in their transcript levels with a large proportion (76%) showing a decrease. As a comparison, in S. frugiperda fat body, after injection of the pathogenic JcDNV densovirus, 8 genes display significant changes in their transcript level. They differ from the 7 affected by HdIV and, as opposed to HdIV injection, are all up-regulated. Interestingly, several of the genes that are modulated by HdIV injection have been shown to be involved in lepidopteran innate immunity. Levels of transcripts related to calreticulin, prophenoloxidase-activating enzyme, immulectin-2 and a novel lepidopteran scavenger receptor are decreased in hemocytes of HdIV-injected caterpillars. This was confirmed by quantitative RT-PCR analysis but not observed after injection of heat-inactivated HdIV. Conversely, an increased level of transcripts was found for a galactose-binding lectin and, surprisingly, for the prophenoloxidase subunits. The results obtained suggest that HdIV injection affects transcript levels of genes encoding different components of the host immune response (non-self recognition, humoral and cellular responses).

          Conclusion

          This analysis of the host-polydnavirus interactions by a microarray approach indicates that the presence of HdIV induces, directly or indirectly, variations in transcript levels of specific host genes, changes that could be responsible in part for the alterations observed in the parasitized host physiology. Development of such global approaches will allow a better understanding of the strategies employed by parasites to manipulate their host physiology, and will permit the identification of potential targets of the immunosuppressive polydnaviruses.

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          Most cited references107

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

            Y. H. Yang (2002)
            There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is often used to force the distribution of the intensity log ratios to have a median of zero for each slide. However, such global normalization approaches are not adequate in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP) is introduced to aid in intensity-dependent normalization. Lastly, to allow for comparisons of expression levels across slides, a robust method based on maximum likelihood estimation is proposed to adjust for scale differences among slides.
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              Cell-surface calreticulin initiates clearance of viable or apoptotic cells through trans-activation of LRP on the phagocyte.

              Apoptotic-cell removal is critical for development, tissue homeostasis, and resolution of inflammation. Although many candidate systems exist, only phosphatidylserine has been identified as a general recognition ligand on apoptotic cells. We demonstrate here that calreticulin acts as a second general recognition ligand by binding and activating LDL-receptor-related protein (LRP) on the engulfing cell. Since surface calreticulin is also found on viable cells, a mechanism preventing inadvertent uptake was sought. Disruption of interactions between CD47 (integrin-associated protein) on the target cell and SIRPalpha (SHPS-1), a heavily glycosylated transmembrane protein on the engulfing cell, permitted uptake of viable cells in a calreticulin/LRP-dependent manner. On apoptotic cells, CD47 was altered and/or lost and no longer activated SIRPalpha. These changes on the apoptotic cell create an environment where "don't eat me" signals are rendered inactive and "eat me" signals, including calreticulin and phosphatidylserine, congregate together and signal for removal.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                2006
                21 June 2006
                : 7
                : 160
                Affiliations
                [1 ]UMR 1231 Biologie Intégrative et Virologie des Insectes. INRA – Université de Montpellier II. Place Eugène Bataillon, Case Courrier 101, 34 095 Montpellier Cedex, France
                [2 ]UMR 1112 R.O.S.E. INRA – Université de Nice-Sophia Antipolis, Laboratoire de Génomique Fonctionnelle des Insectes, 400 route des Chappes, BP 167, 06 903 Sophia Antipolis Cedex, France
                [3 ]INRA U.M.R. Sciences pour l'Oenologie, Equipe Microbiologie – Bât 28, 2, place Viala, 34 060 Montpellier Cedex 01, France
                Article
                1471-2164-7-160
                10.1186/1471-2164-7-160
                1559612
                16790040
                5ff9b2b1-ad13-408e-9b09-7da956e63e7b
                Copyright © 2006 Barat-Houari et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 February 2006
                : 21 June 2006
                Categories
                Research Article

                Genetics
                Genetics

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