BackgroundOnce a list of differentially expressed genes has been identified from a microarray experiment, a subsequent post-analysis task is required in order to find the main biological processes associated to the experimental system. This paper describes two pathways analysis tools, ArrayUnlock and Ingenuity Pathways Analysis (IPA) to deal with the post-analyses of microarray data, in the context of the EADGENE and SABRE post-analysis workshop. Dataset employed in this study proceeded from an experimental chicken infection performed to study the host reactions after a homologous or heterologous secondary challenge with two species of Eimeria.ResultsAnalysis of the same microarray data source employing both commercial pathway analysis tools in parallel let to identify several biological and/or molecular functions altered in the chicken Eimeria maxima infection model, including several immune system related pathways. Biological functions differentially altered in the homologous and heterologous second infection were identified. Similarly, the effect of the timing in a homologous second infection was characterized by several biological functions.ConclusionFunctional analysis with ArrayUnlock and IPA provided information related to functional differences with the three comparisons of the chicken infection leading to similar conclusions. ArrayUnlock let an improvement of the annotations of the chicken genome adding InterPro annotations to the data set file. IPA provides two powerful tools to understand the pathway analysis results: the networks and canonical pathways that showed several pathways related to an adaptative immune response.

Salmonella enterica serovar Typhimurium causes enteric disease and compromises food safety. In pigs, the molecular response of the intestine to S. typhimurium has been traditionally characterized by in vitro models that do not reflect the actual immunological competence of the intestinal mucosa. In this work, we performed an oral S. typhimurium infection study to obtain insight into the in vitro response in three different sections (jejunum, ileum and colon) of the porcine intestine. For this, samples from one-month-old infected piglets were collected during a time course comprising 1, 2, and 6 days post inoculation to evaluate the intestinal response by quantifying the mRNA expression of gene coding for 28 innate immune system molecules using quantitative real-time PCR assays. In addition, samples from non-infected control animals were also employed to establish differences in the steady state gene expression between intestinal sections. The panel of quantified molecules included an assortment of cytokines, chemokines, pattern-recognition receptors, intracellular signaling molecules, transcription factors and antimicrobial molecules. Changes in gene expression occurred in the three different parts of the intestine and during the course of the S. typhimurium infection. Moreover, the high variation observed in expression patterns of genes coding for inflammatory mediators could indicate that each intestinal section responds differently to the infection. Thus, on the contrary to findings in the jejunum and colon, a down-regulation and lack of induction of some proinflammatory cytokine transcripts was observed in the ileum. Nevertheless, all chemoattractant cytokines assayed were up-regulated in the ileum and jejunum whereas only interleukin-8 and MIP-1α mRNA were over expressed in the colon. In conclusion, our results reveal regional differences in gene expression profiles along the porcine intestinal gut as well as regional differences in the inflammatory response to S. typhimurium infection. Taken together, these data should provide a basis for a complete understanding of the porcine intestinal response to bacterial infection.

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BackgroundThe aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria.ResultsSeveral conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached.ConclusionIt is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.

In this paper, we present the protein map corresponding to the porcine peripheral blood mononuclear cells (PBMC) to better understand the role of these cells in the pig immune system. To conform the map, the proteins were separated by 2-DE using a 5-8 range pH gradient in IEF and approximately 800 spots were detected. Due to the high level of indeterminate variability associates to the 2-DE, analytical and biological variances were analyzed. The analytical variance was calculated for 50 proteins in three replicate 2-DE gels from the same protein extract whereas the biological variance was determined by comparison of the patterns obtained for the same 50 proteins in different animals. Values of 15.13 and 33.70% were determined for analytical and biological variances, respectively. These average variances will provide a quantified and statistical basis for future proteomic studies directed to evaluate relevant quantitative changes in the biological response. A representative set of the major proteins was subjected to MALDI-TOF analysis and over 75% of the proteins were identified on the basis of their similarity with its human homologue proteins. A large number of cytoskeletal and metabolic proteins were found as well as some proteins related to cell mobility and immunological functions. Finally, other proteins implicated in the cell signaling process, transport or apoptosis were also identified giving a wide overview of the porcine PBMC protein map.

Porcine circovirus type 2 (PCV2) has been identified as the essential causal agent of postweaning multisystemic wasting syndrome. However, little is known regarding the mechanism(s) underlying the pathogenesis of PCV2-induced disease and the interaction of the virus with the host immune system. Here, we present a proteomics study on inguinal lymph nodes of piglets inoculated with PCV2, in order to better understand the pathogenesis of postweaning multisystemic wasting syndrome and the pathways might be affected after infection. We used two proteomics strategies, 2-DE and 1-DE followed by (16)O/(18)O peptide labelling and peptide identification and quantification by MS. More than 100 proteins were found to be differentially regulated and the results obtained by the two strategies were fairly concordant but also complementary, the (18)O labelling approach being a more robust alternative. Analysis of these proteins by systems biology tools revealed the implication of acute phase response and NrF2-mediated oxidative stress, suggesting a putative role for these pathways in the pig immune response. Besides, CD81 was found to be up-regulated, suggesting a possible role in the internalization of the virus. The use of proteomics technologies together with biology analysis systems opens up the way to gain more exhaustive and systematic knowledge of virus-pathogen interactions.

Despite continuous advances in hyperglycemia treatments, a precise control through monitoring of glucose and glycated hemoglobin remains in most diabetic patients as the diagnosis/prognosis tool. An alternative perspective could be the discovery and quantitation of new blood glycated proteins formed by nonenzymatic reaction with circulatory glucose. As a result, the human hemolysate is an incomparable source of glycated proteins to further monitor glycemia and interpret changes at the level of this post-translational modification. The human hemolysate is here studied based on the differential labeling of proteins with isotopically labeled-glucose ([(13)C(6)] glucose), named glycation isotopic labeling. Due to the chemoselectivity of glycation, only preferential targets are labeled by this protocol. The approach provides qualitative data through the detection of preferential protein glycation sites as well as quantitative information to evaluate the abundance of this modification. This strategy was applied to human hemolysate samples corresponding to different glycemic states estimated by laboratory-certified concentrations of glycated hemoglobin. The glycation level of each protein can then be employed to interpret the effect of glucose exposition as a consequence of glycemic unbalance. This information should provide new molecular insights into protein glycation mechanisms that might generate a new hypothesis to clinicians to improve the understanding of underlying pathologies associated to prolonged hyperglycemia.

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