1a. Objectives (from AD-416):
1. Profile the in vivo whole blood RNA and cytokine response to Salmonella Typhimurium infection in animals with high and low fecal shedding phenotypes. 2. Using the same animals in Aim 1, profile the in vitro whole blood RNA and cytokine response to lipopolysaccaride or Salmonella Typhimurium treatments prior to in vivo exposure to Salmonella Typhimurium of the pigs. 3. Annotate response profiles for common expression patterns and functional themes and develop regulatory network information on response to inflammatory stimuli. 4. Develop and test predictive models for identifying pigs with decreased fecal shedding post-infection.
1b. Approach (from AD-416):
The assembled team has expertise and recent experience in collecting and analyzing porcine transcriptional profiling data, as well as in developing computational regulatory networks. We will propose to integrate and extend these datasets to specifically build a database containing transcriptional and regulatory factor-chromatin binding data of the inflammatory response to pathogen challenge. We will use the most comprehensive approaches possible, including the Affymetrix Porcine GeneChip' and/or pig long oligo arrays for ribonucleicacid (RNA) work, and chromatin immunoprecipitation methods for selected transcription factors to develop regulatory network data. These data will then be analyzed using several computational approaches to find genes and develop an understanding of regulatory networks responsible for differences in outcome after infection, and this new information will be applied to find predictors for not only which swine are more resistant to Salmonella infection and shedding but also optimal health traits. We believe this approach will be successful in both establishing molecular measures of health and disease, predicting Salmonella resistant versus susceptible pigs, and identifying the most promising targets for improving animal health and growth in challenging environments.
3. Progress Report:
Research progress with our colleagues at Iowa State University in transcriptionally profiling the porcine response to Salmonella shedding has proceeded to the bioinformatics and statistics stage of analysis. Briefly, 120 pigs were inoculated with Salmonella enterica serovar Typhimurium and monitored over a three week period to identify low shedding and highly persistent shedding pigs. Following classification of ten low and ten persistently shedding pigs based on quantitated Salmonella fecal shedding data, ribonucleicacid (RNA) from porcine blood taken throughout the study was transcriptionally profiled using Affymetrix microarray analysis. Currently the gene expression data is being analyzed for profile patterns to predict a pig’s response to Salmonella. Our goal of the project is to identify a transcriptional profile in pigs (a “classifier”) associated with the susceptibility/resistance of pigs to Salmonella colonization, shedding and carrier status. This classifier will aid in the selection of breeder herds that have elevated resistance to Salmonella and support the development of microbial diagnostic tools to identify Salmonella-carrier pigs.