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United States Department of Agriculture

Agricultural Research Service

Title: Identification of Differentially Expressed Genes in Porcine Lung Tissue During Salmonella Enterica Serovar Choleraesuis Infection Using a 13,000 Swine Gene Oligo Microarray.

Authors
item Zhao, Shu-Hong - AMES, IOWA
item Recknor, Justin - AMES, IOWA
item Nettleton, Dan - AMES, IOWA
item Lunney, Joan
item Uthe, Jolita - CDC AMES, IOWA
item Bearson, Shawn - CDC AMES, IOWA
item Tuggle, Christopher - AMES, IOWA

Submitted to: Plant and Animal Genome VX Conference Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: January 24, 2005
Publication Date: February 5, 2005
Citation: Zhao, S., Recknor, J., Nettleton, D., Lunney, J.K., Uthe, J.J., Bearson, S., Tuggle, C.K. 2005. Identification of differentially expressed genes in porcine lung tissue during salmonella enterica serovar choleraesuis infection using a 13,000 swine gene oligo microarray. [abstract]. Plant and Animal Genome. http://www.intl-pag.org/cgi-bin/swish-bin/SwishPAGXIII.pl.

Technical Abstract: Salmonella infections are economically important in the pig industry. Our research is aimed at defining means of controlling, or preventing, these infections. Previous investigations have highlighted the importance of inflammatory cytokine gene expression during Salmonella infection. High-throughput gene expression profiling is seldom used in this area. The first-generation 13,000 element porcine oligo microarray was used to investigate gene expression in porcine lung during Salmonella infection. Salmonella spp-free seven-week-old piglets were intranasally challenged with one billion CFU Salmonella enterica serovar choleraesuis '3246. Total RNA from control, 24 hour, and 48 hour post-infection lung were used for the microarray hybridizations. Pig lung samples from each time point were randomly assigned to three loops and nine slides were used. Data were analyzed by ANOVA using a mixed model in SAS. Fifty-seven genes showed differential expression at a p < 0.001 significance level (40 genes among them are annotated genes, 16 (40%) are immune-related genes). A total of 339 genes showed differential expression at p < 0.01, 1,300 genes at a p < 0.05 significance level. Cluster analysis by GeneCluster 2.0 software revealed five gene expression clusters with increased or decreased expression post-infection. For example, among the 57 genes with strongest statistical evidence for differential expression, 24 genes decreased their expression level and 33 genes showed increased expression at 48 hours post-infection. Validation of differential expression for selected immune related genes using quantitative PCR is underway and should help confirm immune regulatory pathways activated in lung defence against this infection.

Last Modified: 11/28/2014