Microarray analysis of gene expression following preparation of sterile intestinal “loops” in calves

Abstract

The surgical preparation of multiple, sterile intestinal “loops” has provided an effective model for the analysis of vaccine-induced mucosal immune responses in ruminants. The objective of the present investigation was to evaluate intestinal “loops” as a model for genomic analyses of mucosal immune responses. Immunohistochemistry revealed no significant changes in mucosal epithelial cell architecture but microarray analyses were completed to determine if surgery and elimination of microflora significantly altered gene expression in the small intestine of one month-old calves. RNA was isolated from intestinal “loops” (Sample) and adjacent, intact intestine (Control) of each animal at 48 h (n = 3) and 12 d (n = 3) postsurgery. Total RNA from control and sample tissues was hybridized on Pyxis Genomics bovine cDNA microarrays (7884 ESTs) to identify differentially expressed genes. We observed only 2.3% (180/7884) of ESTs were significantly and differentially changed in expression at 48 h post-surgery and approximately 80% (143/180) of these genes were up-regulated. A subset of these differentially expressed genes was validated by quantitative Real Time PCR and these analyses demonstrated that many genes were returning to baseline expression levels at 12 d post-surgery. Notable among differentially expressed genes were gene clusters involved in apoptosis, cell cycle, and cell differentiation. Surgery and elimination of microflora in 1-mo-old calves significantly altered the expression of a relatively minor number of genes but these genes were implicated in important aspects of normal mucosal function. Therefore, intestinal “loops” that control for the effects of surgical manipulation and commensal microflora must be included when conducting mucosal gene expression analyses within this animal model. Key words: Bovine, Cy-dye fluorescence, immunohistochemistry, intestine, microarray, microflora, resonance light scattering, qRT-PCR