Mammalian Genome

, Volume 17, Issue 7, pp 777–789 | Cite as

Gene expression profiling in Salmonella Choleraesuis-infected porcine lung using a long oligonucleotide microarray

  • Shu-Hong Zhao
  • Daniel Kuhar
  • Joan K. Lunney
  • Harry Dawson
  • Catherine Guidry
  • Jolita J. Uthe
  • Shawn M.D. Bearson
  • Justin Recknor
  • Dan Nettleton
  • Christopher K. TuggleEmail author


Understanding the transcriptional response to pathogenic bacterial infection within food animals is of fundamental and applied interest. To determine the transcriptional response to Salmonella enterica serovar Choleraesuis (SC) infection, a 13,297-oligonucleotide swine array was used to analyze RNA from control, 24-h postinoculation (hpi), and 48-hpi porcine lung tissue from pigs infected with SC. In total, 57 genes showed differential expression (p < 0.001; false discovery rate = 12%). Quantitative real-time PCR (qRT-PCR) of 61 genes was used to confirm the microarray results and to identify pathways responding to infection. Of the 33 genes identified by microarray analysis as differentially expressed, 23 were confirmed by qRT-PCR results. A novel finding was that two transglutaminase family genes (TGM1 and TGM3) showed dramatic increases in expression postinoculation; combined with several other apoptotic genes, they indicated the induction of apoptotic pathways during SC infection. A predominant T helper 1-type immune response occurred during infection, with interferon γ (IFNG) significantly increased at 48 hpi. Genes induced by IFNs (GBP1, GBP2, C1S, C1R, MHC2TA, PSMB8, TAP1, TAP2) showed increased expression during porcine lung infection. These data represent the first thorough investigation of gene regulation pathways that control an important porcine respiratory and foodborne bacterial infection.


Differential Gene Expression Analysis Tentative Consensus LOWESS Normalization Mycoplasma Hyopneumoniae Porcine Lung 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This project was supported by USDA-NRI-2004-35205-14202 to CKT, JKL, and DN. Slides used in this study were spotted in collaboration with Dr. V. Kapur of the University of Minnesota as part of the USDA NRSP8 Swine Subcommittee collaborative agreement, and partially subsidized by the Pig Genome Coordinator. The authors thank Sajeev Batra of Qiagen-Operon for producing and providing BLAST analyses data before distribution.

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Shu-Hong Zhao
    • 1
    • 2
  • Daniel Kuhar
    • 3
  • Joan K. Lunney
    • 3
  • Harry Dawson
    • 4
  • Catherine Guidry
    • 4
  • Jolita J. Uthe
    • 5
  • Shawn M.D. Bearson
    • 5
  • Justin Recknor
    • 6
  • Dan Nettleton
    • 6
  • Christopher K. Tuggle
    • 1
    Email author
  1. 1.Department of Animal ScienceIowa State UniversityAmesUSA
  2. 2.Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education & Department of Animal Genetics and BreedingCollege of Animal Science and Technology, Huazhong Agricultural UniversityWuhanPeople’s Republic of China
  3. 3.Animal Parasitic Diseases Laboratory, Animal Natural Resource Institute (ANRI), Agricultural Research Service (ARS)U.S. Department of Agriculture (USDA)BeltsvilleUSA
  4. 4.Nutrient Requirements and Functions Laboratory, Beltsville Human Nutrition Research Center (BHNRC), Agricultural Research Service (ARS)U.S. Department of Agriculture (USDA)BeltsvilleUSA
  5. 5.National Animal Disease Center, Agricultural Research Service (ARS)U.S. Department of Agriculture (USDA)AmesUSA
  6. 6.Department of StatisticsIowa State UniversityAmesUSA

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