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Understanding the hidden relations between pro- and anti-inflammatory cytokine genes in bovine oviduct epithelium using a multilayer response surface method.

Rasoul KowsarBehrooz KeshtegarAkio Miyamoto
Published in: Scientific reports (2019)
An understanding gene-gene interaction helps users to design the next experiments efficiently and (if applicable) to make a better decision of drugs application based on the different biological conditions of the patients. This study aimed to identify changes in the hidden relationships between pro- and anti-inflammatory cytokine genes in the bovine oviduct epithelial cells (BOECs) under various experimental conditions using a multilayer response surface method. It was noted that under physiological conditions (BOECs with sperm or sex hormones, such as ovarian sex steroids and LH), the mRNA expressions of IL10, IL1B, TNFA, TLR4, and TNFA were associated with IL1B, TNFA, TLR4, IL4, and IL10, respectively. Under pathophysiological + physiological conditions (BOECs with lipopolysaccharide + hormones, alpha-1-acid glycoprotein + hormones, zearalenone + hormones, or urea + hormones), the relationship among genes was changed. For example, the expression of IL10 and TNFA was associated with (IL1B, TNFA, or IL4) and TLR4 expression, respectively. Furthermore, under physiological conditions, the co-expression of IL10 + TNFA, TLR4 + IL4, TNFA + IL4, TNFA + IL4, or IL10 + IL1B and under pathophysiological + physiological conditions, the co-expression of IL10 + IL4, IL4 + IL10, TNFA + IL10, TNFA + TLR4, or IL10 + IL1B were associated with IL1B, TNFA, TLR4, IL10, or IL4 expression, respectively. Collectively, the relationships between pro- and anti-inflammatory cytokine genes can be changed with respect to the presence/absence of toxins, sex hormones, sperm, and co-expression of other gene pairs in BOECs, suggesting that considerable cautions are needed in interpreting the results obtained from such narrowly focused in vitro studies.
Keyphrases
  • poor prognosis
  • inflammatory response
  • immune response
  • toll like receptor
  • genome wide
  • gene expression
  • dna methylation
  • patient reported outcomes
  • genome wide analysis
  • patient reported