Towards identification of gene interaction networks of human cholesterol biosynthesis

Peter Juvan, Tadeja Režen, Damjana Rozman, K. Monostory, Jean Marc Pascussi, Aleš Belič

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

It has long been demonstrated that the level of cholesterol in cells regulates the cholesterol biosynthesis through SREBF transcription factors, but lately it has been shown that other factors are also important. To study the system we employed Bayesian network inference and combined it with mathematical modeling and simulation. We constructed a mathematical model of cholesterol biosynthesis and studied its properties through simulation. We measured transcriptional changes of cholesterogenic genes using the Steroltalk microarray and treated human hepatocyte samples. We employed Bayesian inference to identify gene-to-gene interactions from both microarray measurements and simulated data. The inferred networks show that the expression of cholesterogenic genes can be predicted from the expression of 4 key genes, one of them being SREBF2. Networks also indicate a strong interaction between SREBF2 and CYP51A1, but not between SREBF2 and HMGCR, the rate-limiting enzyme of cholesterol biosynthesis. The expression of HMGCR seems to be regulated by other factor(s). Computer simulations of the mathematical model of cholesterol biosynthesis exposed that a large number of perturbations of the system is critical for identification of gene-to-gene interactions, and that differences between human individuals (biological variability) and measurement noise (technical variability) pose a serious problem for their automatic inference from DNA microarray data.

Original languageEnglish
Pages (from-to)396-407
Number of pages12
JournalActa Chimica Slovenica
Volume55
Issue number2
Publication statusPublished - 2008

Fingerprint

Biosynthesis
Genes
Cholesterol
Microarrays
Mathematical models
Bayesian networks
Transcription Factors
DNA
Computer simulation
Enzymes

Keywords

  • Bayesian inference
  • Functional genomics
  • Gene interaction network
  • Human cholesterol biosynthesis
  • Mathematical modeling and simulation
  • Systems biology

ASJC Scopus subject areas

  • Chemistry(all)

Cite this

Juvan, P., Režen, T., Rozman, D., Monostory, K., Pascussi, J. M., & Belič, A. (2008). Towards identification of gene interaction networks of human cholesterol biosynthesis. Acta Chimica Slovenica, 55(2), 396-407.

Towards identification of gene interaction networks of human cholesterol biosynthesis. / Juvan, Peter; Režen, Tadeja; Rozman, Damjana; Monostory, K.; Pascussi, Jean Marc; Belič, Aleš.

In: Acta Chimica Slovenica, Vol. 55, No. 2, 2008, p. 396-407.

Research output: Contribution to journalArticle

Juvan, P, Režen, T, Rozman, D, Monostory, K, Pascussi, JM & Belič, A 2008, 'Towards identification of gene interaction networks of human cholesterol biosynthesis', Acta Chimica Slovenica, vol. 55, no. 2, pp. 396-407.
Juvan, Peter ; Režen, Tadeja ; Rozman, Damjana ; Monostory, K. ; Pascussi, Jean Marc ; Belič, Aleš. / Towards identification of gene interaction networks of human cholesterol biosynthesis. In: Acta Chimica Slovenica. 2008 ; Vol. 55, No. 2. pp. 396-407.
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