Discrete Dynamical System Modeling for Gene Regulatory Networks of HMF Tolerance for Ethanologenic Yeast

Composed of linear difference equations, a discrete dynamical system model was designed to reconstruct transcriptional regulations in gene regulatory networks for ethanologenic yeast Saccharomyces cerevisiae in response to 5-hydroxymethylfurfural, a bioethanol conversion inhibitor. The modeling aims at identification of a system of linear difference equations to represent temporal interactions among significantly expressed genes. Power-stability is imposed on a system model under the normal condition in the absence of the inhibitor. Non-uniform sampling, typical in a time course experimental design, is addressed by a log-time domain interpolation. A statistically significant discrete dynamical system model of the yeast gene regulatory network derived from time course gene expression measurements by exposure to 5-hydroxymethylfurfural, revealed several verified transcriptional regulation events. These events implicate Yap1 and Pdr3, transcription factors consistently known for their regulatory roles by other studies or postulated by independent sequence motif analysis, suggesting their involvement in yeast tolerance and detoxification of the inhibitor.