Cross-talks of sensory transcription networks in response to various environmental stresses.

For living organisms like Saccharomyces cerevisiae, instinctual response to sudden environmental changes leads to swift establishment of adaptive mechanisms. The issue about how TFs sense and adapt to various environmental stresses has not been systematically studied yet. Here we try to elucidate this problem with the assistance of genomic expression patterns from a computation perspective. A dynamic transcriptional regulatory model is employed to uncover significant TF-target regulatory relationships under various environmental stresses. Based on a global microarray dataset that describes how transcriptional regulators significantly respond to one specific stress, we constructed a sensory transcriptional network for the potential specific stressresponsive regulators. Alternatively, we have observed cross-talks among these sensory transcription networks that may shed light on general stress-responsive regulators. Results reveal that our method not only reconstructs the potential global protection mechanisms under various environmental stresses but also presents a set of reported specific stress-responsive regulators (i.e., Aft2, Hsf1, Msn2, Msn4, Skn7 and Yap1) as well as a set of inferred specific/general stress-responsive regulators that may provide new guidance for further experiments on yeast cells' adaption to environmental stimuli. Though we only make a study on the yeast S. cerevisiae, our method can be broadly applied to all species.