Promoter decoding of transcription factor dynamics.
Promoter decoding of transcription factor dynamics.
复制标题
转录因子动力学的启动子解码。
DOI:
10.1038/msb.2013.63
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发表时间:
2013
影响因子:
9.9
通讯作者:
Batchelor,Eric
中科院分区:
文献类型:
--
作者:
Moody,AmieD;Batchelor,Eric
‘Steganography,’meaning ‘concealed writing,’is the art of hiding a secret message within another message. The original message appears to be simply a letter or photograph, yet a person with the requisite knowledge can decode it to find hidden information. As it turns out, cells may have developed a form of steganography. Recent studies have shown that a single transcription factor (TF) can exhibit different dynamics in response to different stimuli (Nelson et al, 2004; Tay et al, 2010; Batchelor et al, 2011; Hao and O’Shea, 2012) and that TF dynamics can alter target gene activation (Tay et al, 2010; Purvis et al, 2012). Hansen and O’Shea (2013) now provide insight into how individual promoters can decode specific TF dynamic patterns to effect distinct gene expression responses. To understand this process, the authors studied Msn2, a yeast transcription factor that responds to different stresses with distinct dynamic expression patterns: short-duration repeated pulses, a single pulse with a dose-dependent duration, or a single pulse with a dose-dependent amplitude (Hao and O’Shea, 2012). Using a small molecule to control nuclear translocation of Msn2, Hansen and O’Shea (2013) challenged cells with a panel of 30 activation profiles simulating the natural Msn2 dynamics, covering a range of duration, amplitude, and number of pulses. To measure the effects of Msn2 dynamics on target gene expression, they generated diploid yeast strains in which genes encoding YFP or CFP replaced the ORFs on homologous chromosomes for seven strongly activated Msn2 target genes. Measuring fluorescence levels from the reporter strains treated with the Msn2 activation profiles demonstrated that promoters responded differently to either sustained Msn2 nuclear localization or pulses (Figure 1). Applying a three-state promoter model to the data, the authors identified two promoter classes: High amplitude threshold, Slow promoters (HS); and Low amplitude threshold, Fast promoters (LF). Of the seven promoters analyzed, three were classified as HS promoters, three as LF promoters, and one promoter was a hybrid that exhibited characteristics of both classes. The authors speculated that four classes of promoters might