Transcription factor mobility

目前的研究表明，许多重要基因的表达是周期性的，并且可能在不同的时间尺度上包含多个周期，例如小时尺度上的昼夜节律或超昼夜周期，以及分钟尺度上的快速和短的转录爆发。这种循环的机制尚不清楚，但对药物的正确应用非常重要。在转录水平上，基因表达受DNA启动子和增强子内调控元件的可及性控制。对酵母和哺乳动物细胞的研究表明，染色质可及性的调节是通过转录因子（TF）和染色质重塑子的相互作用发生的。某些TF与目标DNA序列的结合是高度动态的，以秒为单位。此外，一些TF经历了以分钟为单位的“慢”循环，其中包括交替的“on”和“OFF”基因状态。目前尚不清楚这种TF循环与转录循环之间的关系。我们对启动子上TF循环的分子机制及其与转录周期的相关性感兴趣。我们使用酵母基因CUP1编码金属硫蛋白在重金属胁迫下的表达作为模型。CUP1被铜结合的TF Ace1p激活。我们之前的研究表明，在CUP1上Ace1p循环有两种类型：快的（以秒为单位）和慢的（以分钟为单位）。快循环发生在慢循环中。在单个细胞中，通过常规荧光成像可以定量结合的慢周期，通过单分子跟踪（SMT）可以定量结合的快周期。在此之前，我们已经建立了一个定制的SMT仪器，并优化了SMT数据的解释。我们已经开发了在酵母细胞核中进行SMT的方法和在特定启动子上进行SMT的方法。通过SMT，我们测量了染色质重塑剂RSC和TF Ace1p与CUP1启动子内特定位点（金属响应元件，MRE）的结合参数。CUP1的转录可以通过smFISH（荧光原位杂交）或荧光标记mRNA的实时成像来观察。最近，我们通过smFISH将CUP1启动子的转录活性与寻找结合位点的变化和TF的特定停留时间联系起来。我们证明了tf的短暂募集是由快速的周期性染色质重塑事件调节的，以确保最佳的动态转录反应。我们目前的目标是通过对活细胞转录的分析来证实这些发现。初步观察表明，转录的慢周期由单个基因的快速表达周期（爆发）组成。smFISH无法在固定细胞中进行这种观察，并提供了有关转录的新信息。这是第一个遗传模型，其中转录的叠加慢周期和快速周期与转录因子的叠加慢周期和快速周期相关。我们正致力于通过活体TS模拟慢速和快速转录周期，并通过smFISH模型证实观察结果。最终，这些研究将为分析转录机制组成部分的体内相互作用奠定基础。smFISH数据通过茎环法原位实时转录定量证实。我们正在开发的TF生物物理学与转录建模的相关技术，可以应用于细胞生物学的许多其他问题，这些问题需要转录的分子调控信息。

Current research indicates that expression of many important genes is cyclical, and may incorporate multiple cycles at the different time scale, such as circadian or ultradian cycles on the scale of hours, and fast and short bursts of transcription on the scale of minutes. The mechanisms of this cycling are poorly understood, but very important for the correct application of the drugs. At the transcription level, gene expression is controlled by the accessibility of the regulatory elements within DNA - promoters and enhancers. Research in yeast and mammalian cells indicates that modulation of chromatin accessibility occurs through interaction of transcription factors (TF) and chromatin remodelers. Binding of certain TF to their target DNA sequences is highly dynamic, on the scale of seconds. Also, some TF undergo the "slow" cycling on the scale of minutes, which consist of alternating "ON" and "OFF" gene states. It is unclear how this TF cycling is related to the transcriptional cycling. We are interested in molecular mechanisms of the TF cycling on promoters and its correlation with transcription cycles. We use as a model a yeast gene CUP1 encoding metallothionein expressed in response to heavy metal stress. CUP1 is activated by copper-bound TF Ace1p. Our previous studies demonstrated two types of Ace1p cycling at CUP1: fast - on the scale of seconds, and slow - on the scale of minutes. The fast cycling occurs within the slow cycle. The slow cycle of binding may be quantified in individual cells by the regular fluorescence imaging, and the fast cycling - by Single Molecule Tracking (SMT). Previously, we have built a custom instrument for SMT and optimized SMT data interpretation. We have developed methods for SMT in yeast cell nuclei and methods of performing SMT on specific promoters. By SMT, we have measured binding parameters of a chromatin remodeler RSC and TF Ace1p to specific sites (Metal Response Elements, MRE) within CUP1 promoter. Transcription of CUP1 may be observed either by smFISH (Fluorescence In Situ Hybridization) or by live imaging of the fluorescently tagged mRNA. Recently, we correlated the transcriptional activity of CUP1 promoter by smFISH with changes in the search for the binding sites and the specific residence time of TF. We demonstrated that the transient recruitment of TFs is regulated by fast cyclical chromatin remodeling events to ensure the best dynamic transcriptional response. Our current goal is to corroborate these findings with analysis of the transcription in live cells. Preliminary observations indicate that the slow cycle of transcription consists of the fast cycles (bursts) of expression on individual genes. This kind of observations cannot be made by smFISH in fixed cells and provides new information about transcription. This is the first genetic model where the superimposed slow and fast cycles of transcription correlate with superimposed slow and fast cycling of the transcriptional factor. We are working on modeling of the slow and fast transcription cycles by live TS and corroborating the observations by smFISH modeling. Ultimately, these studies will lay the groundwork for the analysis of in vivo interactions of the components of the transcriptional machinery. The smFISH data are corroborated by the live transcription quantification in situ by a stem-loop approach. The technique of correlation of the TF biophysics with transcription modeling that we are in process of developing may be applied to a number of other problems of cellular biology where the information for molecular regulation of transcription is desired.