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，例如以小时为尺度的昼夜节律或超昼夜周期，以及以分钟为尺度的快速和短暂的转录爆发。这种循环的机制知之甚少，但对于药物的正确应用非常重要。在转录水平，基因表达由DNA启动子和增强子内的调控元件的可及性控制。在酵母和哺乳动物细胞中的研究表明，染色质可及性的调节通过转录因子（TF）和染色质重塑剂的相互作用发生。某些TF与其靶DNA序列的结合是高度动态的，以秒为尺度。此外，一些TF经历分钟尺度的“缓慢”循环，其由交替的“ON”和“OFF”基因状态组成。目前还不清楚这种TF循环与转录循环的关系。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。我们使用作为一个模型的酵母基因CUP 1编码金属硫蛋白表达的重金属胁迫。CUP 1由铜结合的TF Ace 1 p激活。我们以前的研究证明了两种类型的Ace 1 p循环在CUP 1：快-在秒的规模，和慢-在分钟的规模。快循环发生在慢循环中。结合的慢循环可以通过常规荧光成像在单个细胞中定量，并且快速循环-通过单分子追踪（SMT）。此前，我们已经为SMT构建了定制仪器，并优化了SMT数据解释。我们已经开发了在酵母细胞核中进行SMT的方法和在特异性启动子上进行SMT的方法。通过SMT，我们测量了染色质重塑剂RSC和TF Ace 1 p与CUP 1启动子内特定位点（金属反应元件，MRE）的结合参数。CUP 1的转录可以通过smFISH（荧光原位杂交）或通过荧光标记的mRNA的实时成像来观察。最近，我们通过smFISH将CUP 1启动子的转录活性与TF的结合位点和特定停留时间的搜索变化相关联。我们证明了转录因子的瞬时募集受快速周期性染色质重塑事件的调节，以确保最佳的动态转录反应。我们目前的目标是通过分析活细胞中的转录来证实这些发现。初步观察表明，慢转录周期由单个基因表达的快周期（爆发）组成。这种观察不能在固定的细胞中通过smFISH进行，并提供了有关转录的新信息。这是第一个遗传模型，其中叠加的慢和快的转录周期与叠加的慢和快的转录因子循环相关。我们正在通过实时TS对慢转录和快转录周期进行建模，并通过smFISH建模证实观察结果。最终，这些研究将奠定基础的转录机制的组成部分在体内的相互作用的分析。通过茎环方法原位活转录定量证实了smFISH数据。我们正在开发的TF生物物理学与转录建模相关的技术可以应用于细胞生物学的许多其他问题，其中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.