发布: 2018年02月20日第8卷第4期 DOI: 10.21769/BioProtoc.2905 浏览次数: 8355
评审: Gal HaimovichAnonymous reviewer(s)
Abstract
Formaldehyde crosslinking is widely used in combination with chromatin immunoprecipitation (ChIP) to measure the locations along DNA and relative levels of transcription factor (TF)-DNA interactions in vivo. However, the measurements that are typically made do not provide unambiguous information about the dynamic properties of these interactions. We have developed a method to estimate binding kinetic parameters from time-dependent formaldehyde crosslinking data, called crosslinking kinetics (CLK) analysis. Cultures of yeast cells are crosslinked with formaldehyde for various periods of time, yielding the relative ChIP signal at particular loci. We fit the data using the mass-action CLK model to extract kinetic parameters of the TF-chromatin interaction, including the on- and off-rates and crosslinking rate. From the on- and off-rate we obtain the occupancy and residence time. The following protocol is the second iteration of this method, CLKv2, updated with improved crosslinking and quenching conditions, more information about crosslinking rates, and systematic procedures for modeling the observed kinetic regimes. CLKv2 analysis has been applied to investigate the binding behavior of the TATA-binding protein (TBP), and a selected subset of other TFs. The protocol was developed using yeast cells, but may be applicable to cells from other organisms as well.
Keywords: Chromatin immunoprecipitation (ChIP) (染色质免疫沉淀(ChIP))Background
Transcription initiation is a complicated process that involves the cooperation and coordinated interaction of dozens of proteins on a chromatinized promoter (Kim et al., 2005; Encode Consortium, 2012; Rhee et al., 2012; Dowen et al., 2014). Many studies have investigated the assembly and regulation of the core transcriptional machinery in vitro (Zawel and Reinberg, 1992; Conaway and Conaway, 1993; Roeder, 1996; Hager et al., 2009; He et al., 2013; Cramer, 2014; Luse, 2014; Horn et al., 2016), but it has been more challenging to examine the stochastic nature of these processes in vivo. There are two general approaches used to measure chromatin-binding dynamics in vivo: microscopy and ChIP-based techniques (Coulon et al., 2013; Mueller et al., 2013). Microscopic techniques, such as fluorescence recovery after photobleaching (FRAP) or single molecule tracking (SMT), have high temporal resolution and have provided fundamental insight into chromatin binding dynamics, including results obtained by tracking individual molecules (Larson et al., 2009; Mueller et al., 2013; Morisaki et al., 2014). However, these approaches can be limited by photophysical effects such as photobleaching, and in addition, in the great majority of cases it is not possible to determine the identity of particular single copy loci where the measured interactions occur (Mueller et al., 2013). Alternatively, ChIP-based approaches provide precise chromatin location information. In Competition ChIP (CC), expression of a differentially tagged isoform of the TF of interest is induced and the relative levels of the constitutive and induced forms of the TF are monitored over time, yielding binding kinetic information through measurements of TF turnover at the sites of interest (van Werven et al., 2009; Lickwar et al., 2013). With advancements in modeling of CC data, residence times as short as 1.3 min have been measured (Zaidi et al., 2017). Relative dynamic measurements have also been made by conditional depletion of TFs from the nucleus using the Anchor Away technique (Haruki et al., 2008; Grimaldi et al., 2014), although specific mathematical models of the process have not yet been reported. The CLK method is complementary to these other ChIP-based approaches, exploiting the time dependence of formaldehyde crosslinking to derive binding kinetic parameters as well as fractional occupancy (Poorey et al., 2013). The first iteration of the CLK assay used ‘standard’ crosslinking and quenching conditions (1% formaldehyde and 250 mM glycine, respectively). Additional work has recently yielded experimental conditions that increase the crosslinking rate and improve quenching of the crosslinking reaction (Zaidi et al., 2017). These new conditions have resulted in a more robust method and the ability to model and analyze crosslinking kinetic data with more reliability and confidence.
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版权信息
© 2018 The Authors; exclusive licensee Bio-protocol LLC.
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Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
分类
分子生物学 > DNA > DNA-蛋白质相互作用
生物化学 > 蛋白质 > 相互作用
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