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Dynamic enhancer function in the chromatin context

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Enhancers serve as critical regulatory elements in higher eukaryotic cells. The characterization of enhancer function has evolved primarily from genome‐wide methodologies, including chromatin immunoprecipitation (ChIP‐seq), DNase‐I hypersensitivity (DNase‐seq), digital genomic footprinting (DGF), and the chromosome conformation capture techniques (3C, 4C, and Hi‐C). These population‐based assays average signals across millions of cells and lead to enhancer models characterized by static and sequential binding. More recently, fluorescent microscopy techniques, including fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, and single molecule tracking (SMT), reveal a highly dynamic binding behavior for these factors in live cells. Furthermore, a refined analysis of genomic footprinting suggests that many transcription factors leave minimal or no footprints in chromatin, even when present and active in a given cell type. In this study, we review the implications of these new approaches for an accurate understanding of enhancer function in real time. In vivo SMT, in particular, has recently evolved as a promising methodology to probe enhancer function in live cells. Integration of findings from the many approaches now employed in the study of enhancer function suggest a highly dynamic view for the action of enhancer activating factors, viewed on a time scale of milliseconds to seconds, rather than minutes to hours.

Current paradigm for enhancer function. (a) Enhancers are regulated by transcription factors that bind and create regions of modified ‘open’ chromatin at the enhancer site. (b) During this process, the enhancer is brought into proximity of a target promoter by putative bridging factors (c), thereby activating the promoter. (d) In some cases, enhancers produce transcripts from their site, termed enhancer RNAs (eRNAs). These eRNAs either act at other targets in the genome by poorly understood mechanisms, or provide some cis function directly at the site. Enhancers are organized within large domains (designated as topologically associating domains, clusters, and other terms), that are formed by boundary proteins (e). Their activity is thought to be limited within these domains, but mutations in the boundary elements (f) can break the boundary and allow penetration of other enhancers external to the domain (g).
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Tracking enhancer‐binding factors in live cells. Transcription factor (TF) action at enhancers has been studied in live cells primarily by two methodologies. (a) In fluorescence recovery after photobleaching (FRAP), GFP‐labeled factors are visualized either throughout the nucleus, or at gene arrays containing specific binding sites for a given factor. (b) Bleaching of the bound factors followed by observation during recovery provides direct information regarding the residence time of the factors. (c) In single‐molecule tracking (SMT), movements of individual molecules are observed within a thin slice of the nucleus. In this example, the zone of observation is provided by highly inclined laminated optical sheet microscopy. (d) Single molecules are visualized as bright diffraction‐limited spots, and their movement is tracked in real time. (e) Representation of SMT data. Collected tracks (black) showing the single‐molecule residence times fitted to a single‐ (blue) or double‐exponential (red) decay model. Expanded view represents the same data and fits with y‐axis plotted as a log 10. (f) Results from SMT from several laboratories suggest that factors search the genome via many very short binding events, but eventually find authentic response elements, where they reside for longer binding times on the order of 5–15 seconds.
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Genomic footprinting. (a) The genome‐wide accessibility of transcription factors (TFs) to their DNA motif sequences is measured via sequencing DNA liberated from the chromatin fiber by cleaving enzymes. In the resulting enhancer landscape map, regions bound by TFs can be locally protected and are thus less frequently cleaved. A motif‐centered aggregate plot of cleavage events across the genome can present this reduced cleavage rate as a footprint (pink). However, some TFs do not leave a footprint although they measurably bind to DNA (grey). The zigzag pattern at the motif sequence (‘signature’) occurs regardless of TF binding and originates from enzyme cleavage bias. (b) Several scenarios arising by combining chromatin immunoprecipitation (ChIP‐seq) and footprinting data. (1) The appearance of both a ChIP‐seq peak as well as a footprint at the motif is the canonical case. (2) A lack of a footprint in bound sites is possible in highly dynamic TFs or in the case of a DBD structure that more readily allows DNase access. (3) A footprint at unbound sites can originate from another factor recognizing the same motif. (4) Peaks bound with no detectable motif (and therefore no footprint) can suggest indirect binding. (5) When the TF is inactive under the examined conditions, no footprint would be found.
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In the Spotlight

Jens Nielsen

Jens Nielsen
is a Professor in the Department of Biology and Biological Engineering at Chalmers University of Technology in Göteborg, Sweden. His research focus is on systems biology of metabolism. The yeast Saccharomyces cerevisiae is the lab’s key organism for experimental research, but they also work with Aspergilli oryzae.

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