Recent applications of fluorescence correlation spectroscopy in live systems

Macháň, Radek; Wohland, Thorsten

doi:10.1016/j.febslet.2014.03.056

Cited by 118 publications

(67 citation statements)

References 166 publications

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“…diffusion) of multiple components of a dynamic factor need to be characterized. Fluorescence correlation spectroscopy (FCS) is a fluorescence microscopy technique based on the detection and quantification of fluctuations of fluorescence intensity of molecules diffusing through a well‐defined (subfemtoliter) observation volume (Machan & Wohland, 2014). FCS is particularly useful for the analysis of diffusion properties of very mobile factors and can be used to gain more detailed information than those obtained by photobleaching approaches.…”

Section: Introductionmentioning

confidence: 99%

Coactivators and general transcription factors have two distinct dynamic populations dependent on transcription

et al. 2017

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SAGA and ATAC are two distinct chromatin modifying co‐activator complexes with distinct enzymatic activities involved in RNA polymerase II (Pol II) transcription regulation. To investigate the mobility of co‐activator complexes and general transcription factors in live‐cell nuclei, we performed imaging experiments based on photobleaching. SAGA and ATAC, but also two general transcription factors (TFIID and TFIIB), were highly dynamic, exhibiting mainly transient associations with chromatin, contrary to Pol II, which formed more stable chromatin interactions. Fluorescence correlation spectroscopy analyses revealed that the mobile pool of the two co‐activators, as well as that of TFIID and TFIIB, can be subdivided into “fast” (free) and “slow” (chromatin‐interacting) populations. Inhibiting transcription elongation decreased H3K4 trimethylation and reduced the “slow” population of SAGA, ATAC, TFIIB and TFIID. In addition, inhibiting histone H3K4 trimethylation also reduced the “slow” populations of SAGA and ATAC. Thus, our results demonstrate that in the nuclei of live cells the equilibrium between fast and slow population of SAGA or ATAC complexes is regulated by active transcription via changes in the abundance of H3K4me3 on chromatin.

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Section: Introductionmentioning

confidence: 99%

Coactivators and general transcription factors have two distinct dynamic populations dependent on transcription

et al. 2017

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“…In addition, spectromicroscopy techniques ) such as fluorescence cross-correlation spectroscopy (Macháň and Wohland, 2014) represent technological improvements that greatly improve the detection of the spatiotemporal resolution of interactions, particularly in (but not limited to) membrane environments. While these novel techniques allow dynamic PPI studies to be performed in an in vivo environment, the greatest limitation to their application at present remains the expensive equipment needed for their execution.…”

Section: Discussionmentioning

confidence: 99%

Techniques for the analysis of protein-protein interactions in vivo

et al. 2016

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ORCID ID: 0000-0002-5820-4466 (C.G.).Identifying key players and their interactions is fundamental for understanding biochemical mechanisms at the molecular level. The ever-increasing number of alternative ways to detect protein-protein interactions (PPIs) speaks volumes about the creativity of scientists in hunting for the optimal technique. PPIs derived from single experiments or high-throughput screens enable the decoding of binary interactions, the building of large-scale interaction maps of single organisms, and the establishment of crossspecies networks. This review provides a historical view of the development of PPI technology over the past three decades, particularly focusing on in vivo PPI techniques that are inexpensive to perform and/or easy to implement in a state-of-the-art molecular biology laboratory. Special emphasis is given to their feasibility and application for plant biology as well as recent improvements or additions to these established techniques. The biology behind each method and its advantages and disadvantages are discussed in detail, as are the design, execution, and evaluation of PPI analysis. We also aim to raise awareness about the technological considerations and the inherent flaws of these methods, which may have an impact on the biological interpretation of PPIs. Ultimately, we hope this review serves as a useful reference when choosing the most suitable PPI technique.

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“…The temporal window of the fluctuations depends on the photophysics of the fluorescent molecules as well as their mobility, and can thus span timescales from microseconds to seconds. As such, FCS is capable of probing a wide range of dynamic processes in living systems, including diffusion, transport, and binding interactions [28, 29], and the analysis can be complemented with Monte Carlo simulations to uncover the dynamics of even more complex processes [30, 31]. FCS can be combined with photoactivation (paFCS) to fine-tune the number of fluorescent molecules detected by selectively activating only a desired fraction of the molecules [32], thereby enhancing the signal-to-noise ratio and making it suitable for systems with high fluorescence background.…”

Section: The “Space-time” Of the Cell Nucleus And Techniques For Its mentioning

confidence: 99%

Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos

et al. 2016

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Probing dynamic processes occurring within the cell nucleus at the quantitative level has long been a challenge in mammalian biology. Advances in bio-imaging techniques over the past decade have enabled us to directly visualize nuclear processes in situ with unprecedented spatial and temporal resolution and single-molecule sensitivity. Here, using transcription as our primary focus, we survey recent imaging studies that specifically emphasize the quantitative understanding of nuclear dynamics in both time and space. These analyses not only inform on previously hidden physical parameters and mechanistic details, but also reveal a hierarchical organizational landscape for coordinating a wide range of transcriptional processes shared by mammalian systems of varying complexity, from single cells to whole embryos.

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Recent applications of fluorescence correlation spectroscopy in live systems

Cited by 118 publications

References 166 publications

Coactivators and general transcription factors have two distinct dynamic populations dependent on transcription

Coactivators and general transcription factors have two distinct dynamic populations dependent on transcription

Techniques for the analysis of protein-protein interactions in vivo

Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos

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