Quantifying transcription factor binding dynamics at the single-molecule level in live cells
•Single-molecule tracking acquires binding properties of transcription factors.•A detailed set-up to perform single molecule tracking is presented.•Challenges of the methodology are discussed. Progressive, technological achievements in the quantitative fluorescence microscopy field are allowing rese...
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Published in | Methods (San Diego, Calif.) Vol. 123; pp. 76 - 88 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.07.2017
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Subjects | |
Online Access | Get full text |
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Summary: | •Single-molecule tracking acquires binding properties of transcription factors.•A detailed set-up to perform single molecule tracking is presented.•Challenges of the methodology are discussed.
Progressive, technological achievements in the quantitative fluorescence microscopy field are allowing researches from many different areas to start unraveling the dynamic intricacies of biological processes inside living cells. From super-resolution microscopy techniques to tracking of individual proteins, fluorescence microscopy is changing our perspective on how the cell works. Fortunately, a growing number of research groups are exploring single-molecule studies in living cells. However, no clear consensus exists on several key aspects of the technique such as image acquisition conditions, or analysis of the obtained data. Here, we describe a detailed approach to perform single-molecule tracking (SMT) of transcription factors in living cells to obtain key binding characteristics, namely their residence time and bound fractions. We discuss different types of fluorophores, labeling density, microscope, cameras, data acquisition, and data analysis. Using the glucocorticoid receptor as a model transcription factor, we compared alternate tags (GFP, mEOS, HaloTag, SNAP-tag, CLIP-tag) for potential multicolor applications. We also examine different methods to extract the dissociation rates and compare them with simulated data. Finally, we discuss several challenges that this exciting technique still faces. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors contributed equally to this work |
ISSN: | 1046-2023 1095-9130 |
DOI: | 10.1016/j.ymeth.2017.03.014 |