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Determining the structure of a biomolecule is a key prerequisite for understanding its function. Two well-established methods for structure determination are cryo-electron microscopy and X-ray crystallography1,2. Today, both methods provide high-resolution structural information with a resolution down to the angstrom level. These two methods have been used extensively to elucidate the structure of large biomolecules such as protein complexes. Though the existing methods have constantly been improved throughout the last decades, the complexity of biological structures still poses a major challenge to structural biology, in particular when large, dynamic and transient complexes are investigated3.
In order to study the dynamics of macromolecular complexes and the structure-function relationship in particular, single-molecule methodologies have provided useful information4. Several new strategies were developed providing an orthogonal approach on acquiring structural and dynamic information. Examples are high speed AFM5, mechanical manipulation6, fluorescence localization microscopy7, as well as single-molecule Förster Resonance Energy Transfer (smFRET)8,9. Since quite early on FRET has been termed a molecular ruler, due to the distance dependence on the length scale of biomacromolecules10.
One particularly interesting application of smFRET is to use the distance information obtained from smFRET measurements to infer structural information11,12,13,14,15,16,17,18,19,20,21,22,23. Due to the high time resolution of smFRET, the position of mobile parts of a protein structure can be localized. However, in order to extract quantitative information from smFRET data important correction parameters about the dye molecules need to be determined during the measurement24. With these correction factors, the FRET efficiency EFRET can be calculated using the formula
,
where IA and ID are the fluorescence intensities of the donor and the acceptor molecule, respectively (see Figure 2). The β-factor accounts for cross-talk, the leakage of donor emission into the acceptor channel and is calculated by

where I'A and I'D are the fluorescence intensities of the donor and the acceptor molecule after photo bleaching of the acceptor molecule.
The γ-factor corrects the difference in the relative detection efficiencies in the two channels as well as the differences in the fluorescence quantum yield of the donor and the acceptor dye. It is calculated from every individual time trace by

Note, that this description neglects direct excitation of the acceptor molecule, which sometimes becomes important and would need to be corrected for as well. For determining these correction factors it is useful to excite both the donor as well as the acceptor in an alternating scheme25 in order to differentiate between photo-physical changes and structural dynamics.
In order to not only obtain quantitative smFRET efficiencies but also quantitative structural information, the Nano-Positioning System (NPS) was introduced in 200826. The name was chosen based on its similarities to the satellite-based Global Positioning System (GPS). The NPS is a hybrid technique combining smFRET and X-ray crystallography data for the localization of unknown dye positions in biomacromolecular complexes. The crystal structure serves as a reference frame and the smFRET results are used to obtain distance information between an unknown fluorophore position (antenna) and a position known from the crystal structure (satellite). In consecutive experiments the distances between the antenna and several satellites are measured and the position of the antenna is determined by means of a statistically rigorous analysis scheme based on Bayesian parameter estimation. As a result, not only the likeliest position of the antenna is computed, but its complete 3D uncertainty distribution, the so-called posterior, visualized by credible volumes. Moreover, NPS was expanded to allow for the analysis of complete smFRET networks27.
The NPS has been used to solve a number of important questions in eukaryotic transcription, namely the course of the upstream DNA, the non-template DNA and the nascent mRNA within the RNA Polymerase II elongation complex12,28, also demonstrating the effect of transcription initiation factors26 and the dynamic architecture of an open-promotor complex29. Moreover, the NPS was used to elucidate the structure of the archaeal RNA Polymerase open complex30 and in particular the position of transcription initiation factor TFE, which binds competitively to the same site as transcription elongation factor Spt4/531.
Since then, a number of smFRET based structural approaches have been published15,18,21,23. When comparing different smFRET based structural methods, it becomes clear that the apparent precision of the method is highly dependent on the particular choice of dye models. One should note that dye molecules may exhibit different spatial and orientational behavior depending on their local environment.
To this end, Fast-NPS was introduced32. Fast-NPS uses an advanced sampling algorithm reducing the calculation times drastically. Furthermore, Fast-NPS allows one to perform a structural analysis and for each dye molecule the user can choose from a set of five different dye models which will be described next. The most conservative model, called classic, assumes that the dye occupies only one, but unknown, position. At this position, the fluorophore can rotate freely within a cone, whose size is determined from its respective (time-dependent) fluorescence anisotropy. The orientation of the cone is not known, which leads to large uncertainties when converting measured smFRET efficiencies into distances. In this respect, the model is conservative, since it will lead to the smallest precision compared to the other dye models. Only for very short distances should the assumptions made by the classic model lead to a noticeably incorrect position determination. For typical smFRET values, the correct position is always enclosed in the comparatively large credible volume.
However, since a higher precision is desirable, it is important to develop and test alternative dye models, which could help to improve the precision. If the dye rotates much faster than its inherent fluorescence lifetime, the so-called iso model can be applied. Here, the orientation factor κ2 (needed for calculating the characteristic isotropic Förster radius
) is set to 2/3. As a result, the computed credible volumes are almost two orders of magnitude smaller as compared to those in the classic model32. In the case that the fluorophore is found in an environment that enables not only fast reorientation, but additionally fast motion all over its accessible volume, the meanpos-iso model should be used. In this model, the dye effectively occupies only one mean position, where the spatial averaging is accounted for by a polynomial distance conversion15. This model applies if for example the (commonly hydrophobic) dye is attached to a hydrophilic region, e.g., the DNA. Application of the meanpos-iso model leads to a further reduction in the size of the credible volumes by a factor of approximately two. However, a dye linked to a protein might bind reversibly to several hydrophobic patches in its sterically accessible volume (AV). A fluorophore that instantaneously switches between these regions, but within one region undergoes free rotation and fast localized motion is best described by the var-meanpos-iso model. For a similar situation in which the dye is not free to rotate the var-meanpos model applies. More details about these models can be found in our recent publication32.
These models provide an extensive repertoire to specifically account for the various environments a dye might encounter and applying them wisely optimizes its localization precision. In Fast-NPS every dye molecule attached to a specific position can be assigned to an individual model, such that FRET-partners are allowed to have different models. This enables limitless and close-to-nature modelling. However, it is important that one performs rigorous statistical tests to ensure that the result obtained by the final model combination is still in agreement with the experimental data. These tests are included in the Fast-NPS software.
In order to apply Fast-NPS to experimental data the measurement of (only) three input parameters is required. First, the dye-pair specific isotropic Förster radii (
) have to be determined. Therefore, the quantum yield (QY) of the donor dye, the donor fluorescence emission spectra and the acceptor absorption spectra need to be measured. These measurements can be carried out in bulk, using a standard spectrometer and a standard fluorescence spectrometer. For each pair, the R0 is then calculated using the freeware PhotochemCAD and can be used in the NPS analysis. Moreover, the (time-resolved) fluorescence anisotropies of the dye molecules need to be obtained using a polarization (and time) sensitive fluorescence spectrometer. However, the most important input parameters for Fast-NPS are the smFRET efficiencies measured on a single-molecule fluorescence microscopy setup, such as a total internal reflection fluorescence microscope (TIRFM).
Here, we present a step-by-step protocol for obtaining smFRET data and applying Fast-NPS (Figure 1).