Here, we present the protocol to study the local flexibility and dynamics of biomolecules using time-resolved fluorescence anisotropy at the single-molecule level in confocal microscopy mode.
We describe a protocol for conducting time-resolved fluorescence anisotropy at the single-molecule level using confocal microscopy to investigate the local flexibility and dynamics of the deoxyribonucleic acid (DNA)-binding forkhead (FKH) domain of the FoxP1 transcription factor. FoxP1 dimerizes through a three-dimensional domain-swapping (3D-DS) mechanism, forming a disordered intermediate with or without DNA. Since 3D-DS involves an intrinsically disordered region, understanding its behavior is crucial for elucidating the structural and functional properties of FoxP1. Using a single-cysteine-labeled FoxP1, we conducted single-molecule fluorescence anisotropy (smFA) experiments, applying dynamic anisotropy Photon Distribution Analysis (daPDA) and time-resolved anisotropy Burst Variance Analysis (traBVA) approaches to probe local flexibility and dynamics. This protocol provides a detailed, step-by-step guide for smFA measurements, emphasizing time-resolved analyses, variance, and probability distribution techniques to capture structural dynamics across different timescales. This approach enabled us to relate dynamics and heterogeneity to FoxP1 dimerization and DNA binding, highlighting the complex action mechanism that characterizes this transcription factor.
The functional activity of biomolecules depends on their molecular flexibility and structural dynamics1,2,3. Naturally, biomolecules experience constant thermal fluctuations, ranging from rapid movements to long-term conformational changes influencing their function (Figure 1)4. In biomolecules, local backbone motions contribute to larger-scale global movements, including hinge bending in enzymes and significant conformational changes in motor proteins. Structure determination methods such as nuclear magnetic resonance (NMR)5, X-ray crystallography6, and cryogenic electron microscopy (cryo-EM)7 have revealed multiple conformations in various biomolecules. Nevertheless, connecting the local fluctuations to large conformational dynamics of biomolecules and their role in function are mostly unexplored. Relating dynamics and structure can be challenging, especially for intrinsically disordered proteins (IDPs)8,9,10. Unlike structured proteins, IDPs do not maintain a stable tertiary structure. Instead, they undergo extensive conformational changes with similar free energy levels, enabling a wide range of biological activities11,12.
Several experimental approaches have been employed to investigate the conformational dynamics of proteins by probing their molecular flexibility1,13,14,15,16. Among these, NMR stands out for its ability to provide atomic-level resolution across various timescales, from tens of picoseconds to several hours12. However, determining macromolecular flexibility remains challenging due to the high degrees of freedom and for large-size proteins; thus, NMR is often limited to studying biomolecules of around 100 kDa17.
Given the structural complexity of highly dynamic proteins like IDPs, additional methodological advancements have been developed to explore local and long-range conformational space to understand their function11. Single-molecule multiparameter Fluorescence Spectroscopy (smMFS)18,19,20,21,22 offers extensive information on biomolecules, providing crucial insights into their function, conformational dynamics, binding states, and stoichiometry. However, interpreting the vast amount of structural data obtained from biomolecules is challenging, and factors such as molecular dynamics, fluorophore behavior, and the complex behavior of molecules can further complicate data analysis23,24,25,26,27,28.
We employ single-molecule fluorescence anisotropy (smFA) as a robust method for assessing local and global dynamics along the backbone of biomolecules (Figure 1A). Fluorescence anisotropy, first described by Perrin29 and introduced by Weber30,31 as a bioanalytical tool32, was later adapted for single-molecule studies with the advent of time-resolved fluorescence techniques and the increment of detectors' sensitivity33,34,35,36,37. smFA spans a broad range of timescales -- from picoseconds to several hours -- and complements the data obtained from single-molecule Förster Resonance Energy Transfer (smFRET) experiments38.
smFA can be visualized in various formats to extract critical information about biomolecular dynamics (Figure 1B). Time-resolved fluorescence anisotropy decays are one-dimensional histograms that capture dynamics on the picosecond to nanosecond timescale39,40. Two-dimensional single-molecule histograms, which correlate fluorescence lifetime with anisotropy for individual molecules, can reveal anisotropy state heterogeneity and provide visual insights into potential dynamics within the observation time in confocal experiments (~ms)41,42. For studying sub-millisecond dynamics, dynamic anisotropy photon distribution analysis (daPDA) can be used, while time-resolved anisotropy Burst Variance Analysis (traBVA) offers a robust method for confirming specific dynamics around milliseconds43 (Figure 1B).
These methods complement more traditional tools, such as polarization-resolved fluorescence correlation spectroscopy (pFCS), which has a broader spectrum44,45,46,47. Overall, multiple data analysis tools for smFA facilitate identifying local and global conformational changes, provided proper calibration is considered.
Here, we apply smFA to study the DNA binding of the human FoxP1 transcription factor48,49,50,51. This protein adopts domain-swapped dimer due to the intrinsically disordered nature of its polypeptide chain, which is notably affected depending on the quaternary state of the protein and the presence of DNA. We generated different single-cysteine mutants to label with BODIPY-FL, performed smFA experiments, and employed daPDA and trBVAa. This approach allowed us to relate dynamics and heterogeneity to FoxP1 dimerization and the DNA binding, highlighting the complex mechanism of action that characterizes this transcription factor.
NOTE: Selecting the proper fluorophore is essential for smFA experiments. Biomolecules can be labeled at site-specific positions either by modifying amino acids in proteins or nucleotide bases in nucleic acids with fluorescent markers, depending on the available reactive groups. Among organic dyes52, the Alexa Fluor, Cy, BODIPY, and Janelia Farms families are the most popular choices for smFA, thanks to their long fluorescence lifetimes, photostability, and high quantum yields. BODIPY-FL is often favored for its extended fluorescence lifetime, superior quantum yield, and short connecting linker. Additionally, alternative fluorophores are commonly used in drug screening where bulk techniques are preferred53. Chimeric fluorescent proteins can also be used for live-cell anisotropy experiments and imaging, although there is a limitation of a lower dynamic range.
1. Buffer preparation
NOTE: Wear gloves, eye protection goggles, and a laboratory coat while doing laboratory experiments.
2. Fluorescent probes
3. Calibration measurements
4. Calibration and data analysis
5. FoxP1 protein preparation
6. Microscope sample chamber preparation
7. Single-molecule fluorescence anisotropy experiment
Fluorescence anisotropy arises from the relative orientation of the fluorophore's absorption and the emission dipole moments. When fluorophores are exposed to polarized light, fluorophores with absorption transition moments aligned with the electric field vector of the incident light are preferentially excited (photoselection). Consequently, the excited-state population becomes partially oriented, with a significant fraction of the excited molecules having their transition moments aligned with the electric field vector of the polarized exciting light61. Fluorophores rotate due to their Brownian motion. Thus, the emission transition moment also rotates, resulting in time dependency on fluorescence anisotropy. This effect can be used to measure the rotational motions of fluorescent molecules, detect binding events, characterize the fluorophore's environment, and capture molecular dynamics.
Single-molecule experiments are uniquely poised to determine the sample's heterogeneity. Taking advantage of single molecule sensitivity and fluorescence anisotropy adds another dimensionality to multiparameter fluorescence spectroscopy. In a typical single-molecule confocal microscope (Figure 2)20,21, fluorescence anisotropy can be determined via intensity-based or time-resolved when pulsed lasers are used.
To consider the depolarizing effects of the high numerical aperture objective in a confocal microscope62, the proper form of the time-resolved anisotropy35,63 is given by
(1)
where and
are the time-resolved fluorescence intensity in the y-th detection channel after excitation at the wavelength x, for the parallel and perpendicular polarization l1 and l2 and are factors that describe the mixing between the parallel and perpendicular signals due to the high numerical aperture (NA) objective used in these measurements35,62,64. Differences in detection efficiencies of the parallel,
, and perpendicular detection channel,
, for the dye are corrected with the ratio of the detection efficiencies,
. The GUV is also referred to as the G-factor.
The time-resolved fluorescence anisotropy can be modeled using a multiexponential decay to account for the fluorophore being attached to a larger biomolecule as
, (2)
where r0 is fluorophore dependent fundamental anisotropy (typically r0 = 0.38), r∞ is the residual anisotropy, and ρ1 and ρ2 are fast (local motions of the fluorophore) and slow (global motion of the macromolecule) rotational correlation times, respectively.
In single-molecule anisotropy measurements (Figure 2), photon arrival times are recorded to identify individual emitters using burst-integrated fluorescence lifetime (BIFL) analysis33,35. The inter-photon arrival times (Δt) are smoothed using a running average and then plotted to aid visualization. The histogram of these times is fitted with a half Gaussian to determine the mean and standard deviation of photons originating from the background. An arbitrary threshold, set at multiples of the standard deviation, is used to filter out individual events while identifying the first and last photons in each burst. Photons within each burst are then integrated for further analysis, which includes calculating time-resolved and intensity-based steady-state fluorescence anisotropy using equations 1 and 2 or via a maximum likelihood estimator35. Due to the limited number of photons in single-molecule events, the maximum likelihood estimator considers only a single exponential component and will not be further discussed.
In a two-dimensional histogram of single molecule events, the mean fluorescence lifetime (τ) and anisotropy (rxy) can be related by Perrin's equation29,61 for obtaining (ρ) as an average rotational time.
(3)
Specific ρ values can be obtained with higher certainty by "sub-ensemble" (se) analysis where the photons of different bursts are integrated into a combined time-resolved fluorescence anisotropy decay that can be analyzed by optimizing parameters of equation 2 to the experimental decay (seTRFA). Time-resolved anisotropy can resolve heterogeneity and dynamics associated with rotational motions (local and global) of the biomolecules within the emission of fluorescence that occurs within the ns timeframe.
To detect dynamics within single molecule events (on the submillisecond scale), we introduced time-resolved anisotropy Burst Variance Analysis (traBVA)57. In traBVA, for a photon burst containing Mi consecutive photon segments, the excess anisotropy variance (s2) for bursts is
. (4)
For a single anisotropic state, the variance σ2 arises solely from shot noise65 (sn: √N, where N is the number of photons)
(5)
where m is the number of photons in a burst. Hence, to identify additional variance in the anisotropy, we can define the excess anisotropy variance (S2) due to conformational heterogeneity as the difference between equations 4 and 5.
(6)
To capture dynamics that occur within the observation of individual molecules and consider the variance approximation, dynamic anisotropy Photon Distribution Analysis (daPDA)55,56 can be used. In daPDA, the fluorescence intensity is modeled by following a conditional probability () expressed as a binomial distribution.
(7)
Together, with an estimate of the background count rate that follows a Poisson distribution
(8)
where is the average number of background photons per set time window. The parallel and perpendicular background counts,
and
, can be measured using buffer samples as a reference. The experimentally determined fluorescence anisotropy is optimized by minimizing a figure of merit χ2 with a fluorescence intensity distribution per polarization channel that can include kinetic changes.
The analysis routines and data representations provided offer a comprehensive approach to interpreting the collected data. Although this protocol primarily focuses on confocal measurements, which are limited in capturing anisotropy changes from nanoseconds to milliseconds, it is possible to adopt a Total Internal Reflection microscope to monitor fluorescence anisotropy over longer timescales, enabling time series analysis66. For single-molecule confocal measurements, we highlight the use of multidimensional histograms that create a unique fingerprint of the observed ensemble. Time-resolved fluorescence decays, reconstructed from selected populations, can track the evolution of fluorescence anisotropy at the nanosecond scale (Figure 3). Photon distribution analysis55,56 and burst variance analysis (BVA)57,58 can also capture dynamics at intermediate timescales between time-resolved decays and multidimensional histograms. While this protocol does not cover the use of polarization fluorescence correlation spectroscopy (FCS), with or without pulsed excitation67,68, which can bridge the nanosecond to millisecond timescales, the same data can be used to compute FCS69, though this falls outside the scope of the presented protocol. If such experiments are undertaken, longer sample measurement time is recommended.
This approach has been applied to a complex system like the human FoxP proteins, providing valuable insights into the motions involved in their mechanism of action. FoxP proteins are transcription factors involved in several physiological aspects such as brain and lung development; importantly, different mutations have been recognized as impairing the function of these proteins70,71. Using the DNA-binding domain of FoxP1 as a model, we generated different single-cysteine mutants to introduce a BODIPY-FL dye as a tracker for motions (Figure 4A). In fact, we evaluated the effect of dimerization and the DNA binding as major structural regulators of this protein. Using the smFA approach, we generated 2D-smFA plots and made traBVA and daPDA for each mutant in monomeric and dimeric conditions. We show an example of one of the single mutants studied (Figure 4). The anisotropy behavior is similar in all mutants in terms of determining high and low rotational correlation times and, therefore, presumable, disordered, and folded ensembles. Still, it is also highly heterogeneous in all mutants in terms of the fraction and kinetics of each ensemble, evidencing different order-to-disorder transition changes influenced by the dimerization and the DNA-binding, and shows the description at high resolution of the structural dynamics along the chain (Figure 5).
Figure 1: Dynamic range of biomolecules and fluorescence anisotropy methods. (A) The anisotropy of small fluorophores tethered to various positions along the backbone of the biomolecule of interest informs local structural dynamics. (B) Timescales probed by fluorescence intensity decays (time-resolved fluorescence anisotropy, FA) and single-molecule histograms of confocal single-molecule microscope data. Please click here to view a larger version of this figure.
Figure 2: Single-molecule fluorescence anisotropy data registration and processing. (A) Freely diffusing molecules are analyzed using a confocal single-molecule microscope equipped with a single linearly polarized excitation laser (blue in our case). Fluorescence emission (green in our case) is detected by two detectors after a beam polarizer splits the signal into two polarizations (parallel, , and perpendicular,
, to the excitation source). (B) Each detected photon is characterized by three parameters: micro time, macro time, and channel type. The data is stored in a Time-Tagged Time-Resolved (TTTR) format72. (C) Bursts of individual molecules are selected and processed to extract fluorescence parameters, including fluorescence anisotropy for each observed molecule. (D) Data is represented in multiple ways, including two-dimensional plots of fluorescence anisotropy versus fluorescence lifetime and time-resolved anisotropy decays. These representations allow for both visual and quantitative determination of fluorescence lifetimes, rotational correlation times, and system heterogeneity. Please click here to view a larger version of this figure.
Figure 3: Representative data for FoxP1 domain-swapped dimer. (A) Correlation of the fluorescence anisotropy (rscatter) against the mean fluorescence lifetime per molecule as a contour plot. Overlay of a single Perrin equation for two rotational components as a representative of the ensemble average of the molecule, considering ρ1 and ρ2 of 0.2 ns and 8.5 ns, respectively. (B) Sub-ensemble time-resolved fluorescence decays are used to compute the time-resolved fluorescence anisotropy of the sample. Fit with equation 2 resolved the local and global components of fluorescence anisotropy. Please click here to view a larger version of this figure.
Figure 4: Sub-millisecond FoxP1 dynamics monitored using single-molecule fluorescence anisotropy (smFA). (A) A cartoon representation of the monomeric FoxP1 structure. (B) A two-dimensional histogram illustrates dynamic heterogeneity, revealing two distinct rotational correlation times identified through time-resolved fluorescence anisotropy. Time-resolved anisotropy Burst Variance Analysis (traBVA) uncovers a small subset of events with excess variance (Eq. 6) that exhibit large anisotropy. Quantitative dynamic anisotropy analysis using Photon Distribution Analysis (PDA) further extracts the exchange rates for this process. Please click here to view a larger version of this figure.
Figure 5: Screening the local and global motions of FoxP1 during dimerization. (A) A cartoon representation compares the monomeric FoxP1 with its dimeric form. (B) Mean excess variance per location under monomeric and dimeric conditions is shown, with larger excess variance indicating more significant changes in anisotropy. (C) Dynamic anisotropy analysis using Photon Distribution Analysis (PDA) helps determine population fractions (high anisotropy in dark colors and low anisotropy in light color) in the absence (green) and presence (yellow) of DNA. In this approach, rates (not shown) were estimated for transitions between local and global behaviors, revealing that FoxP1 undergoes partial unfolding. Please click here to view a larger version of this figure.
For single-molecule fluorescence anisotropy experiments, it is crucial to consider the chosen fluorophore's photophysical properties carefully. These properties include the emission wavelength, which must align with the detection system, and the excitation wavelength, which should be compatible with the available pulsed lasers. To optimize the dynamic range, the fluorophore should have a long fluorescence lifetime relative to the molecule's rotational diffusion time. This is critical for tracking rotational dynamics and the linkage/orientation of the fluorophore's dipole relative to the biomolecule of interest. Additionally, brightness, photostability, and quantum yield are essential for producing strong signals with a stable signal-to-noise ratio. For these reasons, BODIPY-FL has been chosen as the fluorophore in several studies39,40,42.
Screening the backbone dynamics of biomolecules often requires protein labeling, typically achieved through site-specific labeling. This is usually done by introducing a residue for targeted chemical modification. The most common approach is introducing cysteines at positions of interest, where their thiol side chains can be selectively modified with reagents such as maleimides or iodoacetamides. Less commonly, benzylic halides and bromomethyl ketones are used to form thioether bonds. Other amino acid side chains can also be targeted, but their abundance in proteins is less commonly used. However, alternative approaches, like unnatural amino acids, can also be used73. Proper site selection for labeling is crucial to minimize interference with the biomolecule under study, and appropriate controls must be in place. For example, if the labeled molecule is used in binding assays, complementary label-free methods should verify that the fluorophores do not impact binding affinity.
After identifying the appropriate sample and implementing the optimal labeling strategy, the next step is to ensure the confocal microscope is properly aligned and calibrated for single-molecule experiments. The protocol describes how to determine the required factor for further analysis. Once the instrument is calibrated, the next step is to measure the sample and process the data to extract as much information as possible from the detected photons. The key parameters, such as micro-time, macro-time, and channel type, as shown in Figure 2, can be used for further analysis and visualization using typical TCSPC electronics.
Recent advances in single-molecule fluorescence spectroscopy can be extensively used to study structural information from the heterogeneous ensembles of biomolecules. However, relatively few studies leverage the insights provided by fluorescence anisotropy, and a complete protein model is required to derive the structural dynamics of biomolecules. Therefore, unraveling the dynamics of interdomain and protein-protein interactions of several transcription factors is challenging.
In conclusion, single-molecule fluorescence anisotropy experiments offer complementary information about the local and global motions of the biomolecular backbone, which are critical for understanding its function.
All the authors declare that they have no competing financial interests with the contents of this article.
This work was supported by FONDECYT grants 11200729 and FONDEQUIP EQM200202 to E.M., NIH R15CA280699 R01GM151334, and NSF CAREER MCB 1749778 awards to HS. NK acknowledged support from the Clemson University Postdoctoral fellowship program.
Name | Company | Catalog Number | Comments |
Alexa Fluor 488 | ThermoFisher Scienctific | A20100 | https://www.thermofisher.com/order/catalog/product/A20100?SID=srch-srp-A20100 |
Amicon Ultra Centrifugal Filter, 10 kDa MWCO | Millipore Sigma | UFC901008 | https://www.sigmaaldrich.com/US/en/product/mm/ufc9010 |
Ampicillin sodium salt | Millipore Sigma | A0166-5G | https://www.sigmaaldrich.com/US/en/product/sigma/a0166 |
BODIP FL Maleimide (BODIPY FL N-(2-Aminoethyl))Maleimide) | ThermoFisher Scienctific | B10250 | https://www.thermofisher.com/order/catalog/product/B10250?SID=srch-srp-B10250 |
Disposable PD 10 Desalting Columns | Millipore Sigma | GE17-0851-01 | https://www.sigmaaldrich.com/US/en/product/sigma/ge17085101 |
Dithiothreitol | Millipore Sigma | 10197777001 | https://www.sigmaaldrich.com/US/en/product/roche/dttro |
DMSO, Anhydrous | ThermoFisher Scienctific | D12345 | https://www.thermofisher.com/order/catalog/product/D12345?SID=srch-srp-D12345 |
DNAse | Millipore Sigma | 10104159001 | https://www.sigmaaldrich.com/US/en/product/roche/10104159001 |
E. coli C41 bacterial cells | Invitrogen | ||
Foresigh Nuvi Ni-Charged IMAC, 5 mL column | Bio-Rad | 12004037 | https://www.bio-rad.com/en-us/sku/12004037-foresight-nuvia-ni-charged-imac-5-ml-column?ID=12004037 |
HEPES | Millipore Sigma | 7365-45-9 | https://www.sigmaaldrich.com/US/en/product/sigma/h3375 |
Imidazole | Millipore Sigma | 288-32-4 | https://www.sigmaaldrich.com/US/en/product/sigma/i5513 |
IPTG | Millipore Sigma | I6758-1G | https://www.sigmaaldrich.com/US/en/product/sial/i6758 |
MCE Membrane Filter, 0.22 μm Pore Size | Millipore Sigma | GSWP02500 | https://www.sigmaaldrich.com/US/en/product/mm/gswp02500 |
NaCl | Millipore Sigma | 7647-14-5 | https://www.sigmaaldrich.com/US/en/product/sigma/s3014 |
Nunc Lab-Tek II Chamber Slide System | ThermoFisher Scienctific | 154534 | https://www.thermofisher.com/order/catalog/product/154534 |
OverExpress C41(DE3) Chemically Competent Cells | Millipore Sigma | CMC0017-20X40UL | https://www.sigmaaldrich.com/US/en/product/sigma/cmc0017 |
PMSF | Millipore Sigma | 329-98-6 | https://www.sigmaaldrich.com/US/en/product/sigma/78830 |
Rhodamine 110 | ThermoFisher Scienctific | 419075000 | https://www.thermofisher.com/order/catalog/product/419075000?SID=srch-hj-419075000 |
Sodium phosphate dibasic | Millipore Sigma | 7558-79-4 | https://www.sigmaaldrich.com/US/en/product/sigma/s3264 |
Sodium phosphate monobasic dihydrate | Millipore Sigma | 13472-35-0 | https://www.sigmaaldrich.com/US/en/product/sigma/71505 |
TCEP, Hydrochloride, Reagent Grade | Millipore Sigma | 580567-5GM | https://www.sigmaaldrich.com/US/en/product/mm/580567 |
Tween 20 | Millipore Sigma | 11332465001 | https://www.sigmaaldrich.com/US/en/product/roche/11332465001 |
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