A benchmark for chromatin binding measurements in live cells

Abstract

Live-cell measurement of protein binding to chromatin allows probing cellular biochemistry in physiological conditions, which are difficult to mimic in vitro. However, different studies have yielded widely discrepant predictions, and so it remains uncertain how to make the measurements accurately. To establish a benchmark we measured binding of the transcription factor p53 to chromatin by three approaches: fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS) and single-molecule tracking (SMT). Using new procedures to analyze the SMT data and to guide the FRAP and FCS analysis, we show how all three approaches yield similar estimates for both the fraction of p53 molecules bound to chromatin (only about 20%) and the residence time of these bound molecules (∼1.8 s). We also apply these procedures to mutants in p53 chromatin binding. Our results support the model that p53 locates specific sites by first binding at sequence-independent sites.

Figure 1.

Differences in FRAP, FCS and SMT analysis result in discrepant binding estimates. (a) FRAP, FCS and SMT were performed on a p53 construct fused with a Halotag receptor transiently transfected in the human H1299 p53-null cell line. The tetramethylrhodamine (TMR) ligand (red cross) is membrane permeable and binds covalently to the HaloTag fusion protein (grey circle). The ligand concentration can be adjusted depending on the technique. FRAP and FCS were performed on a commercially available confocal microscope, while SMT was performed on a custom-built widefield microscope using an inclined illumination scheme (See also Supplementary Figure S2). The numbers in the image sequences represent the acquisition time in ms. The scale bar corresponds to 5 µm. The blue circle in the first image of the FRAP sequence (left) represent the bleached area. The blue square in the FCS image (center) represents the location of the FCS observation volume. (b) The FRAP data could be fit equally well by three different models: (1) a model accounting for two binding states and no diffusion (green line); (2) a model accounting for one binding state and one diffusion state (red line); (3) a model accounting for two diffusion states (blue line). The different models resulted in discrepant estimates of residence times, ranging from 0.4 to 6.3 s and bound fractions, ranging from 23 to 100% (error bar SEM n = 27). (c) FCS data obtained on p53-wt-HaloTag are also well fit by any of the three models in (b), resulting in residence times ranging from 0.02 to 3.2 s and bound fractions ranging from 22 to 100% (error bars SEM n = 15). Note that only model (2) provides reasonably self-consistent estimates by FRAP and FCS. (d) Binding parameters are isolated from the single molecule tracks by defining the bound molecules as those tracked for at least N_min consecutive frames yielding frame-to-frame displacements less than r_max. The same track (black) is shown in each case, but the segment(s) of the track identified as bound (blue purple, green) depends on the threshold used. Applying these same thresholds to all of the p53 tracks results in residence times ranging from 0.05 to 2 s and bound fractions ranging from 10 to 40% (error bars are 95% confidence intervals).

Figure 2.

Analysis of the SMT data for H2B and p53. (a) We performed SMT on histone H2B, which is tightly bound to chromatin. The histogram of displacements was calculated at all possible time lags between frames of the single molecule movie, but for clarity only one time lag of the full 2D histogram is shown, t = 0.04 s. (Histograms at different time lags are shown in Supplementary Figure S4). The histogram at t = 0.04 s shows a peak at a displacement of ∼50 nm, with 99% of the displacements shorter than 220 nm. The histogram was well described by a diffusion model, resulting in an estimate for the diffusion of the chromatin-bound H2B molecules equal to 0.0019 µm²/s. (b) We chose the maximum H2B displacement observed between consecutive frames r_max as a threshold to define chromatin bound molecules. However, as some free p53 molecules can diffuse slowly enough to mimic binding, we discarded p53 track segments with displacements less than r_max for shorter than a minimum number of frames N_min. The estimated p53 residence time increases for higher values of N_min, until a plateau is reached at N_min∼16 frames, corresponding to a situation where the probability for a free molecule (with a diffusion coefficient D > 0.2 µm²/s) to be counted as bound is less than 1%. (c) We therefore used N_min= 16 frames and r_max= 220 nm to select bound p53 molecules. We compared the MSD plot for the putative bound p53 molecules (red circles) and to the MSD plot obtained for all the histone H2B molecules (black circles). Although the plots show considerable overlap, at early times the bound p53 molecules diffuse faster, suggesting that there are some differences between chromatin bound by p53 versus H2B. Control experiments on fixed samples (blue triangles) yielded a flat MSD curve, which we used to estimate the localization accuracy of the system σ as (51): MSD = 4σ², resulting in σ= 27 nm. (d) Like H2B, the time-dependent histogram of displacements for p53 also shows a peak at ∼50 nm, which likely reflects chromatin-bound molecules. However, the p53 histogram exhibits a much longer tail than the H2B histogram. The full 2D histogram for p53 was fit with two different kinetic models, but for clarity the fit at only one time lag of the full 2D histogram is shown, t = 0.04 s (16 221 jumps). (Fitting results at other time lags are shown in Supplementary Figure S5). The estimated binding parameters from the fits are provided in Table 1.

Figure 3.

Identification of the proper kinetic model for p53. (a) The durations of p53-wt binding events as measured by our objective thresholding of the SMT data were plotted as a cumulative histogram (circles). This was well fit by a single exponential (solid black line), Indicating that a kinetic model for p53 should account for a single binding state. Larger displacements of p53-wt that the objective threshold procedure identified as free yielded an MSD plot (errors SEM, n > 200) that was not described by simple diffusion (dashed line), but rather by hindered diffusion (solid line). (b) The MSD plot was used to quantify the time p53-wt takes to diffuse through the FRAP spot, 0.28 s and through the FCS volume, 0.07 s. These times indicate that diffusion should be included in the FRAP and FCS kinetic models (see section ‘Results’). (c) The FRAP and FCS predictions using a kinetic model with one bound state and one diffusing state match the SMT estimates for bound fractions and differ by a factor of four and two, respectively from the SMT estimates for residence times. The differences in residence-time estimates correlate with the spatial resolution of the technique, as confirmed by performing FRAP with a smaller bleach-spot size (error bars: 95% confidence intervals for SMT, SEM., n = 27 for FRAP with 2 µm bleach spot, SEM., n = 24 for FRAP with 0.5 µm bleach spot, SEM., n = 15 for FCS).

Figure 4.

Comparison of wild-type and mutant p53 displacement histograms. The histogram of displacements for p53-wt obtained at a frame rate of 50 Hz (a) was compared to the one obtained for a mutant (p53-R273H) known to suppress binding to specific sites (b), a mutant (p53-d30) known to suppress binding to non-specific DNA sequences (c) and a double mutant p53-R273H/d30 (d). All mutants resulted in a drop of the peak at short displacements corresponding to bound molecules. Interestingly, the histograms for the p53 double mutant and p53-d30 were very similar, indicating that p53-d30 not only affected the sequence-independent interactions but also suppressed binding to specific sites. Fitting of the histograms with a model accounting for two free populations exchanging with one bound population resulted in the estimates of the bound fractions and residence times reported in Table 2.