Volume 96, Issue 5, Pages (March 2009)

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Volume 96, Issue 5, Pages 1911-1917 (March 2009) Using the Bias from Flow to Elucidate Single DNA Repair Protein Sliding and Interactions with DNA  Yihan Lin, Tong Zhao, Xing Jian, Zishaan Farooqui, Xiaohui Qu, Chuan He, Aaron R. Dinner, Norbert F. Scherer  Biophysical Journal  Volume 96, Issue 5, Pages 1911-1917 (March 2009) DOI: 10.1016/j.bpj.2008.11.021 Copyright © 2009 Biophysical Society Terms and Conditions

Figure 1 Properties of C-Ada dynamics on λ-DNA. (a) Accumulated single-protein trajectories on the same flow-extended DNA at two different flow rates. The flow is along the +x direction. (Upper image) A plot of 196 protein trajectories on the DNA at 2 μL/min volume flow rate. (Lower image) Plot of 216 protein trajectories on the same DNA at 4 μL/min flow rate. The scale bar is 1 μm. (b) A sample single C-Ada position time series (dots) showing that the protein scans over almost the entire DNA length in 12 s. (c) MSD versus time curve calculated from the two pools of trajectories in a: (+) low flow rate, (○) high flow rate. The MSD is calculated by the internal averaging method for better statistics (30). (d) Step size (x) distribution (+) at t = 0.5 s constructed from the pool of protein trajectories for 2 μL/min (left) and the best Gaussian fit. Analogous histogram and fit for 4 μL/min (○). Peak positions (0.13 μm and 0.48 μm, respectively) are indicated by dashed lines. Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions

Figure 2 Extraction of αu/γ and D. Each set of protein trajectories was taken on one DNA molecule. In a total of 12 data sets shown, there are three DNA molecules that allowed the production of more than one data set; in other words, we were able to perform experiments for more than one flow rate condition on these three DNA molecules. The rest of the data sets were collected on separate DNAs. Each data set contains on average ∼100 protein trajectories. (a) The peak positions of the Gaussian fits for the x distributions constructed at different times from four different sets of protein trajectories at 2 μL/min. The slope of the linear fit gives αu/γ. (b) The variances of the Gaussian fits for the same histograms in a versus time. The slope of the linear fit gives 2D. (c and d) Analogous plots for trajectories at 3 μL/min. (e and f) Analogous plots for trajectories at 4 μL/min. Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions

Figure 3 The quantity αu/γ at three different flow rates (four data sets per flow rate) (○) on some single DNA molecules. The slope of the linear fit is 1 × 10−2. The diffusion constants (▿) determined from experiments are independent of flow. The error bars represent standard deviations. Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions

Figure 4 Protein dwell time distributions on the DNA under three different flow conditions (colors). Each dwell time value is a bin in the histograms. Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions

Figure 5 Satisfaction of a detailed fluctuation theorem. (a) Distribution of x for t = 0.5 s constructed from a set of protein trajectories at 2 μL/min flow rate with bin width 0.5 μm. The black curve is the best Gaussian fit. The dashed line indicates x = 0 μm. (b) Logarithm of the ratio of the number of trajectories with displacement x (i.e., entropy Σt) to the number of trajectories with displacement −x (i.e., entropy − Σt) versus x. The experimental data (○) are fitted with y =ax (solid black). (c and d) Analogous plots for a set of trajectories at 3 μL/min. (e and f) Analogous plots for a set of trajectories at 4 μL/min. The slopes of the fitted lines are in agreement with the αu/γD parameters extracted independently. Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions

Figure 6 Satisfaction of an integral fluctuation theorem. Logarithm of the ratio of the number of entropy-producing trajectory segments to the number of entropy-consuming trajectory segments versus t (leftmost quantity in Eq. 6; + symbols and fit, solid lines), and logarithm of 1/〈exp(− Σt/k)〉Σt>0 versus t (rightmost quantity in Eq. 6; ○ symbols and fit, dashed lines) plots for three sets of trajectories under different flow rates, 2 μL/min (bottom), 3 μL/min (middle), and 4 μL/min (top, blue online). A power law of the form y =axb is used to fit the data. The fitting parameters are a = 0.37 and b = 0.53 (bottom, solid), a = 0.31 and b = 0.50 (bottom, dashed), a = 0.87 and b = 0.53 (middle, solid), a = 0.85 and b = 0.49 (middle, dashed), a = 1.1 and b = 0.48 (top, solid), and a = 1.1 and b = 0.50 (top, dashed). Biophysical Journal 2009 96, 1911-1917DOI: (10.1016/j.bpj.2008.11.021) Copyright © 2009 Biophysical Society Terms and Conditions