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Inserm Transfert frap data analysis
Frap Data Analysis, supplied by Inserm Transfert, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See <xref ref-type=Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates. " width="250" height="auto" />
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Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See <xref ref-type=Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates. " width="250" height="auto" />
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APC full-length and mutant dynamics at the centrosome are slowed by nocodazole treatment. ( A ) pAPC-FL-GFP and pAPC1-1309-GFP ( green ) were each co-transfected with pRFP-PCNT-C241 (red) into HeLa cells. APC-GFP was analysed for dynamic recruitment at the centrosome by <t>FRAP</t> in the presence and absence of 33 µM nocodazole. The effect of γ-tubulin on APC dynamics was also tested where FRAP was performed after depletion with γ-tubulin siRNA. ( B ) Fluorescence recovery curves were plotted as shown for APC-FL, indicating relative rates of recovery and equilibration (plateau) at the centrosome for up to 100 s after bleaching. The presence of nocodazole ( black dashed line ) significantly reduced the rate of recovery of APC-FL-GFP compared to that of untreated cells ( blue line ) ( n = 20–30). This was also indicated by comparison of T 1/2 values for the fast recovery pools (T = 0–40 s) ( p < 0.0001), and extrapolated retention levels, calculated from the recovery curve data using Graph Pad <t>Prism</t> <t>software</t> as above (see ). ( C ) The dynamic exchange profile of APC1-1309 at the centrosome +/− nocodazole ( black dotted line ) showed a small difference in the dynamic rate of recruitment compared to untreated cells ( p = 0.0447). There was a small but significant difference in T 1/2 value; however, no change in retention after nocodazole treatment. ( D ) Fluorescence recovery curves are shown for APC1-1309 for siCTRL ( red ) and γ-tubulin siRNA ( green ) transfected cells ( n = 9–10). Confirmation of γ-tubulin knockdown was by Western blot, and vinculin was used as loading control. Column graph shows the T 1/2 of the fluorescence recovery over 40 s, which was significantly increased after the knockdown of γ-tubulin ( p = 0.0194). No significant change in the maximum recovery (retention) was detected. (*, p < 0.05; ****, p < 0.0001).
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APC full-length and mutant dynamics at the centrosome are slowed by nocodazole treatment. ( A ) pAPC-FL-GFP and pAPC1-1309-GFP ( green ) were each co-transfected with pRFP-PCNT-C241 (red) into HeLa cells. APC-GFP was analysed for dynamic recruitment at the centrosome by <t>FRAP</t> in the presence and absence of 33 µM nocodazole. The effect of γ-tubulin on APC dynamics was also tested where FRAP was performed after depletion with γ-tubulin siRNA. ( B ) Fluorescence recovery curves were plotted as shown for APC-FL, indicating relative rates of recovery and equilibration (plateau) at the centrosome for up to 100 s after bleaching. The presence of nocodazole ( black dashed line ) significantly reduced the rate of recovery of APC-FL-GFP compared to that of untreated cells ( blue line ) ( n = 20–30). This was also indicated by comparison of T 1/2 values for the fast recovery pools (T = 0–40 s) ( p < 0.0001), and extrapolated retention levels, calculated from the recovery curve data using Graph Pad <t>Prism</t> <t>software</t> as above (see ). ( C ) The dynamic exchange profile of APC1-1309 at the centrosome +/− nocodazole ( black dotted line ) showed a small difference in the dynamic rate of recruitment compared to untreated cells ( p = 0.0447). There was a small but significant difference in T 1/2 value; however, no change in retention after nocodazole treatment. ( D ) Fluorescence recovery curves are shown for APC1-1309 for siCTRL ( red ) and γ-tubulin siRNA ( green ) transfected cells ( n = 9–10). Confirmation of γ-tubulin knockdown was by Western blot, and vinculin was used as loading control. Column graph shows the T 1/2 of the fluorescence recovery over 40 s, which was significantly increased after the knockdown of γ-tubulin ( p = 0.0194). No significant change in the maximum recovery (retention) was detected. (*, p < 0.05; ****, p < 0.0001).
Program For Frap Data Analysis, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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APC full-length and mutant dynamics at the centrosome are slowed by nocodazole treatment. ( A ) pAPC-FL-GFP and pAPC1-1309-GFP ( green ) were each co-transfected with pRFP-PCNT-C241 (red) into HeLa cells. APC-GFP was analysed for dynamic recruitment at the centrosome by <t>FRAP</t> in the presence and absence of 33 µM nocodazole. The effect of γ-tubulin on APC dynamics was also tested where FRAP was performed after depletion with γ-tubulin siRNA. ( B ) Fluorescence recovery curves were plotted as shown for APC-FL, indicating relative rates of recovery and equilibration (plateau) at the centrosome for up to 100 s after bleaching. The presence of nocodazole ( black dashed line ) significantly reduced the rate of recovery of APC-FL-GFP compared to that of untreated cells ( blue line ) ( n = 20–30). This was also indicated by comparison of T 1/2 values for the fast recovery pools (T = 0–40 s) ( p < 0.0001), and extrapolated retention levels, calculated from the recovery curve data using Graph Pad <t>Prism</t> <t>software</t> as above (see ). ( C ) The dynamic exchange profile of APC1-1309 at the centrosome +/− nocodazole ( black dotted line ) showed a small difference in the dynamic rate of recruitment compared to untreated cells ( p = 0.0447). There was a small but significant difference in T 1/2 value; however, no change in retention after nocodazole treatment. ( D ) Fluorescence recovery curves are shown for APC1-1309 for siCTRL ( red ) and γ-tubulin siRNA ( green ) transfected cells ( n = 9–10). Confirmation of γ-tubulin knockdown was by Western blot, and vinculin was used as loading control. Column graph shows the T 1/2 of the fluorescence recovery over 40 s, which was significantly increased after the knockdown of γ-tubulin ( p = 0.0194). No significant change in the maximum recovery (retention) was detected. (*, p < 0.05; ****, p < 0.0001).
Frap Data Analysis, supplied by Inserm Transfert, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See <xref ref-type=Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates. " width="100%" height="100%">

Journal: iScience

Article Title: Dynamics of endogenous PARP1 and PARP2 during DNA damage revealed by live-cell single-molecule imaging

doi: 10.1016/j.isci.2022.105779

Figure Lengend Snippet: Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates.

Article Snippet: FRAP data analysis (MatLab script) , Hansen et al. and Sprague et al. , , https://gitlab.com/anders.sejr.hansen/Mahadevan_2022.

Techniques: Microscopy, Stable Transfection, Binding Assay, Imaging, Single Particle, Diffusion-based Assay

Journal: iScience

Article Title: Dynamics of endogenous PARP1 and PARP2 during DNA damage revealed by live-cell single-molecule imaging

doi: 10.1016/j.isci.2022.105779

Figure Lengend Snippet:

Article Snippet: FRAP data analysis (MatLab script) , Hansen et al. and Sprague et al. , , https://gitlab.com/anders.sejr.hansen/Mahadevan_2022.

Techniques: Virus, Recombinant, Western Blot, Software, Modification, DNA Extraction

APC full-length and mutant dynamics at the centrosome are slowed by nocodazole treatment. ( A ) pAPC-FL-GFP and pAPC1-1309-GFP ( green ) were each co-transfected with pRFP-PCNT-C241 (red) into HeLa cells. APC-GFP was analysed for dynamic recruitment at the centrosome by FRAP in the presence and absence of 33 µM nocodazole. The effect of γ-tubulin on APC dynamics was also tested where FRAP was performed after depletion with γ-tubulin siRNA. ( B ) Fluorescence recovery curves were plotted as shown for APC-FL, indicating relative rates of recovery and equilibration (plateau) at the centrosome for up to 100 s after bleaching. The presence of nocodazole ( black dashed line ) significantly reduced the rate of recovery of APC-FL-GFP compared to that of untreated cells ( blue line ) ( n = 20–30). This was also indicated by comparison of T 1/2 values for the fast recovery pools (T = 0–40 s) ( p < 0.0001), and extrapolated retention levels, calculated from the recovery curve data using Graph Pad Prism software as above (see ). ( C ) The dynamic exchange profile of APC1-1309 at the centrosome +/− nocodazole ( black dotted line ) showed a small difference in the dynamic rate of recruitment compared to untreated cells ( p = 0.0447). There was a small but significant difference in T 1/2 value; however, no change in retention after nocodazole treatment. ( D ) Fluorescence recovery curves are shown for APC1-1309 for siCTRL ( red ) and γ-tubulin siRNA ( green ) transfected cells ( n = 9–10). Confirmation of γ-tubulin knockdown was by Western blot, and vinculin was used as loading control. Column graph shows the T 1/2 of the fluorescence recovery over 40 s, which was significantly increased after the knockdown of γ-tubulin ( p = 0.0194). No significant change in the maximum recovery (retention) was detected. (*, p < 0.05; ****, p < 0.0001).

Journal: Cancers

Article Title: Characterization of Adenomatous Polyposis Coli Protein Dynamics and Localization at the Centrosome

doi: 10.3390/cancers8050047

Figure Lengend Snippet: APC full-length and mutant dynamics at the centrosome are slowed by nocodazole treatment. ( A ) pAPC-FL-GFP and pAPC1-1309-GFP ( green ) were each co-transfected with pRFP-PCNT-C241 (red) into HeLa cells. APC-GFP was analysed for dynamic recruitment at the centrosome by FRAP in the presence and absence of 33 µM nocodazole. The effect of γ-tubulin on APC dynamics was also tested where FRAP was performed after depletion with γ-tubulin siRNA. ( B ) Fluorescence recovery curves were plotted as shown for APC-FL, indicating relative rates of recovery and equilibration (plateau) at the centrosome for up to 100 s after bleaching. The presence of nocodazole ( black dashed line ) significantly reduced the rate of recovery of APC-FL-GFP compared to that of untreated cells ( blue line ) ( n = 20–30). This was also indicated by comparison of T 1/2 values for the fast recovery pools (T = 0–40 s) ( p < 0.0001), and extrapolated retention levels, calculated from the recovery curve data using Graph Pad Prism software as above (see ). ( C ) The dynamic exchange profile of APC1-1309 at the centrosome +/− nocodazole ( black dotted line ) showed a small difference in the dynamic rate of recruitment compared to untreated cells ( p = 0.0447). There was a small but significant difference in T 1/2 value; however, no change in retention after nocodazole treatment. ( D ) Fluorescence recovery curves are shown for APC1-1309 for siCTRL ( red ) and γ-tubulin siRNA ( green ) transfected cells ( n = 9–10). Confirmation of γ-tubulin knockdown was by Western blot, and vinculin was used as loading control. Column graph shows the T 1/2 of the fluorescence recovery over 40 s, which was significantly increased after the knockdown of γ-tubulin ( p = 0.0194). No significant change in the maximum recovery (retention) was detected. (*, p < 0.05; ****, p < 0.0001).

Article Snippet: The FRAP assay data was analysed in GraphPad Prism 5 (GraphPad Software Inc., La Jolla, CA, USA) to determine the rate of fluorescence recovery over time, and the relative size of the dynamic and immobile pools of APC ( B–D).

Techniques: Mutagenesis, Transfection, Fluorescence, Comparison, Software, Knockdown, Western Blot, Control