Chromosome position data were generated by manual tracking of k-fiber plus ends, ablation sites, and spindle poles in live-imaged GFP–α-tubulin PtK2 cells, using overlaid GFP–α-tubulin and phase-contrast time-lapse videos in a home-written MatLab (R2012a Version 7.4) program. As controls, we also tracked neighboring k-fiber plus ends (of unmanipulated chromosomes in metaphase and monopolar spindles, and of the paired sister chromatids in anaphase spindles). We manually selected the start and end times of the poleward transport response (for ablated k-fibers) or the first poleward movement after ablation (for control chromosomes) by examining plots of k-fiber plus end position over time and choosing the segment over which poleward motion was processive, and we used these times and positions to calculate mean speeds. We calculated the delay times as the difference between the first frame after ablation and the first frame of this sustained poleward response. For non–k-fibers, we manually tracked the position of their new minus ends as long as possible.
Line scan analysis of immunofluorescence colocalization was performed using the plot profile function of ImageJ with a line width of 1 pixel.
Kymographs of GFP-Arp1A and GFP-NuMA puncta and pole position over time were generated in ImageJ. A second home-written MatLab program generated fluorescence intensity line scans for each frame from the kymograph. Using each sequence of line scans, the peaks indicating the positions of GFP-Arp1A/GFP-NuMA puncta and the spindle pole were manually selected, with the intensity maxima of these peaks used to indicate puncta positions. We defined the initial recruitment time of GFP-Arp1A/GFP-NuMA puncta as the first frame in which a clear peak was visible in the line scan. We continued to track puncta until their intensity peaks could not be clearly separated from those of the spindle poles. To calculate the distance of these peak positions from the ablation sites, we used the ablation targeting coordinates from Metamorph. For comparing the intensity of GFP-NuMA puncta recruited to sites of ablation to other puncta, we calculated the fold difference in the mean integrated intensity of at least four puncta in each cell at sites/times without ablation and the integrated intensity of puncta recruited after ablation.
Data are expressed as mean ± SEM. Calculations of correlation coefficients (Pearson’s r) and p-values were performed in MatLab. For calculating mean traces inFig. 5 G , data from all traces were collected into 10-s-wide bins in time and the mean position within this bin was calculated.
Line scan analysis of immunofluorescence colocalization was performed using the plot profile function of ImageJ with a line width of 1 pixel.
Kymographs of GFP-Arp1A and GFP-NuMA puncta and pole position over time were generated in ImageJ. A second home-written MatLab program generated fluorescence intensity line scans for each frame from the kymograph. Using each sequence of line scans, the peaks indicating the positions of GFP-Arp1A/GFP-NuMA puncta and the spindle pole were manually selected, with the intensity maxima of these peaks used to indicate puncta positions. We defined the initial recruitment time of GFP-Arp1A/GFP-NuMA puncta as the first frame in which a clear peak was visible in the line scan. We continued to track puncta until their intensity peaks could not be clearly separated from those of the spindle poles. To calculate the distance of these peak positions from the ablation sites, we used the ablation targeting coordinates from Metamorph. For comparing the intensity of GFP-NuMA puncta recruited to sites of ablation to other puncta, we calculated the fold difference in the mean integrated intensity of at least four puncta in each cell at sites/times without ablation and the integrated intensity of puncta recruited after ablation.
Data are expressed as mean ± SEM. Calculations of correlation coefficients (Pearson’s r) and p-values were performed in MatLab. For calculating mean traces in
