Figure 4.
Separase autoactivation is unlikely. (A) Schematic depicting a positive feedback loop, where separase accelerates its own activation downstream of securin degradation. (B) Computational model for separase (Sep) release mediated by APC/C-mediated securin (Sec) degradation with or without separase autoactivation. Left side: diagram of the reactions in the model. Right side: simulation for high or low APC/C activity, without or with separase autoactivation, assuming a sigmoidal increase of APC/C activity with time. Solid lines indicate high APC/C activity; dashed lines indicate low APC/C activity, mimicking an APC/C mutant. See Materials and methods for model details. (C and D) Frequency distributions and Gaussian fit (continuous lines) of the time difference between the separation of centromeres 1 and 2 or centromeres 2 and 3. Cells were carrying either a temperature-sensitive allele of the APC/C subunit Cut9 (cut9-665) and were grown in rich medium before imaging (C, orange) or were grown in minimal medium and treated with 100 µM of the proteasome inhibitor velcade (bortezomib) 30 min prior to imaging (D, red). The fitted Gaussian distributions of WT cells grown under similar conditions and without inhibitor are shown for comparison (black). Mean ± SD of the fit; n = number of cells; P values from a two-sample Kolmogorov–Smirnov test. Refer to the image caption for details. Panel A shows a schematic illustrating separase autoactivation feedback, where active separase enhances its own activation following securin degradation during mitotic progression. Panel B shows a computational model diagram and simulation graphs of APC/C-mediated securin degradation and separase activation, where the x-axis represents time in seconds and the y-axis represents concentration in micromolar, comparing conditions with and without separase autoactivation under different APC/C activity levels. Panel C shows histograms with Gaussian fits of time differences between centromere separations in APC/C mutant versus wild-type cells, where the x-axis represents time difference in seconds and the y-axis represents percentage of cells. Panel D shows histograms with Gaussian fits of time differences between centromere separations after proteasome inhibition versus unperturbed cells, where the x-axis represents time difference in seconds and the y-axis represents percentage of cells.

Separase autoactivation is unlikely. (A) Schematic depicting a positive feedback loop, where separase accelerates its own activation downstream of securin degradation. (B) Computational model for separase (Sep) release mediated by APC/C-mediated securin (Sec) degradation with or without separase autoactivation. Left side: diagram of the reactions in the model. Right side: simulation for high or low APC/C activity, without or with separase autoactivation, assuming a sigmoidal increase of APC/C activity with time. Solid lines indicate high APC/C activity; dashed lines indicate low APC/C activity, mimicking an APC/C mutant. See Materials and methods for model details. (C and D) Frequency distributions and Gaussian fit (continuous lines) of the time difference between the separation of centromeres 1 and 2 or centromeres 2 and 3. Cells were carrying either a temperature-sensitive allele of the APC/C subunit Cut9 (cut9-665) and were grown in rich medium before imaging (C, orange) or were grown in minimal medium and treated with 100 µM of the proteasome inhibitor velcade (bortezomib) 30 min prior to imaging (D, red). The fitted Gaussian distributions of WT cells grown under similar conditions and without inhibitor are shown for comparison (black). Mean ± SD of the fit; n = number of cells; P values from a two-sample Kolmogorov–Smirnov test.

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