Abstract | With a mathematical population model comprised of individually growing cells, we show that cyclin translation would suffice to explain the observed growth rate dependence of cell volume at START. |
Introduction | It emerges as a combination of the cell cycle, controlling the orderly orchestration of duplication and division, and the individual growth rate , reflecting extra and intracellular physiological conditions. |
Introduction | The cell cycle and the growth rate are coupled, such that proliferation and growth are balanced, avoiding abnormally large or small cells. |
Introduction | The growth or biosynthetic capacity of the cell determines the growth rate and the unstable regulator is presumed to be one of the G1 cyclins, most likely Cln3 [8]. |
Results | Linking growth and division through cyclin translation leads to size homeostasis and a growth rate dependent sizer in G1 |
Results | The volume trajectory for a single cell is biphasic With altered growth rates dependent on cell cycle stage as observed experimentally as well (Fig 1B) [15, 40—42]. |
Results | Moreover, in both models there is a strong dependence of the cell volume at START on the individual growth rate in G1 phase (Figs 2B and 81—83), as observed experimentally [15]. |
Discussion | However, at low oxygen levels, glioblastoma will have drastically higher HIFloc levels which result in a much different phenotype and growth rate . |
Discussion | In fact, the top four rate constants that glioblastoma growth was most sensitive to when individually perturbed were the production of HIFloc (k8), production of IGFBP2 (k1), growth rate due to HIFloc (km) and promotion of HIFloc by IGFBP2 (kw). |
Fitting model parameters | The model was fitted for three outputs: glioblastoma growth rate ; HIFloc vs. 02 levels; and IGFI as a function of IGFBP2. |
Fitting model parameters | The glioblastoma growth rates were found for two distinct experiments (U87 and LN229) by fitting the same model and obtaining different initial conditions and growth rates for the two cell lines. |
Growth of glioblastoma experiments | The growth rate of the glioblastoma tumor, Eq 5, was determined by regression analysis using the data from both our previous experiments on spheroid growth in vitro using the U87 glio-blastoma cell line and LN229 glioblastoma growth in mice [70]. |
Insulin signaling pathway reactions that drive glioma growth | Results are plotted in Fig 4, which shows that LN229 glioblastoma growth was most sensitive to the production of HIFloc (k8) production of IGFBP2 (k1), growth rate due to HIFloc (k1 1) and promotion of HIFloc by IGFBP2 (km). |
Insulin signaling pathway reactions that drive glioma growth | Rate constants that glioblastoma growth rate were most sensitive to in LN229 cells. |
RpoS —| cell growth | Importantly, further studies show that although the growth rate of the population is zero at S = 81, the substrate consumption rate is not zero; see [36] for review. |
RpoS —| cell growth | This observation also agrees with previous studies [33—35]; in these studies, it is shown that as the substrate concentration 8 decreases, the growth rate 1 decreases, but 1 becomes zero at a nonzero substrate concentration. |
RpoS —| cell growth | Importantly, even when the growth rate of a population is zero (i.e., l = 0 at S = 81 in Fig. |