Introduction | Eventually, nutrients required for cell growth will be depleted and cells will be subject to long periods of starvation. |
Prolonged survival of starving cells by a RpoS-mediated negative feedback loop | As cells grow and consume substrates, the concentration of substrates in the medium will decrease (green line in Fig. |
Prolonged survival of starving cells by a RpoS-mediated negative feedback loop | When the concentration falls to the level reducing the rate of cell growth , the expression of RpoS is activated (blue line; note that higher RpoS levels at lower substrate concentrations were previously established [26,27]). |
Prolonged survival of starving cells by a RpoS-mediated negative feedback loop | It is well known that the expression of RpoS represses cell growth (red line in Fig. |
RpoS —| cell growth | RpoS —| cell growth |
RpoS —| cell growth | (A) Cells consume substrates for cell growth and the substrate concentration decreases in the medium (green line). |
RpoS —| cell growth | When the concentration decreases to the levels affecting the rate of cell growth , RpoS accumulates (blue line) [26,27]. |
Survival of starving cells is cell-density-dependent and biphasic | As cells grow , glycerol is consumed and eventually exhausted, leading to the cessation of growth; we provided low enough amounts of glycerol to ensure that the growth is arrested as a result of the exhaustion of glycerol, not by other nutrient sources (SI Fig; see Materials and methods for the exact glycerol concentrations used). |
Abstract | Maintenance of cellular size is a fundamental systems level process that requires balancing of cell growth with proliferation. |
Author Summary | Cell size emerges from the balance between how fast the cell grows and the frequency with which it divides. |
Discussion | Here, we present a mechanistic single cell growth model that is able to predict cell growth and division timing in budding yeast populations. |
Discussion | In conclusion, we present a cell growth model, which unifies integration of growth and division in the G1 and G2 phases of the cell division cycle to accurately reproduce and predict cell size at birth and at budding, as well as timing of the cell cycle phases over four different nutritional conditions for budding yeast. |
Results | Through cell growth and division, we evolve an entire asynchronously growing population from one progenitor cell, as previously described [32]. |
Results | In the models, simulation of cell growth on different carbon sources can be achieved by modulating the parameter growth (Table 2). |
The model | As a cell grows , the ratio of the area to the volume shifts, since the area eXpands slower than the volume. |
The model | The idea that the surface area-to-volume-ratio plays an important role in connecting the cell growth to the cell division cycle was also eXplored by others [50, 57]. |
The model | During the simulation, a cell grows during G1, then it grows a bud during S-Gz-M. At division, the bud is detached from the mother cell. |
Development of a computational model | Thus, it would be expected that higher IGFBP2 levels would reduce IGFIR activation and attenuate downstream signaling—re-ducing cell growth . |
Development of a computational model | Thus, there exists a link between IGFBP2 and glioma cell growth independent of its effects through the binding of IGFI and the blocking of IGFIR activation. |
Development of a computational model | However, excess HIFloc that has not been degraded (in hypoxic conditions) is transported into the nucleus, where it binds to its dimer ARNT / HIFIB and subsequently upregulates other genes that promote cell growth [55]. |
Discussion | This study offers an explanation for the difficulties encountered by current drugs targeting IGFIR to reduce glioblastoma cell growth : a secondary mechanism that upregulates HIFloc. |