The molecular networks regulating basic physiological processes in a cell can be converted into mathematical equations (eg differential equations) and solved by a computer. The division cycle of eukaryotic cells is an important example of such a control system, and fission yeast is an excellent test organism for the computational modelling approach. The mathematical model is tested by simulating wild-type cells and many known cell cycle mutants. This paper describes an example where this approach is useful in understanding multiple rounds of DNA synthesis (endoreplication) in fission yeast cells that lack the main (B-type) mitotic cyclin, Cdc13. It is proposed that the key physiological variable driving progression through the cell cycle during balanced growth and division is the mass/DNA ratio, rather than the mass/nucleus ratio.

There is considerable controversy concerning the exact growth profile of size parameters during the cell cycle. Linear, exponential and bilinear models are commonly considered, and the same model may not apply for all species. Selection of the most adequate model to describe a given data-set requires the use of quantitative model selection criteria, such as the partial (sequential) F-test, the Akaike information criterion and the Schwarz Bayesian information criterion, which are suitable for comparing differently parameterized models in terms of the quality and robustness of the fit but have not yet been used in cell growth-profile studies. Length increase data from representative individual fission yeast (Schizosaccharomyces pombe) cells measured on time-lapse films have been reanalyzed using these model selection criteria. To fit the data, an extended version of a recently introduced linearized biexponential (LinBiExp) model was developed, which makes possible a smooth, continuously differentiable transition between two linear segments and, hence, allows fully parametrized bilinear fittings. Despite relatively small differences, essentially all the quantitative selection criteria considered here indicated that the bilinear model was somewhat more adequate than the exponential model for fitting these fission yeast data. A general quantitative framework was introduced to judge the adequacy of bilinear versus exponential models in the description of growth time-profiles. For single cell growth, because of the relatively limited data-range, the statistical evidence is not strong enough to favor one model clearly over the other and to settle the bilinear versus exponential dispute. Nevertheless, for the present individual cell growth data for fission yeast, the bilinear model seems more adequate according to all metrics, especially in the case of wee1 Δ cells.

In a recent publication it was claimed that cultured mammalian cells, in contrast to yeasts, maintain a constant size distribution in the population without a size checkpoint. This inference may be challengeable. (1) It is argued that "weak" size control implies the existence of a checkpoint, and unfortunately the technique used by Conlon and Raff might obscure such a weak mechanism. (2) Previous investigations of size control in yeasts have shown that individual cell data, rather than means and variances of cell populations, are prerequisites for reliable interpretation. (3) No experimental data so far obtained suggest that in any cell culture a linear growth pattern in cell mass can maintain size homeostasis on its own without size control. (4) Studies on fission yeast mutants indicate that the molecular mechanisms of size control vary with genetic background, implying that no single mechanism is likely to apply to any cell type, including cultured mammalian cells, under all conditions. The claim that cultured mammalian cells maintain size homeostasis without a checkpoint needs to be re-evaluated by measurements on individual cells.