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Cellular functions like cell division are remarkably conserved across phyla. However the evolutionary principles of cellular organization that drive it are less well explored. Thus, an essential question remains: to what extent cellular parameters evolve without altering the basic function they sustain? Here we have observed 6 different nematode species for which the mitotic spindle is positioned asymmetrically during the first embryonic division. Whereas the C. elegans spindle undergoes oscillations during its displacement, the spindle elongates without oscillations in other species. We asked which evolutionary changes in biophysical parameters could explain differences in spindle motion while maintaining a constant output. Using laser microsurgery of the spindle we revealed that all species are subjected to cortical pulling forces, of varying magnitudes. Using a viscoelastic model to fit the recoil trajectories and with an independent measurement of cytoplasmic viscosity, we extracted the values of cytoplasmic drag, cortical pulling forces and spindle elasticity for all species. We found large variations in cytoplasmic viscosity whereas cortical pulling forces and elasticity were often more constrained. In agreement with previous simulations, we found that increased viscosity correlates with decreased oscillation speeds across species. However, the absence of oscillations despite low viscosity in some species, can only be explained by smaller pulling forces. Consequently, we find that spindle mobility across the species analyzed here is characterized by a tradeoff between cytoplasmic viscosity and pulling forces normalized by the size of the embryo. Our work provides a framework for understanding mechanical constraints on evolutionary diversification of spindle mobility.

The cell surface area (SA) increase with volume (V) is determined by growth and regulation of size and shape. Most studies of the rod-shaped model bacterium Escherichia coli have focussed on the phenomenology or molecular mechanisms governing such scaling. Here, we proceed to examine the role of population statistics and cell division dynamics in such scaling by a combination of microscopy, image analysis and statistical simulations. We find that while the SA of cells sampled from mid-log cultures scales with V by a scaling exponent 2/3, i.e. the geometric law SA ∼V2/3, filamentous cells have higher exponent values. We modulate the growth rate to change the proportion of filamentous cells, and find SA-V scales with an exponent > 2/3, exceeding that predicted by the geometric scaling law. However, since increasing growth rates alter the mean and spread of population cell size distributions, we use statistical modeling to disambiguate between the effect of the mean size and variability. Simulating (i) increasing mean cell length with a constant standard deviation (s.d.), (ii) a constant mean length with increasing s.d. and (iii) varying both simultaneously, results in scaling exponents that exceed the 2/3 geometric law, when population variability is included, with the s.d. having a stronger effect. In order to overcome possible effects of statistical sampling of unsynchronized cell populations, we ‘virtually synchronized’ time-series of cells by using the frames between birth and division identified by the image-analysis pipeline and divided them into four equally spaced phases- B, C1, C2 and D. Phase-specific scaling exponents estimated from these time series and the cell length variability were both found to decrease with the successive stages of birth (B), C1, C2 and division (D). These results point to a need to consider population statistics and a role for cell growth and division when estimating SA-V scaling of bacterial cells.

The cell surface area (SA) increase with volume (V) for cells is determined by growth and regulation of size and shape. Most studies of the rod-shaped model bacterium Escherichia coli have focussed on the phenomenology or molecular mechanisms governing such scaling. Here, we proceed to examine the role of population statistics and cell division dynamics in such scaling by a combination of microscopy, image analysis and statistical simulations. We find that while cells sampled from mid-log cultures follow a 2/3 exponent, similar to geometric (Platonic) solids, drug induced filamentous cells have higher exponent values. Modulating the growth rate to change the proportion of filamentous cells, we find SA-V scales with an exponent >2/3, exceeding that predicted by the geometric scaling law. However, since increasing growth rates alter the mean and spread of population cell size distributions, we use statistical modeling to disambiguate between the effect of the mean size and variability. Simulating (i) increasing mean cell length with a constant standard deviation (s.d.) and (ii) a constant mean length with increasing s.d. results in scaling exponents that exceed the 2/3 geometric law, when population variability is included. In order to overcome possible effects of statistical sampling of unsynchronized cell populations, we virtually 'synchronized' the estimation of SA-V scaling from single cell growth experiments. We find the exponent depends on the stage with the maximal cell length heterogeneity and scaling exponent observed during the intermediate period between birth (B) and division (D) stages. These results point to a need to consider population statistics and a role for cell growth and division when estimating SA-V scaling of bacterial cells.

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