Uncovering the quantitative laws that govern the growth and division of single cells remains a major challenge. Using a unique combination of technologies that yields unprecedented statistical precision, we find that the sizes of individual Caulobacter crescentus cells increase exponentially in time. We also establish that they divide upon reaching a critical multiple (≈1.8) of their initial sizes, rather than an absolute size. We show that when the temperature is varied, the growth and division timescales scale proportionally with each other over the physiological temperature range. Strikingly, the cell-size and division-time distributions can both be rescaled by their mean values such that the conditionspecific distributions collapse to universal curves. We account for these observations with a minimal stochastic model that is based on an autocatalytic cycle. It predicts the scalings, as well as specific functional forms for the universal curves. Our experimental and theoretical analysis reveals a simple physical principle governing these complex biological processes: a single temperature-dependent scale of cellular time governs the stochastic dynamics of growth and division in balanced growth conditions. single-cell dynamics | cell-to-cell variability | exponential growth | Hinshelwood cycle | Arrhenius law

Iwanir S; Tramm N; Nagy S; Wright C; Ish D; Biron D. The microarchitecture of C. elegans behavior during lethargus: homeostatic bout dynamics, a typical body posture, and regulation by a central neuron. SLEEP 2013;36(3):385-395.

How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division. These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to the replicationcompetent (stalked) stage of the Caulobacter crescentus life cycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For C. crescentus cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time and, thus, yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell-age distribution, and the quiescence timescale.

Despite their simplicity, longitudinal studies of invertebrate models are rare. We thus sought to characterize behavioral trends of Caenorhabditis elegans, from the mid fourth larval stage through the mid young adult stage. We found that, outside of lethargus, animals exhibited abrupt switching between two distinct behavioral states: active wakefulness and quiet wakefulness. The durations of epochs of active wakefulness exhibited non-Poisson statistics. Increased Gαs signaling stabilized the active wakefulness state before, during and after lethargus. In contrast, decreased Gαs signaling, decreased neuropeptide release, or decreased CREB activity destabilized active wakefulness outside of, but not during, lethargus. Taken together, our findings support a model in which protein kinase A (PKA) stabilizes active wakefulness, at least in part through two of its downstream targets: neuropeptide release and CREB. However, during lethargus, when active wakefulness is strongly suppressed, the native role of PKA signaling in modulating locomotion and quiescence may be minor.DOI: http://dx.doi.org/10.7554/eLife.00782.001

We investigate the intergenerational shape dynamics of single Caulobacter crescentus cells using a novel combination of imaging techniques and theoretical modeling. We determine the dynamics of cell pole-to-pole lengths, cross-sectional widths, and medial curvatures from high accuracy measurements of cell contours. Moreover, these shape parameters are determined for over 250 cells across approximately 10000 total generations, which affords high statistical precision. Our data and model show that constriction is initiated early in the cell cycle and that its dynamics are controlled by the time scale of exponential longitudinal growth. Based on our extensive and detailed growth and contour data, we develop a minimal mechanical model that quantitatively accounts for the cell shape dynamics and suggests that the asymmetric location of the division plane reflects the distinct mechanical properties of the stalked and swarmer poles. Furthermore, we find that the asymmetry in the division plane location is inherited from the previous generation. We interpret these results in terms of the current molecular understanding of shape, growth, and division of C. crescentus.

BackgroundTo survive dynamic environments, it is essential for all animals to appropriately modulate their behavior in response to various stimulus intensities. For instance, the nematode Caenorhabditis elegans suppresses the rate of egg-laying in response to intense mechanical stimuli, in a manner dependent on the mechanosensory neurons FLP and PVD. We have found that the unilaterally placed single interneuron ALA acted as a high-threshold mechanosensor, and that it was required for this protective behavioral response.ResultsALA was required for the inhibition of egg-laying in response to a strong (picking-like) mechanical stimulus, characteristic of routine handling of the animals. Moreover, ALA did not respond physiologically to less intense touch stimuli, but exhibited distinct physiological responses to anterior and posterior picking-like touch, suggesting that it could distinguish between spatially separated stimuli. These responses required neither neurotransmitter nor neuropeptide release from potential upstream neurons. In contrast, the long, bilaterally symmetric processes of ALA itself were required for producing its physiological responses; when they were severed, responses to stimuli administered between the cut and the cell body were unaffected, while responses to stimuli administered posterior to the cut were abolished.ConclusionC. elegans neurons are typically classified into three major groups: sensory neurons with specialized sensory dendrites, interneurons, and motoneurons with neuromuscular junctions. Our findings suggest that ALA can autonomously sense intense touch and is thus a dual-function neuron, i.e., an interneuron as well as a novel high-threshold mechanosensor.

Summary We report a novel method for obtaining simultaneous images from multiple vantage points of a microscopic specimen using size-matched microscopic mirrors created from anisotropically etched silicon. The resulting pyramidal wells enable bright-field and fluorescent side-view images, and when combined with z-sectioning, provide additional information for 3D reconstructions of the specimen. We have demonstrated the 3D localization and tracking over time of the centrosome of a live Dictyostelium discoideum. The simultaneous acquisition of images from multiple perspectives also provides a five-fold increase in the theoretical collection efficiency of emitted photons, a property which may be useful for low-light imaging modalities such as bioluminescence, or low abundance surface-marker labelling.

We reconceptualize homeostasis from an inherently stochastic, intergenerational perspective. Here we use our SChemostat technology to directly record high-precision multigenerational trains of sizes of statistically identical non-interacting individual cells of Caulobacter crescentus in precisely controlled environmental conditions. We first show that individual cells indeed maintain stochastic intergenerational homeostasis of their characteristic sizes, then extract organizational principles in the form of an intergenerational scaling law and other "emergent simplicities", which facilitate a principled route to dimensional reduction of the problem. We use these emergent simplicities to formulate the precise theoretical framework for stochastic homeostasis, which not only captures the exact kinematics of stochastic intergenerational cell size homeostasis (providing spectacular theory-data matches with no fitting parameters), but also determines the necessary and sufficient condition for stochastic intergenerational homeostasis. Compellingly, our reanalysis of existing data published by other groups using different single-cell technologies demonstrates that this intergenerational framework is applicable to other microorganisms (Escherichia coli and Bacillus subtilis) in a variety of growth conditions. Finally, we establish that in balanced growth conditions stochastic intergenerational cell size homeostasis is achieved through elastic adaptation, thus precluding the possibility that cell size can act as a repository of intergenerational memory.