Collective gradient sensing with limited positional information.

Eukaryotic cells sense chemical gradients to decide where and when to move. Clusters of cells can sense gradients more accurately than individual cells by integrating measurements of the concentration made across the cluster. Is this gradient-sensing accuracy impeded when cells have limited knowledge of their position within the cluster, i.e., limited positional information? We apply maximum likelihood estimation to study gradient-sensing accuracy of a cluster of cells with finite positional information. If cells must estimate their location within the cluster, this lowers the accuracy of collective gradient sensing. We compare our results with a tug-of-war model where cells respond to the gradient by polarizing away from their neighbors without relying on their positional information. As the cell positional uncertainty increases, there is a trade-off where the tug-of-war model responds more accurately to the chemical gradient. However, for sufficiently large cell clusters or sufficiently shallow chemical gradients, the tug-of-war model will always be suboptimal to one that integrates information from all cells, even if positional uncertainty is high.

Statistics of pathogenic bacteria in the search of host cells.

A crucial phase in the infection process, which remains poorly understood, is the localization of suitable host cells by bacteria. It is often assumed that chemotaxis plays a key role during this phase. Here, we report a quantitative study on how Salmonella Typhimurium search for T84 human colonic epithelial cells. Combining time-lapse microscopy and mathematical modeling, we show that bacteria can be described as chiral active particles with strong active speed fluctuations, which are of biological, as opposed to thermal, origin. We observe that there exists a giant range of inter-individual variability of the bacterial exploring capacity. Furthermore, we find Salmonella Typhimurium does not exhibit biased motion towards the cells and show that the search time statistics is consistent with a random search strategy. Our results indicate that in vitro localization of host cells, and also cell infection, are random processes, not involving chemotaxis, that strongly depend on bacterial motility parameters.

The effect of reactions on the formation and readout of the gradient of Bicoid.

During early development, the establishment of gradients of transcriptional factors determines the patterning of cell fates. The case of Bicoid (Bcd) in Drosophila melanogaster embryos is well documented and studied. There are still controversies as to whether SDD models in which Bcd is Synthesized at one end, then Diffuses and is Degraded can explain the gradient formation within the timescale observed experimentally. The Bcd gradient is observed in embryos that express a Bicoid-eGFP fusion protein (Bcd-GFP) which cannot differentiate if Bcd is freely diffusing or bound to immobile sites. In this work we analyze an SDID model that includes the Interaction of Bcd with binding sites. We simulate numerically the resulting full reaction-diffusion system in a cylindrical domain using previously determined biophysical parameters and a simplified version of the Bcd source. In this way we obtain solutions that depend on the spatial location approximately as observed experimentally and that reach such dependence at a time that is also compatible with the experimental observations. Analyzing the differences between the free and bound Bcd distributions we observe that the latter spans over a longer lengthscale. We conclude that deriving the lengthscale from the distribution of Bcd-GFP can lead to an overestimation of the gradient lengthscale and of the Hill coefficient that relates the concentrations of Bcd and of the protein, Hunchback, whose production is regulated by Bcd.

Sexual pheromone modulates the frequency of cytosolic Ca2+ bursts in Saccharomyces cerevisiae.

Transient and highly regulated elevations of cytosolic Ca2+ control a variety of cellular processes. Bulk measurements using radioactive Ca2+ and the luminescent sensor aequorin have shown that in response to pheromone, budding yeast cells undergo a rise of cytosolic Ca2+ that is mediated by two import systems composed of the Mid1-Cch1-Ecm7 protein complex and the Fig1 protein. Although this response has been widely studied, there is no treatment of Ca2+ dynamics at the single-cell level. Here, using protein calcium indicators, we show that both vegetative and pheromone-treated yeast cells exhibit discrete and asynchronous Ca2+ bursts. Most bursts reach maximal amplitude in 1-10 s, range between 7 and 30 s, and decay in a way that fits a single-exponential model. In vegetative cells, bursts are scarce but preferentially occur when cells are transitioning G1 and S phases. On pheromone presence, Ca2+ burst occurrence increases dramatically, persisting during cell growth polarization. Pheromone concentration modulates burst frequency in a mechanism that depends on Mid1, Fig1, and a third, unidentified, import system. We also show that the calcineurin-responsive transcription factor Crz1 undergoes nuclear localization bursts during the pheromone response.

From free to effective diffusion coefficients in fluorescence correlation spectroscopy experiments.

Diffusion is one of the main transport processes that occur inside cells determining the spatial and time distribution of relevant action molecules. In most cases these molecules not only diffuse but also interact with others as they get transported. When these interactions occur faster than diffusion the resulting transport can be characterized by "effective diffusion coefficients" that depend on both the reaction rates and the "free" diffusion coefficients. Fluorescence correlation spectroscopy (FCS) gives information on effective rather than free diffusion coefficients under this condition. In the present paper we investigate what coefficients can be drawn from FCS experiments for a wide range of values of the ratio of reaction to diffusion time scales, using different fitting functions. We find that the effective coefficients can be inferred with relatively small errors even when the condition of fast reactions does not exactly hold. Since the diffusion time scale depends on the size of the observation volume and the reaction time scale depends on concentrations, we also discuss how by changing either one or the other property one can switch between the two limits and extract more information on the system under study.