43 research outputs found

    E. coli chemotaxis is information-limited

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    Organisms must acquire and use environmental information to guide their behaviors. However, it is unclear whether and how information quantitatively limits behavioral performance. Here, we relate information to behavioral performance in Escherichia coli chemotaxis. First, we derive a theoretical limit for the maximum achievable gradient-climbing speed given a cell's information acquisition rate. Next, we measure cells' gradient-climbing speeds and the rate of information acquisition by the chemotaxis pathway. We find that E. coli make behavioral decisions with much less than the 1 bit required to determine whether they are swimming up-gradient. However, they use this information efficiently, performing near the theoretical limit. Thus, information can limit organisms' performance, and sensory-motor pathways may have evolved to efficiently use information from the environment.Comment: 17 pages of main text, 3 main text figures, 66 pages of supplementary text, 10 supplementary figure

    Parallel imaging of Drosophila embryos for quantitative analysis of genetic perturbations of the Ras pathway

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    The Ras pathway patterns the poles of the Drosophila embryo by downregulating the levels and activity of a DNA-binding transcriptional repressor Capicua (Cic). We demonstrate that the spatiotemporal pattern of Cic during this signaling event can be harnessed for functional studies of mutations in the Ras pathway in human diseases. Our approach relies on a new microfluidic device that enables parallel imaging of Cic dynamics in dozens of live embryos. We found that although the pattern of Cic in early embryos is complex, it can be accurately approximated by a product of one spatial profile and one time-dependent amplitude. Analysis of these functions of space and time alone reveals the differential effects of mutations within the Ras pathway. Given the highly conserved nature of Ras-dependent control of Cic, our approach provides new opportunities for functional analysis of multiple sequence variants from developmental abnormalities and cancers

    Spatial Self-Organization Resolves Conflicts Between Individuality and Collective Migration

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    Files containing data for each figure of the paper in MATLAB .fig file format from which the data points can be extracted. <br
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