Instantaneous cell migration velocity may be ill-defined

Cell crawling is critical to biological development, homeostasis and disease. In many cases, cell trajectories are quasi-random-walk. In vitro assays on flat surfaces often described such quasi-random-walk cell trajectories as approximations to a solution of a Langevin process. However, experiments show quasi-diffusive behavior at small timescales, indicating that instantaneous velocity and velocity autocorrelations are not well-defined. We propose to characterize mean-squared cell displacement using a modified F\"urth equation with three temporal and spatial regimes: short- and long-time/range diffusion and intermediate time/range ballistic motion. This analysis collapses mean-squared displacements of previously published experimental data onto a single-parameter family of curves, allowing direct comparison between movement in different cell types, and between experiments and numerical simulations. Our method also show that robust cell-motility quantification requires an experiment with a maximum interval between images of a few percent of the cell-motion persistence time or less, and a duration of a few orders-of-magnitude longer than the cell-motion persistence time or more.Comment: 5 pages, plus Supplemental materia

Redes de neurônios

In the last ten years many scientific advances regarding neurons and the way they are interconnected has mad o it possible to study the dynamics of storage and Processing of information in the brain. In particular, the physicist J. J. Hopfield proposed a formal minimalist model to these neural networks reducing the problem to a particular case of a well – defined physical problem – the spin glass. Although the problem í s well defined, its solution is far from being trivial.Here we introduce the problem, describe Hopfield model, with its achievements and limitations, and present our contribution to the description of information storage in neural networks.Na última década várias descobertas em relação a neurônios e á maneira como estão interconectados, formando redes, possibilitaram o estudo da dinâmica do armazenamento e processamento de informação pelo cérebro. Em particular, o físico J. J. Hopfield propôs um modelo formal, minimalista para estas redes neuronais, reduzindo o problema a um caso particular de um sistema físico bem definido - o vidro de spin. Embora o problema esteja bem definido, sua solução está longe de ser trivial.Neste texto nós introduzimos o problema, descrevemos o modelo de Hopfield com seus resultados e limitações e apresentamos nossa contribuição para a descrição do armazenamento da informação em redes de neurônios

Geometrical distribution of Cryptococcus neoformans mediates flower-like biofilm development

Microbial biofilms are highly structured and dynamic communities in which phenotypic diversification allows microorganisms to adapt to different environments under distinct conditions. The environmentally ubiquitous pathogen Cryptococcus neoformans colonizes many niches of the human body and implanted medical devices in the form of biofilms, an important virulence factor. A new approach was used to characterize the underlying geometrical distribution of C. neoformans cells during the adhesion stage of biofilm formation. Geometrical aspects of adhered cells were calculated from the Delaunay triangulation and Voronoi diagramobtained fromscanning electronmicroscopy images (SEM). A correlation between increased biofilm formation and higher ordering of the underlying cell distribution was found. Mature biofilm aggregates were analyzed by applying an adapted protocol developed for ultrastructure visualization of cryptococcal cells by SEM. Flower-like clusters consisting of cells embedded in a dense layer of extracellular matrix were observed as well as distinct levels of spatial organization: adhered cells, clusters of cells and community of clusters. The results add insights into yeast motility during the dispersion stage of biofilm formation. This study highlights the importance of cellular organization for biofilm growth and presents a novel application of the geometrical method of analysis

Shape-velocity correlation defines polarization in migrating cell simulations

Cell migration plays essential roles in development, wound healing, diseases, and in the maintenance of a complex body. Experiments in collective cell migration generally measure quantities such as cell displacement and velocity. The observed short-time diffusion regime for mean square displacement in single-cell migration experiments on flat surfaces calls into question the definition of cell velocity and the measurement protocol. Theoretical results in stochastic modeling for single-cell migration have shown that this fast diffusive regime is explained by a white noise acting on displacement on the direction perpendicular to the migrating cell polarization axis (not on velocity). The prediction is that only the component of velocity parallel to the polarization axis is a well-defined quantity, with a robust measurement protocol. Here, we ask whether we can find a definition of a migrating-cell polarization that is able to predict the cell's subsequent displacement, based on measurements of its shape. Supported by experimental evidence that cell nucleus lags behind the cell center of mass in a migrating cell, we propose a robust parametrization for cell migration where the distance between cell nucleus and the cell's center of mass defines cell shape polarization. We tested the proposed methods by applying to a simulation model for three-dimensional cells performed in the CompuCell3D environment, previously shown to reproduce biological cells kinematics migrating on a flat surface

Growth laws and self-similar growth regimes of coarsening two-dimensional foams: Transition from dry to wet limits

We study the topology and geometry of two dimensional coarsening foams with arbitrary liquid fraction. To interpolate between the dry limit described by von Neumann's law, and the wet limit described by Marqusee equation, the relevant bubble characteristics are the Plateau border radius and a new variable, the effective number of sides. We propose an equation for the individual bubble growth rate as the weighted sum of the growth through bubble-bubble interfaces and through bubble-Plateau borders interfaces. The resulting prediction is successfully tested, without adjustable parameter, using extensive bidimensional Potts model simulations. Simulations also show that a selfsimilar growth regime is observed at any liquid fraction and determine how the average size growth exponent, side number distribution and relative size distribution interpolate between the extreme limits. Applications include concentrated emulsions, grains in polycrystals and other domains with coarsening driven by curvature

Epigenetic reprogramming by TET enzymes impacts co-transcriptional R-loops

PTDC/BIA-MOL/30438/2017 PTDC/MED-OUT/4301/2020 RiboMed 857119 PD/BD/128292/2017 LCF/PR/HP21/52310016 PTDC/BIA-MOL/6624/2020 PTDC/MED-ONC/7864/2020DNA oxidation by ten-eleven translocation (TET) family enzymes is essential for epigenetic reprogramming. The conversion of 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) initiates developmental and cell-type-specific transcriptional programs through mechanisms that include changes in the chromatin structure. Here, we show that the presence of 5hmC in the transcribed gene promotes the annealing of the nascent RNA to the template DNA strand, leading to the formation of an R-loop. Depletion of TET enzymes reduced global R-loops in the absence of gene expression changes, whereas CRISPR-mediated tethering of TET to an active gene promoted the formation of R-loops. The genome-wide distribution of 5hmC and R-loops shows a positive correlation in mouse and human stem cells and overlap in half of all active genes. Moreover, R-loop resolution leads to differential expression of a subset of genes that are involved in crucial events during stem cell proliferation. Altogether, our data reveal that epigenetic reprogramming via TET activity promotes co-transcriptional R-loop formation, disclosing new mechanisms of gene expression regulation.publishersversionpublishe