A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis

In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease.Fil: Uriu, Koichiro. Kanazawa University; JapónFil: Bhavna, Rajasekaran. Max Planck Institute of Molecular Cell Biology and Genetics; Alemania. Max Planck Institute for the Physics of Complex Systems; AlemaniaFil: Oates, Andrew C.. Francis Crick Institute; Reino Unido. University College London; Reino UnidoFil: Morelli, Luis Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Max Planck Institute for Molecular Physiology; Alemania. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentin

Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions

Cell movement and intercellular signaling occur simultaneously during the development of tissues, but little is known about how movement affects signaling. Previous theoretical studies have shown that faster moving cells favor synchronization across a population of locally coupled genetic oscillators. An important assumption in these studies is that cells can immediately interact with their new neighbors after arriving at a new location. However, intercellular interactions in cellular systems may need some time to become fully established. How movement affects synchronization in this situation has not been examined. Here we develop a coupled phase oscillator model in which we consider cell movement and the gradual recovery of intercellular coupling experienced by a cell after movement, characterized by a moving rate and a coupling recovery rate respectively. We find (1) an optimal moving rate for synchronization, and (2) a critical moving rate above which achieving synchronization is not possible. These results indicate that the extent to which movement enhances synchrony is limited by a gradual recovery of coupling. These findings suggest that the ratio of time scales of movement and signaling recovery is critical for information transfer between moving cells.Comment: 18 single column pages + 1 table + 5 figures + Supporting Informatio

Genetic oscillators in development

In development, morphogenetic processes are strictly coordinated in time. Cells in a developing tissue would need mechanisms for time-keeping. One such time-keeping mechanism is to use oscillations of gene expression. Oscillatory gene expression can be generated by transcriptional/translational feedback loops, usually referred to as a genetic oscillator. In this review article, we discuss genetic oscillators in the presence of developmental processes such as cell division, cell movement and cell differentiation. We first introduce the gene regulatory network for generating a rhythm of gene expression. We then discuss how developmental processes influence genetic oscillators. Examples include vertebrate somitogenesis and neural progenitor cell differentiation, as well as the circadian clock for comparison. To understand the behaviors of genetic oscillators in development, it is necessary to consider both gene expression dynamics and cellular behaviors simultaneously. Theoretical modeling combined with live imaging at single-cell resolution will be a powerful tool to analyze genetic oscillators in development. In this review article, we discuss genetic oscillators in the presence of developmental processes such as cell division, cell movement and cell differentiation. We first introduce the gene regulatory network for generating a rhythm of gene expression. We then discuss how developmental processes influence genetic oscillators. © 2016 Japanese Society of Developmental Biologists

Experiences in Designing Technologies for Honoring Deceased Loved Ones

This article describes and reflects on the processes of designing two devices, Timecard and Fenestra, that both aim to propose new ideas for creating technologies that support rituals of honoring deceased loved ones. The discussion provides insight into how their respective designs were crafted to provide a range of interactions and to interweave with domestic practices, artifacts, and spaces; the article also describes the projects' similar strategies to supporting relationships with the deceased. Reflections then are offered about the design of future technologies aimed at supporting the processes both of adapting to the loss of loved ones and of honoring their continued evolving place in the lives of the living after they are gone

Object Segmentation and Ground Truth in 3D Embryonic Imaging

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets