bioRxiv Science⌕ Search

Biology subjects

Kip, A.

Publications and source records attributed to Kip, A..

2 recordsLinked to original sources

Position-sensing established duringcompaction dictates cell fate in themammalian embryo

Precise patterning within the 3-dimensional context of tissues, organs and embryos implies that cells can sense their relative position. We still understand relatively little about how cells sense their relative position within small groups of cells. During preimplantation development, outside and inside cells rely on apicobasal polarity and the Hippo pathway to choose their fate. Despite recent findings suggesting that mechanosensing may be central to this process, the relationship between blastomere geometry (i.e. shape and position) and the Hippo pathway effector YAP remains unknown. To address this, we used a highly quantitative approach to collect and analyse information on the geometry and YAP localisation of individual blastomeres of mouse and human embryos. We find that the fraction of YAP in the nucleus responds to the proportion of exposed cell surface area rather than blastomere shape. To directly test the influence of blastomere position on YAP localisation we developed an approach using hydrogel based cylindrical cavities to alter blastomere arrangement in cultured embryos. Unbiased clustering analyses of blastomeres from such embryos reveal that the ability to respond to position emerges as early as the 8-cell stage during compaction and that altering the relative position of a blastomere within an embryo can alter its fate. Finally, we demonstrate that this response is lost upon inhibiting PKC signalling, linking it to the cell polarity. Our results pinpoint when during early embryogenesis cell specification decisions are initiated and show how blastomeres can sense their position in a polarity dependent manner to alter YAP localisation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/856161v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@845b46org.highwire.dtl.DTLVardef@18473ceorg.highwire.dtl.DTLVardef@cf0124org.highwire.dtl.DTLVardef@53fc8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Spatial protein analysis in developing tissues: a sampling-based image processing approach

Advances in fluorescence microscopy approaches have made it relatively easy to generate multi-dimensional image volumes and have highlighted the need for flexible image analysis tools for the extraction of quantitative information from such data. Here we demonstrate that by focusing on simplified feature-based nuclear segmentation and probabilistic cytoplasmic detection we can create a tool that is able to extract geometry based information from diverse mammalian tissue images. Our open-source image analysis platform, called SilentMark can cope with noisy images and with crowded fields of cells to quantify signal intensity in different cellular compartments. Additionally, it provides tissue geometry related information, which allows one to quantify protein distribution with respect to marked regions of interest. The lightweight SilentMark algorithms have the advantage of not requiring multiple processors and graphics cards and can be run even with just several hundred MB of memory. This makes it possible to use the method as a web application, effectively eliminating setup hurdles and compatibility issues with operating systems. We test this platform on mouse pre-implantation embryos, embryonic stem cell derived embryoid bodies and mouse embryonic heart and relate protein localisation to tissue geometry.

developmental biology↗