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Portero Migueles, R.

Publications and source records attributed to Portero Migueles, R..

3 recordsLinked to original sources

A toolkit for mapping cell identities in relation to neighbours reveals Notch-dependent heterogeneity within neuromesodermal progenitor populations

Patterning of cell fates is central to embryonic development, tissue homeostasis, and disease. Quantitative analysis of patterning reveals the logic by which cell-cell interactions orchestrate changes in cell fate. However, it is challenging to quantify patterning when graded changes in identity occur over complex 4D trajectories, or where different cell states are intermingled. Furthermore, comparing patterns across multiple individual embryos, tissues, or organoids is difficult because these often vary in shape and size. Here we present a toolkit of computational approaches to tackle these problems. These strategies are based on measuring properties of each cell in relation to the properties of its neighbours to quantify patterning, and on using embryonic landmarks in order to compare these patterns between embryos. We use this toolkit to characterise patterning of cell identities within the caudal lateral epiblast of E8.5 embryos, revealing local patterning in emergence of early mesoderm cells that is sensitive to inhibition of Notch activity.

developmental biology↗

SyNPL: Synthetic Notch pluripotent cell lines to monitor and manipulate cell interactions in vitro and in vivo.

Cell-cell interactions govern differentiation and cell competition in pluripotent cells during early development, but the investigation of such processes is hindered by a lack of efficient analysis tools. Here we introduce SyNPL: clonal pluripotent stem cell lines which employ optimised Synthetic Notch (SynNotch) technology to report cell-cell interactions between engineered "sender" and "receiver" cells in cultured pluripotent cells and chimaeric mouse embryos. A modular design makes it straightforward to adapt the system for programming differentiation decisions non-cell-autonomously in receiver cells in response to direct contact with sender cells. We demonstrate the utility of this system by enforcing neuronal differentiation at the boundary between two cell populations. In summary, we provide a new tool which could be used to identify cell interactions and to profile changes in gene or protein expression that result from direct cell-cell contact with defined cell populations in culture and in early embryos, and which can be adapted to generate synthetic patterning of cell fate decisions. SUMMARY STATEMENTOptimised Synthetic Notch circuitry in mouse pluripotent stem cells provides a modular tool to monitor cell-cell interactions and program synthetic patterning of cell fates in culture and in embryos.

developmental biology↗

Nessys: a novel method for accurate nuclear segmentation in 3D

Methods for measuring the properties of individual cells within their native 3D environment will enable a deeper understanding of embryonic development, tissue regeneration, and tumorigenesis. However current methods for segmenting nuclei in 3D tissues are not designed for situations where nuclei are densely packed, non-spherical, heterogeneous in shape, size, or texture, all of which are true of many embryonic and adult tissue types as well as in many cases for cells differentiating in culture.\n\nHere we overcome this bottleneck by devising a novel method based on labelling the nuclear envelope (NE) and automatically distinguishing individual nuclei using a tree structured ridge tracing method followed by shape ranking according to a trained classifier. The method is fast and makes it possible to process images that are larger than the computers memory. We consistently obtain accurate segmentation rates of >90% even for challenging images such as mid-gestation embryos or 3D cultures. We provide a 3D editor and inspector for the manual curation of the segmentation results as well as a program to assess the accuracy of the segmentation.\n\nWe have also generated a live reporter of the NE that can be used to track live cells in three dimensions over time. We use this to monitor the history of cell interactions and occurrences of neighbour exchange within cultures of pluripotent cells during differentiation.\n\nWe provide these tools in an open-access user-friendly format.

developmental biology↗