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Torregrosa, G.

Publications and source records attributed to Torregrosa, G..

2 recordsLinked to original sources

Morphogenetic constrains in the development of gastruloids: implications for mouse gastrulation

Mammalian embryonic size is tightly controlled with checkpoints and compensatory mechanisms correcting size defects. Here, we take advantage of gastruloids, a stem cell embryoid system not subject to most size controls, to study the role of size in emergent properties of mammalian embryogenesis. We report that gastruloids exhibit robust morphology and transcriptional profiles within a size range. However, size affects the dynamics, and, outside a range of robust morphogenesis, the precision of anterior-posterior (AP) axial elongation. Gastruloid axial elongation exhibits active cellular contractility, requires planar cell polarity (PCP), adhesion and cell-cell contact remodelling. Smaller gastruloids initiate elongation earlier, correlated with an earlier Brachyury polarisation. Brachyury expression increases tissue fluidity. Axis formation is regulated by the balance of Brachyury multifoci coalescence and the timing of initiation of the elongation programme. Sizes beyond the robust range can modify relative tissue composition. Very small aggregates have increased neural fate bias, accompanied by a loss of paraxial mesoderm mediated by differences in Nodal signalling activity.

developmental biology↗

Single-cell Bayesian deconvolution

Individual cells exhibit substantial heterogeneity in protein abundance and activity, which is frequently reflected in broad distributions of fluorescently labeled reporters. Since all cellular components are intrinsically fluorescent to some extent, the observed distributions contain background noise that masks the natural heterogeneity of cellular populations. This limits our ability to characterize cell-fate decision processes that are key for development, immune response, tissue homeostasis, and many other biological functions. It is therefore important to separate the contributions from signal and noise in single-cell measurements. Addressing this issue rigorously requires deconvolving the noise distribution from the signal, but approaches in that direction are still limited. Here we present a non-parametric Bayesian formalism that performs such a deconvolution efficiently on multidimensional measurements, in a way that allows us to estimate confidence intervals. We use the approach to study the expression of the mesodermal transcription factor Brachyury in mouse embryonic stem cells undergoing differentiation.

developmental biology↗