Generation of Single-Cell Transcript Variability by Repression

Gene expression levels vary greatly within similar cells, even within clonal cell populations [1]. These spontaneous expression differences underlie cell fate diversity in both differentiation and disease [2]. The mechanisms responsible for generating expression variability are poorly understood. Using single-cell transcriptomics, we show that transcript variability emerging during Dictyostelium differentiation is driven predominantly by repression rather than activation. The increased variability of repressed genes was observed over a broad range of expression levels, indicating that variability is actively imposed and not a passive statistical effect of the reduced numbers of molecules accompanying repression. These findings can be explained by a simple model of transcript production, with expression controlled by the frequency, rather than the magnitude, of transcriptional firing events. Our study reveals that the generation of differences between cells can be a direct consequence of the basic mechanisms of transcriptional regulation

Multiple cell and population-level interactions with mouse embryonic stem cell heterogeneity

Much of development and disease concerns the generation of gene expression differences between related cells sharing similar niches. However, most analyses of gene expression only assess population and time-averaged levels of steady-state transcription. The mechanisms driving differentiation are buried within snapshots of the average cell, lacking dynamic information and the diverse regulatory history experienced by individual cells. Here, we use a quantitative imaging platform with large time series data sets to determine the regulation of developmental gene expression by cell cycle, lineage, motility and environment. We apply this technology to the regulation of the pluripotency gene Nanog in mouse embryonic stem cells. Our data reveal the diversity of cell and population-level interactions with Nanog dynamics and heterogeneity, and how this regulation responds to triggers of pluripotency. Cell cycles are highly heterogeneous and cycle time increases with Nanog reporter expression, with longer, more variable cycle times as cells approach ground-state pluripotency. Nanog reporter expression is highly stable over multiple cell generations, with fluctuations within cycles confined by an attractor state. Modelling reveals an environmental component to expression stability, in addition to any cell-autonomous behaviour, and we identify interactions of cell density with both cycle behaviour and Nanog. Rex1 expression dynamics showed shared and distinct regulatory effects. Overall, our observations of multiple partially overlapping dynamic heterogeneities imply complex cell and environmental regulation of pluripotent cell behaviour, and suggest simple deterministic views of stem cell states are inappropriate

Packing and Hausdorff measures of stable trees

In this paper we discuss Hausdorff and packing measures of random continuous trees called stable trees. Stable trees form a specific class of L\'evy trees (introduced by Le Gall and Le Jan in 1998) that contains Aldous's continuum random tree (1991) which corresponds to the Brownian case. We provide results for the whole stable trees and for their level sets that are the sets of points situated at a given distance from the root. We first show that there is no exact packing measure for levels sets. We also prove that non-Brownian stable trees and their level sets have no exact Hausdorff measure with regularly varying gauge function, which continues previous results from a joint work with J-F Le Gall (2006).Comment: 40 page

A recursive approach to the O(n) model on random maps via nested loops

We consider the O(n) loop model on tetravalent maps and show how to rephrase it into a model of bipartite maps without loops. This follows from a combinatorial decomposition that consists in cutting the O(n) model configurations along their loops so that each elementary piece is a map that may have arbitrary even face degrees. In the induced statistics, these maps are drawn according to a Boltzmann distribution whose parameters (the face weights) are determined by a fixed point condition. In particular, we show that the dense and dilute critical points of the O(n) model correspond to bipartite maps with large faces (i.e. whose degree distribution has a fat tail). The re-expression of the fixed point condition in terms of linear integral equations allows us to explore the phase diagram of the model. In particular, we determine this phase diagram exactly for the simplest version of the model where the loops are "rigid". Several generalizations of the model are discussed.Comment: 47 pages, 13 figures, final version (minor changes with v2 after proof corrections

Transition state dynamics during a stochastic fate choice

The generation of multiple fates from a uniform cell population via self-organisation is a recurring feature in development and regeneration. However, for most self-organising systems, we have little understanding of the processes that allow cells to become different. One of the clearest examples of developmental self-organisation is shown by Dictyostelium, with cells segregating into two major fates, stalk and spore, within multicellular aggregates. To characterise the gene expression decisions underlying this cell fate bifurcation, we carried out single cell transcriptomics on Dictyostelium aggregates. Our data show the transition of progenitors into prespore and prestalk cells occurs via distinct developmental intermediates. Few cells were captured switching between states, with minimal overlap in fate marker expression between cell types, suggesting states are discrete and transitions rapid. Surprisingly, fate-specific transcript dynamics were a small proportion of overall gene expression changes, with transcript divergence coinciding precisely with large scale remodelling of the transcriptome shared by prestalk and prespore cells. These observations suggest the stepwise separation of cell identity is temporally coupled to global expression transitions common to both fates

Quantitative screening of the effects of hyper-osmotic stress on cancer cells cultured in 2- or 3-dimensional settings

10.1038/s41598-019-50198-wScientific Reports911378

The fate of cells undergoing spontaneous DNA damage during development

Embryonic development involves extensive and often rapid cell proliferation. An unavoidable side effect of cell proliferation is DNA damage. The consequences of spontaneous DNA damage during development are not clear. Here we define an approach to determine the effects of DNA damage on cell fate choice. Using single cell transcriptomics, we identified a sub-population of Dictyostelium cells experiencing spontaneous DNA damage. Damaged cells displayed high expression of rad51, with the gene induced by multiple types of genotoxic stress. Using live imaging, we tracked high Rad51 cells from differentiation onset until cell fate assignment. High Rad51 cells were shed from multicellular structures, excluding damaged cells from the spore population. Cell shedding resulted from impaired cell motility and defective cell-cell adhesion, with damaged cells additionally defective in activation of spore gene expression. These data indicate DNA damage is not insulated from other aspects of cell physiology during development and multiple features of damaged cells prevent propagation of genetic error. Our approach is generally applicable for monitoring rare sub-populations during development, and permits analysis of developmental perturbations occurring within a physiological dynamic range

Matériels associés à l'utilisation des produits explosifs et aux dispositifs d'amorçage

Cet article rédigé par le sous-groupe Matériels associés du GFEE synthétise le travail qu'il a mené. Il a pour vocation d'apporter des compléments d'informations aux utilisateurs, aux responsables sécurité et aux donneurs d'ordre afin d'orienter les prescriptions d'utilisation de ces matériels

A combined microfluidic-transcriptomic approach to characterize the extravasation potential of cancer cells

10.18632/oncotarget.26306Oncotarget99036110-3612