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Plunder, S.

Publications and source records attributed to Plunder, S..

6 recordsLinked to original sources

Self-organized fingering instabilities drive the emergence of tissue morphogenesis in digit organoids.

The emergence of complex anatomical structures -such as the hands- from unstructured tissues remains a fundamental question in developmental biology. Turing-type reaction-diffusion models have provided a molecular explanation for the periodic pre-patterning of digits; however, the physical principles driving 3D morphogenesis remain incompletely understood. To identify the biophysical design principles leading to digit formation, we develop a limb-mesenchymal organoid system that spontaneously forms elongated, digit-like protrusions. Iterations between experiments and agent-based models at the cellular level identify sufficient microscopic mechanisms leading to morphogenesis of digit-like structures: symmetry-breaking and the elongation of digits result from a combination of differential cell adhesion and morphogen-induced chemotaxis and convergent-extension. Lastly, to describe tissue-scale deformations, we perform a coarse-graining analysis of the agent-based model and derive a continuum model that reveals a structural analogy to Cahn-Hilliard-type equations. These equations are typically used to describe fluid phase separation and so-called ''fingering instabilities'' in fluid physics. Here, we show that they also accurately describe organoid morphogenesis. These findings suggest that ''finger'' formation is driven by a mechanical fingering instability acting in concert with chemical patterning, shedding a new light on vertebrate limb morphogenesis.

developmental biology↗

Boundary-guided cell alignment drives mouse epiblast maturation

Symmetry breaking and pattern formation are critical events that occur throughout embryonic development. In early mouse development, a mass of non-polarized epiblast (EPI) cells in the blastocyst forms the egg-cylinder, while cells become apico-basally polarized and build a radial configuration. Yet, what drives the formation of this tissue architecture remains unclear. Here, we demonstrate that orientational patterning of EPI cells is dictated by heterogeneous tissue boundaries, which then defines central lumen positioning. We show that EPI cells progressively orient perpendicular to the visceral endoderm (VE) boundary enriched with laminin and active integrin {beta}1, but parallel to the extraembryonic ectoderm interface. These orientation dynamics are consistent with general boundary-induced alignment effects in polar materials, with a topological defect predicting the position where the pro-amniotic cavity nucleates. Knockout of laminin {gamma}1 and integrin {beta}1 confirms the essential role of adhesion at the EPI-VE-boundary. The established EPI pattern, in turn, facilitates ERK activation to ensure proper EPI maturation. Together, these findings present the mechanistic basis and functional significance of EPI tissue patterning.

developmental biology↗

The directionality of collective cell delamination is governed by tissue architecture and cell adhesion in a Drosophila carcinoma model

Carcinomas originate in epithelia and are the most frequent type of cancers. Tumor progression starts with the collective delamination of live tumors out of the epithelium, and requires modulation of cell adhesion. Yet, it remains elusive exactly how remodeling of epithelial cell-cell and cell-extracellular matrix contacts contribute to metastasis onset and delamination directionality. We used Drosophila melanogaster larval eye disc to study cooperative oncogenesis and determine the contribution of bi- and tricellular septate junction (SJ) components to tumor progression in flat and pseudostratified epithelia. We reveal that loss-of-function of septate junction components alone can promote cell death whereas synergic interaction with oncogenic Ras triggers the collective delamination of living tumorigenic cells. Spatiotemporal analyses reveal apical and basal delamination processes differ in terms of cell identity, cell polarity and remodeling of cell-cell and cell-ECM contacts. Using a combination of in vivo and in silico approaches, we report that SJ-depleted RasV12 tumors in pseudostratified epithelia trigger tissue folding or basal collective delamination regardless of the order in which cell contacts are remodeled. In striking contrast, SJ-depleted RasV12 tumors formed in flat, squamous epithelia, first undergo apical constriction and acquire a dome-like shape. Tumors are enriched in adhesion molecules and form an apical neck at the interface of contact between mutant cells and wild-type neighbors. Concomitant to cytoskeleton remodeling, tumors emit apical protrusions in the lumen and progressively delaminate through the apical neck while remaining cohesive. Our study reveals that tissue architecture and changes in cell adhesion drive the directionality of collective delamination of neoplastic tumors out of an epithelium.

developmental biology↗

Occurrence of non-apical mitoses at the primitive streak, induced by relaxation of actomyosin and acceleration of the cell cycle, contributes to cell delamination during mouse gastrulation.

During the epithelial-mesenchymal transition driving mouse embryo gastrulation, cells at the primitive streak divide more frequently that in the rest of the epiblast, and half of those divisions happen away from the apical pole. These observations suggests that non-apical mitoses might play a role in cell delamination and/or mesoderm specification. We aimed to uncover and challenge the molecular determinants of mitosis position in the different regions of the epiblast through a combination of computational modeling and pharmacological treatments of embryos. Blocking basement membrane degradation at the streak had no impact on the asymmetry in mitosis frequency and position. By contrast disturbance of actomyosin cytoskeleton or cell cycle dynamics elicited ectopic non-apical mitosis and showed that the streak region is characterized by local relaxation of the actomyosin cytoskeleton and less stringent regulation of cell division. These factors are essential for normal dynamics at the streak but are not sufficient to promote acquisition of mesoderm identity or ectopic cell delamination in the epiblast. Exit from the epithelium requires additional events, such as detachment from the basement membrane. Altogether, our data indicate that cell delamination at the streak is a morphogenetic process which results from a cooperation between EMT events and the local occurrence of non-apical mitoses driven by specific cell cycle and contractility parameters.

developmental biology↗

Modelling variability and heterogeneity of EMT scenarios highlights nuclear positioning and protrusions as main drivers of extrusion

Epithelial-Mesenchymal Transition (EMT) is a key process in physiological and pathological settings (i.e. development, fibrosis, cancer). EMT is often presented as a linear sequence of events including (i) disassembly of cell-cell junctions, (ii) loss of epithelial polarity and (iii) reorganization of the cytoskeleton leading to basal extrusion from the epithelium. Once out, cells can adopt a migratory phenotype with a front-rear polarity and may additionally become invasive. While this stereotyped sequence can occur, many in vivo observations have challenged this notion. It is now accepted that there are multiple EMT scenarios and that cell populations implementing EMT are often heterogeneous. However, the relative importance of each EMT step towards extrusion is unclear. Similarly, the overall impact of variability and heterogeneity on the efficiency and directionality of cell extrusion has not been assessed. Here we used computational modelling of a pseudostratified epithelium to model multiple EMT-like scenarios. We confronted these in silico data to the EMT occurring during neural crest delamination. Overall, our simulated and biological data point to a key role of nuclear positioning and protrusive activity to generate timely basal extrusion of cells and suggest a non-linear model of EMT allowing multiple scenarios to co-exist.

developmental biology↗

Identification of viral dose and administration time in simulated phage therapy occurrences

The rise in multidrug-resistant bacteria has sprung a renewed interest in applying phages as antibacterial, a procedure Western practitioners eventually abandoned due to several downfalls, including poor understanding of the dynamics between phages and bacteria. A successful phage therapy needs to account for the loss of infective virions and the multiplication of the hosts. The parameters critical inoculation size (VF) and failure threshold time (TF) have been introduced to assure that the viral dose (v{phi}) and administration time (t{phi}) would lead to an effective treatment. The problem with the definition of VF and TF is that they are non-linear equations with two unknowns; thus, their solution is cumbersome and not unique. The current study used machine learning in the form of a decision tree algorithm to determine ranges for the viral dose and administration times required to achieve an effective phage therapy. Within these ranges, a Pareto optimal solution of a multi-criterial optimization problem (MCOP) provides values leading to effective treatment. The algorithm was tested on a series of microbial consortia that described allochthonous invasions (the outgrowing of a species at high cell density by another species initially present at low concentration) to inhibit the growth of the invading species. The present study also introduced the concept of mediated phage therapy, where targeting a booster bacteria might decrease the virulence of a pathogen immune to phagial infection. The results demonstrated that the MCOP could provide pairs of v{phi} and t{phi} that could effectively wipe out the bacterial target from the considered micro-environment. In summary, the present work introduced a novel method for investigating the phage/bacteria interaction that could help increase the effectiveness of phage therapy. Author summaryPhage therapy is a treatment that can help fight infections with bacteria resistant to antibiotics. However, several phage therapy application have failed, possibly because phages were administered at the wrong time or in insufficient amounts. The present study implemented a machine learning protocol to correctly calculate the administration time and viral load to obtain effective phage therapy. Four simulated microbial consortia, including one case where the pathogen was not directly a phages host, were employed to prove the procedures concept. The results demonstrated that the procedure is suitable to help the microbiologists to instantiate an effective phage therapy and clear infections.

microbiology↗