Using mechanics in the modelling of meristem morphogenesis

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Flux-Based Transport Enhancement as a Plausible Unifying Mechanism for Auxin Transport in Meristem Development

Plants continuously generate new organs through the activity of populations of stem cells called meristems. The shoot apical meristem initiates leaves, flowers, and lateral meristems in highly ordered, spiralled, or whorled patterns via a process called phyllotaxis. It is commonly accepted that the active transport of the plant hormone auxin plays a major role in this process. Current hypotheses propose that cellular hormone transporters of the PIN family would create local auxin maxima at precise positions, which in turn would lead to organ initiation. To explain how auxin transporters could create hormone fluxes to distinct regions within the plant, different concepts have been proposed. A major hypothesis, canalization, proposes that the auxin transporters act by amplifying and stabilizing existing fluxes, which could be initiated, for example, by local diffusion. This convincingly explains the organised auxin fluxes during vein formation, but for the shoot apical meristem a second hypothesis was proposed, where the hormone would be systematically transported towards the areas with the highest concentrations. This implies the coexistence of two radically different mechanisms for PIN allocation in the membrane, one based on flux sensing and the other on local concentration sensing. Because these patterning processes require the interaction of hundreds of cells, it is impossible to estimate on a purely intuitive basis if a particular scenario is plausible or not. Therefore, computational modelling provides a powerful means to test this type of complex hypothesis. Here, using a dedicated computer simulation tool, we show that a flux-based polarization hypothesis is able to explain auxin transport at the shoot meristem as well, thus providing a unifying concept for the control of auxin distribution in the plant. Further experiments are now required to distinguish between flux-based polarization and other hypotheses

Using mechanics in the modelling of meristem morphogenesis

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STSE: Spatio-Temporal Simulation Environment Dedicated to Biology

<p>Abstract</p> <p>Background</p> <p>Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers.</p> <p>Results</p> <p>The Spatio-Temporal Simulation Environment (STSE) is a set of <it>open-source </it>tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to <it>digitize, represent, analyze</it>, and <it>mathematically model </it>spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from <url>http://www.stse-software.org/</url>. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We demonstrate it's usefulness using the example of a signaling cascade leading to formation of a morphological gradient of Fus3 within the cytoplasm of the mating yeast cell <it>Saccharomyces cerevisiae</it>.</p> <p>Conclusions</p> <p>STSE is an efficient and powerful novel platform, designed for computational handling and evaluation of microscopic images. It allows for an uninterrupted workflow including digitization, representation, analysis, and mathematical modeling. By providing the means to relate the simulation to the image data it allows for systematic, image driven model validation or rejection. STSE can be scripted and extended using the Python language. STSE should be considered rather as an API together with workflow guidelines and a collection of GUI tools than a stand alone application. The priority of the project is to provide an easy and intuitive way of extending and customizing software using the Python language.</p

Posttranscriptional Regulation of the Human LDL Receptor by the U2-Spliceosome

Background: The low-density lipoprotein receptor (LDLR) in the liver is the major determinant of LDL-cholesterol levels in human plasma. The discovery of genes that regulate the activity of LDLR helps to identify pathomechanisms of hypercholesterolemia and novel therapeutic targets against atherosclerotic cardiovascular disease.Methods: We performed a genome-wide RNA interference screen for genes limiting the uptake of fluorescent LDL into Huh-7 hepatocarcinoma cells. Top hit genes were validated by in vitro experiments as well as analyses of datasets on gene expression and variants in human populations.Results: The knockdown of 54 genes significantly inhibited LDL uptake. Fifteen of them encode for components or interactors of the U2-spliceosome. Knocking down any one of 11 out of 15 genes resulted in the selective retention of intron 3 of LDLR. The translated LDLR fragment lacks 88% of the full length LDLR and is detectable neither in non-transfected cells nor in human plasma. The hepatic expression of the intron 3 retention transcript is increased in non-alcoholic fatty liver disease as well as after bariatric surgery. Its expression in blood cells correlates with LDL-cholesterol and age. Single nucleotide polymorphisms and three rare variants of one spliceosome gene, RBM25, are associated with LDL-cholesterol in the population and familial hypercholesterolemia, respectively. Compared to overexpression of wild type RBM25, overexpression of the three rare RBM25 mutants in Huh-7 cells led to lower LDL uptake.Conclusions: We identified a novel mechanism of post-transcriptional regulation of LDLR activity in humans and associations of genetic variants of RBM25 with LDL-cholesterol levels.</p

Modelling development of shoot apical meristem of Arabidopsis

The research presented in this thesis uses computational techniques to heighten our comprehension of shoot apical meristem (SAM) development, and in particular the process of regular organ initiation, called phyllotaxis. This work is focused on the role of an essential plant hormone, auxin, in SAM development. In this thesis, I introduce an auxin-transport model of phyllotaxis at cellular scale, which is able to reproduce spiral phyllotaxis patterns observed in vivo. The auxin-transport is mediated by special membrane carrier molecules, called PIN proteins. The polarization of PIN inside of the cell is regulated by the flux of auxin, as it was suggested in the original canalization concept proposed by Tsvi Sachs. The proposed flux-based model reproduces PIN distribution observed in vivo both, in L1 meristem layer and as well in the rib zone of the meristem. Second part of the thesis is dedicated to the simulations of growth. In this part, I introduce the physical-based framework to simulate growth of the meristem including tropisms. Since auxin modifies rigidity of cell walls leading to an increase in growth rates in the spots of its high concentration, the introduced framework is used to upgrade auxin transport-based model of phyllotaxis. In this upgraded model the transport-based patterning mechanism directly modifies the growth directions of the meristem, allowing us to study the coupling of growth, auxin and PIN distributionsMONTPELLIER-BU Sciences (341722106) / SudocSudocFranceF

Modeling Dynamics of Cell-to-Cell Variability in TRAIL-Induced Apoptosis Explains Fractional Killing and Predicts Reversible Resistance

International audienceIsogenic cells sensing identical external signals can take markedly different decisions. Such decisions often correlate with pre-existing cell-to-cell differences in protein levels. When not neglected in signal transduction models, these differences are accounted for in a static manner, by assuming randomly distributed initial protein levels. However, this approach ignores the a priori non-trivial interplay between signal transduction and the source of this cell-to-cell variability: temporal fluctuations of protein levels in individual cells, driven by noisy synthesis and degradation. Thus, modeling protein fluctuations, rather than their consequences on the initial population heterogeneity, would set the quantitative analysis of signal transduction on firmer grounds. Adopting this dynamical view on cell-to-cell differences amounts to recast extrinsic variability into intrinsic noise. Here, we propose a generic approach to merge, in a systematic and principled manner, signal transduction models with stochastic protein turnover models. When applied to an established kinetic model of TRAIL-induced apoptosis, our approach markedly increased model prediction capabilities. One obtains a mechanistic explanation of yet-unexplained observations on fractional killing and non-trivial robust predictions of the temporal evolution of cell resistance to TRAIL in HeLa cells. Our results provide an alternative explanation to survival via induction of survival pathways since no TRAIL-induced regulations are needed and suggest that short-lived anti-apoptotic protein Mcl1 exhibit large and rare fluctuations. More generally, our results highlight the importance of accounting for stochastic protein turnover to quantitatively understand signal transduction over extended durations, and imply that fluctuations of short-lived proteins deserve particular attention