Logical modelling of cellular decision processes with GINsim

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Logical modelling of mesoderm differentiation in Drosophila melanogaster

Au cours des dernières décennies, les approches expérimentales nous ont permis d'obtenir des informations importantes en biologie du développement et nous ont conduit à la définition de réseaux complexes de régulation contrôlant les processus développementaux. Actuellement, notre compréhension de ces réseaux est entravée par leur complexité même. La modélisation mathématique est de plus en plus utilisée pour intégrer les voies de régulation et prévoir les effets de perturbations génétiques. Durant ma thèse, je me suis intéressée à la différentiation du mésoderme chez Drosophila melanogaster. Elle commence par la spécification du mésoderme en 4 différents tissus: le muscle viscéral, le coeur, le muscle somatique et le corps gras. La formation de ces tissus se traduit par une organisation segmentale répétitive le long du mésoderme. Mon premier but était de construire un modèle qui récapitule la spécification de ces quatre tissus entre les stades 8 et 10. Par la suite, je me suis concentrée sur le développement du coeur dans le but de proposer un modèle de régulation de la diversification des cellules cardiaques contractiles (cardioblastes) entre les stade 10 et 12. Afin de comprendre ces processus complémentaires, j'ai été amené à modéliser les voies de signalisation qui jouent un rôle important dans le développement du mésoderme et des cardioblastes. Je me suis appuyée sur des données génétiques et des analyses haut-débit publiées (HhIP-chip, ChIP-seq et transcriptome) pour déterminer et annoter des graphes de régulation complet pour chacun de ces réseaux ou voies.During the past decades, experimental approaches have allowed us to gain important insights in developmental biology, and led to the delineation of complex regulatory networks controlling developmental processes. Currently, our understanding of these networks is hindered by their sheer complexity. Mathematical modelling is increasingly used to integrate regulatory pathways and predict the effects of genetic perturbations. My thesis focuses on the development of the specification of the mesoderm in Drosophila melanogaster. Its development results in the formation of different tissues segmentally iterated: the visceral muscle, the heart, the somatic muscle, and the fat body. My first goal was to build a network model recapitulating the specification of these 4 mesodermal tissues during stages 8 to 10. Then, focusing on heart development, my second aim was to build a network model recapitulating contractile cardiac cell (cardioblast) diversification during stages 10 to 12. To understand these complementary processes, I was further led to model the signalling pathways that play important roles in mesoderm and cardioblast development. I rely on a combination of published genetic data and high- throughput analyses (ChIP-chip, ChiP-seq, transcriptome) to delineate and annotate comprehensive regulatory graphs for each of these networks or pathways. Using a logical formalism and the GINsim software, I have further defined logical rules enabling the simulation of wild type and mutant behaviours for each of this networks or pathways. By and large, my model simulations recapitulate all relevant published data

Logical modelling of Drosophila signalling pathways

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Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes

International audienceGiven the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions

In situ RNA staining for two sets of single and double mutants.

<p><b>A:</b> Slp lof and Med lof each results in a perturbation of H. The double mutant displays an even stronger disruption of H, along with a clear expansion of Srp expression. These experimental results are largely consistent with our model predictions and further provide interpretational clues regarding mixed expression patterns. <b>B:</b> Slp gof exhibits a loss of VM, while FB appears perturbed in both Doc gof and Slp gof mutants. The combination of these perturbations leads to stronger losses of FB and VM, while H and SM are barely affected. These results qualitatively agree with model predictions.</p

Regulatory graph for the signalling/transcriptional network controlling drosophila mesoderm specification.

<p>Built with the software GINsim, this regulatory graph encompasses the main regulatory factors and interactions involved in mesoderm specification (stages 8–10), as documented by published (molecular) genetic and functional genomic data. Ellipses denote Boolean nodes, whereas rectangles denote multilevel nodes. Light green filling denotes input nodes, most corresponding to factors expressed in and acting from the ectoderm. Yellow filling denotes output factors, mostly effector genes and tissue markers. Blue or grey filling denotes internal nodes expressed in the mesoderm. Green arrows and red blunt arrows denote activations and inhibitions, respectively. Logical rules are further associated with each node to define its behaviour depending on regulatory inputs (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005073#pcbi.1005073.s006" target="_blank">S1 Table</a>). To ease the dynamical analysis of this regulatory graph, we performed a reduction of this regulatory graph (cf. Material and methods), making implicit the twelve grey components. This logical model is provided as supporting data, including comprehensive annotations and bibliographical references.</p

Key signalling pathways and markers genes involved in mesoderm specification.

<p>A, B: In situ hybridizations for Tin and Bin during mesoderm specification at stages 8 and 9–10. Tin is implicated in the formation of VM and H, while Bin participates only in the development of VM. Initially, the expression of Tin is mainly due to Twist activation. Later, Tin expression needs the presence of Dpp, Tin itself, in combination with Pan. C: Graphical representations of the main pathways activated by signals coming from the ectoderm, encompassing target transcription factors and cross-regulations underlying the specification of VM, H, FB and SM. In the absence of these factors, these tissues do not form or are severely reduced. Black and light grey arcs denote active and inactive regulations, depending on stage or tissue. Normal and blunt end arrows denote activations and inhibitions, respectively.</p

Early stages of drosophila mesoderm specification.

<p><b>A-C:</b> Schematic description of the establishment of mesoderm anterior-posterior and dorsal-ventral patterning. At stage 8, the presumptive mesoderm is largely homogeneous. At stage 9, ectodermal signals outline a characteristic pattern, with stripes of Hh, Eve and En alternating with stripes of Wg and Slp, which delimit anterior/posterior segmental borders, respectively. Dpp signalling further delimits dorsal versus ventral mesoderm domains. Mesoderm specification is achieved at stage 10, when Wg/Slp domains give rise to heart precursors (H, in red, dorsally located) and somatic muscles (SM, orange, ventrally located), whereas En/Eve/Hh domains give rise to visceral mesoderm (VM, blue, dorsal) and fat body (FB, green, ventral). <b>D:</b> Schematic representation of the four main tissues originating from the mesoderm in each segment, with key associated markers (e.g. Srp expression for FB).</p

Systematic simulations of double mutants.

<p>This matrix displays the results of systematic perturbations. Loss- and gain-of-function mutations (rows and column) were simulated iteratively using a set of Python scripts, along with pairwise combinations (cf. Material and methods). The results of the simulations of single mutants are displayed on the diagonal of the matrix. The predicted phenotype for each double mutant is shown at the intersection of the corresponding column and row. Note that the cells corresponding to the crossing of a lof and a gof for the same gene are left empty. Simulation results are graphically depicted using vignettes as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005073#pcbi.1005073.g004" target="_blank">Fig 4</a>, with specific colours denoting situations with miss-expressed genes (cf. colour key top right). This presentation eases the comparison of the results of multiple mutant simulations and enables the identification of dominant or synergic effects. This matrix encompasses numerous predictions, along with a few dozens of documented phenotypes. The web version of the matrix (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005073#pcbi.1005073.s008" target="_blank">S2 File</a>) further provides access to detailed information regarding the predicted patterns of expression for each mutant in each region. We have selected six perturbations (four single and two double ones, surrounded by tick squares in the matrix) for experimental validation (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005073#pcbi.1005073.g006" target="_blank">Fig 6</a>).</p