Efficient Simulation and Parametrization of Stochastic Petri Nets in SystemC: A Case study from Systems Biology

Stochastic Petri nets (SPN) are a form of Petri net where the transitions fire after a probabilistic and randomly determined delay. They are adopted in a wide range of appli- cations thanks to their capability of incorporating randomness in the models and taking into account possible fluctuations and environmental noise. In Systems Biology, they are becoming a reference formalism to model metabolic networks, in which the noise due to molecule interactions in the environment plays a crucial role. Some frameworks have been proposed to implement and dynamically simulate SPN. Nevertheless, they do not allow for automatic model parametrization, which is a crucial task to identify the network configurations that lead the model to satisfy temporal properties of the model. This paper presents a framework that synthesizes the SPN models into SystemC code. The framework allows the user to formally define the network properties to be observed and to automatically extrapolate, thorough Assertion-based Verification (ABV), the parameter configurations that lead the network to satisfy such properties. We applied the framework to implement and simulate a complex biological network, i.e., the purine metabolism, with the aim of reproducing the metabolomics data obtained in-vitro from naive lymphocytes and autoreactive T cells implicated in the induction of experimental autoimmune disorders

Computational Techniques for the Structural and Dynamic Analysis of Biological Networks

The analysis of biological systems involves the study of networks from different omics such as genomics, transcriptomics, metabolomics and proteomics. In general, the computational techniques used in the analysis of biological networks can be divided into those that perform (i) structural analysis, (ii) dynamic analysis of structural prop- erties and (iii) dynamic simulation. Structural analysis is related to the study of the topology or stoichiometry of the biological network such as important nodes of the net- work, network motifs and the analysis of the flux distribution within the network. Dy- namic analysis of structural properties, generally, takes advantage from the availability of interaction and expression datasets in order to analyze the structural properties of a biological network in different conditions or time points. Dynamic simulation is useful to study those changes of the biological system in time that cannot be derived from a structural analysis because it is required to have additional information on the dynamics of the system. This thesis addresses each of these topics proposing three computational techniques useful to study different types of biological networks in which the structural and dynamic analysis is crucial to answer to specific biological questions. In particu- lar, the thesis proposes computational techniques for the analysis of the network motifs of a biological network through the design of heuristics useful to efficiently solve the subgraph isomorphism problem, the construction of a new analysis workflow able to integrate interaction and expression datasets to extract information about the chromo- somal connectivity of miRNA-mRNA interaction networks and, finally, the design of a methodology that applies techniques coming from the Electronic Design Automation (EDA) field that allows the dynamic simulation of biochemical interaction networks and the parameter estimation

Petri nets for modelling metabolic pathways: a survey

In the last 15 years, several research efforts have been directed towards the representation and the analysis of metabolic pathways by using Petri nets. The goal of this paper is twofold. First, we discuss how the knowledge about metabolic pathways can be represented with Petri nets. We point out the main problems that arise in the construction of a Petri net model of a metabolic pathway and we outline some solutions proposed in the literature. Second, we present a comprehensive review of recent research on this topic, in order to assess the maturity of the field and the availability of a methodology for modelling a metabolic pathway by a corresponding Petri net

Méthodes systémiques d'analyse des données de simulation de modèles de voies de signalisation cellulaire

Les réseaux de pétri, un outil de modélisation polyvalent -- Une approche systémique en biologie moléculaire : le génie à la rencontre de la biologie -- Démarche de l'ensemble du travail de recherche et organisation générale du document -- Functional abstraction and spectral representation to visualize the system dynamics and the information flux in a biochemical model -- Petri net-based visualization of signal transduction pathway simulations -- Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways

Systemic Lupus Erythematosus

This book provides a comprehensive overview of the basic and clinical sciences of Systemic Lupus Erythematosus. It is suitable for basic scientists looking for detailed coverage of their areas of interest. It describes how advances in molecular biology have increased our understanding of this disease. It is a valuable clinical resource for practicing clinicians from different disciplines including rheumatologists, rheumatology fellows and residents. This book provides convenient access to information you need about cytokines, genetics, Fas pathway, toll like receptors and atherogenesis in SLE. Animal models have been reviewed as well. How to avoid delay in SLE diagnosis and management, in addition to various clinical manifestations including pregnancy and SLE have all been explained thoroughly in this book

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

This work was supported by the National Institute of General Medical Sciences [GM131919].In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.PostprintPeer reviewe

Insights into the opportunistic fungal pathogen Cryptococcus and neutrophilic inflammation using zebrafish models

The innate immunity provides the first line of defence against infection and inflammation. Zebrafish are a proven model for understanding the in vivo biology of infection and immunity. Here I describe how I have developed and used zebrafish models to understand three different aspects of infection and immunity: 1) The development and use of a zebrafish model of the human fungal infection Cryptococcus neoformans 2) Understanding the virulence of the hypervirulent Cryptococcus gattii and 3) The mechanisms of action of the immunosuppressive drug mycophenolate mofetil (MMF). I have established an innate in vivo model for macrophage response to Cryptococcus by injecting cryptococci into zebrafish embryos. I have developed a high-content imaging method in a zebrafish model of cryptococcosis. This approach enabled me the discovery that while macrophages are critical for control of C. neoformans, a failure of macrophage response is not the limiting defect in fatal infections. I found that phagocytosis is inhibited early in infection and that increases in cryptococcal number are driven by intracellular proliferation. Moreover, macrophages favourably phagocytose cryptococci with smaller polysaccharide capsules and that capsule size is greatly increased over twenty-four hours of infection, a change that is sufficient to severely limit further phagocytosis. I then used the zebrafish model of cryptococcosis to determine the virulence of C. gattii. I have identified a mutant in the hyper virulent strain R265 that is attenuated in vivo. The attenuation of the mutant, R265 GFP14 was further confirmed in a mouse model of infection. I analysed the interaction of macrophages and R265 GFP cryptococci in zebrafish and found that the transgenic R265 GFP was rapidly cleared. Whole genome sequences revealed that R265 GFP14 has 32 kb deletion in chromosome 1, resulting in the loss of six genes. R265 wild-type and R265 GFP14 were characterised for carbon sources utilisation. Finally, following up on colleagues’ use of my zebrafish model of cryptococcosis, I investigated the action of MMF on neutrophilic inflammation. I showed that MMF treatment resulted in neutrophil cell death by apoptosis in vivo, thereby reducing neutrophilic inflammation. Thus in this thesis, I demonstrate how I combined the study of infection and immunity to better understand diseases that cause the biggest disease burden in humans. I pioneered novel approaches to studying cryptococcosis using an experimental zebrafish model, which demonstrated for the first time how the early interactions with macrophages determined the outcome of infection. I subsequently used my model to study the virulence of an emerging pathogen, Vancouver strain R265 of C. gattii, identifying a genome region that may be important for virulence. Finally, from my cryptococcosis model a new mechanism for the immunosuppressant mycophenolate mofetil was identified in macrophages. Using my expertise in neutrophilic inflammation I was able to show that there was a second mechanism in neutrophils and this may explain the usefulness of this drug in treating chronic inflammation