An Approach to the Engineering of Cellular Models Based on P Systems

Living cells assembled into colonies or tissues communicate using complex systems. These systems consist in the interaction between many molecular species distributed over many compartments. Among the different cellular processes used by cells to monitor their environment and respond accordingly, gene regulatory networks, rather than individual genes, are responsible for the information processing and orchestration of the appropriate response [16]. In this respect, synthetic biology has emerged recently as a novel discipline aiming at unravelling the design principles in gene regulatory systems by synthetically engineering transcriptional networks which perform a specific and prefixed task [2]. Formal modelling and analysis are key methodologies used in the field to engineer, assess and compare different genetic designs or devices. In order to model cellular systems in colonies or tissues one requires a formalism able to represent the following relevant features: – Single cells should be described as the elementary units in the system. Nevertheless, they cannot be represented as homogeneous points as they exhibit complex structures containing different compartments where specific molecular species interact according to particular reactions. – The molecular interactions taking place in cellular systems are inherently discrete and stochastic processes. This is a key feature of cellular systems that needs to be taken into account when describing their dynamics [9]. – It has been postulated that gene regulatory networks are organised in a modular manner in such a way that cellular processes arise from the orchestrated interactions between different genetic transcriptional units that can be considered separable modules [1]. – Spatial and geometric information must be represented in the system in order to describe processes involving pattern formation. In this work we review recent advances in the use of the computational paradigm membrane computing or P systems as a formal methodology in synthetic biology for the specification and analysis on cellular system models according to the previously presented points

Discrete Solution of Differential Equations by P Metabolic Algorithm

The relationships existing between MP graphs, metabolic P systems, and ODE systems are investigated. Formal results show that every MP system, once derived by its MP graph, results in an ODE system whose solution equals, in the limit, the solution obtained by a non-cooperative MP system that is ODE equivalent to the original one. The freedom of choice of the ODE equivalent from the original MP system resembles the same freedom which is left in the choice and optimization of a numerical scheme while computing the solution of an ODE system

On Modeling Signal Transduction Networks

Signal transduction networks are very complex processes employed by the living cell to suitably react to environmental stimuli. Qualitative and quantitative computational models play an increasingly important role in the representation of these networks and in the search of new insights about these phenomena. In this work we analyze some graph-based models used to discover qualitative properties of such networks. In turn, we show that MP systems can naturally extend these graph-based models by adding some qualitative elements. The case study of integrins activation during the lymphocyte recruitment, a crucial phenomenon in inflammatory processes, is described, and a first MP graph for this network is designed. Finally, we discuss some open problems related to the qualitative modeling of signaling networks

Cellular modelling using P systems and process algebra.

In this paper various molecular chemical interactions are modelled under different computational paradigms. P systems and -calculus are used to describe intra-cellular reactions like protein-protein interactions and gene regulation control

Towards a P Systems Pseudomonas Quorum Sensing Model

Pseudomonas aeruginosa is an opportunistic bacterium that exploits quorum sensing communication to synchronize individuals in a colony and this leads to an increase in the effectiveness of its virulence. In this paper we derived a mechanistic P systems model to describe the behavior of a single bacterium and we discuss a possible approach, based on an evolutionary algorithm, to tune its parameters that will allow a quantitative simulation of the system.Kingdom's Engineering and Physical Sciences Research Council EP/D021847/

A Multiscale Modeling Framework Based on P Systems

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems. The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems. In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems. The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.Kingdom's Engineering and Physical Sciences Research Council EP/ E017215/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/F01855X/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/D019613/

A Multiscale Modeling Framework Based on P Systems

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems. The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems. In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems. The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.Kingdom's Engineering and Physical Sciences Research Council EP/ E017215/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/F01855X/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/D019613/

Towards Probabilistic Model Checking on P Systems Using PRISM

This paper presents the use of P systems and π-calculus to model interacting molecular entities and how they are translated into a probabilistic and symbolic model checker called PRISM.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58

Membrane Computing as a Modeling Framework. Cellular Systems Case Studies

Membrane computing is a branch of natural computing aiming to abstract computing models from the structure and functioning of the living cell, and from the way cells cooperate in tissues, organs, or other populations of cells. This research area developed very fast, both at the theoretical level and in what concerns the applications. After a very short description of the domain, we mention here the main areas where membrane computing was used as a framework for devising models (biology and bio-medicine, linguistics, economics, computer science, etc.), then we discuss in a certain detail the possibility of using membrane computing as a high level computational modeling framework for addressing structural and dynamical aspects of cellular systems. We close with a comprehensive bibliography of membrane computing applications

A Modeling Approach Based on P Systems with Bounded Parallelism

This paper presents a general framework for modelling with membrane systems that is based on a computational paradigm where rules have associated a finite set of attributes and a corresponding function. Attributes and functions are meant to provide those extra features that allow to define different strategies to run a P system. Such a strategy relying on a bounded parallelism is presented using an operational approach and applying it for a case study presenting the basic model of quorum sensing for Vibrio fischeri bacteria.Ministerio de Ciencia y Tecnología TIN2005-09345-C04-01Junta de Andalucía TIC-58