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

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

Evolution of Daily Gene Co-expression Patterns from Algae to Plants

Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions

A Study of the Robustness of the EGFR Signalling Cascade Using Continuous Membrane Systems

Many approaches to anticancer treatment have had a limited success. A fundamental hurdle to cancer therapy is the robustness of the signalling networks involved in tumourgenesis. The complexity of net- works of biological signalling pathways is such that the development of simplifying models is essential in trying to understand the wide-ranging cellular responses they can generate. In this paper a model of the epider- mal growth factor receptor signalling cascade is developed using contin- uous membrane systems. This model is used to study the robustness of this signalling cascade which is known to play a key role in tumour cell proliferation, angiogenesis and metastasis.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

A CLIPS Simulator for Recognizer P Systems with Active Membranes

In this paper we propose a new way to represent recognizer P systems with active membranes based on Production Systems techniques. This representation allows us to express the set of rules and the configurations in each step of the evolution as facts in a knowledge base. We provide a CLIPS program to simulate the evolutions of this variant of P systems.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Modelling gene expression control using P systems: The Lac Operon, a case study

In this paper P systems are used as a formal framework for the specification and simulation of biological systems. In particular, we will deal with gene regulation systems consisting of protein–protein and protein–DNA interactions that take place in different compartments of the hierarchical structure of the living cell or in different individual cells from a colony. We will explicitly model transcription and translation as concurrent and discrete processes using rewriting rules on multisets of objects and strings. Our approach takes into account the discrete character of the components of the system, its random behaviour and the key role played by membranes in processes involving signalling at the cell surface and selective uptake of substances from the environment. Our systems will evolve according to an extension of Gillespie’s algorithm, called Multicompartmental Gillespie’s Algorithm. The well known gene regulation system in the Lac Operon in Escherichia coli will be modelled as a case study to benchmark our approach.Ministerio de Ciencia y Tecnología TIN2005-09345-C04-0

A Model of the Quorum Sensing System in Vibrio fischeri Using P Systems

Quorum sensing is a cell density dependent gene regulation system that allows an entire population of bacterial cells to communicate in order to regulate the expression of certain or specific genes in a coordinated way depending on the size of the population. In this paper we present a model of the Quorum Sensing System in Vibrio fischeri using a variant of membrane systems called P systems. In this framework each bacterium and the environment are represented by membranes and the rules are applied according to an extension of Gillespie’s Algorithm called Multicompartmental Gillespie’s Algorithm. This algorithm runs on more than one compartment and takes into account the disturbance produced when chemical substances diffuse from one compartment or region to another. Our approach allows us to examine the individual behaviour of each bacterium as an agent as well as the emergent behaviour of the colony as a whole and the processes of swarming and recruitment. Our simulations show that at low cell densities bacteria remain dark while at high cell densities some bacteria start to produce light and a recruitment process takes place that makes the whole colony of bacteria to emit light. Our computational modelling of quorum sensing could provide insights that may enable researchers to develop new applications where multiple agents need to robustly and efficiently coordinate their collective behaviour based only on a very limited information of the local environment

Trading Polarization for Bi-stable Catalysts in P Systems with Active Membranes

In the last time, several efforts have been made in order to remove polarizations of membranes from P systems with active membranes; the present paper is a contribution in this respect. In order to compensate the loss of power represented by avoiding polarizations, we use bi-stable catalysts. Polarizationless systems with active membranes which use bi-stable catalysts are proven to be computationally complete and able to solve efficiently NP-complete problems. In this paper we present a solution to SAT in linear time. In order to illustrate the presented solution, we also provide a simulation with CLIPS.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Attacking the Common Algorithmic Problem by Recognizer P Systems

Many NP-complete problems can be viewed as special cases of the Common Algorithmic Problem (CAP). In a precise sense, which will be defined in the paper, one may say that CAP has a property of local universality. In this paper we present an effective solution to the decision version of the CAP using a family of recognizer P systems with active membranes. The analysis of the solution presented here will be done from the point of view of complexity classes in P systems.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0

Solving the BINPACKING Problem by Recognizer P Systems with Active Membranes

In this paper we present an e®ective solution to the BINPACKING problem using a family of recognizer P systems with active membranes, input membrane and external output. The analysis of the solution presented here will be done form the point of view of complexity classes.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-