An investigation of spatial signal transduction in cellular networks

<p>Abstract</p> <p>Background</p> <p>Spatial signal transduction plays a vital role in many intracellular processes such as eukaryotic chemotaxis, polarity generation and cell division. Furthermore it is being increasingly realized that the spatial dimension to signalling may play an important role in other apparently purely temporal signal transduction processes. It is increasingly being recognized that a conceptual basis for studying spatial signal transduction in signalling networks is necessary.</p> <p>Results</p> <p>In this work we examine spatial signal transduction in a series of standard motifs/networks. These networks include coherent and incoherent feedforward, positive and negative feedback, cyclic motifs, monostable switches, bistable switches and negative feedback oscillators. In all these cases, the driving signal has spatial variation. For each network we consider two cases, one where all elements are essentially non-diffusible, and the other where one of the network elements may be highly diffusible. A careful analysis of steady state signal transduction provides many insights into the behaviour of all these modules. While in the non-diffusible case for the most part, spatial signalling reflects the temporal signalling behaviour, in the diffusible cases, we see significant differences between spatial and temporal signalling characteristics. Our results demonstrate that the presence of diffusible elements in the networks provides important constraints and capabilities for signalling.</p> <p>Conclusions</p> <p>Our results provide a systematic basis for understanding spatial signalling in networks and the role of diffusible elements therein. This provides many insights into the signal transduction capabilities and constraints in such networks and suggests ways in which cellular signalling and information processing is organized to conform to or bypass those constraints. It also provides a framework for starting to understand the organization and regulation of spatial signal transduction in individual processes.</p

Partial differential equations for self-organization in cellular and developmental biology

Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

The macroscopic effects of microscopic heterogeneity

Over the past decade, advances in super-resolution microscopy and particle-based modeling have driven an intense interest in investigating spatial heterogeneity at the level of single molecules in cells. Remarkably, it is becoming clear that spatiotemporal correlations between just a few molecules can have profound effects on the signaling behavior of the entire cell. While such correlations are often explicitly imposed by molecular structures such as rafts, clusters, or scaffolds, they also arise intrinsically, due strictly to the small numbers of molecules involved, the finite speed of diffusion, and the effects of macromolecular crowding. In this chapter we review examples of both explicitly imposed and intrinsic correlations, focusing on the mechanisms by which microscopic heterogeneity is amplified to macroscopic effect.Comment: 20 pages, 5 figures. To appear in Advances in Chemical Physic

Understanding the Dynamics of Gene Regulatory Systems : Characterisation and Clinical Relevance of cis-Regulatory Polymorphisms

Peer reviewedPublisher PD

From Network Structure to Dynamics and Back Again: Relating dynamical stability and connection topology in biological complex systems

The recent discovery of universal principles underlying many complex networks occurring across a wide range of length scales in the biological world has spurred physicists in trying to understand such features using techniques from statistical physics and non-linear dynamics. In this paper, we look at a few examples of biological networks to see how similar questions can come up in very different contexts. We review some of our recent work that looks at how network structure (e.g., its connection topology) can dictate the nature of its dynamics, and conversely, how dynamical considerations constrain the network structure. We also see how networks occurring in nature can evolve to modular configurations as a result of simultaneously trying to satisfy multiple structural and dynamical constraints. The resulting optimal networks possess hubs and have heterogeneous degree distribution similar to those seen in biological systems.Comment: 15 pages, 6 figures, to appear in Proceedings of "Dynamics On and Of Complex Networks", ECSS'07 Satellite Workshop, Dresden, Oct 1-5, 200

Elucidating the spatial organization and control of information processing in cell signalling networks: from network and enzymatic building blocks to concrete systems

Cells function and survive by making decisions in response to dynamic environments. The core controllers of decision-making are highly complex intracellular networks of proteins and genes, which harbour sophisticated information processing capabilities. The effect of spatial organization and control of signaling networks is typically ignored. However, the role of space in signalling networks is being increasingly recognized. While there are some experimental and modelling efforts that incorporate spatial aspects in specific cellular contexts, the role of spatial regulation of signalling across different cell networks remains largely unexplored. In this thesis, we utilize a combination of mathematical modeling, systems engineering and in silico synthetic approaches to understand the spatial organization and control of signaling networks at multiple levels. We examine spatial effects in representative networks and enzymatic building blocks, including typical network modules, covalent modification cycles and enzymatic modification cascades and pathways. We complement these studies by dissecting the role of spatial regulation in the concrete context of the Caulobacter cell cycle, which involves specific combinations of these building blocks. In another investigation, we examine the organization of spatially regulated signaling networks underlying chemotaxis. We explicitly examine the effects of diffusion and its interplay with spatially varying signals and localization/compartmentalization of signalling entities and gain key insights into the interplay of these factors. At the network level, examining typical network modules reveals how introduction of diffusion/global entities may significantly distort temporal characteristics and introduce new types of signal transduction characteristics. At the enzymatic level, dissecting spatial regulation in enzymatic modules highlights the subtle effect and new facets that arise due to the interweaving of cycle kinetics and diffusion. The var- ious ways in which spatial compartmentalization affects pathway behaviour is revealed in the study of various types of signaling pathways. The study of spatial regulation of these enzymatic/network building blocks provides a systematic basis for understanding how spatial control can affect the spatiotemporal interactions driving Caulobacter cell cycle and we use an in-silico synthetic approach to create a platform for further understanding the functioning of the networks controlling this process. In a different study, we use a design approach to shed light on different signalling configurations of chemotactic networks that allow cells to exhibit both attractive and repulsive behaviour, in light of known signalling characteristics seen in cells. Our results uncover the various capabilities, constraints and trade-offs associated with the spatial control of information processing in signalling networks, which come to the surface only if spatial factors are explicitly considered. Overall, using a focused multipronged approach reveals different facets of spatial regulation of signalling at multiple levels and in different contexts. Combining mathematical modelling, systems engineering and synthetic design approaches creates a powerful framework, which may be used to elucidate spatial control of information processing in multiple contexts and design synthetic systems that could fruitfully exploit spatial organization and regulation.Open Acces