Cellular Regulatory Systems Research Articles

Dynamical properties of gene regulatory networks involved in long-term potentiation.

The long-lasting enhancement of synaptic effectiveness known as long-term potentiation (LTP) is considered to be the cellular basis of long-term memory. LTP elicits changes at the cellular and molecular level, including temporally specific alterations in gene networks. LTP can be seen as a biological process in which a transient signal sets a new homeostatic state that is “remembered” by cellular regulatory systems. Previously, we have shown that early growth response (Egr) transcription factors are of fundamental importance to gene networks recruited early after LTP induction. From a systems perspective, we hypothesized that these networks will show less stable architecture, while networks recruited later will exhibit increased stability, being more directly related to LTP consolidation. Using random Boolean network (RBN) simulations we found that the network derived at 24 h was markedly more stable than those derived at 20 min or 5 h post-LTP. This temporal effect on the vulnerability of the networks is mirrored by what is known about the vulnerability of LTP and memory itself. Differential gene co-expression analysis further highlighted the importance of the Egr family and found a rapid enrichment in connectivity at 20 min, followed by a systematic decrease, providing a potential explanation for the down-regulation of gene expression at 24 h documented in our preceding studies. We also found that the architecture exhibited by a control and the 24 h LTP co-expression networks fit well to a scale-free distribution, known to be robust against perturbations. By contrast the 20 min and 5 h networks showed more truncated distributions. These results suggest that a new homeostatic state is achieved 24 h post-LTP. Together, these data present an integrated view of the genomic response following LTP induction by which the stability of the networks regulated at different times parallel the properties observed at the synapse.

Synergistic Effects of Phenolic Mixtures in Human Cell Models of Aging

The health benefits associated with fruit and vegetable consumption are attributed, in the main, to fiber and micronutrients and recent research has focused on the role of phenolics (polyphenols) in mediating healthful dietary effects. While most plants contain complex mixtures of polyphenols, isolated compounds, such as resveratrol, have been widely studied and shown to influence the activity of multiple cellular metabolic and signaling pathways. Indeed, based on its actions on several cellular regulatory systems, resveratrol has been proposed to be the active molecule underlying the benefits of grape and red wine consumption. To test the hypothesis that phenolic mixtures containing resveratrol produce variable and non‐additive effects versus resveratrol alone, their antioxidant capacity (ORAC) and their effects in several in vitro models of cellular aging were compared using identical concentrations (µg phenolics/ml). Compared to resveratrol alone, the same concentration of a mixture of muscadine grape polyphenols plus resveratrol produced synergistic effects on ORAClipophilic but not ORAChydrophilic. Likewise, the phenolic mixture exhibited 10X greater potency versus resveratrol in inhibiting protein glycation. Non‐additive/synergistic effects (p<0.01) of the mixture versus resveratrol on mitochondrial mass, oxygen consumption and gene expression were measured in human skeletal muscle cells. Finally, synergistic effects (p<0.01) of the phenolic mixture in preventing oxidative damage to DNA (COMET assay) were observed in human pancreatic cells. These results suggest that, compared to isolated plant phenolics, the complex mixtures occurring naturally in plants have greater potency to influence various mechanisms of cellular aging.

Local Perturbation Analysis: A Computational Tool for Biophysical Reaction-Diffusion Models

Diffusion and interaction of molecular regulators in cells is often modeled using reaction-diffusion partial differential equations. Analysis of such models and exploration of their parameter space is challenging, particularly for systems of high dimensionality. Here, we present a relatively simple and straightforward analysis, the local perturbation analysis, that reveals how parameter variations affect model behavior. This computational tool, which greatly aids exploration of the behavior of a model, exploits a structural feature common to many cellular regulatory systems: regulators are typically either bound to a membrane or freely diffusing in the interior of the cell. Using well-documented, readily available bifurcation software, the local perturbation analysis tracks the approximate early evolution of an arbitrarily large perturbation of a homogeneous steady state. In doing so, it provides a bifurcation diagram that concisely describes various regimes of the model’s behavior, reducing the need for exhaustive simulations to explore parameter space. We explain the method and provide detailed step-by-step guides to its use and application.

History of the discovery of a master locus producing piRNAs: the flamenco/COM locus in Drosophila melanogaster.

The discovery of transposable elements (TEs) in the 1950s by B. McClintock implied the existence of cellular regulatory systems controlling TE activity. The discovery of flamenco (flam) an heterochromatic locus from Drosophila melanogaster and its ability to survey several TEs such as gypsy, ZAM, and Idefix contributed to peer deeply into the mechanisms of the genetic and epigenetic regulation of TEs. flam was the first cluster producing small RNAs to be discovered long before RNAi pathways were identified in 1998. As a result of the detailed genetic analyses performed by certain laboratories and of the sophisticated genetic tools they developed, this locus has played a major role in our understanding of piRNA mediated TE repression in animals. Here we review the first discovery of this locus and retrace decades of studies that led to our current understanding of the relationship between genomes and their TE targets.

Functional association networks as priors for gene regulatory network inference.

Motivation: Gene regulatory network (GRN) inference reveals the influences genes have on one another in cellular regulatory systems. If the experimental data are inadequate for reliable inference of the network, informative priors have been shown to improve the accuracy of inferences.Results: This study explores the potential of undirected, confidence-weighted networks, such as those in functional association databases, as a prior source for GRN inference. Such networks often erroneously indicate symmetric interaction between genes and may contain mostly correlation-based interaction information. Despite these drawbacks, our testing on synthetic datasets indicates that even noisy priors reflect some causal information that can improve GRN inference accuracy. Our analysis on yeast data indicates that using the functional association databases FunCoup and STRING as priors can give a small improvement in GRN inference accuracy with biological data.Contact: matthew.studham@scilifelab.seSupplementary information: Supplementary data are available at Bioinformatics online.

Large T Antigens of Polyomaviruses: Amazing Molecular Machines

The large tumor antigen (T antigen) encoded by simian virus 40 is an amazing molecular machine because it orchestrates viral infection by modulating multiple fundamental viral and cellular processes. T antigen is required for viral DNA replication, transcription, and virion assembly. In addition, T antigen targets multiple cellular pathways, including those that regulate cell proliferation, cell death, and the inflammatory response. Ectopic T antigen expression results in the immortalization and transformation of many cell types in culture and T antigen induces neoplasia when expressed in rodents. The analysis of the mechanisms by which T antigen carries out its many functions has proved to be a powerful way of gaining insights into cell biology. The accelerating pace at which new polyomaviruses are being discovered provides a collection of novel T antigens that, like simian virus 40, can be used to discover and study key cellular regulatory systems.

Characterizing multistationarity regimes in biochemical reaction networks.

Switch like responses appear as common strategies in the regulation of cellular systems. Here we present a method to characterize bistable regimes in biochemical reaction networks that can be of use to both direct and reverse engineering of biological switches. In the design of a synthetic biological switch, it is important to study the capability for bistability of the underlying biochemical network structure. Chemical Reaction Network Theory (CRNT) may help at this level to decide whether a given network has the capacity for multiple positive equilibria, based on their structural properties. However, in order to build a working switch, we also need to ensure that the bistability property is robust, by studying the conditions leading to the existence of two different steady states. In the reverse engineering of biological switches, knowledge collected about the bistable regimes of the underlying potential model structures can contribute at the model identification stage to a drastic reduction of the feasible region in the parameter space of search. In this work, we make use and extend previous results of the CRNT, aiming not only to discriminate whether a biochemical reaction network can exhibit multiple steady states, but also to determine the regions within the whole space of parameters capable of producing multistationarity. To that purpose we present and justify a condition on the parameters of biochemical networks for the appearance of multistationarity, and propose an efficient and reliable computational method to check its satisfaction through the parameter space.

Regulatory systems controlling motility and gene transfer agent production and release in Rhodobacter capsulatus

Production of the gene transfer agent of Rhodobacter capsulatus, RcGTA, is dependent upon several cellular regulatory systems, including a putative phosphorelay involving the CtrA and CckA proteins. These proteins are also involved in flagellar motility in R. capsulatus. The interactions of proteins in this system are best understood in Caulobacter crescentus where CtrA is activated by phosphorylation by the CckA-ChpT phosphorelay. CtrA~P activity is further controlled by SciP, which represses ctrA transcription and CtrA activation of transcription. We show that R. capsulatus chpT and cckA mutants both have greatly reduced motility and RcGTA activity. Unlike the ctrA mutant where RcGTA gene transcription is absent, the decrease in RcGTA activity is because of reduced release of RcGTA from the cells. The sciP mutant is not affected for RcGTA production but our results support the C. crescentus model of SciP repression of flagellar motility genes. We show that both unphosphorylated and phosphorylated CtrA can activate RcGTA gene expression, while CtrA~P seems to be required for release of the particle and expression of motility genes. This has led us to a new model of how this regulatory system controls motility and production of RcGTA in R. capsulatus.

Fluorescence Correlation Spectroscopy to Monitor Kai Protein-based Circadian Oscillations in Real Time

Dynamic protein-protein interactions play an essential role in cellular regulatory systems. The cyanobacterial circadian clock is an oscillatory system that can be reconstituted in vitro by mixing ATP and three clock proteins: KaiA, KaiB, and KaiC. Association and dissociation of KaiB from KaiC-containing complexes are critical to circadian phosphorylation and dephosphorylation of KaiC. We developed an automated and noninvasive method to monitor dynamic complex formation in real time using confocal fluorescence correlation spectroscopy (FCS) and uniformly labeled KaiB as a probe. A nanomolar concentration of the labeled KaiB for FCS measurement did not interfere with the oscillatory system but behaved similarly to the wild-type one during the measurement period (>5 days). The fluorescent probe was stable against repeated laser exposure. As an application, we show that this detection system allowed analysis of the dynamics of both long term circadian oscillations and short term responses to temperature changes (∼10 min) in the same sample. This suggested that a phase shift of the clock with a high temperature pulse occurred just after the stimulus through dissociation of KaiB from the KaiC complex. This monitoring method should improve our understanding of the mechanisms underlying this cellular circadian oscillator and provide a means to assess dynamic protein interactions in biological systems characterized by rates similar to those observed with the Kai proteins.

The cytoskeleton and the cellular transduction of mechanical strain in the heart: a special issue

There is a fundamental requirement for all cells to communicate and process information with regard to their surroundings and this is accomplished by vast array of signals that, at its basis, are all based on four principal physical processes: electricity, force, chemical reaction, and light. Mechanical strain sensing in muscle is unique in that forces are both generated by the muscle cells itself (“insideout” pathway) as well as acted upon these cells from the exterior (“outside-in” pathway). These mechanisms are critically important in the heart to alter its form and function and meet varied hemodynamic demands. Accordingly, this special issue of Pfluger s Archiv European Journal of Physiology is focused on the cellular transduction of mechanical strain in the heart. The issue is composed of invited reviews written by world leaders in their respective fields of research. A well-known example of acute strain regulation in cardiac tissue is the Frank–Starling Law of the heart [9]. Interestingly, although this basic beat-to-beat regulatory mechanism has been appreciated for over a century, the cellular mechanisms that underlie this strain transduction system have only been identified in recent decades as being caused by (a) an immediate change in cardiac cell contractility that is secondary to changes in contractile protein Ca sensitivity [11, 12], and (b) a slower change in cardiac cell contractility that develops over the course of several beats that is secondary to changes in intracellular Ca homeostasis [1, 17]. However, the molecular mechanisms and cellular signal transduction processes that underlie these cellular regulatory systems are still under intense investigation [9]. In this issue, this area of research is reviewed by contributions from the groups of Campbell [5], Cazorla [6], Cingolani [7], Peter Kohl [2], Landesberg [23], and McDonald [16]. Cardiac muscle cells are dynamic; increased mechanical load induces a hypertrophic response, while reduced load elicits the reverse response [21]. The cellular signal transduction processes responsible for this tight, long term, regulatory system that leads to remodeling of the sarcomeric architecture in the cardiac muscle cell are varied and complex. In addition, the cardiac cell is integrated into the extracellular scaffolding and force transmission system formed by the extracellular matrix, which itself is a dynamic structure that is subject to regulation and remodeling. This rapidly expanding area of research is reviewed in this special issue by contributions from the groups of Borg [3], Kresh [13], Parker [15], and Russell [8]. Among the several cytoskeletal protein structures that play a role in the cellular transduction system, the giant sarcomeric protein titin (the “fourth filament”) is particularly intriguing. Titin’s role as the predominant contributor to passive force generation within the physiological range in striated muscle is now well established [14]. However, recent observations indicate a far greater role of this giant protein in a vast array of cellular functions, including the response to cellular strain in myofilament length dependent activation, protein turnover, hypertrophic responses, and modulation of cardiac function in cardiac pathologies such P. P. de Tombe (*) Department of Cell and Molecular Physiology, Loyola University Chicago, Stritch School of Medicine, 2160 South First Ave, Maywood, IL 60153-5500, USA e-mail: pdetombe@lumc.edu

Disturbance Analysis of Nonlinear Differential Equation Models of Genetic SUM Regulatory Networks

Noise disturbances and time delays are frequently met in cellular genetic regulatory systems. This paper is concerned with the disturbance analysis of a class of genetic regulatory networks described by nonlinear differential equation models. The mechanisms of genetic regulatory networks to amplify (attenuate) external disturbance are explored, and a simple measure of the amplification (attenuation) level is developed from a nonlinear robust control point of view. It should be noted that the conditions used to measure the disturbance level are delay-independent or delay-dependent, and are expressed within the framework of linear matrix inequalities, which can be characterized as convex optimization, and computed by the interior-point algorithm easily. Finally, by the proposed method, a numerical example is provided to illustrate how to measure the attenuation of proteins in the presence of external disturbances.

Regulation of Human Sickle Erythrocyte Hydration Status by Endothelin-1 Is Mediated by Casein Kinase II.

Abstract 3020Poster Board II-996In Sickle Cell Disease, K+ efflux and osmotically induced water loss leads to erythrocyte dehydration, an important step in the formation of hemoglobin S polymers and irreversible sickle cells. We have previously reported that activation of sickle erythrocyte endothelin-1 (ET-1) receptors is partially responsible for dense irreversible sickle cell formation thru mechanisms that are still undefined. Casein Kinase II (CK2), a serine/threonine kinase that phosphorylates acidic proteins, has been shown to regulate calmodulin activity and cytoskeletal proteins. Thus, we posit that CK2 may regulate cellular hydration status. CK2 activity is modulated by apigenin, emodin, heparin, and ornithine decarboxylase. Our results indicate that CK2 activity in erythrocyte membranes increases in the presence of ET-1 (2.8 ± 0.1 to 4.9 ± 0.01 nmol/min/mL * 106 cell) an event that is blunted by pre-incubation with the ET-1 B receptor blocker, BQ788 (2.5 ± 0.1 nmol/min/mL * 106 cell). Our data also indicate that 20 μM apigenin blocks ET-1 induced CK2 activity in sickle erythrocytes (2.8 ± 0.1 to 2.7 ± 0.4 nmol/min/mL * 106 cell). We then examined the role of CK2 activation in cellular dehydration. We incubated sickle erythrocytes for 3 hours in deoxygenation-oxygenation cycles in the presence or absence of 20μM apigenin or 2μM 4,5,6,7-tetrabromobenzotriazole (TBB), another specific CK2 inhibitor, and measured the changes in erythrocyte density by the phthalate oil method. We observed that inhibition of CK2 led to the inhibition of deoxygenation-stimulated cellular dehydration in sickle erythrocytes by apigenin (D50= 1.106 to 1.100 g/mL) or TBB (D50 =1.097 g/mL). Apigenin also inhibited the volume-stimulated K+ efflux in a dose-dependent manner (IC50 = 18 ± 1 μM). These results strongly implicate CK2 as an intermediate of the ET-1 stimulated cellular volume regulatory systems in erythrocytes and suggest that regulation of CK2 activity may lead to reduction of hemoglobin S polymerization in vivo. Supported by NIH R01-HL09632 to AR. DisclosuresNo relevant conflicts of interest to declare.

The Importance of Being Flexible: The Case of Basic Region Leucine Zipper Transcriptional Regulators

Large volumes of protein sequence and structure data acquired by proteomic studies led to the development of computational bioinformatic techniques that made possible the functional annotation and structural characterization of proteins based on their primary structure. It has become evident from genome-wide analyses that many proteins in eukaryotic cells are either completely disordered or contain long unstructured regions that are crucial for their biological functions. The content of disorder increases with evolution indicating a possibly important role of disorder in the regulation of cellular systems. Transcription factors are no exception and several proteins of this class have recently been characterized as premolten/molten globules. Yet, mammalian cells rely on these proteins to control expression of their 30,000 or so genes. Basic region:leucine zipper (bZIP) DNA-binding proteins constitute a major class of eukaryotic transcriptional regulators. This review discusses how conformational flexibility "built" into the amino acid sequence allows bZIP proteins to interact with a large number of diverse molecular partners and to accomplish their manifold cellular tasks in a strictly regulated and coordinated manner.

How to deal with large models?

Mol Syst Biol. 5: 240 The regulatory systems that allow cells to adapt to their environments are exceedingly complex, and although we know a great deal about the intricate mechanistic details of many of these systems, our ability to make accurate predictions about their system‐level behaviors is severely limited. We would like to make such predictions for a number of reasons. How can we reverse dysfunctional molecular changes of these systems that cause disease? More generally, how can we harness and direct cellular activities for beneficial purposes? Our ability to make accurate predictions about a system is also a measure of our fundamental understanding of that system. As evidenced by our mastery of technological systems, a useful understanding of a complex system can often be obtained through the development and analysis of a mathematical model, but predictive modeling of cellular regulatory systems, which necessarily relies on quantitative experimentation, is still in its infancy. There is much that we need to learn before modeling for practical applications becomes routine. In particular, we need to address a number of issues surrounding the large number of parameters that are typically found in a model for a cellular regulatory system. In a recent article published in Molecular Systems Biology , Peter Sorger et al report a significant contribution not only to our system‐level understanding of an important signal‐transduction system but also to our understanding of the methodology needed for developing and testing a large‐scale mathematical model for this type of system (Chen et al , 2009). The power of sensitivity analysis is demonstrated. In this study, to which William Chen, Birgit Schoeberl and Paul Jasper contributed equally, an ordinary differential equation (ODE) model for immediate‐early events in signaling by the epidermal growth factor (EGF) receptor (EGFR, which is also called ErbB1) (Schoeberl et …

From Protein Interactions to Complex Physiology

Docking or adaptor proteins may provide the building blocks from which complex cellular biological regulatory systems could be built during the course of evolution. Hardy et al . examined the docking protein ShcA, which has a phosphotyrosine binding (PTB) domain and a Src homology 2 (SH2) domain, each of which can bind to phosphorylated receptors and other proteins. Shc proteins also contain tyrosine residues that become phosphorylated and serve as binding sites for the adaptor protein Grb2 (growth factor receptor-bound protein 2). In mice that expressed mutant proteins with one or more domains altered, the PTB domain was essential for development of the heart, but the SH2 domain and Grb2-binding domains were not. However, successful development of skeletal muscle required that the PTB, SH2, and Grb2-binding domains be present within the same Shc molecule. Thus, acquisition of new protein-protein interaction motifs within proteins and their distinct use in various cell types or organisms may support complex physiological functions. W. R. Hardy, L. Li, Z. Wang, J. Sedy, J. Fawcett, E. Frank, J. Kucera, T. Pawson, Combinatorial ShcA docking interactions support diversity in tissue morphogenesis. Science 317 , 251-256 (2007). [Abstract] [Full Text]

Ovarian acetylcholine and ovarian KCNQ channels: Insights into cellular regulatory systems of steroidogenic granulosa cells

Acetylcholine (ACh) may be an ovarian signaling molecule, since ACh is produced by non-neuronal granulosa cells (GCs) derived from the antral follicle, and likely also by their in vivo counterparts in the growing follicle. Furthermore, muscarinic ACh receptors (MR) are present in GC membranes and in cultured human GCs a number of MR-mediated actions have been described, including regulation of proliferation and gap junctional communication. Importantly, muscarinic stimulation elevates intracellular calcium levels, thereby opening a calcium-activated potassium channel (BKCa) and causing membrane hyperpolarization. In the course of electrophysiological experiments with human GCs we also observed a reversible inhibitory action of an ACh analogue (carbachol) on an outward potassium current. This current is reminiscent of a so-called M-current described in neuronal systems, of which muscarinic regulation is well-known. Indeed, the current is sensitive to the specific KCNQ blocker XE991 and a possible underlying channel, KCNQ1 (Kv7.1/KvLQT1) was detected by RT-PCR in GCs and by immunohistochemistry in large ovarian follicles. Pharmacological inhibition of the channel by XE991 blocked gonadotropin-stimulated steroid production and increased cell proliferation, i.e. fundamental processes of GCs in the ovary. Assuming a similar effect of ACh in vivo, this channel may be a pivotal regulator of physiological GC function linked to actions of the novel intraovarian signaling molecule ACh.

In Remembrance: Reinhart Heinrich 1946–2006

Reinhart Heinrich, former professor at Humboldt University, Berlin, and best-known as a founder of metabolic control theory, died October 23, 2006, at the age of 60. Among his many services to the scientific community, Reinhart was associate editor of PLoS Computational Biology. His far-reaching theoretical work on metabolism, signal transduction, and other cellular processes has made him one of the most influential forerunners of present-day systems biology. Having been educated as a theoretical physicist at Technical University, Dresden, Reinhart conducted his postdoctoral research in the early 1970s at the Institute of Biochemistry in East Berlin. He could not fail to notice the absence of mathematical theory from cell biology as compared with other natural sciences. Enzyme kinetics was a notable exception. However, how enzymes affect the flux through a metabolic pathway was still discussed using the rather vague term rate-limiting step. Working with Tom Rapoport on mathematical models of glycolysis in red blood cells, Reinhart discovered a precise and general definition of rate limitation in metabolic pathways. The parallel development of metabolic control theory by Henrik Kacser and Jim Burns in Edinburgh shows that the time was ripe for a quantitative understanding of metabolic regulation. Instead of postulating a single rate-limiting step, Reinhart's and Henrik Kacser's theories evaluated the degree of flux control exerted by an individual enzyme in a linear pathway or in a more complex network. The corresponding measure—termed flux control coefficient—turned out to be a truly systemic quantity, depending not only on the kinetic parameters of the enzyme itself but also on those of other enzymes, as well as on the position of the reaction in the network. Several years after its original publication, metabolic control theory became widely absorbed by biochemists. Control coefficients have been measured for many pathways, confirming the theoretical prediction that flux control is frequently shared by several reactions. This finding has recently become of very practical importance for the genetic engineering of large metabolic networks in biotechnology. The dual approach—modeling concrete cellular processes and, at the same time, searching for general laws—has been a characteristic of Reinhart's work. The areas he worked in were amazingly diverse, including metabolic control, osmoregulation, cell shapes, signal transduction, vesicular transport, protein translation and transport, as well as the population dynamics of malaria parasites. Perhaps his most favored questions were those of evolution. To understand the kinetic design of enzymes and enzymatic reaction networks, Reinhart strove to rationalize, in mathematical terms, the selective pressures and physico–chemical constraints that these systems were subjected to. Reinhart's work on this topic is full of original insight and makes specific predictions, some of which have begun to be tested successfully in recent years. Reinhart was author of more than 150 research articles and, together with Stefan Schuster, wrote the book The Regulation of Cellular Systems—already a classic of cell systems biology. In addition to this large body of original work, he was a gifted mentor of young scientists and for more than ten years ran the highly successful interdisciplinary graduate program “Dynamics and Evolution of Cellular Processes” at Humboldt University, Berlin. Reinhart's many talents made him appear as a modern Renaissance man. He played the violin, wrote poetry, and published an autobiographic novel (Jenseits von Babel). Reinhart had a large international circle of friends and collaborators by whom he will be remembered for his kindness, generosity, and contagious humor. From the Editor: Reinhart was a recent, highly commended, member of the PLoS Computational Biology Editorial Team. Thomas has made it abundantly clear why we asked Reinhart to join us. He was an active and timely contributor and he will be sorely missed by all of us at PLoS as well as by the rest of the scientific community. Our condolences go out to his family. — Philip E. Bourne, Editor-in-Chief

Book Review: Function and Regulation of Cellular Systems: Experiments and Models. By A. Deutsch, J. Howard, M. Falcke and W. Zimmermann

Book Review: Function and Regulation of Cellular Systems: Experiments and Models. By A. Deutsch, J. Howard, M. Falcke and W. Zimmermann

Collado-Vides J, Hofestädt R, (editors): Gene Regulation and Metabolism: Postgenomic Computational Approaches

The inference, analysis and integration of networks of genes and products are fundamental goals of post-genomic research. Over the past few years several data- and knowledge-driven computational approaches have been proposed, which have provided relevant insights into the informational complexity and function of some of such networks in different organisms. Gene Regulation and Metabolism probably represents one of the first books attempting to discuss essential computational concepts, methods and applications in this area. Although its editors did not aim to offer a comprehensive review of advances available at the time of its publication, this book may still be seen as a useful introduction for computer scientists to key problems, solutions and questions relevant to the study of regulatory and metabolic networks. Collado-Vides and Hofestadt edited a collection of contributions by internationally-recognised authors, which were motivated by a summer school following a series of Dagstuhl seminars in Germany. The book is divided into three main parts addressing information and knowledge representation problems, gene regulation and post-genomic approaches. Each chapter also provides lists of suggested readings and relevant websites, which include some of the databases and tools discussed in the book. The book also offers a glossary of terms and acronyms. Overall, the chapters are well-written and organised. Readers would have benefited from an introductory chapter to overview fundamental biological concepts and problems. However, this is partially compensated by some chapters, which adequately present basic concepts and motivation necessary to approach specific applications such as DNA regulatory motif discovery. In the first chapter, Ahouse discusses the concept of homology and its inference within the context of regulatory networks, which represents an important source for predicting potential interactions. The second chapter, by Apweiler et al., describes several techniques for automated protein sequence characterisation and its applications in whole proteome analysis. Chapter 3, by Freier et al., overviews approaches to database integration, which are relevant to the prediction and analysis of metabolic networks. They also put emphasis on the application of a rule-based simulation tool (MetabSim). In Chapter 4, Stormo introduces quantitative indicators required to support the prediction of regulatory binding sites from sets of co-regulated genes. This is followed by Collado-Vides et al.'s review of methods for identifying regulatory elements, e.g. promoters and regulatory binding sites. Chapter 6, by Manson McGuire and Church, focuses on the discovery of DNA regulatory motifs. It introduces different techniques for regulon prediction and an algorithm for detecting motifs (AlignACE). In Chapter 7, Kolchanov et al. discusses the representation and modelling of gene networks using the GeneNet database. This system encodes different types of networks, e.g. networks relating to cell growth and differentiation. This chapter concludes with an introduction to the mathematical simulation of gene network dynamics. Chapter 8, by Huang, emphasises Boolean networks approaches to modelling cellular regulatory systems. In Chapter 9, Marcotte discusses important questions and challenges for the large-scale prediction of protein function and networks. Chapter 10, by Schmidt and Dandekar, concentrates on metabolic pathways. It introduces fundamental concepts and problems, such as enzymatic reactions and pathway alignment. The final chapter, by Tomita, introduces the E-CELL project, which has been applied to simulate several cellular processes, e.g. signal transduction and gene regulation. The ultimate goal of this project is to model the cell based on large-scale representations of thousands of functionally-diverse processes. Even when it does not provide a comprehensive, up-to-date review of techniques and tools for supporting the inference and analysis of gene regulation and metabolism networks, this book represents a useful reference to reflect on recent advances and challenges ahead. Moreover, some of its chapters highlight crucial open questions and computational opportunities in the systems biology era.

Mathematical Analysis of Hepatic High Density Lipoprotein Transport Based on Quantitative Imaging Data

Hepatocytes internalize high density lipoprotein (HDL) at the basolateral membrane. Most HDL is recycled while some is shuttled to the canalicular membrane by transcytosis. Here, transport of HDL was analyzed by mathematical modeling based on measurements in polarized hepatic HepG2 cells. Recycling of HDL from basolateral sorting endosomes was modeled by applying the rapid equilibrium approach. Analytical expressions were derived, which describe in one model the transport of HDL to the subapical compartment/apical recycling compartment, the biliary canaliculus (BC), and to late endosomes and lysosomes (LE/LYS). Apical endocytosis of HDL predicted by the model was confirmed for rhodamine-dextran and fluorescent asialoorosomucoid, markers for LE/LYS in living HepG2 cells. Budding of endocytic vesicles from the BC was directly observed by time lapse imaging of a fluorescent lipid probe. Based on fitted kinetic parameters and their covariance matrix a Monte Carlo simulation of HDL transport in hepatocytes was performed. The model was used to quantitatively assess release of HDL-associated free cholesterol by scavenger receptor BI. It is shown that only 6% of HDL-associated sterol reaches the BC as a constituent of the HDL particles, whereas the remaining sterol is rapidly released from HDL and shuttled to the BC by non-vesicular transport.