Gene Regulatory Signaling Research Articles

Costs and constraints from time-delayed feedback in small gene regulatory motifs

The multistep character of transcription, translation, and protein modification inevitably leads to time delays between sensing gene regulatory signals and responding with changed concentrations of functional proteins. However, the interplay between the time-delayed and the stochastic nature of gene regulation has been poorly investigated. Here we present an extension of the linear noise approximation which makes it possible to estimate second moments--variances and covariances--of fluctuations around stationary states in time-delayed systems. The usefulness of the method is exemplified by analyzing two ubiquitous regulatory motifs. In the first system, we show that there is an optimal combination of transcriptional repression and direct product inhibition in determining the activity of an enzyme system. In particular, we demonstrate that direct product inhibition is necessary to avoid deleterious fluctuations in a system when the gene regulatory response is delayed. The second system is an anabolic motif where the substrate fluxes are balanced by time-delayed regulation responding to the substrate concentrations. The extended linear noise approximation makes it possible to show analytically that increased association rate between the substrates leads to a lower product flux because of increasing unbalance in substrate pools.

Plant development: A TALE story

Plant development depends on the activity of a group of dividing cells called the meristem. Extensive genetic analyses have identified the major regulators of the shoot apical meristem (SAM), which control the development of all aerial organs. Among them, the three-amino-acid-loop-extension (TALE) class of homeoproteins has been shown to control meristem formation and/or maintenance, organ morphogenesis, organ position, and several aspects of the reproductive phase. This family contains the KNOTTED-like homeodomain (KNOX) and BEL1-like Homeodomain (BELL) members, which function as heterodimers. In this review, we have reported the functions of the TALE members throughout the Arabidopsis life cycle. Genetic analyses revealed a complex network, as TALE members exhibit both overlapping and antagonistic activities. The characterization of a new KNOX member (KNATM), which lacks a homeodomain and interacts with other members to modulate their activities, adds another layer of complexity to this network. While the mode of action of these transcription factors is still largely unknown, they have been implicated in the regulation of several hormonal pathways, providing a link between gene regulatory networks and signaling in the SAM.

The formation of the embryonic mouse heart

During cardiogenesis in the mouse, the second heart field (SHF) is the source of the myocardium of the outflow tract and it contributes to other regions of the heart with the exception of the primitive left ventricle. This contribution corresponds with that of the second myocardial cell lineage, identified by retrospective clonal analysis. Gene regulatory networks, signaling pathways, and heterogeneity within the SHF are discussed, together with the question of regulation of myocardial progenitor cells within the first heart field. The extension of the SHF into the mesodermal core of the arches also gives rise to endothelial cells of the pharyngeal arch arteries. Knowledge about the origin and genetic regulation of cells that contribute to the heart and associated vasculature is important for the diagnosis and treatment of congenital heart malformations.

Fan-out in gene regulatory networks

BackgroundIn synthetic biology, gene regulatory circuits are often constructed by combining smaller circuit components. Connections between components are achieved by transcription factors acting on promoters. If the individual components behave as true modules and certain module interface conditions are satisfied, the function of the composite circuits can in principle be predicted.ResultsIn this paper, we investigate one of the interface conditions: fan-out. We quantify the fan-out, a concept widely used in electrical engineering, to indicate the maximum number of the downstream inputs that an upstream output transcription factor can regulate. The fan-out is shown to be closely related to retroactivity studied by Del Vecchio, et al. An efficient operational method for measuring the fan-out is proposed and shown to be applied to various types of module interfaces. The fan-out is also shown to be enhanced by self-inhibitory regulation on the output. The potential role of an inhibitory regulation is discussed.ConclusionsThe proposed estimation method for fan-out not only provides an experimentally efficient way for quantifying the level of modularity in gene regulatory circuits but also helps characterize and design module interfaces, enabling the modular construction of gene circuits.

MicroRNA-Based Therapeutics for Cancer

MicroRNAs (miRNAs) are non-protein-coding small RNA molecules that negatively regulate target messenger RNA through degradation or suppression of protein translation. MiRNAs play important roles in the control of many biologic processes, such as development, differentiation, proliferation, and apoptosis. Increasing evidence shows that aberrant miRNA expression profiles and unique miRNA signaling pathways are present in a variety of cancers. MiRNAs function as oncogenes or tumor suppressors during tumor development and progression. Experimental evidence demonstrates that correction of specific miRNA alterations using miRNA mimics or antagomirs can normalize the gene regulatory network and signaling pathways, and reverse the phenotype in cancerous cells. MiRNA-based gene therapy provides an attractive anti-tumor approach for integrated cancer therapy. In this review, we focus on miRNA-based treatment for cancers, summarize the delivery systems used in experimental and preclinical research, such as liposomes, viral vectors, and nanoparticles, and consider the safety and toxicity of miRNA therapy.

Adaptive Discrete Galerkin Methods Applied to the Chemical Master Equation

In systems biology, the stochastic description of biochemical reaction kinetics is increasingly being employed to model gene regulatory networks and signaling pathways. Mathematically speaking, such models require the numerical solution of the underlying evolution equation, known as the chemical master equation (CME). Until now, the CME has primarily been treated by Monte Carlo techniques, the most prominent of which is the stochastic simulation algorithm [D. T. Gillespie, J. Comput. Phys., 22 (1976), pp. 403–434]. The paper presents an alternative, which focuses on the discrete partial differential equation (PDE) structure of the CME. This allows us to adopt ideas from adaptive discrete Galerkin methods as first suggested by Deuflhard and Wulkow [IMPACT Comput. Sci. Engrg., 1 (1989), pp. 269–301] for polyreaction kinetics and independently developed by Engblom. From the two different options for discretizing the CME as a discrete PDE, Engblom chose the method of lines approach (first space, then time), whereas we strongly advocate use of the Rothe method (first time, then space) for clear theoretical and algorithmic reasons. Numerical findings at two rather challenging problems illustrate the promising features of the proposed method and, at the same time, indicate lines of necessary further improvement of the method worked out here.

Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference

Statistical inference of biological networks such as gene regulatory networks, signaling pathways and metabolic networks can contribute to build a picture of complex interactions that take place in the cell. However, biological systems considered as dynamical, non-linear and generally partially observed processes may be difficult to estimate even if the structure of interactions is given. Using the same approach as Sitz et al. proposed in another context, we derive non-linear state-space models from ODEs describing biological networks. In this framework, we apply Unscented Kalman Filtering (UKF) to the estimation of both parameters and hidden variables of non-linear state-space models. We instantiate the method on a transcriptional regulatory model based on Hill kinetics and a signaling pathway model based on mass action kinetics. We successfully use synthetic data and experimental data to test our approach. This approach covers a large set of biological networks models and gives rise to simple and fast estimation algorithms. Moreover, the Bayesian tool used here directly provides uncertainty estimates on parameters and hidden states. Let us also emphasize that it can be coupled with structure inference methods used in Graphical Probabilistic Models. Matlab code available on demand.

Expanding the Spectrum of Genetic Elements Transferable by Retroviral Vectors

Retroviral vectors are powerful tools to study gene function. However, conventional methods require a cellular transcription step to generate the genomic RNA for viral production. This limits the scope of genetic elements that may be transferred by these vectors, excluding many key gene regulatory signals, including RNA editing motifs, alternative splicing, and various promoter/enhancer constellations, as well as cytotoxic genes. To address this problem, we devised a simple approach where in vitro-synthesized vector genomic RNA is transfected into the cytoplasm of a packaging cell, allowing immediate viral particle assembly. We demonstrate that high-titer retroviruses that efficiently transduce mammalian cell lines and primary cells are readily generated. Importantly, we show that an intron-containing expression cassette can be transferred by this method, leading to increased expression levels in the target cell. Further, we demonstrate that the cap structure is not required for retroviral packaging, thus avoiding translation of vector-encoded genes in the packaging cell. This allows the retroviral transfer of cytotoxic genes or proteins that otherwise inhibit viral production.

Positive feedback, stochasticity and genetic competence

A single gene, regulating its own expression via a positive feedback loop, constitutes a common motif in gene regulatory networks and signalling cascades. Recent experiments on the development of competence in the bacterial population B. subtilis show that the autoregulatory genetic module by itself can give rise to two types of cellular states. The states correspond to the low and high expression states of the master regulator ComK. The high expression state is attained when the ComK protein level exceeds a threshold value leading to a full activation of the autostimulatory loop. Stochasticity in gene expression drives the transitions between the two stable states. In this paper, we explain the appearance of bimodal protein distributions in B. subtilis cell population in the framework of three possible scenarios. In two of the cases, bistability provides the basis for binary gene expression. In the third case, the system is monostable in a deterministic description and stochasticity in gene expression is solely responsible for the appearance of the two expression states.

Single molecule biology: Coming of age

Cellular heterogeneity and stochastic fluctuation play key roles in biological processes. Single molecule approaches have the key advantage of avoiding ensemble averaging, allowing the observation of transient intermediates and heterogeneity (both static and dynamic). Thus they have revolutionised the way many biological questions are addressed. The challenge ahead is to develop integrated approaches such as the combination of single molecule imaging with single molecule manipulation to probe the dynamics of gene regulatory and cell signalling networks in living cells.

Cellular networks and the aging process

The most important interactions between cellular molecules have a high affinity, are unique and specific, and require a network approach for a detailed description. After a brief introduction to cellular networks (protein – protein interaction networks, metabolic networks, gene regulatory networks, signalling networks and membrane – organelle networks) an overview is given on the network aspects of the theories on aging. The most important part of the review summarizes our knowledge on the aging of networks. The effects of aging on the general network models are described, as well as the initial findings on the effects of aging on the cellular networks. Finally we suggest a ‘weak link theory of aging’ linking the random damage of the network constituents to the overwhelming majority of the low affinity, transient interactions (weak links) in the cellular networks. We show that random damage of weak links may lead to an increase of noise and an increased vulnerability of cellular networks, and make a comparison between these predictions and the observed behaviour of the emergent properties of cellular networks in aged organisms.

Sampling Rare Switching Events in Biochemical Networks

Bistable biochemical switches are widely found in gene regulatory networks and signal transduction pathways. Their switching dynamics are difficult to study, however, because switching events are rare, and the systems are out of equilibrium. We present a simulation method for predicting the rate and mechanism of the flipping of these switches. We apply it to a genetic switch and find that it is highly efficient. The path ensembles for the forward and reverse processes do not coincide. The method is widely applicable to rare events and nonequilibrium processes.

The proinflammatory cytokines tumor necrosis factor-alpha and interleukin-1 stimulate neuropeptide gene transcription and secretion in adrenochromaffin cells via activation of extracellularly regulated kinase 1/2 and p38 protein kinases, and activator protein-1 transcription factors.

Immune-autonomic interactions are known to occur at the level of the adrenal medulla, and to be important in immune and stress responses, but the molecular signaling pathways through which cytokines actually affect adrenal chromaffin cell function are unknown. Here, we studied the effects of the proinflammatory cytokines, TNF-alpha and IL-1, on gene transcription and secretion of bioactive neuropeptides, in primary bovine adrenochromaffin cells. TNF-alpha and IL-1 induced a time- and dose-dependent increase in galanin, vasoactive intestinal polypeptide, and secretogranin II mRNA levels. The two cytokines also stimulated the basal as well as depolarization-provoked release of enkephalin and secretoneurin from chromaffin cells. Stimulatory effects of TNF-alpha on neuropeptide gene expression and release appeared to be mediated through the type 2 TNF-alpha receptor, and required activation of ERK 1/2 and p38, but not Janus kinase, MAPKs. In addition, TNF-alpha increased the binding activity of activator protein-1 (AP-1) and stimulated transcription of a reporter gene containing AP-1-responsive elements in chromaffin cells. The AP-1-responsive reporter gene could also be activated through the ERK pathway. These results suggest that neuropeptide biosynthesis in chromaffin cells is regulated by TNF-alpha via an ERK-dependent activation of AP-1-responsive gene elements. Either locally produced or systemic cytokines might regulate biosynthesis and release of neuropeptides in chromaffin cells, integrating the adrenal medulla in the physiological response to inflammation. This study describes, for the first time, a signal transduction pathway activated by TNF-alpha in a major class of neuroendocrine cells that, unlike TNF-alpha signaling in lymphoid cells, employs ERK and p38 rather than Janus kinase and p38 to transmit gene-regulatory signals to the cell nucleus.

4 Patterning the sea urchin embryo: Gene regulatory networks, signaling pathways, and cellular interactions

We discuss steps in the specification of major tissue territories of the sea urchin embryo that occur between fertilization and hatching blastula stage and the cellular interactions required to coordinate morphogenetic processes that begin after hatching. We review evidence that has led to new ideas about how this embryo is initially patterned: (1) Specification of most of the tissue territories is not direct, but proceeds gradually by progressive subdivision of broad, maternally specified domains that depend on opposing gradients in the ratios of animalizing transcription factors (ATFs) and vegetalizing (beta-catenin) transcription factors; (2) the range of maternal nuclear beta-catenin extends further than previously proposed, that is, into the animal hemisphere, where it programs many cells to adopt early aboral ectoderm characteristics; (3) cells at the extreme animal pole constitute a unique ectoderm region, lacking nuclear beta-catenin; (4) the pluripotential mesendoderm is created by the combined outputs of ATFs and nuclear beta-catenin, which initially overlap in the macromeres, and by an undefined early micromere signal; (5) later micromere signals, which activate Notch and Wnt pathways, subdivide mesendoderm into secondary mesenchyme and endoderm; and (6) oral ectoderm specification requires reprogramming early aboral ectoderm at about the hatching blastula stage. Morphogenetic processes that follow initial fate specification depend critically on continued interactions among cells in different territories. As illustrations, we discuss the regulation of (1) the ectoderm/endoderm boundary, (2) mesenchyme positioning and skeletal growth, (3) ciliated band formation, and (4) several suppressive interactions operating late in embryogenesis to limit the fates of multipotent cells.

On the Number of Experiments Required to Find the Causal Structure of Complex Systems

The need to capture the complexity of biological systems in a simpler formalism is the underlying impetus of biological sciences. Understanding the function of many biological complex systems, such as genetic networks or molecular signalling pathways, requires precise identification of the interactions between their individual components. A number of questions in the study of complex systems are then important—in particular, what can be inferred about the interactions in a complex system from an arbitrary set of experiments, and, what is the minimum number of experiments required to characterize the system? This paper shows that the problem of finding the minimal causal structure of a system based on a set of observations is computationally intractable for even moderately sized systems (it is NP-hard), but a reasonable approximation can be found in a relatively short (polynomial) time. Next, it is shown that the number of experiments required to characterize a complex system grows exponentially with the upper bound on the number of immediate upstream influences of each element, but only logarithmically with the number of elements in the system. This makes it possible to study biological systems with extremely large number of interacting elements and relatively sparse interconnections, such as gene regulatory and cell signalling networks. Finally, the construction of a randomized experimental sequence which achieves this bound is discussed.

Development of Genomic Object Net Builder for Supporting XML Design for Visualization

Genomic Object Net (GON) is a biosimlation tool that allows us to model various kinds of biopathways including gene regulatory networks, metabolic pathways, and signal transduction pathways in a biologically intuitive way [4]. In GON, biopathway is modeled as an extension of hybrid Petri net called hybrid functional Petri net (HFPN) for which XML documentation is defined. As a graphical editor of a biopathway, GON equips with a tool GON Assembler for drawing and simulating the biopathway. Of couse, user need not touch any XML definitions. Furthermore, neither ordinary differential equations with messy coefficients nor programming labors are explicity required for user to model biopathways in GON. Since it is designed so powerful and flexible, E-CELL can also be realized as a subsystem of GON [1]. GON also has a visulalization tool for simulation called GON Visualizer. By writing an XML document for GON Visualizer, user can animate and see visually the interactions in a biopathway so that user can create and test hypotheses for biological phenomena [2, 3]. However, user has to write XML documents for personalized visualization although it is not a disastrous obstacle like the ODE designs and C++ programming for biologists.

Metals and the rhizobial-legume symbiosis — Uptake, utilization and signalling

In this review, we consider how the nitrogen-fixing root nodule bacteria, the 'rhizobia', acquire various metals, paying particular attention to the uptake of iron. We also review the literature pertaining to the roles of molybdenum and nickel in the symbiosis with legumes. We highlight some gaps in our knowledge, for example the lack of information on how rhizobia acquire molybdenum. We examine the means whereby different metals affect rhizobial physiology and the role of metals as signals for gene regulation. We describe the ways in which genetics has shown (or not) if, and how, particular metal uptake and/or metal-mediated signalling pathways are required for the symbiotic interaction with legumes.

MAP Kinases Erk1/2 Phosphorylate Sterol Regulatory Element-binding Protein (SREBP)-1a at Serine 117 in Vitro

Sterol regulatory element-binding protein (SREBP)-1a is a transcription factor sensing cellular cholesterol levels and integrating gene regulatory signals mediated by MAP kinase cascades. Here we report the identification of serine 117 in SREBP-1a as the major phosphorylation site of the MAP kinases Erk1/2. This site was identified by nanoelectrospray mass spectrometry and peptide sequencing of recombinant fusion proteins phosphorylated by Erk1/2 in vitro. Serine 117 was verified as the major phosphorylation site by in vitro mutagenesis. Mutation of serine 117 to alanine abolished Erk2-mediated phosphorylation in vitro and the MAP kinase-related transcriptional activation of SREBP-1a by insulin and platelet-derived growth factor in vivo. Our data indicate that the MAP kinase-mediated effects on SREBP-1a-regulated target genes are linked to this phosphorylation site.

Structural code for DNA recognition revealed in crystal structures of papillomavirus E2-DNA targets.

Transcriptional regulation in papillomaviruses depends on sequence-specific binding of the regulatory protein E2 to several sites in the viral genome. Crystal structures of bovine papillomavirus E2 DNA targets reveal a conformational variant of B-DNA characterized by a roll-induced writhe and helical repeat of 10.5 bp per turn. A comparison between the free and the protein-bound DNA demonstrates that the intrinsic structure of the DNA regions contacted directly by the protein and the deformability of the DNA region that is not contacted by the protein are critical for sequence-specific protein/DNA recognition and hence for gene-regulatory signals in the viral system. We show that the selection of dinucleotide or longer segments with appropriate conformational characteristics, when positioned at correct intervals along the DNA helix, can constitute a structural code for DNA recognition by regulatory proteins. This structural code facilitates the formation of a complementary protein-DNA interface that can be further specified by hydrogen bonds and nonpolar interactions between the protein amino acids and the DNA bases.

Primary Role of Mitochondria and Calcium Ions in the Induction of Reactive Oxygen Species by External Stimuli such as Triorganotins

Tributyltin (TBT) salts are potent skin irritants both in humans and rodents. Data in the literature indicate mitochondria as target of TBT effects. The purpose of this study was to investigate the early intracellular molecular events that follow TBT treatment and mitochondrial impairment and the relevance of mitochondria in gene-regulatory signalling pathways. The results obtained indicate the pivotal role of Ca 2+ as the starting event following TBT treatment and confirm the important role of mitochondria as the source of second messenger molecules essential for TBT-induced NF- κB activation and IL-1 α production.