Biological Signaling Systems Research Articles

Multi-state modeling of biomolecules.

Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the “specification problem”) and the problem of how to use a computer to simulate the progress of the system over time (the “computation problem”). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus [1], BioNetGen [2]–[5], the Allosteric Network Compiler [6], and others [7], [8]. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm [9], [10]. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim [11], DYNSTOC [12], RuleMonkey [9], [13], and the Network-Free Stochastic Simulator (NFSim) [14], and spatial simulators, including Meredys [15], SRSim [16], [17], and MCell [18]–[20]. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.

Biosemiotic Entropy: Concluding the Series

This article concludes the special issue on Biosemiotic Entropy looking toward the future on the basis of current and prior results. It highlights certain aspects of the series, concerning factors that damage and degenerate biosignaling systems. As in ordinary linguistic discourse, well-formedness (coherence) in biological signaling systems depends on valid representations correctly construed: a series of proofs are presented and generalized to all meaningful sign systems. The proofs show why infants must (as empirical evidence shows they do) proceed through a strict sequence of formal steps in acquiring any language. Classical and contemporary conceptions of entropy and information are deployed showing why factors that interfere with coherence in biological signaling systems are necessary and sufficient causes of disorders, diseases, and mortality. Known sources of such formal degeneracy in living organisms (here termed, biosemiotic entropy) include: (a) toxicants, (b) pathogens; (c) excessive exposures to radiant energy and/or sufficiently powerful electromagnetic fields; (d) traumatic injuries; and (e) interactions between the foregoing factors. Just as Jaynes proved that irreversible changes invariably increase entropy, the theory of true narrative representations (TNR theory) demonstrates that factors disrupting the well-formedness (coherence) of valid representations, all else being held equal, must increase biosemiotic entropy—the kind impacting biosignaling systems.

A model study of sequential enzyme reactions and electrostatic channeling

We study models of two sequential enzyme-catalyzed reactions as a basic functional building block for coupled biochemical networks. We investigate the influence of enzyme distributions and long-range molecular interactions on reaction kinetics, which have been exploited in biological systems to maximize metabolic efficiency and signaling effects. Specifically, we examine how the maximal rate of product generation in a series of sequential reactions is dependent on the enzyme distribution and the electrostatic composition of its participant enzymes and substrates. We find that close proximity between enzymes does not guarantee optimal reaction rates, as the benefit of decreasing enzyme separation is countered by the volume excluded by adjacent enzymes. We further quantify the extent to which the electrostatic potential increases the efficiency of transferring substrate between enzymes, which supports the existence of electrostatic channeling in nature. Here, a major finding is that the role of attractive electrostatic interactions in confining intermediate substrates in the vicinity of the enzymes can contribute more to net reactive throughput than the directional properties of the electrostatic fields. These findings shed light on the interplay of long-range interactions and enzyme distributions in coupled enzyme-catalyzed reactions, and their influence on signaling in biological systems.

Aluminum-induced entropy in biological systems: implications for neurological disease.

Over the last 200 years, mining, smelting, and refining of aluminum (Al) in various forms have increasingly exposed living species to this naturally abundant metal. Because of its prevalence in the earth's crust, prior to its recent uses it was regarded as inert and therefore harmless. However, Al is invariably toxic to living systems and has no known beneficial role in any biological systems. Humans are increasingly exposed to Al from food, water, medicinals, vaccines, and cosmetics, as well as from industrial occupational exposure. Al disrupts biological self-ordering, energy transduction, and signaling systems, thus increasing biosemiotic entropy. Beginning with the biophysics of water, disruption progresses through the macromolecules that are crucial to living processes (DNAs, RNAs, proteoglycans, and proteins). It injures cells, circuits, and subsystems and can cause catastrophic failures ending in death. Al forms toxic complexes with other elements, such as fluorine, and interacts negatively with mercury, lead, and glyphosate. Al negatively impacts the central nervous system in all species that have been studied, including humans. Because of the global impacts of Al on water dynamics and biosemiotic systems, CNS disorders in humans are sensitive indicators of the Al toxicants to which we are being exposed.

Дуальность представления информационных сигналов в биосистемах: обобщенная теорема Котельникова

This article presents a conceptual approach to the substantiation of a factor of duality of information presentation, and it signals in biological systems. The purpose is to study relations between discrete and continuous bio-informational signals, which provide all the aspects of functioning of biosystems. Strict physical-mathematical and biophysical evidence of a generalized Kotelnikov theorem for biological systems is formulated. This material is essentially important in the context of the development of the information biophysical models. This aim is realized by the decision of the following tasks. It is shown that a structured living organism is a complex, organized in its hierarchy functional system in which information exchange is carried out set of discrete and continuous (analog) signals of various physical nature: from simple and electrochemical to magnetic and electromagnetic. Their analysis are developed, theorem of duality of presentation of information in biological systems is formulated. Basic generalized theorem Kotelnikov - Yashin (see explanation in the text) with the use of physical and mathematical apparatus of integral equations, the Lebesgue integral, the Fourier and Hubert transforms etc. is formulated and proved. This theorem states that in the biosystem information-containing signal has the quality of dualism, which combines quantum potentiality of the wave function and discreteness of collapsing. This paper contains useful application.

Sensitivity and Robustness in Covalent Modification Cycles with a Bifunctional Converter Enzyme

Regulation by covalent modification is a common mechanism to transmit signals in biological systems. The modifying reactions are catalyzed either by two distinct converter enzymes or by a single bifunctional enzyme (which may employ either one or two catalytic sites for its opposing activities). The reason for this diversification is unclear, but contemporary theoretical models predict that systems with distinct converter enzymes can exhibit enhanced sensitivity to input signals whereas bifunctional enzymes with two catalytic sites are believed to generate robustness against variations in system’s components. However, experiments indicate that bifunctional enzymes can also exhibit enhanced sensitivity due to the zero-order effect, raising the question whether both phenomena could be understood within a common mechanistic model. Here, I argue that this is, indeed, the case. Specifically, I show that bifunctional enzymes with two catalytic sites can exhibit both ultrasensitivity and concentration robustness, depending on the kinetic operating regime of the enzyme’s opposing activities. The model predictions are discussed in the context of experimental observations of ultrasensitivity and concentration robustness in the uridylylation cycle of the PII protein, and in the phosphorylation cycle of the isocitrate dehydrogenase, respectively.

Quorum Sensing Signal Synthesis May Represent a Selective Advantage Independent of Its Role in Regulation of Bioluminescence in Vibrio fischeri

The evolution of biological signalling systems and apparently altruistic or cooperative traits in diverse organisms has required selection against the subversive tendencies of self-interested biological entities. The bacterial signalling and response system known as quorum sensing or Acylated Homoserine Lactone (AHL) mediated gene expression is thought to have evolved through kin selection. In this in vitro study on the model quorum sensing bioluminescent marine symbiont Vibrio fischeri, competition and long-term sub culturing experiments suggest that selection for AHL synthesis (encoded by the AHL synthase gene luxI) is independent of the quorum sensing regulated phenotype (bioluminescence encoded by luxCDABE). Whilst results support the hypothesis that signal response (AHL binding and transcriptional activation encoded by the luxR gene) is maintained through indirect fitness benefits (kin selection), signal synthesis is maintained in the V. fischeri genome over evolutionary time through direct fitness benefits at the individual level from an unknown function.

ChemInform Abstract: Halogen Bonding: An Interim Discussion

AbstractReview: 181 refs.

Polyunsaturated fatty acid derived signaling in reproduction and development: Insights from Caenorhabditis elegans and Drosophila melanogaster

Polyunsaturated fatty acids (PUFAs) exhibit a diverse range of critical functions in biological systems. PUFAs modulate the biophysical properties of membranes and, along with their derivatives, the eicosanoids and endocannabinoids, form a wide array potent lipid signaling molecules. Much of our early understanding of PUFAs and PUFA-derived signaling stems from work in mammals; however, technological advances have made comprehensive lipid analysis possible in small genetic models such as Caenorhabditis elegans and Drosophila melanogaster. These models have a number of advantages, such as simple anatomy and genome-wide genetic screening techniques, which can broaden our understanding of fatty-acid-derived signaling in biological systems. Here we review what is known about PUFAs, eicosanoids, and endocannabinoids in the development and reproduction of C. elegans and D. melanogaster. Fatty acid signaling appears to be fundamental for multicellular organisms, and simple invertebrates often employ functionally similar pathways. In particular, studies in C. elegans and Drosophila are providing insight into the roles of PUFAs and PUFA-derived signaling in early developmental processes, such as meiosis, fertilization, and early embryonic cleavage.

Halogen Bonding: An Interim Discussion

Halogen bonding is a noncovalent interaction that is receiving rapidly increasing attention because of its significance in biological systems and its importance in the design of new materials in a variety of areas, for example, electronics, nonlinear optical activity, and pharmaceuticals. The interactions can be understood in terms of electrostatics/polarization and dispersion; they involve a region of positive electrostatic potential on a covalently bonded halogen and a negative site, such as the lone pair of a Lewis base. The positive potential, labeled a σ hole, is on the extension of the covalent bond to the halogen, which accounts for the characteristic near-linearity of halogen bonding. In many instances, the lateral sides of the halogen have negative electrostatic potentials, allowing it to also interact favorably with positive sites. In this discussion, after looking at some of the experimental observations of halogen bonding, we address the origins of σ holes, the factors that govern the magnitudes of their electrostatic potentials, and the properties of the resulting complexes with negative sites. The relationship of halogen and hydrogen bonding is examined. We also point out that σ-hole interactions are not limited to halogens, but can also involve covalently bonded atoms of Groups IV-VI. Examples of applications in biological/medicinal chemistry and in crystal engineering are mentioned, taking note that halogen bonding can be "tuned" to fit various requirements, that is, strength of interaction, steric factors, and so forth.

Refined Distances Between Paramagnetic Centers of a Multi‐Copper Nitrite Reductase Determined by Pulsed EPR (iDEER) Spectroscopy

Refined Distances Between Paramagnetic Centers of a Multi‐Copper Nitrite Reductase Determined by Pulsed EPR (<i>i</i>DEER) Spectroscopy

Self-organized node coordination scheme based on a biological inter-cell signaling system for wireless sensor networks

In this paper, we propose an energy efficient and delay guaranteed node coordination scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique. With the identification of analogies between biological cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired scheme determines the state of the sensor node, as required by each mission-critical application and as determined by the local environmental conditions. A control analysis and simulation results show that the proposed bio-inspired scheme guarantees the system stability and provides significant energy savings, as well as reliable delay guarantees.

Quantifying Heterogeneity of Cell Death

Heterogeneity is a common property of biological signalling systems. In most cases, heterogeneity is described qualitatively, only for some classes of responses have qualitative measures been proposed. For cell death signalling, this paper is the first to propose a quantification of heterogeneity. The challenge hereby is the dual aspect of heterogeneity. First, only part of the cell population may die while the others survive a specific death stimulus. Second, the time of death can vary from cell to cell.The proposed heterogeneity measure is based on an ℒ1 measure of the deviation between a homogeneous response and the population cumulative density function, on a nonlinearly scaled time. This measure allows for a quantitative study of the dependency of the heterogeneity of the responses to different stimulus doses or parametric variations. This will for example enable sensitivity analyses of heterogeneity.The heterogeneity measure is illustrated by applying it to two different published cell ensemble models of apoptosis signalling, each having approximately 50 states and over 100 kinetic parameters. This analysis reveals that heterogeneity is more pronounced at an intermediate range of doses. In other words, high doses or low ones yield more homogeneous responses in the cell population.

Learnt information in species-specific ‘trail pheromone’ communication in stingless bees

Specificity in biological signalling systems is often important to keep information private. Foragers of several species of stingless bees deposit chemical marking signals to guide nestmates to food sources. The markings show species- and colony-specific compositions and primarily attract a bee's nestmates. An interesting question is whether the bees innately recognize specific trail markings or learn their particular composition from nestmates. To investigate this question, we tested whether Scaptotrigona pectoralis and Scaptotrigona subobscuripennis workers taken from their mother colonies and workers that emerged from combs transferred to foster colonies of the congeneric species are attracted to the marking compounds of workers from their natal colony or from the foster colony. A significant majority of workers were attracted to extracts prepared from foragers of the nest they inhabited, regardless of whether this was the original mother or the congeneric foster colony. Thus, the preference of stingless bee workers for specific food-marking scent mixtures is not innate, but is influenced by the odour they experience within their colony. Despite marked differences in the chemical composition of the scent marks in labial gland secretions of the two investigated species they also shared some main components. We hypothesize that recruitment trail information in stingless bees is composed of one or a few key pheromone compounds acting in conjunction with an additional signature mixture that is species and colony specific and must be learnt by recruited workers.

Signalling through mechanical inputs – a coordinated process

There is growing awareness that mechanical forces - in parallel to electrical or chemical inputs - have a central role in driving development and influencing the outcome of many diseases. However, we still have an incomplete understanding of how such forces function in coordination with each other and with other signalling inputs in vivo. Mechanical forces, which are generated throughout the organism, can produce signals through force-sensitive processes. Here, we first explore the mechanisms through which forces can be generated and the cellular responses to forces by discussing several examples from animal development. We then go on to examine the mechanotransduction-induced signalling processes that have been identified in vivo. Finally, we discuss what is known about the specificity of the responses to different forces, the mechanisms that might stabilize cells in response to such forces, and the crosstalk between mechanical forces and chemical signalling. Where known, we mention kinetic parameters that characterize forces and their responses. The multi-layered regulatory control of force generation, force response and force adaptation should be viewed as a well-integrated aspect in the greater biological signalling systems.

125thAnniversary Review: The role of proteins in beer redox stability

Flavour stability is usually approached through inhibition of reactive oxygen species (ROS). It may be possible to suppress ROS, but never to entirely eliminate them in packaged beer. The role of proteins in ROS suppression seems to have been lost in the compliant acquiescence to supply haze-free bright beer. Proteomics allows beer polypeptides to be finely resolved, identified and correlated with beer quality and stability. This has already produced a broader view of what stabilizes beer foam. No doubt it could do the same for beer stability and the broader roles that proteins, such as LTP1, can have in redox reactions and free radical suppression. Cysteine oxidation and reversibility is central to cellular signalling in biological systems. Thiol chemistry is also integral to beer redox stability. We can, and should, extrapolate the recent biological findings to the simple pleasure of creating a high-quality beer. Copyright © 2012 The Institute of Brewing & Distilling

Gain control in molecular information processing: lessons from neuroscience

Statistical properties of environments experienced by biological signaling systems in the real world change, which necessitates adaptive responses to achieve high fidelity information transmission. One form of such adaptive response is gain control. Here, we argue that a certain simple mechanism of gain control, understood well in the context of systems neuroscience, also works for molecular signaling. The mechanism allows us to transmit more than 1 bit (on or off) of information about the signal independent of the signal variance. It does not require additional molecular circuitry beyond that already present in many molecular systems, and in particular, it does not depend on existence of feedback loops. The mechanism provides a potential explanation for abundance of ultrasensitive response curves in biological regulatory networks.

Multi-Scale Stochastic Simulation of Diffusion-Coupled Agents and Its Application to Cell Culture Simulation

Many biological systems consist of multiple cells that interact by secretion and binding of diffusing molecules, thus coordinating responses across cells. Techniques for simulating systems coupling extracellular and intracellular processes are very limited. Here we present an efficient method to stochastically simulate diffusion processes, which at the same time allows synchronization between internal and external cellular conditions through a modification of Gillespie's chemical reaction algorithm. Individual cells are simulated as independent agents, and each cell accurately reacts to changes in its local environment affected by diffusing molecules. Such a simulation provides time-scale separation between the intra-cellular and extra-cellular processes. We use our methodology to study how human monocyte-derived dendritic cells alert neighboring cells about viral infection using diffusing interferon molecules. A subpopulation of the infected cells reacts early to the infection and secretes interferon into the extra-cellular medium, which helps activate other cells. Findings predicted by our simulation and confirmed by experimental results suggest that the early activation is largely independent of the fraction of infected cells and is thus both sensitive and robust. The concordance with the experimental results supports the value of our method for overcoming the challenges of accurately simulating multiscale biological signaling systems.

How uniform is cAMP signaling? Focus on “Systems analysis of GLP-1 receptor signaling in pancreatic β-cells”

the goal of many cell physiologists is to ascribe cellular behavior to specific molecular signaling mechanisms. However, the reductionist experimental approach commonly used to understand molecular function often makes this task harder rather than easier to accomplish because of the complexity of

Classification of Cell Signalling in Tissue Development

The traditional classification of signalling in biological systems is insufficient and outdated and novel efforts must take into account advances in systems theory, information theory and linguistics. We present some of the classification systems currently used both within and outside of the biological field and discuss some specific aspects of the nature of signalling in tissue development. The analytical methods used in understanding non-biological networks provide a valuable vocabulary, which requires integration and a system of classification to further facilitate development.