Homeostatic mechanisms of biological systems: Development homeostasis

Homeostasis as an ability to maintain structural-functional parameters of the system at the required level is a basic characteristic for providing the stability of any biological system (from biosphere and separate ecosystems to communities, populations, and individuals). The study of homeostatic mechanisms that provide the stability of biological systems is the main task for solving many theoretical and practical questions. The search for criteria of homeostasis estimation and study of homeostatic mechanism ratio at different levels are principally important in this direction. Estimation of the role of homeostatic mechanisms of the organism and population for providing the stability of biological systems of different levels when using the approach based on estimation of the population state from ontogenetic positions (population developmental biology) seems promising.     

Volume signalling in real and robot nervous systems

Summary This paper presents recent work in computational modelling of diffusing gaseous neuromodulators in biological nervous systems. A variety of interesting and significant properties of such four dimensional neural signalling systems are demonstrated. It is shown that the morphology of the neuromodulator source plays a highly significant role in the diffusion patterns observed. The paper goes on to describe work in adaptive autonomous systems directly inspired by this: an exploration of the use of virtual diffusing modulators in robot nervous systems built from non-standard artificial neural networks. These virtual chemicals act over space and time modulating a variety of node and connection properties in the networks. A wide variety of rich dynamics are possible in such systems; in the work described here, evolutionary robotics techniques have been used to harness the dynamics to produce autonomous behaviour in mobile robots. Detailed comparative analyses of evolutionary searches, and search spaces, for robot controllers with and without the virtual gases are introduced. The virtual diffusing modulators are found to provide significant advantages.     

An evolving model of undirected networks based on microscopic biological interaction systems

With protein or gene interaction systems as the background, this paper proposes an evolving model of biological undirected networks, which are consistent with some plausible mechanisms in biology. Through introducing a rule of preferential duplication of a node inversely proportional to the degree of existing nodes and an attribute of the age of the node (the older, the more influence), by which the probability of a node receiving re-wiring links is chosen, the model networks generated in certain parameter conditions could reproduce series of statistic topological characteristics of real biological graphs, including the scale-free feature, small world effect, hierarchical modularity, limited structural robustness, and disassortativity of degree–degree correlation.     

Regulating quiescence: new insights into hematopoietic stem cell biology

Blood-forming hematopoietic stem cells (HSCs) ensure production of all mature blood cells during homeostatic and regenerative hematopoiesis. Proliferation, cell cycle regulation, and quiescence are key processes involved in this function, and in a recent issue of Cancer Cell, show that HSC quiescence is actively regulated by specific molecular mechanisms that appear to distinguish normal HSC maintenance from HSC responses to hematologic injury.     

Robust Concentration and Frequency Control in Oscillatory Homeostats

Homeostatic and adaptive control mechanisms are essential for keeping organisms structurally and functionally stable. Integral feedback is a control theoretic concept which has long been known to keep a controlled variable robustly (i.e. perturbation-independent) at a given set-point by feeding the integrated error back into the process that generates . The classical concept of homeostasis as robust regulation within narrow limits is often considered as unsatisfactory and even incompatible with many biological systems which show sustained oscillations, such as circadian rhythms and oscillatory calcium signaling. Nevertheless, there are many similarities between the biological processes which participate in oscillatory mechanisms and classical homeostatic (non-oscillatory) mechanisms. We have investigated whether biological oscillators can show robust homeostatic and adaptive behaviors, and this paper is an attempt to extend the homeostatic concept to include oscillatory conditions. Based on our previously published kinetic conditions on how to generate biochemical models with robust homeostasis we found two properties, which appear to be of general interest concerning oscillatory and homeostatic controlled biological systems. The first one is the ability of these oscillators (“oscillatory homeostats”) to keep the average level of a controlled variable at a defined set-point by involving compensatory changes in frequency and/or amplitude. The second property is the ability to keep the period/frequency of the oscillator tuned within a certain well-defined range. In this paper we highlight mechanisms that lead to these two properties. The biological applications of these findings are discussed using three examples, the homeostatic aspects during oscillatory calcium and p53 signaling, and the involvement of circadian rhythms in homeostatic regulation.     

Dynamical roles of biological regulatory circuits

Regulatory circuits are found at the basis of all non-trivial dynamical properties of biological networks. More specifically, positive circuits are involved in the generation of multiple differentiated states, whereas negative circuits can generate cyclic or homeostatic behaviours. These notions are briefly reviewed, from initial biological formulations to mathematical formalisations, further encompassing their application to the design of synthetic regulatory systems. Finally, current challenges for the analysis of increasingly complex regulatory networks are indicated, as well as prospects for our understanding of development and evolution.     

Quiescence: early evolutionary origins and universality do not imply uniformity

Cell cycle investigations have focused on relentless exponential proliferation of cells, an unsustainable situation in nature. Proliferation of cells, whether microbial or metazoan, is interrupted by periods of quiescence. The vast majority of cells in an adult metazoan lie quiescent. As disruptions in this quiescence are at the foundation of cancer, it will be important for the field to turn its attention to the mechanisms regulating quiescence. While often presented as a single topic, there are multiple forms of quiescence each with complex inputs, some of which are tied to conceptually challenging aspects of metazoan regulation such as size control. In an effort to expose the enormity of the challenge, I describe the differing biological purposes of quiescence, and the coupling of quiescence in metazoans to growth and to the structuring of tissues during development. I emphasize studies in the organism rather than in tissue culture, because these expose the diversity of regulation. While quiescence is likely to be a primitive biological process, it appears that in adapting quiescence to its many distinct biological settings, evolution has diversified it. Consideration of quiescence in different models gives us an overview of this diversity.     

Analysis of Homeostatic Mechanisms in Biochemical Networks

Cell metabolism is an extremely complicated dynamical system that maintains important cellular functions despite large changes in inputs. This “homeostasis” does not mean that the dynamical system is rigid and fixed. Typically, large changes in external variables cause large changes in some internal variables so that, through various regulatory mechanisms, certain other internal variables (concentrations or velocities) remain approximately constant over a finite range of inputs. Outside that range, the mechanisms cease to function and concentrations change rapidly with changes in inputs. In this paper we analyze four different common biochemical homeostatic mechanisms: feedforward excitation, feedback inhibition, kinetic homeostasis, and parallel inhibition. We show that all four mechanisms can occur in a single biological network, using folate and methionine metabolism as an example. Golubitsky and Stewart have proposed a method to find homeostatic nodes in networks. We show that their method works for two of these mechanisms but not the other two. We discuss the many interesting mathematical and biological questions that emerge from this analysis, and we explain why understanding homeostatic control is crucial for precision medicine.     

Fast homeostatic plasticity of inhibition via activity-dependent vesicular filling

Synaptic activity in the central nervous system undergoes rapid state-dependent changes, requiring constant adaptation of the homeostasis between excitation and inhibition. The underlying mechanisms are, however, largely unclear. Chronic changes in network activity result in enhanced production of the inhibitory transmitter GABA, indicating that presynaptic GABA content is a variable parameter for homeostatic plasticity. Here we tested whether such changes in inhibitory transmitter content do also occur at the fast time scale required to ensure inhibition-excitation-homeostasis in dynamic cortical networks. We found that intense stimulation of afferent fibers in the CA1 region of mouse hippocampal slices yielded a rapid and lasting increase in quantal size of miniature inhibitory postsynaptic currents. This potentiation was mediated by the uptake of GABA and glutamate into presynaptic endings of inhibitory interneurons (the latter serving as precursor for the synthesis of GABA). Thus, enhanced release of inhibitory and excitatory transmitters from active networks leads to enhanced presynaptic GABA content. Thereby, inhibitory efficacy follows local neuronal activity, constituting a negative feedback loop and providing a mechanism for rapid homeostatic scaling in cortical circuits.     

Interaction between differentiating cell- and niche-derived signals in hematopoietic progenitor maintenance

Maintenance of a hematopoietic progenitor population requires extensive interaction with cells within a microenvironment or niche. In the Drosophila hematopoietic organ, niche-derived Hedgehog signaling maintains the progenitor population. Here, we show that the hematopoietic progenitors also require a signal mediated by Adenosine deaminase growth factor A (Adgf-A) arising from differentiating cells that regulates extracellular levels of adenosine. The adenosine signal opposes the effects of Hedgehog signaling within the hematopoietic progenitor cells and the magnitude of the adenosine signal is kept in check by the level of Adgf-A secreted from differentiating cells. Our findings reveal signals arising from differentiating cells that are required for maintaining progenitor cell quiescence and that function with the niche-derived signal in maintaining the progenitor state. Similar homeostatic mechanisms are likely to be utilized in other systems that maintain relatively large numbers of progenitors that are not all in direct contact with the cells of the niche.     

Saltatory transitions are a naturally occurring property of evolving systems

On the basis of paleological evidence, it has been suggested that biological evolution need not necessarily be characterized by gradual change. Rather, evolutionary history may display saltatory periods of rapid speciation alternating with periods of relative quiescence, the whole dynamic being called punctuated equilibria. The empirical evidence that has been presented in support of this hypothesis has been the object of a vigorous dispute. Mathematical investigations of complex models of biological evolution that contain random elements have demonstrated that these systems can display saltatory behavior. In this paper we address a more abstract question: can saltations occur in the evolution of very simple, deterministic mathematical systems that function in a constant environment? The answer appears to be yes. Saltations appear as a natural dynamical behavior in the evolution of simplistic information processing networks. We stress that these networks do not constitute a model of biological evolution. However, the appearance of saltations in such simple systems suggests that their appearance in a process as complex as biological evolution is not surprising.     

In silico evolution of functional modules in biochemical networks

Understanding the large reaction networks found in biological systems is a daunting task. One approach is to divide a network into more manageable smaller modules, thus simplifying the problem. This is a common strategy used in engineering. However, the process of identifying biological modules is still in its infancy and very little is understood about the range and capabilities of motif structures found in biological modules. In order to delineate these modules, a library of functional motifs has been generated via in silico evolution techniques. On the basis of their functional forms, networks were evolved from four broad areas: oscillators, bistable switches, homeostatic systems and frequency filters. Some of these motifs were constructed from simple mass action kinetics, others were based on Michaelis-Menten kinetics as found in protein/protein networks and the remainder were based on Hill equations as found in gene/protein interaction networks. The purpose of the study is to explore the capabilities of different network architectures and the rich variety of functional forms that can be generated. Ultimately, the library may be used to delineate functional motifs in real biological networks.     

Organization of excitable dynamics in hierarchical biological networks

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.     

Bridging the gap - from ion channels to networks and behaviour

A major challenge for current research in neuroscience is to understand the intrinsic operation of the functional modules of the central nervous system, such as those formed by cortical columns and the neuronal networks controlling motor behaviour. Most vertebrate experimental models used in network analyses involve developing nervous systems, which are in rapid transition with regard to their cellular properties and the expression of different ion channels. Recent advances in our understanding of the cellular and circuit properties of motor networks are making it possible to decipher the mechanisms involved in vertebrate motor pattern generation.     

3种禾草圆锥花序小穗及小花分布格局的比较

分析草芦、鸭茅、苇状羊茅 3种圆锥花序禾草小穗及小花的分布格局 ,结果表明 ,3种禾草在各节位上的小穗、小花数量均适合于Weibull分布 ,随着节位序的增加均呈饱和型曲线增长 .通过赋予各统计参数生物学涵义 ,从宏观上分析与揭示了有关生命现象与发展规律及其生物生态学机理 .     

A survey on biomarker identification based on molecular networks

Background: Identifying biomarkers for accurate diagnosis and prognosis of diseases is important for the prevention of disease development. The molecular networks that describe the functional relationships among molecules provide a global view of the complex biological systems. With the molecular networks, the molecular mechanisms underlying diseases can be unveiled, which helps identify biomarkers in a systematic way. Results: In this survey, we report the recent progress on identifying biomarkers based on the topology of molecular networks, and we categorize those biomarkers into three groups, including node biomarkers, edge biomarkers and network biomarkers. These distinct types of biomarkers can be detected under different conditions depending on the data available. Conclusions: The biomarkers identified based on molecular networks can provide more accurate diagnosis and prognosis. The pros and cons of different types of biomarkers as well as future directions to improve the methods for identifying biomarkers are also discussed.     

Recent Progress on the Analysis of Power-law Features in Complex Cellular Networks

Complex interactions between different kinds of bio-molecules and essential nutrients are responsible for cellular functions. Rapid advances in theoretical modeling and experimental analyses have shown that drastically different biological and non-biological networks share a common architecture. That is, the probability that a selected node in the network has exactly k edges decays as a power-law. This finding has definitely opened an intense research and debate on the origin and implications of this ubiquitous pattern. In this review, we describe the recent progress on the emergence of power-law distributions in cellular networks. We first show the internal characteristics of the observed complex networks uncovered using graph theory. We then briefly review some works that have significantly contributed to the theoretical analysis of cellular networks and systems, from metabolic and protein networks to gene expression profiles. This prevalent topology observed in so many diverse biological systems suggests the existence of generic laws and organizing principles behind the cellular networks.     

Molecular mechanisms of homeostatic plasticity in central pattern generator networks

Central pattern generator (CPG) networks rely on a balance of intrinsic and network properties to produce reliable, repeatable activity patterns. This balance is maintained by homeostatic plasticity where alterations in neuronal properties dynamically maintain appropriate neural output in the face of changing environmental conditions and perturbations. However, it remains unclear just how these neurons and networks can both monitor their ongoing activity and use this information to elicit homeostatic physiological responses to ensure robustness of output over time. Evidence exists that CPG networks use a mixed strategy of activity‐dependent, activity‐independent, modulator‐dependent, and synaptically regulated homeostatic plasticity to achieve this critical stability. In this review, we focus on some of the current understanding of the molecular pathways and mechanisms responsible for this homeostatic plasticity in the context of central pattern generator function, with a special emphasis on some of the smaller invertebrate networks that have allowed for extensive cellular‐level analyses that have brought recent insights to these questions.     

Homeostatic activity-dependent paradigm for neurotransmitter specification

Calcium-signaling plays a central role in specification of the chemical transmitters neurons express, adjusting the numbers of cells that express excitatory and inhibitory transmitters as if to achieve homeostatic regulation of excitability. Here we review the extent to which this activity-dependent regulation is observed for a range of different transmitters. Strikingly the homeostatic paradigm is observed both for classical and for peptide transmitters and in mature as well as in embryonic nervous systems. Transmitter homeostasis adds another dimension to homeostatic regulation of function in the nervous system that includes regulation of levels of voltage-gated ion channels, densities of neurotransmitter receptors, and synapse numbers and strength.     

Catecholamines in adrenergic nerve fibers of the lymph nodes after sympathectomy

Using Falck method in combination with microfluorimetry, catecholamine level in adrenergic nervous fibers has been measured in the canine popliteal lymph nodes, normal and in 12 h, 7, 30, and 90 days after unilateral lumbar sympathectomy. During first 24 h after the operation the level of catecholamines is for certain increased in the nervous fibers of the lymph node of the sympathectomized extremity. In 30 days after the sympathectomy their content drops at the side of the operation and increases in the contralateral extremity. By 3 months the equilibrium of the catecholamine content is restored in the nervous fibers of the lymph nodes in the homo- and contralateral extremities at the level higher than in the control. A conclusion is made that under conditions of unilateral sympathectomy only a partial sympathectomy of the popliteal lymph node is reached. All luminiscent adrenergic nervous fibers of the sympathectomized lymph node are processes of neurons, situating in the contralateral sympathetic trunk, or neurites of cells in sacral nodes, getting their preganglionic fibers from the contralateral trunk. The changes in catecholamine concentrations mentioned are considered as a compensatory reaction, directed to maintenance of general homeostatic equilibrium under conditions, when the nervous system transfers to a new level, ensuring the partly desympathized tissue by mediators.