From proteomics toward systems biology: integration of different types of proteomics data into network models

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.     

Anticipatory Functions, Digital-Analog Forms and Biosemiotics: Integrating the Tools to Model Information and Normativity in Autonomous Biological Agents

We argue that living systems process information such that functionality emerges in them on a continuous basis. We then provide a framework that can explain and model the normativity of biological functionality. In addition we offer an explanation of the anticipatory nature of functionality within our overall approach. We adopt a Peircean approach to Biosemiotics, and a dynamical approach to Digital-Analog relations and to the interplay between different levels of functionality in autonomous systems, taking an integrative approach. We then apply the underlying biosemiotic logic to a particular biological system, giving a model of the B-Cell Receptor signaling system, in order to demonstrate how biosemiotic concepts can be used to build an account of biological information and functionality. Next we show how this framework can be used to explain and model more complex aspects of biological normativity, for example, how cross-talk between different signaling pathways can be avoided. Overall, we describe an integrated theoretical framework for the emergence of normative functions and, consequently, for the way information is transduced across several interconnected organizational levels in an autonomous system, and we demonstrate how this can be applied in real biological phenomena. Our aim is to open the way towards realistic tools for the modeling of information and normativity in autonomous biological agents.     

Bootstrap choice of estimators in parametric and semiparametric families: an extension of EIC

Ishiguro, Sakamoto, and Kitagawa (1997, Annals of the Institute of Statistical Mathematics 49, 411-434) proposed EIC as an extension of Akaike criterion (AIC); the idea leading to EIC is to correct the bias of the log-likelihood, considered as an estimator of the Kullback-Leibler information, using bootstrap. We develop this criterion for its use in multivariate semiparametric situations, and argue that it can be used for choosing among parametric and semiparametric estimators. A simulation study based on aregression model shows that EIC is better than its competitors although likelihood cross-validation performs nearly as well except for small sample size. Its use is illustrated by estimating the mean evolution of viral RNA levels in a group of infants infected by HIV.     

Information compression in biological systems

In biological systems a high coordination between their individual parts occurs. The concept of coordination can be given a rigorous mathematical basis by the concept of order parameters and the slaving principle. We calculate the information of the total system in terms of order parameters and slaved subsystems. When qualitative changes of a system happen, the information change is given by that of the order parameter alone and may amount to few bits only.     

Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks.     

On the thermodynamics of multilevel evolution

Biodiversity is hierarchically structured both phylogenetically and functionally. Phylogenetic hierarchy is understood as a product of branching organic evolution as described by Darwin. Ecosystem biologists understand some aspects of functional hierarchy, such as food web architecture, as a product of evolutionary ecology; but functional hierarchy extends to much lower scales of organization than those studied by ecologists. We argue that the more general use of the term “evolution” employed by physicists and applied to non-living systems connects directly to the narrow biological meaning. Physical evolution is best understood as a thermodynamic phenomenon, and this perspective comfortably includes all of biological evolution. We suggest four dynamical factors that build on each other in a hierarchical fashion and set the stage for the Darwinian evolution of biological systems: (1) the entropic erosion of structure; (2) the construction of dissipative systems; (3) the reproduction of growing systems and (4) the historical memory accrued to populations of reproductive agents by the acquisition of hereditary mechanisms. A particular level of evolution can underpin the emergence of higher levels, but evolutionary processes persist at each level in the hierarchy. We also argue that particular evolutionary processes can occur at any level of the hierarchy where they are not obstructed by material constraints. This theoretical framework provides an extensive basis for understanding natural selection as a multilevel process. The extensive literature on thermodynamics in turn provides an important advantage to this perspective on the evolution of higher levels of organization, such as the evolution of altruism that can accompany the emergence of social organization.     

Coordination of many oscillators and generation of locomotory patterns

This paper considers a synthesis approach to a decentralized autonomous system in which the functional order of the entire system is generated by cooperative interaction among its subsystems, each of which has the autonomy to control a part of the state of the system, and its application to pattern generators of animal locomotion. First, biological locomotory rhythms and their generators, swimming patterns of aquatic animals and gait patterns of quadrupeds, are reviewed briefly. Then, a design principle for autonomous coordination of many oscillators is proposed. Using these results, we synthesize a swimming pattern generator and a gait pattern generator. Finally, it is shown using computer simulations that the proposed systems generate desirable patterns.     

Characterizing the role benthos plays in large coastal seas and estuaries: A modular approach

Ecologists studying coastal and estuarine benthic communities have long taken a macroecological view, by relating benthic community patterns to environmental factors across several spatial scales. Although many general ecological patterns have been established, often a significant amount of the spatial and temporal variation in soft-sediment communities within and among systems remains unexplained. Here we propose a framework that may aid in unraveling the complex influence of environmental factors associated with the different components of coastal systems (i.e. the terrestrial and benthic landscapes, and the hydrological seascape) on benthic communities, and use this information to assess the role played by benthos in coastal ecosystems. A primary component of the approach is the recognition of system modules (e.g. marshes, dendritic systems, tidal rivers, enclosed basins, open bays, lagoons). The modules may differentially interact with key forcing functions (e.g. temperature, salinity, currents) that influence system processes and in turn benthic responses and functions. Modules may also constrain benthic characteristics and related processes within certain ecological boundaries and help explain their overall spatio-temporal variation. We present an example of how benthic community characteristics are related to the modular structure of 14 coastal seas and estuaries, and show that benthic functional group composition is significantly related to the modular structure of these systems. We also propose a framework for exploring the role of benthic communities in coastal systems using this modular approach and offer predictions of how benthic communities may vary depending on the modular composition and characteristics of a coastal system.     

When two become one: the limits of causality analysis of brain dynamics

Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM). Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest.     

Multi-level convergence of complex traits and the evolution of bioluminescence

Evolutionary convergence provides natural opportunities to investigate how, when, and why novel traits evolve. Many convergent traits are complex, highlighting the importance of explicitly considering convergence at different levels of biological organization, or ‘multi-level convergent evolution’. To investigate multi-level convergent evolution, we propose a holistic and hierarchical framework that emphasizes breaking down traits into several functional modules. We begin by identifying long-standing questions on the origins of complexity and the diverse evolutionary processes underlying phenotypic convergence to discuss how they can be addressed by examining convergent systems. We argue that bioluminescence, a complex trait that evolved dozens of times through either novel mechanisms or conserved toolkits, is particularly well suited for these studies. We present an updated estimate of at least 94 independent origins of bioluminescence across the tree of life, which we calculated by reviewing and summarizing all estimates of independent origins. Then, we use our framework to review the biology, chemistry, and evolution of bioluminescence, and for each biological level identify questions that arise from our systematic review. We focus on luminous organisms that use the shared luciferin substrates coelenterazine or vargulin to produce light because these organisms convergently evolved bioluminescent proteins that use the same luciferins to produce bioluminescence. Evolutionary convergence does not necessarily extend across biological levels, as exemplified by cases of conservation and disparity in biological functions, organs, cells, and molecules associated with bioluminescence systems. Investigating differences across bioluminescent organisms will address fundamental questions on predictability and contingency in convergent evolution. Lastly, we highlight unexplored areas of bioluminescence research and advances in sequencing and chemical techniques useful for developing bioluminescence as a model system for studying multi-level convergent evolution.     

Functional annotation of hierarchical modularity

In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology) and the association of individual genes or proteins with these concepts (e.g., GO terms), our method will assign a Hierarchical Modularity Score (HMS) to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our method using Saccharomyces cerevisiae data from KEGG and MIPS databases and several other computationally derived and curated datasets. The code and additional supplemental files can be obtained from http://code.google.com/p/functional-annotation-of-hierarchical-modularity/ (Accessed 2012 March 13).     

THE BIOLOGY OF PUBERTY

The objective of this review was to develop a broader, more biological, overview of puberty, as opposed to the more limited, laboratory-dominated, view that has emanated from experimental physiology. Three conceptual schemes form the basis for our broader perspective. The first deals with the ways in which genes and environmental factors interact to program the timing of reproductive development. The second focuses on the ways environmental factors interact with each other to influence puberty. The third relates the genetic and environmental controls to specific endocrine and neuroendocrine pathways of action.
The more traditional approach of studying domesticated animals under carefully controlled conditions predetermines one's conclusions. One logically will conclude that the final stages of reproductive development are rather rigidly determined genetically and not greatly subject to environmental regulation, except for obviously adaptive pheromonal and photoperiodic regulation. One also will search within the reproductive axis itself for the final developmental step that allows functional fertility. In contrast, a more biological view suggests that for most mammals puberty is a highly labile process subject to several kinds of environmental influences that operate at many times during a mammal's life. Furthermore this perspective suggests that the final developmental step allowing fertility onset normally will occur outside rather than within the reproductive axis proper. This conclusion has a potentially great impact upon the way we look at the organization of the brain and endocrine system and in the way we choose animal models for studying human puberty and the types of controls we study.     

On the stationary state analysis of reaction-diffusion mechanisms for biological pattern formation

We present a biologically plausible two-variable reaction-diffusion model for the developing vertebrate limb, for which we postulate the existence of a stationary solution. A consequence of this assumption is that the stationary state depends on only a single concentration-variable. Under these circumstances, features of potential biological significance, such as the dependence of the steady-state concentration profile of this variable on parameters such as tissue size and shape, can be studied without detailed information about the rate functions. As the existence and stability of stationary solutions, which must be assumed for any biochemical system governing morphogenesis, cannot be investigated without such information, an analysis is made of the minimal requirements for stable, stationary non-uniform solutions in a general class of reaction-diffusion systems. We discuss the strategy of studying stationary-state properties of systems that are incompletely specified. Where abrupt transitions between successive compartment-sizes occur, as in the developing limb, we argue that it is reasonable to model pattern reorganization as a sequence of independent stationary states.     

The inactivation of alpha-1-proteinase inhibitor by gas-phase cigarette smoke: protection by antioxidants and reducing species

The abilities of a number of compounds of biological interest to protect alpha-1-proteinase inhibitor (alPI) against the loss of elastase inhibitory capacity (EIC) resulting from exposure to gas-phase cigarette smoke have been tested. We have identified several species that protect AlPI. Amino acids prevent the loss of EIC in a manner that correlates with their pK alpha-values; only the unprotonated amine provides protection. Catalase partially prevents the loss of EIC, suggesting that hydrogen peroxide produced from the reduction of oxygen in cigarette smoke extracts is responsible for at least some of the smoke-induced inactivation. The best protection against smoke-induced loss of EIC was provided by two biologically important antioxidant species: glutathione and ascorbic acid. Both species provide almost complete protection to alPI under the experimental conditions used. The nature of species that protect AlPI against the inactivation caused by exposure to gas-phase smoke provides clues upon which speculations about the mechanism of this inactivation may be based. The identification of protective species could lead to the development of compounds that smokers could take (for example, vitamin C) that would protect their lung tissue against the oxidative damage caused by cigarette smoke.     

Pheromonal and host-odor processing in the insect antennal lobe: how different?

In the olfactory bulb of vertebrates and the antennal lobe of insects, precise connections between sensory receptor cells and olfactory glomeruli form the basis of a highly organized chemotopic map at the first stage of central processing in the brain. Beyond this basic level of organization, the olfactory system is typically separated into two subsystems: a 'main' olfactory pathway that detects and processes information about most environmental odorants, and an 'accessory' olfactory pathway that is devoted to information about social signals such as sex pheromones. A growing number of studies show, however, that it is not always possible to draw clear functional distinctions between the two subsystems. These findings have led some to speculate that the organizational principles by which olfactory stimuli are represented across glomeruli may be more similar in these two olfactory subsystems than previously thought.     

New approaches to the system regulating the aggregate state of the blood]

It is shown that in the organism there is an adrenoreactive system of the aggregate blood state regulation (ABSR) including alpha- and beta-adrenoreactive structures of hypothalamus, amygdalar complex and peripheral vessels. The ABSR system consists of two subsystems, each possessing specific action. Both subsystems interact in the reciprocal manner by the mechanism of feedbacks and can exert a modulating effect on each other.     

A theory for environmental systems

A theory for environmental systems is defined on the basis of two elements, termed ‘environmental unity’ and ‘behavior’. Environmental systems are regarded as non-living systems, each one related with only one biological system. We construct a material-energetic environmental diagram, which is introduced in terms of the theory of categories, thereby giving rise to a new categoryE. By means of two biological conditions, and the definition of static property of the biological system (related to its own environment), a set of theorems is obtained, exhibiting mathematical consequences for the represented theory.