From biological pathways to regulatory networks

This paper presents a general theoretical framework for generating Boolean networks whose state transitions realize a set of given biological pathways or minor variations thereof. This ill-posed inverse problem, which is of crucial importance across practically all areas of biology, is solved by using Karnaugh maps which are classical tools for digital system design. It is shown that the incorporation of prior knowledge, presented in the form of biological pathways, can bring about a dramatic reduction in the cardinality of the network search space. Constraining the connectivity of the network, the number and relative importance of the attractors, and concordance with observed time-course data are additional factors that can be used to further reduce the cardinality of the search space. The networks produced by the approaches developed here should facilitate the understanding of multivariate biological phenomena and the subsequent design of intervention approaches that are more likely to be successful in practice. As an example, the results of this paper are applied to the widely studied p53 pathway and it is shown that the resulting network exhibits dynamic behavior consistent with experimental observations from the published literature.     

Measurement of biological information with applications from genes to landscapes

Biological diversity is quantified for reasons ranging from primer design, to bioprospecting, and community ecology. As a common index for all levels, we suggest Shannon's (S)H, already used in information theory and biodiversity of ecological communities. Since Lewontin's first use of this index to describe human genetic variation, it has been used for variation of viruses, splice-junctions, and informativeness of pedigrees. However, until now there has been no theory to predict expected values of this index under given genetic and demographic conditions. We present a new null theory for (S)H at the genetic level, and show that this index has advantages including (i) independence of measures at each hierarchical level of organization; (ii) robust estimation of genetic exchange over a wide range of conditions; (iii) ability to incorporate information on population size; and (iv) explicit relationship to standard statistical tests. Utilization of this index in conjunction with other existing indices offers powerful insights into genetic processes. Our genetic theory is also extendible to the ecological community level, and thus can aid the comparison and integration of diversity at the genetic and community levels, including the need for measures of community diversity that incorporate the genetic differentiation between species.     

Natural enemy diversity and biological control: Making sense of the context-dependency

Numerous studies have demonstrated that diverse predator assemblages can be more effective at controlling prey populations. Yet, other studies have shown no effect of predator diversity on prey mortality, or even negative effects (for example due to intraguild predation or interference). Much research emphasis has been placed on the traits of predators that maximise functional complementarity. However, comparatively less attention has been paid to the traits of the prey or habitat that may maximise predator diversity effects, even though there must be a variety of prey niches available to be partitioned in order for niche complementarity to occur. Following this logic, we review six hypotheses for when diverse enemy assemblages should be most effective: when 1) prey communities are diverse; 2) prey have complex life cycles; 3) prey are patchily distributed in space or time; 4) studies are conducted at larger spatial and temporal scales; 5) plant structures are complex; 6) prey are abundant. Many of these hypotheses lack direct tests, particularly in agricultural systems, but we find little or no direct or indirect support for hypotheses 1, 4, 5 and 6. However, previous work does provide some support for hypotheses 2 and 3. We discuss methods to test these hypotheses directly, and suggest that natural enemy diversity may only benefit the biological control of arthropods in heterogeneous systems.     

From genes to networks: in systematic points of view

We present a report of the BIOCOMP'10 - The 2010 International Conference on Bioinformatics & Computational Biology and other related work in the area of systems biology.     

Plant 'evo-devo' goes genomic: from candidate genes to regulatory networks

Plant development gives rise to a staggering complexity of morphological structures with different shapes, colors, and functions. Understanding the evolution of control mechanisms that underlie developmental processes provides insights into causes of morphological diversity and, therefore, is of great interest to biologists. New genomic resources and techniques enable biologists to assess for the first time the evolution of developmental regulatory networks at a global scale. Here, we address the question of how comparative regulatory genomics can be used to reveal the evolutionary dynamics of control networks linked to morphological evolution in plants.     

Theoretical approaches to holistic biological features: Pattern formation,neural networks and the brain-mind relation

The topic of this article is the relation between bottom-up and top-down, reductionist and “holistic” approaches to the solution of basic biological problems. While there is no doubt that the laws of physics apply to all events in space and time, including the domains of life, understanding biology depends not only on elucidating the role of the molecules involved, but, to an increasing extent, on systems theoretical approaches in diverse fields of the life sciences. Examples discussed in this article are the generation of spatial patterns in development by the interplay of autocatalysis and lateral inhibition; the evolution of integrating capabilities of the human brain, such as cognition-based empathy; and both neurobiological and epistemological aspects of scientific theories of consciousness and the mind.     

Developmental evolution in social insects: regulatory networks from genes to societies

The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration.     

From gene regulation to gene function: regulatory networks in bacillus subtilis

Bacillus subtilis is a sporulating Gram-positive bacterium that lives primarily in the soil and associated water sources. The publication of the B. subtilis genome sequence and subsequent systematic functional analysis and gene regulation programmes, together with an extensive understanding of its biochemistry and physiology, makes this micro-organism a prime candidate in which to model regulatory networks in silico. In this paper we discuss combined molecular biological and bioinformatical approaches that are being developed to model this organism's responses to changes in its environment.     

Effects of chronic exposure to arsenic and estrogen on epigenetic regulatory genes expression and epigenetic code in human prostate epithelial cells

Chronic exposures to arsenic and estrogen are known risk factors for prostate cancer. Though the evidence suggests that exposure to arsenic or estrogens can disrupt normal DNA methylation patterns and histone modifications, the mechanisms by which these chemicals induce epigenetic changes are not fully understood. Moreover, the epigenetic effects of co-exposure to these two chemicals are not known. Therefore, the objective of this study was to evaluate the effects of chronic exposure to arsenic and estrogen, both alone and in combination, on the expression of epigenetic regulatory genes, their consequences on DNA methylation, and histone modifications. Human prostate epithelial cells, RWPE-1, chronically exposed to arsenic and estrogen alone and in combination were used for analysis of epigenetic regulatory genes expression, global DNA methylation changes, and histone modifications at protein level. The result of this study revealed that exposure to arsenic, estrogen, and their combination alters the expression of epigenetic regulatory genes and changes global DNA methylation and histone modification patterns in RWPE-1 cells. These changes were significantly greater in arsenic and estrogen combination treated group than individually treated group. The findings of this study will help explain the epigenetic mechanism of arsenic- and/or estrogen-induced prostate carcinogenesis.     

PiNGO: a Cytoscape plugin to find candidate genes in biological networks

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform. AVAILABILITY: PiNGO is distributed as an open-source Java package under the GNU General Public License (http://www.gnu.org/), and can be downloaded via the Cytoscape plugin manager. A detailed user guide and tutorial are available on the PiNGO website (http://www.psb.ugent.be/esb/PiNGO.     

From minimal signed circuits to the dynamics of Boolean regulatory networks

It is acknowledged that the presence of positive or negative circuits in regulatory networks such as genetic networks is linked to the emergence of significant dynamical properties such as multistability (involved in differentiation) and periodic oscillations (involved in homeostasis). Rules proposed by the biologist R. Thomas assert that these circuits are necessary for such dynamical properties. These rules have been studied by several authors. Their obvious interest is that they relate the rather simple information contained in the structure of the network (signed circuits) to its much more complex dynamical behaviour. We prove in this article a nontrivial converse of these rules, namely that certain positive or negative circuits in a regulatory graph are actually sufficient for the observation of a restricted form of the corresponding dynamical property, differentiation or homeostasis. More precisely, the crucial property that we require is that the circuit be globally minimal. We then apply these results to the vertebrate immune system, and show that the two minimal functional positive circuits of the model indeed behave as modules which combine to explain the presence of the three stable states corresponding to the Th0, Th1 and Th2 cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.