Gene networks in development

Genome assembly and transcriptome analysis provide insights into the antischistosome mechanism of Microtus fortis

Microtus fortis is the only mammalian host that exhibits intrinsic resistance against Schistosoma japonicum infection. However, the underlying molecular mechanisms of this resistance are not yet known. Here, we perform the first de novo genome assembly of M. fortis, comprehensive gene annotation analysis, and evolution analysis. Furthermore, we compare the recovery rate of schistosomes, pathological changes, and liver transcriptomes between M. fortis and mice at different time points after infection. We observe that the time and type of immune response in M. fortis are different from those in mice. M. fortis activates immune and inflammatory responses on the 10th day post infection, such as leukocyte extravasation, antibody activation, Fc-gamma receptor-mediated phagocytosis, and the interferon signaling cascade, which play important roles in preventing the development of schistosomes. In contrast, an intense immune response occurrs in mice at the late stages of infection and could not eliminate schistosomes. Infected mice suffer severe pathological injury and continuous decreases in cell cycle, lipid metabolism, and other functions. Our findings offer new insights into the intrinsic resistance mechanism of M. fortis against schistosome infection. The genome sequence also provides the basis for future studies of other important traits in M. fortis.

Cell-cell interaction and diversity of emergent behaviours

Despite myriads of possible gene expression profiles, cells tend to be found in a confined number of expression patterns. The dynamics of Boolean models of gene regulatory networks has proven to be a likely candidate for the description of such self-organisation phenomena. Because cells do not live in isolation, but they constantly shape their functions to adapt to signals from other cells, this raises the question of whether the cooperation among cells entails an expansion or a reduction of their possible steady states. Multi random Boolean networks are introduced here as a model for interaction among cells that might be suitable for the investigation of some generic properties regarding the influence of communication on the diversity of cell behaviours. In spite of its simplicity, the model exhibits a non-obvious phenomenon according to which a moderate exchange of products among adjacent cells fosters the variety of their possible behaviours, which on the other hand are more similar to one another. On the contrary, a more invasive coupling would lead cells towards homogeneity.

Spatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundary

The isthmic organizer mediating differentiation of mid- and hindbrain during vertebrate development is characterized by a well-defined pattern of locally restricted gene expression domains around the mid-hindbrain boundary (MHB). This pattern is established and maintained by a regulatory network between several transcription and secreted factors that is not yet understood in full detail. In this contribution we show that a Boolean analysis of the characteristic spatial gene expression patterns at the murine MHB reveals key regulatory interactions in this network. Our analysis employs techniques from computational logic for the minimization of Boolean functions. This approach allows us to predict also the interplay of the various regulatory interactions. In particular, we predict a maintaining, rather than inducing, effect of Fgf8 on Wnt1 expression, an issue that remained unclear from published data. Using mouse anterior neural plate/tube explant cultures, we provide experimental evidence that Fgf8 in fact only maintains but does not induce ectopic Wnt1 expression in these explants. In combination with previously validated interactions, this finding allows for the construction of a regulatory network between key transcription and secreted factors at the MHB. Analyses of Boolean, differential equation and reaction-diffusion models of this network confirm that it is indeed able to explain the stable maintenance of the MHB as well as time-courses of expression patterns both under wild-type and various knock-out conditions. In conclusion, we demonstrate that similar to temporal also spatial expression patterns can be used to gain information about the structure of regulatory networks. We show, in particular, that the spatial gene expression patterns around the MHB help us to understand the maintenance of this boundary on a systems level.

Understanding brain formation during development is a tantalizing challenge. It is also essential for the fight against neurodegenerative diseases. In vertebrates, the central nervous system arises from a structure called the neural plate. This tissue is divided into four regions, which continue to develop into forebrain, midbrain, hindbrain and spinal cord. Interactions between locally expressed genes and signaling molecules are responsible for this patterning. Two key signaling molecules in this process are Fgf8 and Wnt1 proteins. They are secreted from a signaling center located at the boundary between prospective mid- and hindbrain (mid-hindbrain boundary, MHB) and mediate development of these two brain regions. Here, we logically analyze the spatial gene expression patterns at the MHB and predict interactions involved in the differentiation of mid- and hindbrain. In particular, our analysis indicates that Wnt1 depends on Fgf8 for stable maintenance. A time-course analysis of Wnt1 expression after implantation of Fgf8-coated beads in mouse neural plate/tube explants experimentally validates our prediction about the interactions between these two key patterning molecules. Subsequently, we demonstrate that available data allows construction of a mathematical model able to explain the maintenance of the signaling center at the MHB. We begin to understand this small aspect of brain formation on a systems level.

Morphogenesis by coupled regulatory networks: reliable control of positional information and proportion regulation

Based on a non-equilibrium mechanism for spatial pattern formation we study how position information can be controlled by locally coupled discrete dynamical networks, similar to gene regulation networks of cells in a developing multicellular organism. As an example we study the developmental problems of domain formation and proportion regulation in the presence of noise, as well as in the presence of cell flow. We find that networks that solve this task exhibit a hierarchical structure of information processing and are of similar complexity as developmental circuits of living cells. Proportion regulation is scalable with system size and leads to sharp, precisely localized boundaries of gene expression domains, even for large numbers of cells. A detailed analysis of noise-induced dynamics, using a mean-field approximation, shows that noise in gene expression states stabilizes (rather than disrupts) the spatial pattern in the presence of cell movements, both for stationary as well as growing systems. Finally, we discuss how this mechanism could be realized in the highly dynamic environment of growing tissues in multicellular organisms.

Critical line in random-threshold networks with inhomogeneous thresholds

We calculate analytically the critical connectivity K_{c} of random-threshold networks (RTNs) for homogeneous and inhomogeneous thresholds, and confirm the results by numerical simulations. We find a superlinear increase of K_{c} with the (average) absolute threshold mid R:hmid R: , which approaches K_{c}(mid R:hmid R:) approximately h;{2}(2lnmid R:hmid R:) for large mid R:hmid R: , and show that this asymptotic scaling is universal for RTNs with Poissonian distributed connectivity and threshold distributions with a variance that grows slower than h;{2} . Interestingly, we find that inhomogeneous distribution of thresholds leads to increased propagation of perturbations for sparsely connected networks, while for densely connected networks damage is reduced; the crossover point yields a characteristic connectivity K_{d} , that has no counterpart in Boolean networks with transition functions not restricted to threshold-dependent switching. Last, local correlations between node thresholds and in-degree are introduced. Here, numerical simulations show that even weak (anti)correlations can lead to a transition from ordered to chaotic dynamics, and vice versa.

Neutrality and robustness in evo-devo: emergence of lateral inhibition

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.

Simulation study on effects of signaling network structure on the developmental increase in complexity

The developmental increase in structural complexity in multicellular lifeforms depends on local, often non-periodic differences in gene expression. These, in turn, depend on a network of gene-gene interactions coded within the organismal genome. To see what architectural features of a network (size, connectivity, etc.) affect the likelihood of patterns with multiple cell types (i.e. patterns where cells express > or = 3 different combinations of genes), developmental pattern formation was simulated in virtual blastoderm embryos with small artificial genomes. Several basic properties of these genomic signaling networks, such as the number of genes, the distributions of positive (inductive) and negative (repressive) interactions, and the strengths of gene-gene interactions were tested. The results show that the frequencies of complex and/or stable patterns depended not only on the existence of negative interactions, but also on the distribution of regulatory interactions: for example, coregulation of signals and their intracellular effectors increased the likelihood of pattern formation compared to differential regulation of signaling pathway components. Interestingly, neither quantitative differences in strengths of signaling interactions nor multiple response thresholds to different levels of signal concentration (as in morphogen gradients) were essential for formation of multiple, spatially unique "cell types". However, those combinations of architectural features that greatly increased the likelihood for pattern complexity tended to decrease the likelihoods for pattern stability and developmental robustness. Nevertheless, elements of complex patterns (e.g. genes, cell type order within the pattern) could differ in their developmental robustness, which may be important for the evolution of complexity. The results show that depending on the network structure, the same set of genes can produce patterns of different complexity, robustness and stability. Because of this, the evolution of metazoan complexity with a combinatorial code of gene regulation may have depended at least as much on selection for favorable distribution of connections between existing developmental regulatory genes as on the simple increase in numbers of regulatory genes.

Genetic Networks in the Early Development of Caenorhabditis elegans

One of the best-studied model organisms in biology is Caenorhabditis elegans. Because of its simple architecture and other biological advantages, considerable data have been collected about the regulation of its development. In this review, currently available data concerning the early phase of embryonic development are presented in the form of genetic networks. We performed computer simulations of regulatory mechanisms in embryonic development, and the results are described and compared with experimental observations.

Modeling and simulation of genetic regulatory systems: a literature review

In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between DNA, RNA, proteins, and small molecules. As most genetic regulatory networks of interest involve many components connected through interlocking positive and negative feedback loops, an intuitive understanding of their dynamics is hard to obtain. As a consequence, formal methods and computer tools for the modeling and simulation of genetic regulatory networks will be indispensable. This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equations, stochastic equations, and rule-based formalisms. In addition, the paper discusses how these formalisms have been used in the simulation of the behavior of actual regulatory systems.

Gene networks capable of pattern formation: from induction to reaction-diffusion

One of the main aims of developmental biology is to understand how a single and apparently homogeneous egg cell achieves the intricate complexity of the adult. Here we present two models to explain the generation of developmental patterns through interactions at the gene level. One model considers direct-contact induction between cells while the other takes into account diffusion of hormones. We show that sets of cells involving identical gene networks and communicating through hormones spontaneously exhibit ordered patterns. We have characterized these patterns and the specific networks responsible for them. The models allow to (i) compare diffusion and direct-contact induction processes as mechanisms of pattern generation; (ii) identify the possible range of behaviour of real gene networks and (iii) suggest causal mechanisms to generate known patterns. The evolutionary implications are discussed.

Evolving mechanisms of morphogenesis: on the interplay between differential adhesion and cell differentiation

Differential cell adhesion, mediated by e.g. integrin and cadherins/catenines, plays an important role in morphogenesis and it has been shown that there is intimate cross-talk between their expression and modification, and inter-cellular signalling, cell differentiation, cell growth and apoptosis. In this paper, we introduce and use a formal model to explore the morphogenetic potential of the interplay between these processes. We demonstrate the formation of interesting morphologies. Initiated by cell differentiation, differential cell adhesion leads to a long transient of cell migrations, e.g. engulfing and intercalation of cells and cell layers. This transient can be sustained dynamically by further cell differentiation, and by cell growth/division and cell death which are triggered by the (also long range) forces (stretching and squeezing) generated by the cell adhesion. We study the interrelation between modes of cell differentiation and modes of morphogenesis. We use an evolutionary process to zoom in on gene-regulation networks which lead to cell differentiation. Morphogenesis is not selected for but appears as a side-effect. The evolutionary dynamics shows the hallmarks of evolution on a rugged landscape, including long neutral paths. We show that a combinatorially large set of morphologies occurs in the vicinity of a neutral path which sustains cell differentiation. Thus, an almost linear molecular phylogeny gives rise to mosaic evolution on the morphological level.

Adhesion of biofilms to inert surfaces: A molecular level approach directed at the marine environment

Protein/ligand interactions involved in mediating adhesion between microorganisms and biological surfaces have been well-characterized in some cases (e.g. pathogen/host interactions). The strategies microorganisms employ for attachment to inert surfaces have not been so clearly elucidated. An experimental approach is presented which addresses the issues from the point of view of molecular interactions occurring at the interface.