Wnt signaling regulates neural plate patterning in distinct temporal phases with dynamic transcriptional outputs.

The process that partitions the nascent vertebrate central nervous system into forebrain, midbrain, hindbrain, and spinal cord after neural induction is of fundamental interest in developmental biology, and is known to be dependent on Wnt/ß-catenin signaling at multiple steps. Neural induction specifies neural ectoderm with forebrain character that is subsequently posteriorized by graded Wnt signaling: embryological and mutant analyses have shown that progressively higher levels of Wnt signaling induce progressively more posterior fates. However, the mechanistic link between Wnt signaling and the molecular subdivision of the neural ectoderm into distinct domains in the anteroposterior (AP) axis is still not clear. To better understand how Wnt mediates neural AP patterning, we performed a temporal dissection of neural patterning in response to manipulations of Wnt signaling in zebrafish. We show that Wnt-mediated neural patterning in zebrafish can be divided into three phases: (I) a primary AP patterning phase, which occurs during gastrulation, (II) a mes/r1 (mesencephalon-rhombomere 1) specification and refinement phase, which occurs immediately after gastrulation, and (III) a midbrain-hindbrain boundary (MHB) morphogenesis phase, which occurs during segmentation stages. A major outcome of these Wnt signaling phases is the specification of the major compartment divisions of the developing brain: first the MHB, then the diencephalic-mesencephalic boundary (DMB). The specification of these lineage divisions depends upon the dynamic changes of gene transcription in response to Wnt signaling, which we show primarily involves transcriptional repression or indirect activation. We show that otx2b is directly repressed by Wnt signaling during primary AP patterning, but becomes resistant to Wnt-mediated repression during late gastrulation. Also during late gastrulation, Wnt signaling becomes both necessary and sufficient for expression of wnt8b, en2a, and her5 in mes/r1. We suggest that the change in otx2b response to Wnt regulation enables a transition to the mes/r1 phase of Wnt-mediated patterning, as it ensures that Wnts expressed in the midbrain and MHB do not suppress midbrain identity, and consequently reinforce formation of the DMB. These findings integrate important temporal elements into our spatial understanding of Wnt-mediated neural patterning and may serve as an important basis for a better understanding of neural patterning defects that have implications in human health.

Analysis of the wnt1 regulatory chromosomal landscape.

One of the earliest patterning events in the vertebrate neural plate is the specification of mes/r1, the territory comprising the prospective mesencephalon and the first hindbrain rhombomere. Within mes/r1, an interface of gene expression defines the midbrain-hindbrain boundary (MHB), a lineage restriction that separates the mesencephalon and rhombencephalon. wnt1 is critical to mes/r1 development and functions within the MHB as a component of the MHB gene regulatory network (GRN). Despite its importance to these critical and early steps of vertebrate neurogenesis, little is known about the factors responsible for wnt1 transcriptional regulation. In the zebrafish, wnt1 and its neighboring paralog, wnt10b, are expressed in largely overlapping patterns, suggesting co-regulation. To understand wnt1 and wnt10b transcriptional control, we used a comparative genomics approach to identify relevant enhancers. We show that the wnt1-wnt10b locus contains multiple cis-regulatory elements that likely interact to generate the wnt1 and wnt10b expression patterns. Two of 11 conserved enhancers tested show activity restricted to the midbrain and MHB, an activity that is conserved in the distantly related spotted gar orthologous elements. Three non-conserved elements also play a likely role in wnt1 regulation. The identified enhancers display dynamic modes of chromatin accessibility, suggesting controlled deployment during embryogenesis. Our results suggest that the control of wnt1 and wnt10b expression is under complex regulation involving the interaction of multiple enhancers.

Simulating exploration versus exploitation in agent foraging under different environment uncertainties.

For artificial agents trading off exploration (food seeking) versus (short-term) exploitation (or consumption), our experiments suggest that uncertainty (interpreted information, theoretically) magnifies food seeking. In more uncertain environments, with food distributed uniformly randomly, exploration appears to be beneficial. In contrast, in biassed (less uncertain) environments, with food concentrated in only one part, exploitation appears to be more advantageous. Agents also appear to do better in biassed environments.

The α-Catenin mechanosensing M region is required for cell adhesion during tissue morphogenesis.

α-Catenin couples the cadherin-catenin complex to the actin cytoskeleton. The mechanosensitive α-Catenin M region undergoes conformational changes upon application of force to recruit interaction partners. Here, we took advantage of the tension landscape in the Drosophila embryo to define three different states of α-Catenin mechanosensing in support of cell adhesion. Low-, medium-, and high-tension contacts showed a corresponding recruitment of Vinculin and Ajuba, which was dependent on the α-Catenin M region. In contrast, the Afadin homolog Canoe acts in parallel to α-Catenin at bicellular low- and medium-tension junctions but requires an interaction with α-Catenin for its tension-sensitive enrichment at high-tension tricellular junctions. Individual M region domains make complex contributions to cell adhesion through their impact on interaction partner recruitment, and redundancies with the function of Canoe. Our data argue that α-Catenin and its interaction partners are part of a cooperative and partially redundant mechanoresponsive network that supports AJs remodeling during morphogenesis.

Molecular dynamics extended for fluctuating networks: application to water.

Molecular simulation models are increasingly important tools in efforts to understand the role that water plays in biochemical processes. However, existing models of water have limited capacity to deal with the characteristics of hydrogen bond networks. This article proposes a new fluctuating network (FN) algorithm as an extension of the standard molecular dynamics algorithm. The new algorithm allows for the simulation of a molecular system based on an underlying network, such as the hydrogen bond network in water. This algorithm distinguishes strong from weak network connections, applying a potential that best describes the specific connection behavior. We model liquid water with this new technique using a single-site, isotropic, short-range potential. We successfully reproduce liquid water's signature molecular spacing (as represented by the radial distribution function) and characterize its dynamic properties including the exponential hydrogen bond lifetime distribution, diffusion rate, and average hydrogen bonds per molecule. The FN algorithm allows exploration of the behavior of networked systems where explicit coordination limits are required. As such it could also be used to model covalent interactions, reaction dynamics, and applied to simulation of cellular networks.

Motif difficulty (MD): a predictive measure of problem difficulty for evolutionary algorithms using network motifs.

One of the major challenges in the field of evolutionary algorithms (EAs) is to characterise which kinds of problems are easy and which are not. Researchers have been attracted to predict the behaviour of EAs in different domains. We introduce fitness landscape networks (FLNs) that are formed using operators satisfying specific conditions and define a new predictive measure that we call motif difficulty (MD) for comparison-based EAs. Because it is impractical to exhaustively search the whole network, we propose a sampling technique for calculating an approximate MD measure. Extensive experiments on binary search spaces are conducted to show both the advantages and limitations of MD. Multidimensional knapsack problems (MKPs) are also used to validate the performance of approximate MD on FLNs with different topologies. The effect of two representations, namely binary and permutation, on the difficulty of MKPs is analysed.

Quantifiable Intravital Light Sheet Microscopy.

Live imaging of zebrafish embryos that maintains normal development can be difficult to achieve due to a combination of sample mounting, immobilization, and phototoxicity issues that, once overcome, often still results in image quality sufficiently poor that computer-aided analysis or even manual analysis is not possible. Here, we describe our mounting strategy for imaging the zebrafish midbrain-hindbrain boundary (MHB) with light sheet fluorescence microscopy (LSFM) and pilot experiments to create a study-specific set of parameters for semiautomatically tracking cellular movements in the embryonic midbrain primordium during zebrafish segmentation.

Dual-phase evolution in complex adaptive systems.

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

Local-global interaction and the emergence of scale-free networks with community structures.

Understanding complex networks in the real world is a nontrivial task. In the study of community structures we normally encounter several examples of these networks, which makes any statistical inferencing a challenging endeavor. Researchers resort to computer-generated networks that resemble networks encountered in the real world as a means to generate many networks with different sizes, while maintaining the real-world characteristics of interest. The generation of networks that resemble the real world turns out in itself to be a complex search problem. We present a new rewiring algorithm for the generation of networks with unique characteristics that combine the scale-free effects and community structures encountered in the real world. The algorithm is inspired by social interactions in the real world, whereby people tend to connect locally while occasionally they connect globally. This local-global coupling turns out to be a powerful characteristics that is required for our proposed rewiring algorithm to generate networks with community structures, power law distributions both in degree and in community size, positive assortative mixing by degree, and the rich-club phenomenon.

The role of translocation and selection in the emergence of genetic clusters and modules.

Biomolecular studies point increasingly to the importance of modularity in the organization of the genome. Processes such as the maintenance of metabolism are controlled by suites of genes that act as distinct, self-contained units, or modules. One effect is to promote stability of inherited characters. Despite the obvious importance of genetic modules, the mechanisms by which they form and persist are not understood. One clue is that functionally related genes tend to cluster together. Here we show that genetic translocation, recombination, and natural selection play a central role in this process. We distill the question of emerging genetic modularity into three simulation experiments that show: (1) a tendency, under natural selection, for essential genes to co-locate on the same chromosome and to settle in fixed loci; (2) that genes associated with a particular function tend to form functional clusters; and (3) that genes within a functional cluster tend to become arranged in transcription order. The results also imply that high proportions of junk DNA are essential to the process.