Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Dynamics of gene expression in an artificial genome

Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulatory networks from an artificial genome, represented by a sequence of nucleotides, and analyse how variations in the connectivity and degree of inhibition of the extracted networks affects the resulting classes of behaviours. For low connectivity systems were found to be very stable. Only with higher connectivity was a significant occurrence of chaos found. Most interestingly, the peak in occurrence of chaos occurs perched on the edge of a phase transition in the occurrence of attractors.

The value of idiosyncratic markers and changes to conserved tRNA sequences from the mitochondrial genome of hard ticks (Acari: Ixodida: Ixodidae) for phylogenetic inference

Idiosyncratic markers are features of genes and genomes that are so unusual that it is unlikely that they evolved more than once in a lineage of organisms. Here we explore further the potential of idiosyncratic markers and changes to typically conserved tRNA sequences for phylogenetic inference. Hard ticks were chosen as the model group because their phylogeny has been studied extensively. Fifty-eight candidate markers from hard ticks ( family Ixodidae) and 22 markers from the subfamily Rhipicephalinae sensu lato were mapped onto phylogenies of these groups. Two of the most interesting markers, features of the secondary structure of two different tRNAs, gave strong support to the hypothesis that species of the Prostriata ( Ixodes spp.) are monophyletic. Previous analyses of genes and morphology did not strongly support this relationship, instead suggesting that the Prostriata is paraphyletic with respect to the Metastriata ( the rest of the hard ticks). Parallel or convergent evolution was not found in the arrangements of mitochondrial genes in ticks nor were there any reversals to the ancestral arthropod character state. Many of the markers identified were phylogenetically informative, whereas others should be informative with study of additional taxa. Idiosyncratic markers and changes to typically conserved nucleotides in tRNAs that are phylogenetically informative were common in this data set, and thus these types of markers might be found in other organisms.

Transcriptional network dynamics in macrophage activation

Transcriptional regulatory networks govern cell differentiation and the cellular response to external stimuli. However, mammalian model systems have not yet been accessible for network analysis. Here, we present a genome-wide network analysis of the transcriptional regulation underlying the mouse macrophage response to bacterial lipopolysaccharide (LPS). Key to uncovering the network structure is our combination of time-series cap analysis of gene expression with in silico prediction of transcription factor binding sites. By integrating microarray and qPCR time-series expression data with a promoter analysis, we find dynamic subnetworks that describe how signaling pathways change dynamically during the progress of the macrophage LPS response, thus defining regulatory modules characteristic of the inflammatory response. In particular, our integrative analysis enabled us to suggest novel roles for the transcription factors ATF-3 and NRF-2 during the inflammatory response. We believe that our system approach presented here is applicable to understanding cellular differentiation in higher eukaryotes. (c) 2006 Elsevier Inc. All rights reserved.

Evolving genetic regulatory networks using an artificial genome

Boolean models of genetic regulatory networks (GRNs) have been shown to exhibit many of the characteristic dynamics of real GRNs, with gene expression patterns settling to point attractors or limit cycles, or displaying chaotic behaviour, depending upon the connectivity of the network and the relative proportions of excitatory and inhibitory interactions. This range of behaviours is only apparent, however, when the nodes of the GRN are updated synchronously, a biologically implausible state of affairs. In this paper we demonstrate that evolution can produce GRNs with interesting dynamics under an asynchronous update scheme. We use an Artificial Genome to generate networks which exhibit limit cycle dynamics when updated synchronously, but collapse to a point attractor when updated asynchronously. Using a hill climbing algorithm the networks are then evolved using a fitness function which rewards patterns of gene expression which revisit as many previously seen states as possible. The final networks exhibit “fuzzy limit cycle” dynamics when updated asynchronously.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Time-reversal test for stochastic quantum dynamics

The calculation of quantum dynamics is currently a central issue in theoretical physics, with diverse applications ranging from ultracold atomic Bose-Einstein condensates to condensed matter, biology, and even astrophysics. Here we demonstrate a conceptually simple method of determining the regime of validity of stochastic simulations of unitary quantum dynamics by employing a time-reversal test. We apply this test to a simulation of the evolution of a quantum anharmonic oscillator with up to 6.022×1023 (Avogadro's number) of particles. This system is realizable as a Bose-Einstein condensate in an optical lattice, for which the time-reversal procedure could be implemented experimentally.

Superchemistry: dynamics of coupled atomic and molecular Bose condensates

We analyze the dynamics of a dilute, trapped Bose-condensed atomic gas coupled to a diatomic molecular Bose gas by coherent Raman transitions. This system is shown to result in a new type of “superchemistry,” in which giant collective oscillations between the atomic and the molecular gas can occur. The phenomenon is caused by stimulated emission of bosonic atoms or molecules into their condensate phases.

Quantum dynamics of three coupled atomic Bose-Einstein condensates

The simplest model of three coupled Bose-Einstein condensates is investigated using a group theoretical method. The stationary solutions are determined using the SU(3) group under the mean-field approximation. This semiclassical analysis, using system symmetries, shows a transition in the dynamics of the system from self trapping to delocalization at a critical value for the coupling between the condensates. The global dynamics are investigated by examination of the stable points, and our analysis shows that the structure of the stable points depends on the ratio of the condensate coupling to the particle-particle interaction, and undergoes bifurcations as this ratio is varied. This semiclassical model is compared to a full quantum treatment, which also displays a dynamical transition. The quantum case has collapse and revival sequences superimposed on the semiclassical dynamics, reflecting the underlying discreteness of the spectrum. Nonzero circular current states are also demonstrated as one of the higher-dimensional effects displayed in this system.

Substructure and Dynamics of the Fornax Cluster

We present the first dynamical analysis of a galaxy cluster to include a large fraction of dwarf galaxies. Our sample of 108 Fornax Cluster members measured with the UK Schmidt Telescope FLAIR-II spectrograph contains 55 dwarf galaxies (15.5 > b(j) > 18.0 or -16 > M-B > -13.5). H alpha emission shows that of the dwarfs are star forming, twice the fraction implied by morphological classifications. The total sample has a mean velocity of 1493 +/- 36 kms s(-1) and a velocity dispersion of 374 +/- 26 km s(-1). The dwarf galaxies form a distinct population: their velocity dispersion (429 +/- 41 km s(-1)) is larger than that of the giants () at the 98% confidence level. This suggests that the dwarf population is dominated by infalling objects whereas the giants are virialized. The Fornax system has two components, the main Fornax Cluster centered on NGC 1399 with cz = 1478 km s(-1) and sigma (cz) = 370 km s(-1) and a subcluster centered 3 degrees to the southwest including NGC 1316 with cz = 1583 km s(-1) and sigma (cz) = 377 km s(-1). This partition is preferred over a single cluster at the 99% confidence level. The subcluster, a site of intense star formation, is bound to Fornax and probably infalling toward the cluster core for the first time. We discuss the implications of this substructure for distance estimates of the Fornax Cluster. We determine the cluster mass profile using the method of Diaferio, which does not assume a virialized sample. The mass within a projected radius of 1.4 Mpc is (7 +/- 2) x 10(13) M-., and the mass-to-light ratio is 300 +/- 100 M-./L-.. The mass is consistent with values derived from the projected mass virial estimator and X-ray measurements at smaller radii.

Determination of Wolbachia genome size by Pulsed-Field Gel Electrophoresis

Genome sizes of six different Wolbachia strains from insect and nematode hosts have been determined by pulsed-field gel electrophoresis of purified DNA both before and after digestion with rare-cutting restriction endonucleases. Enzymes SmaI, ApaI, AscI, and FseI cleaved the studied Wolbachia strains at a small number of sites and were used for the determination of the genome sizes of wMelPop, wMel, and wMelCS (each 1.36 Mb), wRi (1.66 Mb), wBma (1.1 Mb), and wDim (0.95 Mb). The Wolbachia genomes studied were all much smaller than the genomes of free-living bacteria such as Escherichia coli (4.7 Mb), as is typical for obligate intracellular bacteria. There was considerable genome size variability among Wolbachia strains, especially between the more parasitic A group Wolbachia infections of insects and the mutualistic C and D group infections of nematodes. The studies described here found no evidence for extrachromosomal plasmid DNA in any of the strains examined. They also indicated that the Wolbachia genome is circular.

Wolbachia: why these bacteria are important to genome research

Intracellular bacteria of the genus Wolbachia were first discovered in mosquitoes in the 1920s. Their superficial similarity to pathogenic rickettsia initially raised interest in them as potential human pathogens. However, injection experiments with mice showed that they were non-pathogenic, and they were subsequently classified as symbionts of insects. Until the 1970s, Wolbachia was considered to infect a limited number of species of mosquitoes. It is now clear that Wolbachia is an extremely common intracellular agent of invertebrates, infecting nearly all the major groups of arthropods and other terrestrial invertebrates. Its wide host range and abundance can be attributed partly to the unusual phenotypes it exerts on the host it infects. These include the induction of parthenogenesis (the production of female offspring from unmated mothers) in certain insects, the feminization of genetic male crustaceans to functional phenotypic females, and the failure of fertilization in hosts when males and females have a different infection status (cytoplasmic incompatibility). All of these phenotypes favor maternal transmission of the intracellular Wolbachia. In the last year, Wolbachia has also been shown to be a widespread symbiont of filarial nematodes. It appears that Wolbachia is needed by the adult worm for normal fertility, indicating that Wolbachia is behaving like a classic mutualist in this case. This discovery exemplifies that the extent of the host range of Wolbachia and its associated phenotypes is still far from fully understood.

Evolution of Wolbachia pipientis transmission dynamics in insects

Wolbachia pipientis is an intracellular bacterial parasite of arthropods that enhances its transmission by manipulating host reproduction, most commonly by inducing cytoplasmic incompatibility. The discovery of isolates with modified cytoplasmic incompatibility phenotypes and others with novel virulence properties is an indication of the potential breadth of evolutionary strategies employed by Wolbachia.