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.

The effects of interleukin-10 depletion in vivo on the immune response to Porphyromonas gingivalis in a murine model

Background: The immune response to Porphyromonas gingivalis in the mouse abscess model is known to be dependent upon CD4 T-cell activation and the regulatory role of cytokines. The role of interleukin-10 (IL-10) in this mouse model was examined in vivo. Methods: One-week-old, female BALB/c mice were divided into 4 groups. Groups 1 and 2 were given intraperitoneal (ip) injections of phosphate buffered saline (PBS) weekly for 5 weeks. Group 3 was given an ip injection of rat immunoglobulin. Group 4 was injected with rat anti-IL-10 antibodies. At week 6, group 1 was sham-immunized with PBS, and groups 2, 3, and 4 were injected with P gingivalis lipopolysaccharide (Pg-LPS) weekly for 2 weeks. One week after the final immunization, delayed-type hypersensitivity (DTH) was assessed by footpad swelling to Pg-LPS. The level of serum antibodies to Pg-LPS and IFN-gamma (IFN-gamma) was determined by enzyme-linked immunosorbent assay. Dorsal abscess formation induced by the injection of viable P gingivalis was examined daily for 30 days. Results: The footpad swelling of the anti-IL-10-treated group (group 4) was significantly higher than that of groups 1 to 3. Similarly, the serum IFN-gamma level in group 4 was much higher than that of the other experimental groups. There was no significant difference in serum IgG antibodies to Pg-LPS in any of the experimental groups. However, the level of IgM antibodies in group 4 mice was significantly lower than that in groups 2 and 3. In addition, serum IgG1 was suppressed in group 4 mice, while IgG2a antibodies were raised. However, there was no difference observed between the levels of IgG2b and IgG3 antibodies in any group of mice. The lesions in sham-immunized mice (group 1) persisted for 30 days, and those in group 2 and 3 were undetected by day 18 and 20, respectively. In sharp contrast, lesions in group 4 had healed completely by day 13. Conclusions: This study has shown that IL-10 depletion in vivo in P gingivalis LPS-induced immune response in mice led to an elevated DTH response, an increase in serum IFN-gamma levels, and raised levels of IgG and IgG2a antibodies. Treatment with anti-IL-10 antibodies resulted in suppressed IgG I and IgM responses and a more rapid healing of abscesses than in non-IL-10-depleted mice. These results suggest that IL-10 depletion in Pg-LPS-induced immune response in mice may lead to a Th1-like immune response and provide strong protection against a subsequent challenge with live P gingivalis in an abscess model.

Regulatory interactions in Arabidopsis thaliana acetohydroxyacid synthase

Acetohydroxyacid synthase (AHAS; EC 4.1.3.18) contains catalytic and regulatory subunits, the latter being required for sensitivity to feedback regulation by leucine, valine and isoleucine. The regulatory subunit of Arabidopsis thaliana AHAS possesses a sequence repeat and we have suggested preciously that one repeat binds leucine while the second binds valine or isoleucine, with synergy between the two sites. We have mutated four residues in each repeat, based on a model of the regulatory subunit. The data confirm that there are separate leucine and valine/isoleucine sites, and suggest a complex pathway for regulatory signal transmission to the catalytic subunit. (C) 2002 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

Molecular analysis of the pathway for the synthesis of thiol tripeptides in the model legume Lotus japonicus

The thiol tripeptides, glutathione (GSH) and homoglutathione (hGSH), perform multiple roles in legumes, including protection against toxicity of free radicals and heavy metals. The three genes involved in the synthesis of GSH and hGSH in the model legume, Lotus japonicus, have been fully characterized and appear to be present as single copies in the genome. The gamma-glutamylcysteine synthetase (gammaecs) gene was mapped on the long arm of chromosome 4 (70.0 centimorgans [cM]) and consists of 15 exons, whereas the glutathione synthetase (gshs) and homoglutathione synthetase (hgshs) genes were mapped on the long arm of chromosome 1 (81.3 cM) and found to be arranged in tandem, with a separation of approximately 8 kb. Both genes consist of 12 exons of exactly the same size (except exon 1, which is similar). Two types of transcripts were detected for the gshs gene, which putatively encode proteins localized in the plastids and cytosol. Promoter regions contain cis-acting regulatory elements that may be involved in the plant's response to light, hormones, and stress. Determination of transcript levels, enzyme activities, and thiol contents in nodules, roots, and leaves revealed that gammaecs and hgshs are expressed in all three plant organs, whereas gshs is significantly functional only in nodules. This strongly suggests an important role of GSH in the rhizobia-legume symbiosis.

Donor treatment with pegylated G-CSF augments the generation of IL-10-producing regulatory T cells and promotes transplantation tolerance

We investigated whether the protection from graft-versus-host disease (GVHD) afforded by donor treatment with granulocyte colony-stimulating factor (G-CSF) could be enhanced by dose escalation. Donor treatment with human G-CSIF prevented GVHD in the B6 --> B6D2F1 murine model in a dose-dependent fashion, and murine G-CSF provided equivalent protection from GVHD at 10-fold lower doses. Donor pretreatment with a single dose of pegylated G-CSF (peg-G-CSF) prevented GVHD to a significantly greater extent than standard G-CSIF (survival, 75% versus 11%, P < .001). Donor T cells from peg-G-CSF-treated donors failed to proliferate to alloantigen and inhibited the responses of control T cells in an interleukin 10 (IL-10)-dependent-fashion in vitro. T cells from peg-GCSF-treated IL-10(-/-) donors induced lethal GVHD; T cells from peg-G-CSF-treated wild-type (wt) donors promoted long-term survival. Whereas T cells from peg-G-CSF wt donors were able to regulate GVHD induced by T cells from control-treated donors, T cells from G-CSF-treated wt donors and peg-G-CSF-treated IL-10(-/-) donors did not prevent mortality. Thus, peg-G-CSF is markedly superior to standard G-CSF for the prevention of GVHD following allogeneic stem cell transplantation (SCT), due to the generation of IL-10-producing regulatory T cells. These data support prospective clinical trials of peg-G-CSF-mobilized allogeneic blood SCT. (C) 2004 by The American Society of Hematology.

Bistability and switching in the lysis/lysogeny genetic regulatory network of bacteriophage lambda

Bistability and switching are two important aspects of the genetic regulatory network of phage. Positive and negative feedbacks are key regulatory mechanisms in this network. By the introduction of threshold values, the developmental pathway of A phage is divided into different stages. If the protein level reaches a threshold value, positive or negative feedback will be effective and regulate the process of development. Using this regulatory mechanism, we present a quantitative model to realize bistability and switching of phage based on experimental data. This model gives descriptions of decisive mechanisms for different pathways in induction. A stochastic model is also introduced for describing statistical properties of switching in induction. A stochastic degradation rate is used to represent intrinsic noise in induction for switching the system from the lysogenic pathway to the lysis pathway. The approach in this paper represents an attempt to describe the regulatory mechanism in genetic regulatory network under the influence of intrinsic noise in the framework of continuous models. (C) 2003 Elsevier Ltd. All rights reserved.

The prion protein gene: Identifying regulatory signals using marsupial sequence

The function of the prion protein gene (PRNP) and its normal product PrPC is elusive. We used comparative genomics as a strategy to understand the normal function of PRNP. As the reliability of comparisons increases with the number of species and increased evolutionary distance, we isolated and sequenced a 66.5 kb BAC containing the PRNP gene from a distantly related mammal, the model Australian marsupial Macropus eugenii (tammar wallaby). Marsupials are separated from eutherians such as human and mouse by roughly 180 million years of independent evolution. We found that tammar PRNP, like human PRNP, has two exons. Prion proteins encoded by the tammar wallaby and a distantly related marsupial, Monodelphis domestica (Brazilian opossum) PRNP contain proximal PrP repeats with a distinct, marsupial-specific composition and a variable number. Comparisons of tammar wallaby PRNP with PRNPs from human, mouse, bovine and ovine allowed us to identify non-coding gene regions conserved across the marsupial-eutherian evolutionary distance, which are candidates for regulatory regions. In the PRNP 3' UTR we found a conserved signal for nuclear-specific polyadenylation and the putative cytoplasmic polyadenylation element (CPE), indicating that post-transcriptional control of PRNP mRNA activity is important. Phylogenetic footprinting revealed conserved potential binding sites for the MZF-1 transcription factor in both upstream promoter and intron/intron 1, and for the MEF2, MyTI, Oct-1 and NFAT transcription factors in the intron(s). The presence of a conserved NFAT-binding site and CPE indicates involvement of PrPC in signal transduction and synaptic plasticity. (c) 2004 Elsevier B.V. All rights reserved.

Mutations in the regulatory subunit of yeast acetohydroxyacid synthase affect its activation by MgATP

Isoleucine, leucine and valine are synthesized via a common pathway in which the first reaction is catalysed by AHAS (acetohydroxyacid synthase; EC 2.2.1.6). This heterotetrameric enzyme is composed of a larger subunit that contains the catalytic machinery and a smaller subunit that plays a regulatory role. The RSU (regulatory subunit) enhances the activity of the CSU (catalytic sub unit) and mediates end-product inhibition by one or more of the branched-chain amino acids, usually valine. Fungal AHAS differs front that in other organisms in that the inhibition by valine is reversed by MgATP. The fungal AHAS RSU also differs from that in other organisms in that it contains a sequence insert. We suggest that this insert may form the MgATP-binding site and we have tested this hypothesis by mutating ten highly conserved amino acid residues of the yeast AHAS RSU. The modified subunits were tested for their ability to activate the yeast AHAS CSU, to confer sensitivity to valine inhibition and to mediate reversal of the inhibition by MgATP. All but one of the mutations resulted in substantial changes in the properties of the RSU. Unexpectedly, four of them gave a protein that required mgATP in order for strong stimulation of the CSU and valine inhibition to be observed. A model to explain this result is proposed. Five of the mutations abolished MgATP activation and are suggested to constitute the binding site for this modulator.

Evolving noisy oscillatory dynamics in genetic regulatory networks

We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

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.

Making Fedora easier to implement with Fez: A free open source content model and workflow management front-end to Fedora

The University of Queensland, Australia has developed Fez, a world-leading user-interface and management system for Fedora-based institutional repositories, which bridges the gap between a repository and users. Christiaan Kortekaas, Andrew Bennett and Keith Webster will review this open source software that gives institutions the power to create a comprehensive repository solution without the hassle..

A modified discrete random pore model allowing for different initial surface reactivity

We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.

Adsorption in mesopores: A molecular-continuum model with application to MCM-41

The classical model of surface layering followed by capillary condensation during adsorption in mesopores, is modified here by consideration of the adsorbate solid interaction potential. The new theory accurately predicts the capillary coexistence curve as well as pore criticality, matching that predicted by density functional theory. The model also satisfactorily predicts the isotherm for nitrogen adsorption at 77.4 K on MCM-41 material of various pore sizes, synthesized and characterized in our laboratory, including the multilayer region, using only data on the variation of condensation pressures with pore diameter. The results indicate a minimum mesopore diameter for the surface layering model to hold as 14.1 Å, below which size micropore filling must occur, and a minimum pore diameter for mechanical stability of the hemispherical meniscus during desorption as 34.2 Å. For pores in-between these two sizes reversible condensation is predicted to occur, in accord with the experimental data for nitrogen adsorption on MCM-41 at 77.4 K.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).