Interactions between uncoupling protein 2 gene polymorphisms, obesity and alcohol intake on liver function: a large meta-analysed population-based study

BACKGROUND AND OBJECTIVE: Given the role of uncoupling protein 2 (UCP2) in the accumulation of fat in the hepatocytes and in the enhancement of protective mechanisms in acute ethanol intake, we hypothesised that UCP2 polymorphisms are likely to cause liver disease through their interactions with obesity and alcohol intake. To test this hypothesis, we investigated the interaction between tagging polymorphisms in the UCP2 gene (rs2306819, rs599277 and rs659366), alcohol intake and obesity traits such as BMI and waist circumference (WC) on alanine aminotransferase (ALT) and gamma glutamyl transferase (GGT) in a large meta-analysis of data sets from three populations (n=20 242). DESIGN AND METHODS: The study populations included the Northern Finland Birth Cohort 1966 (n=4996), Netherlands Study of Depression and Anxiety (n=1883) and LifeLines Cohort Study (n=13 363). Interactions between the polymorphisms and obesity and alcohol intake on dichotomised ALT and GGT levels were assessed using logistic regression and the likelihood ratio test. RESULTS: In the meta-analysis of the three cohorts, none of the three UCP2 polymorphisms were associated with GGT or ALT levels. There was no evidence for interaction between the polymorphisms and alcohol intake on GGT and ALT levels. In contrast, the association of WC and BMI with GGT levels varied by rs659366 genotype (Pinteraction=0.03 and 0.007, respectively; adjusted for age, gender, high alcohol intake, diabetes, hypertension and serum lipid concentrations). CONCLUSION: In conclusion, our findings in 20 242 individuals suggest that UCP2 gene polymorphisms may cause liver dysfunction through the interaction with body fat rather than alcohol intake.

The Saccharomyces cerevisiae COQ10 gene encodes a START domain protein required for function of coenzyme Q in respiration

Deletion of the Saccharomyces cerevisiae gene YOL008W, here referred to as COQ10, elicits a respiratory defect as a result of the inability of the mutant to oxidize NADH and succinate. Both activities are restored by exogenous coenzyme Q(2). Respiration is also partially rescued by COQ2, COQ7, or COQ8/ABC1, when these genes are present in high copy. Unlike other coq mutants, all of which lack Q(6), the coq10 mutant has near normal amounts of Q(6) in mitochondria. Coq10p is widely distributed in bacteria and eukaryotes and is homologous to proteins of the aromatic-rich protein family Pfam03654 and to members of the START domain superfamily that have a hydrophobic tunnel implicated in binding lipophilic molecules such as cholesterol and polyketides. Analysis of coenzyme Q in polyhistidine-tagged Coq10p purified from mitochondria indicates the presence 0.032-0.034 mol of Q(6)/mol of protein. We propose that Coq10p is a Q(6)-binding protein and that in the coq10 mutant Q(6) it is not able to act as an electron carrier, possibly because of improper localization.

Inhomogeneous Fractional Diffusion Equations

2000 Mathematics Subject Classification: Primary 26A33; Secondary 35S10, 86A05

Stochastic delay differential equations for genetic regulatory networks

Time delay is an important aspect in the modelling of genetic regulation due to slow biochemical reactions such as gene transcription and translation, and protein diffusion between the cytosol and nucleus. In this paper we introduce a general mathematical formalism via stochastic delay differential equations for describing time delays in genetic regulatory networks. Based on recent developments with the delay stochastic simulation algorithm, the delay chemical masterequation and the delay reaction rate equation are developed for describing biological reactions with time delay, which leads to stochastic delay differential equations derived from the Langevin approach. Two simple genetic regulatory networks are used to study the impact of' intrinsic noise on the system dynamics where there are delays. (c) 2006 Elsevier B.V. All rights reserved.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Regulatory elements involved in the post-transcriptional control of stage-specific gene expression in Trypanosoma cruzi: a review

Trypanosoma cruzi, a protozoan parasite that causes Chagas disease, exhibits unique mechanisms for gene expression such as constitutive polycistronic transcription of protein-coding genes, RNA editing and trans-splicing. In the absence of mechanism controlling transcription initiation, organized subsets of T. cruzi genes must be post-transcriptionally co-regulated in response to extracellular signals. The mechanisms that regulate stage-specific gene expression in this parasite have become much clearer through sequencing its whole genome as well as performing various proteomic and microarray analyses, which have demonstrated that at least half of the T. cruzi genes are differentially regulated during its life cycle. In this review, we attempt to highlight the recent advances in characterising cis and trans-acting elements in the T. cruzi genome that are involved in its post-transcriptional regulatory machinery.

Control of the master virulence regulatory gene atxA in Bacillus anthracis

Transcription of the Bacillus anthracis structural genes for the anthrax toxin proteins and biosynthetic operon for capsule are positively regulated by AtxA, a transcription regulator with unique properties. Consistent with the role of atxA in virulence factor expression, a B. anthracis atxA-null mutant is avirulent in a murine model for anthrax. In batch culture, multiple signals impact atxA transcript levels, and the timing and steady state level of atxA expression is critical for optimal toxin and capsule synthesis. Despite the apparent complex control of atxA transcription, only one trans-acting protein, the transition state regulator AbrB, has been demonstrated to directly interact with the atxA promoter. The AbrB-binding site has been described, but additional cis-acting control sequences have not been defined. Using transcriptional lacZ fusions, electrophoretic mobility shift assays, and Western blot analysis, the cis-acting elements and trans-acting factors involved in regulation of atxA in B. anthracis strains containing either both virulence plasmids, pXO1 and pXO2, or only one plasmid, pXO1, were studied. This work demonstrates that atxA transcription from the major start site P1 is dependent upon a consensus sequence for the housekeeping sigma factor SigA, and an A+T-rich upstream element (UP-element) for RNA polymerase (RNAP). In addition, the data show that a trans-acting protein(s) other than AbrB negatively impacts atxA transcription when it binds specifically to a 9-bp palindrome within atxA promoter sequences located downstream of P1. Mutation of the palindrome prevents binding of the trans-acting protein(s) and results in a corresponding increase in AtxA and anthrax toxin production in a strain- and culture-dependent manner. The identity of the trans-acting repressor protein(s) remains elusive; however, phenotypes associated with mutation of the repressor binding site have revealed that the trans-acting repressor protein(s) indirectly controls B. anthracis development. Mutation of the repressor binding site results in misregulation and overexpression of AtxA in conditions conducive for development, leading to a marked sporulation defect that is both atxA- and pXO2-61-dependent. pXO2-61 is homologous to the sensor domain of sporulation sensor histidine kinases and is proposed to titrate an activating signal away from the sporulation phosphorelay when overexpressed by AtxA. These results indicate that AtxA is not only a master virulence regulator, but also a modulator of proper B. anthracis development. Also demonstrated in this work is the impact of the developmental regulators AbrB, Spo0A, and SigH on atxA expression and anthrax toxin production in a genetically incomplete (pXO1+, pXO2-) and genetically complete (pXO1+, pXO2+) strain background. AtxA and anthrax toxin production resulting from deletion of the developmental regulators are strain-dependent suggesting that factors on pXO2 are involved in control of atxA. The only developmental deletion mutant that resulted in a prominent and consistent strain-independent increase in AtxA protein levels was an abrB-null mutant. As a result of increased AtxA levels, there is early and increased production of anthrax toxins in an abrB-null mutant. In addition, the abrB-null mutant exhibited an increase in virulence in a murine model for anthrax. In contrast, virulence of the atxA promoter mutant was unaffected in a murine model for anthrax despite the production of 5-fold more AtxA than the abrB-null mutant. These results imply that AtxA is not the only factor impacting pathogenesis in an abrB-null mutant. Overall, this work highlights the complex regulatory network that governs expression of atxA and provides an additional role for AtxA in B. anthracis development.

Identification of two evolutionarily conserved and functional regulatory elements in intron 2 of the human BRCA1 gene

Cross-species comparative genomics is a powerful strategy for identifying functional regulatory elements within noncoding DNA. In this paper, comparative analysis of human and mouse intronic sequences in the breast cancer susceptibility gene (BRCA1) revealed two evolutionarily conserved noncoding sequences (CNS) in intron 2, 5 kb downstream of the core BRCA1 promoter. The functionality of these elements was examined using homologous-recombination-based mutagenesis of reporter gene-tagged cosmids incorporating these regions and flanking sequences from the BRCA1 locus. This showed that CNS-1 and CNS-2 have differential transcriptional regulatory activity in epithelial cell lines. Mutation of CNS-1 significantly reduced reporter gene expression to 30% of control levels. Conversely mutation of CNS-2 increased expression to 200% of control levels. Regulation is at the level of transcription and shows promoter specificity. Both elements also specifically bind nuclear proteins in vitro. These studies demonstrate that the combination of comparative genomics and functional analysis is a successful strategy to identify novel regulatory elements and provide the first direct evidence that conserved noncoding sequences in BRCA1 regulate gene expression. (c) 2005 Elsevier Inc. All rights reserved.

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.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Cardiac expression of ms1/STARS, a novel gene involved in cardiac development and disease, is regulated by GATA4.

Ms1/STARS is a novel muscle-specific actin-binding protein that specifically modulates the myocardin-related transcription factor (MRTF)-serum response factor (SRF) regulatory axis within striated muscle. This ms1/STARS-dependent regulatory axis is of central importance within the cardiac gene regulatory network and has been implicated in cardiac development and postnatal cardiac function/homeostasis. The dysregulation of ms1/STARS is associated with and causative of pathological cardiac phenotypes, including cardiac hypertrophy and cardiomyopathy. In order to gain an understanding of the mechanisms governing ms1/STARS expression in the heart, we have coupled a comparative genomic in silico analysis with reporter, gain-of-function, and loss-of-function approaches. Through this integrated analysis, we have identified three evolutionarily conserved regions (ECRs), α, SINA, and DINA, that act as cis-regulatory modules and confer differential cardiac cell-specific activity. Two of these ECRs, α and DINA, displayed distinct regulatory sensitivity to the core cardiac transcription factor GATA4. Overall, our results demonstrate that within embryonic, neonatal, and adult hearts, GATA4 represses ms1/STARS expression with the pathologically associated depletion of GATA4 (type 1/type 2 diabetic models), resulting in ms1/STARS upregulation. This GATA4-dependent repression of ms1/STARS expression has major implications for MRTF-SRF signaling in the context of cardiac development and disease.

Regulation of horizontal gene transfer of the catabolic island ICEclc

ICEclc is a mobile genetic element found in two copies on the chromosome of the bacterium Pseudomonas knackmussii B13. ICEclc harbors genes encoding metabolic pathways for the degradation of chlorocatechols (CLC) and 2-aminophenol (2AP). At low frequencies, ICEclc excises from the chromosome, closes into a circular DNA molecule which can transfer to another bacterium via conjugation. Once in the recipient cell, ICEclc can reintegrate into the chromosome by site-specific recombination. This thesis aimed at identifying the regulatory network underlying the decisions for ICEclc horizontal transfer (HGT). The first chapter is an introduction on integrative and conjugative elements (ICEs) more in general, of which ICEclc is one example. In particular I emphasized the current knowledge of regulation and conjugation machineries of the different classes of ICE. In the second chapter, I describe a transcriptional analysis using microarrays and other experiments to understand expression of ICEclc in exponential and stationary phase. By overlaying transcriptomic profiles with Northern hybridizations and RT- PCR data, we established a transcription map for the entire core region of ICEclc, a region assumed to encode the ICE conjugation process. We also demonstrated how transcription of the ICEclc core is maximal in stationary phase, which correlates to expression of reporter genes fused to key ICEclc promoters. In the third chapter, I present a transcriptome analysis of ICEclc in a variety of different host species, in order to explore whether there are species-specific differences. In the fourth chapter, I focus on the role of a curious ICEclc-encoded TetR-type transcriptional repressor. We find that this gene, which we name mfsR, not only controls its own expression but that of a set of genes for a putative multi-drug efflux pump (mfsABC) as well. By using a combination of biochemical and molecular biology techniques, I could show that MfsR specifically binds to operator boxes in two ICEclc promoters (PmfsR and PmfsA), inhibiting the transcription of both the mfsR and mfsABC-orf38184 operons. Although we could not detect a clear phenotype of an mfsABC deletion, we discuss the implications of pump gene reorganizations in ICEclc and close relatives. In the fifth chapter, we find that mfsR not only controls its own expression and that of the mfsABC operon, but is also indirectly controlling ICEclc transfer. Using gene deletions, microarrays, transfer assays and microscopy-based reporter fusions, we demonstrate that mfsR actually controls a small operon of three regulatory genes. The last gene of this mfsR operon, orf17162, encodes a LysR-type activator that when deleted strongly impairs ICEclc transfer. Interestingly, deletion of mfsR leads to transfer competence in almost all cells, thereby overruling the bistability process in the wild-type. In the final sixth chapter, I discuss the relevance of the present thesis and the resulting perspectives for future studies.