Positive Selection Results in Frequent Reversible Amino Acid Replacements in the G Protein Gene of Human Respiratory Syncytial Virus

Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a ""flipflop'' phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

AFFINE INTERVAL EXCHANGE TRANSFORMATIONS WITH FLIPS AND WANDERING INTERVALS

There exist uniquely ergodic affine interval exchange transformations of [0,1] with flips which have wandering intervals and are such that the support of the invariant measure is a Cantor set.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

Identification of the Schistosoma mansoni TNF-Alpha Receptor Gene and the Effect of Human TNF-Alpha on the Parasite Gene Expression Profile

Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

Lower Bounds on the Exchange-Correlation Energy in Reduced Dimensions

Bounds on the exchange-correlation energy of many-electron systems are derived and tested. By using universal scaling properties of the electron-electron interaction, we obtain the exponent of the bounds in three, two, one, and quasione dimensions. From the properties of the electron gas in the dilute regime, the tightest estimate to date is given for the numerical prefactor of the bound, which is crucial in practical applications. Numerical tests on various low-dimensional systems are in line with the bounds obtained and give evidence of an interesting dimensional crossover between two and one dimensions.

Physical signatures of discontinuities of the time-dependent exchange-correlation potential

The exact exchange-correlation (XC) potential in time-dependent density-functional theory (TDDFT) is known to develop steps and discontinuities upon change of the particle number in spatially confined regions or isolated subsystems. We demonstrate that the self-interaction corrected adiabatic local-density approximation for the XC potential has this property, using the example of electron loss of a model quantum well system. We then study the influence of the XC potential discontinuity in a real-time simulation of a dissociation process of an asymmetric double quantum well system, and show that it dramatically affects the population of the resulting isolated single quantum wells. This indicates the importance of a proper account of the discontinuities in TDDFT descriptions of ionization, dissociation or charge transfer processes.

Contribution of the second Landau level to the exchange energy of the three-dimensional electron gas in a high magnetic field

We derive a closed analytical expression for the exchange energy of the three-dimensional interacting electron gas in strong magnetic fields, which goes beyond the quantum limit (L=0) by explicitly including the effect of the second, L=1, Landau level and arbitrary spin polarization. The inclusion of the L=1 level brings the fields to which the formula applies closer to the laboratory range, as compared to previous expressions, valid only for L=0 and complete spin polarization. We identify and explain two distinct regimes separated by a critical density n(c). Below n(c), the per particle exchange energy is lowered by the contribution of L=1, whereas above n(c) it is increased. As special cases of our general equation we recover various known more limited results for higher fields, and we identify and correct a few inconsistencies in some of these earlier expressions.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Identification of COL6A1 as a differentially expressed gene in human astrocytomas

Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly in patients with heart failure

Background -: Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly and Thr164Ile were suggested to have an effect in heart failure. We evaluated these polymorphisms relative to clinical characteristics and prognosis of alarge cohort of patients with heart failure of different etiologies. Methods -: We studied 501 patients with heart failure of different etiologies. Mean age was 58 years (standard deviation 14.4 years), 298 (60%) were men. Polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism. Results -: During the mean follow-up of 12.6 months (standard deviation 10.3 months), 188 (38%) patients died. Distribution of genotypes of polymorphism Arg16Gly was different relative to body mass index (chi(2) = 9.797; p = 0.04). Overall the probability of survival was not significantly predicted by genotypes of Gln27Glu, Arg16Gly, or Thr164Ile. Allele and haplotype analysis also did not disclose any significant difference regarding mortality. Exploratory analysis through classification trees pointed towards a potential association between the Gln27Glu polymorphism and mortality in older individuals. Conclusion -: In this study sample, we were not able to demonstrate an overall influence of polymorphisms Gln27Glu and Arg16Gly of beta-2 receptor gene on prognosis. Nevertheless, Gln27Glu polymorphism may have a potential predictive value in older individuals.

Ric-8A, a G alpha protein guanine nucleotide exchange factor potentiates taste receptor signaling

Taste receptors for sweet, bitter and umami tastants are G-protein-coupled receptors (GPCRs). While much effort has been devoted to understanding G-protein-receptor interactions and identifying the components of the signalling cascade downstream of these receptors, at the level of the G-protein the modulation of receptor signal transduction remains relatively unexplored. In this regard a taste-specific regulator of G-protein signaling (RGS), RGS21, has recently been identified. To study whether guanine nucleotide exchange factors (GEFs) are involved in the transduction of the signal downstream of the taste GPCRs we investigated the expression of Ric-8A and Ric-8B in mouse taste cells and their interaction with G-protein subunits found in taste buds. Mammalian Ric-8 proteins were initially identified as potent GEFs for a range of G alpha subunits and Ric-8B has recently been shown to amplify olfactory signal transduction. We find that both Ric-8A and Ric-8B are expressed in a large portion of taste bud cells and that most of these cells contain IP3R-3 a marker for sweet, umami and bitter taste receptor cells. Ric-8A interacts with G alpha-gustducin and G alpha i2 through which it amplifies the signal transduction of hTas2R16, a receptor for bitter compounds. Overall, these findings are consistent with a role for Ric-8 in mammalian taste signal transduction.

A NOVEL EPIPHYTIC CYANOBACTERIAL SPECIES FROM THE GENUS BRASILONEMA CAUSING DAMAGE TO EUCALYPTUS LEAVES

A cyanobacterial mat colonizing the leaves of Eucalyptus grandis was determined to be responsible for serious damage affecting the growth and development of whole plants under the clonal hybrid nursery conditions. The dominant cyanobacterial species was isolated in BG-11 medium lacking a source of combined nitrogen and identified by cell morphology characters and molecular phylogenetic analysis (16S rRNA gene and cpcBA-IGS sequences). The isolated strain represents a novel species of the genus Brasilonema and is designated Brasilonema octagenarum strain UFV-E1. Thin sections of E. grandis leaves analyzed by light and electron microscopy showed that the B. octagenarum UFV-E1 filaments penetrate into the leaf mesophyll. The depth of infection and the mechanism by which the cyanobacterium invades leaf tissue were not determined. A major consequence of colonization by this cyanobacterium is a reduction in photosynthesis in the host since the cyanobacterial mats decrease the amount of light incident on leaf surfaces. Moreover, the cyanobacteria also interfere with stomatal gas exchange, decreasing CO2 assimilation. To our knowledge, this is the first report of an epiphytic cyanobacterial species causing damage to E. grandis leaves.

Cuff-induced vascular intima thickening is influenced by titration of the Ace gene in mice

Lacchini S, Heimann AS, Evangelista FS, Cardoso L, Silva GJ, Krieger JE. Cuff-induced vascular intima thickening is influenced by titration of the Ace gene in mice. Physiol Genomics 37: 225-230, 2009. First published March 3, 2009; doi:10.1152/physiolgenomics.90288.2008.-We tested the hypothesis that small changes in angiotensin I-converting enzyme (ACE) expression can alter the vascular response to injury. Male mice containing one, two, three, and four copies of the Ace gene with no detectable vascular abnormality or changes in blood pressure were submitted to cuff-induced femoral artery injury. Femoral thickening was higher in 3- and 4-copy mice (42.4 +/- 4.3% and 45.7 +/- 6.5%, respectively) compared with 1- and 2-copy mice (8.3 +/- 1.3% and 8.5 +/- 0.9%, respectively). Femoral ACE levels from control and injured vessels were assessed in 1- and 3-copy Ace mice, which represent the extremes of the observed response. ACE vascular activity was higher in 3- vs. 1-copy Ace mice (2.4-fold, P < 0.05) in the control uninjured vessel. Upon injury, ACE activity significantly increased in both groups [2.41-fold and 2.14-fold (P < 0.05) for 1- and 3-copy groups, respectively] but reached higher levels in 3- vs. 1-copy Ace mice (P < 0.05). Pharmacological interventions were then used as a counterproof and to indirectly assess the role of angiotensin II (ANG II) on this response. Interestingly, ACE inhibition (enalapril) and ANG II AT(1) receptor blocker (losartan) reduced intima thickening in 3-copy mice to 1-copy mouse values (P < 0.05) while ANG II treatment significantly increased intima thickening in 1-copy mice to 3-copy mouse levels (P < 0.05). Together, these data indicate that small physiologically relevant changes in ACE, not associated with basal vascular abnormalities or blood pressure levels, do influence the magnitude of cuff-induced neointima thickening in mice.