Expression of an activating mutation in the gene encoding the K(ATP) channel subunit Kir6.2 in mouse pancreatic beta cells recapitulates neonatal diabetes

Neonatal diabetes is a rare monogenic form of diabetes that usually presents within the first six months of life. It is commonly caused by gain-of-function mutations in the genes encoding the Kir6.2 and SUR1 subunits of the plasmalemmal ATP-sensitive K(+) (K(ATP)) channel. To better understand this disease, we generated a mouse expressing a Kir6.2 mutation (V59M) that causes neonatal diabetes in humans and we used Cre-lox technology to express the mutation specifically in pancreatic beta cells. These beta-V59M mice developed severe diabetes soon after birth, and by 5 weeks of age, blood glucose levels were markedly increased and insulin was undetectable. Islets isolated from beta-V59M mice secreted substantially less insulin and showed a smaller increase in intracellular calcium in response to glucose. This was due to a reduced sensitivity of K(ATP) channels in pancreatic beta cells to inhibition by ATP or glucose. In contrast, the sulfonylurea tolbutamide, a specific blocker of K(ATP) channels, closed K(ATP) channels, elevated intracellular calcium levels, and stimulated insulin release in beta-V59M beta cells, indicating that events downstream of K(ATP) channel closure remained intact. Expression of the V59M Kir6.2 mutation in pancreatic beta cells alone is thus sufficient to recapitulate the neonatal diabetes observed in humans. beta-V59M islets also displayed a reduced percentage of beta cells, abnormal morphology, lower insulin content, and decreased expression of Kir6.2, SUR1, and insulin mRNA. All these changes are expected to contribute to the diabetes of beta-V59M mice. Their cause requires further investigation.

Activation of endogenous p53 by combined p19Arf gene transfer and nutlin-3 drug treatment modalities in the murine cell lines B16 and C6

Background: Reactivation of p53 by either gene transfer or pharmacologic approaches may compensate for loss of p19Arf or excess mdm2 expression, common events in melanoma and glioma. In our previous work, we constructed the pCLPG retroviral vector where transgene expression is controlled by p53 through a p53-responsive promoter. The use of this vector to introduce p19Arf into tumor cells that harbor p53wt should yield viral expression of p19Arf which, in turn, would activate the endogenous p53 and result in enhanced vector expression and tumor suppression. Since nutlin-3 can activate p53 by blocking its interaction with mdm2, we explored the possibility that the combination of p19Arf gene transfer and nutlin-3 drug treatment may provide an additive benefit in stimulating p53 function. Methods: B16 (mouse melanoma) and C6 (rat glioma) cell lines, which harbor p53wt, were transduced with pCLPGp19 and these were additionally treated with nutlin-3 or the DNA damaging agent, doxorubicin. Viral expression was confirmed by Western, Northern and immunofluorescence assays. p53 function was assessed by reporter gene activity provided by a p53-responsive construct. Alterations in proliferation and viability were measured by colony formation, growth curve, cell cycle and MTT assays. In an animal model, B16 cells were treated with the pCLPGp19 virus and/or drugs before subcutaneous injection in C57BL/6 mice, observation of tumor progression and histopathologic analyses. Results: Here we show that the functional activation of endogenous p53wt in B16 was particularly challenging, but accomplished when combined gene transfer and drug treatments were applied, resulting in increased transactivation by p53, marked cell cycle alteration and reduced viability in culture. In an animal model, B16 cells treated with both p19Arf and nutlin-3 yielded increased necrosis and decreased BrdU marking. In comparison, C6 cells were quite susceptible to either treatment, yet p53 was further activated by the combination of p19Arf and nutlin-3. Conclusions: To the best of our knowledge, this is the first study to apply both p19Arf and nutlin-3 for the stimulation of p53 activity. These results support the notion that a p53 responsive vector may prove to be an interesting gene transfer tool, especially when combined with p53- activating agents, for the treatment of tumors that retain wild-type p53.

Comparison Between Single-Diode Low-Level Laser Therapy (LLLT) and LED Multi-Diode (Cluster) Therapy (LEDT) Applications Before High-Intensity Exercise

Background Data and Objective: There is anecdotal evidence that low-level laser therapy (LLLT) may affect the development of muscular fatigue, minor muscle damage, and recovery after heavy exercises. Although manufacturers claim that cluster probes (LEDT) maybe more effective than single-diode lasers in clinical settings, there is a lack of head-to-head comparisons in controlled trials. This study was designed to compare the effect of single-diode LLLT and cluster LEDT before heavy exercise. Materials and Methods: This was a randomized, placebo-controlled, double-blind cross-over study. Young male volleyball players (n = 8) were enrolled and asked to perform three Wingate cycle tests after 4 x 30 sec LLLT or LEDT pretreatment of the rectus femoris muscle with either (1) an active LEDT cluster-probe (660/850 nm, 10/30mW), (2) a placebo cluster-probe with no output, and (3) a single-diode 810-nm 200-mW laser. Results: The active LEDT group had significantly decreased post-exercise creatine kinase (CK) levels (-18.88 +/- 41.48U/L), compared to the placebo cluster group (26.88 +/- 15.18U/L) (p < 0.05) and the active single-diode laser group (43.38 +/- 32.90U/L) (p<0.01). None of the pre-exercise LLLT or LEDT protocols enhanced performance on the Wingate tests or reduced post-exercise blood lactate levels. However, a non-significant tendency toward lower post-exercise blood lactate levels in the treated groups should be explored further. Conclusion: In this experimental set-up, only the active LEDT probe decreased post-exercise CK levels after the Wingate cycle test. Neither performance nor blood lactate levels were significantly affected by this protocol of pre-exercise LEDT or LLLT.

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.

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.

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.

Protein-polysaccharide viscoelastic matrices: synergic effects of amylose on lysozyme physical gelation in aqueous dimethylsulfoxide

A synergic effect of amylose on rheological characteristics of lysozyme physical gels evolved out of dimethylsulfoxide-water was verified and analyzed. The dynamics of the gels were experimentally approached by oscillatory rheology. The synergic effect was characterized by a decrease in the threshold DMSO volume fraction required for lysozyme gelation, and by a significant strengthening of the gel structure at over-critical solvent and protein concentrations. Drastic changes in the relaxation and creep curve patterns for systems in the presence of amylose were verified. Complex viscosity dependence on temperature was found to conform to an Arrhenius-like equation, allowing the determination of an activation energy term (Ea, apparent) for discrimination of gel rigidity. A dilatant effect was found to be induced by temperature on the flow behavior of lysozyme dispersions in DMSO-H(2)O in sub-critical conditions for gelation, which was greatly intensified by the presence of amylose in the samples. That transition was interpreted as reflecting a change from a predominant colloidal flow regime, where globular components are the prevailing structural elements, to a mainly fibrillar, polymeric flow behavior.

Microsatellite Polymorphisms in Cassava Landraces from the Cerrado Biome, Mato Grosso do Sul, Brazil

Using nine microsatellite loci, we investigated genetic structure and diversity in 83 Brazilian cassava accessions, including several landraces, in the Cerrado biome in Mato Grosso do Sul, Brazil. All nine loci were polymorphic, averaging 6.00 alleles per locus. Treating each of seven municipalities as a cassava group or population, they averaged 3.5 alleles per locus, with 97% polymorphic loci, high values for observed heterozygosity (0.32) and gene diversity (0.56). Total genetic variability was high (0.668), and most of this genetic variability was concentrated within municipalities (0.577). Cluster and structure analyses divided accessions into two major clusters or populations (K = 2). Also, a significant genetic versus geographic correlation was found (r = 0.4567; P < 0.0260). Migratory routes in the Cerrado are considered main contributors to the region`s high cassava diversity and spatial genetic structure, amplifying interactions between traditional farmers and the evolutionary dynamics of this crop.

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.

Exercise training improves muscle vasodilatation in individuals with T786C polymorphism of endothelial nitric oxide synthase gene

Negrão M.V, Alves CR, Alves G.B, Pereira A.C, Dias R.G, Laterza M.C, Mota G.F, Oliveira E.M, Bassaneze V, Krieger J.E, Negrão C.E, Rondon M.U.P. Exercise training improves muscle vasodilatation in individuals with T786C polymorphism of endothelial nitric oxide synthase gene. Physiol Genomics 42A: 71-77, 2010. First published July 6, 2010; doi:10.1152/physiolgenomics.00145.2009.-Allele T at promoter region of the eNOS gene has been associated with an increase in coronary disease mortality, suggesting that this allele increases susceptibility for endothelial dysfunction. In contrast, exercise training improves endothelial function. Thus, we hypothesized that: 1) Muscle vasodilatation during exercise is attenuated in individuals homozygous for allele T, and 2) Exercise training improves muscle vasodilatation in response to exercise for TT genotype individuals. From 133 preselected healthy individuals genotyped for the T786C polymorphism, 72 participated in the study: TT (n = 37; age 27 +/- 1 yr) and CT + CC (n = 35; age 26 +/- 1 yr). Forearm blood flow (venous occlusion plethysmography) and blood pressure (oscillometric automatic cuff) were evaluated at rest and during 30% handgrip exercise. Exercise training consisted of three sessions per week for 18 wk, with intensity between anaerobic threshold and respiratory compensation point. Resting forearm vascular conductance (FVC, P = 0.17) and mean blood pressure (P = 0.70) were similar between groups. However, FVC responses during handgrip exercise were significantly lower in TT individuals compared with CT + CC individuals (0.39 +/- 0.12 vs. 1.08 +/- 0.27 units, P = 0.01). Exercise training significantly increased peak VO(2) in both groups, but resting FVC remained unchanged. This intervention significantly increased FVC response to handgrip exercise in TT individuals (P = 0.03), but not in CT + CC individuals (P = 0.49), leading to an equivalent FVC response between TT and CT + CC individuals (1.05 +/- 0.18 vs. 1.59 +/- 0.27 units, P = 0.27). In conclusion, exercise training improves muscle vasodilatation in response to exercise in TT genotype individuals, demonstrating that genetic variants influence the effects of interventions such as exercise training.