Collagen V-induced nasal tolerance downregulates pulmonary collagen mRNA gene and TGF-beta expression in experimental systemic sclerosis

Background: The purpose of this study was to evaluate collagen deposition, mRNA collagen synthesis and TGFbeta expression in the lung tissue in an experimental model of scleroderma after collagen V-induced nasal tolerance. Methods: Female New Zealand rabbits (N = 12) were immunized with 1 mg/ml of collagen V in Freund's adjuvant (IM). After 150 days, six immunized animals were tolerated by nasal administration of collagen V ( 25 mu g/day) (IM-TOL) daily for 60 days. The collagen content was determined by morphometry, and mRNA expressions of types I, III and V collagen were determined by Real-time PCR. The TGF-beta expression was evaluated by immunostaining and quantified by point counting methods. To statistic analysis ANOVA with Bonferroni test were employed for multiple comparison when appropriate and the level of significance was determined to be p < 0.05. Results: IM-TOL, when compared to IM, showed significant reduction in total collagen content around the vessels (0.371 +/- 0.118 vs. 0.874 +/- 0.282, p < 0.001), bronchioles (0.294 +/- 0.139 vs. 0.646 +/- 0.172, p < 0.001) and in the septal interstitium (0.027 +/- 0.014 vs. 0.067 +/- 0.039, p = 0.026). The lung tissue of IM-TOL, when compared to IM, showed decreased immunostaining of types I, III and V collagen, reduced mRNA expression of types I (0.10 +/- 0.07 vs. 1.0 +/- 0.528, p = 0.002) and V (1.12 +/- 0.42 vs. 4.74 +/- 2.25, p = 0.009) collagen, in addition to decreased TGF-beta expression ( p < 0.0001). Conclusions: Collagen V-induced nasal tolerance in the experimental model of SSc regulated the pulmonary remodeling process, inhibiting collagen deposition and collagen I and V mRNA synthesis. Additionally, it decreased TGF-beta expression, suggesting a promising therapeutic option for scleroderma treatment.

Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the sigma(54) regulon

Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a sigma(54)-dependent manner. A more complete picture of the sigma(54) regulon was achieved by combining the transcriptome data with an in silico search for potential sigma(54)-dependent promoters, using a position weight matrix approach. One of these sigma(54)-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a sigma(54)-dependent promoter. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the sigma(54) regulon.

Novel Primate-Specific Genes, RMEL 1, 2 and 3, with Highly Restricted Expression in Melanoma, Assessed by New Data Mining Tool

Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.

Report of a chimeric origin of transposable elements in a bovine-coding gene

Despite the wide distribution of transposable elements (TEs) in mammalian genomes, part of their evolutionary significance remains to be discovered. Today there is a substantial amount of evidence showing that TEs are involved in the generation of new exons in different species. In the present study, we searched 22,805 genes and reported the occurrence of TE-cassettes in coding sequences of 542 cow genes using the RepeatMasker program. Despite the significant number (542) of genes with TE insertions in exons only 14 (2.6%) of them were translated into protein, which we characterized as chimeric genes. From these chimeric genes, only the FAST kinase domains 3 (FASTKD3) gene, present on chromosome BTA 20, is a functional gene and showed evidence of the exaptation event. The genome sequence analysis showed that the last exon coding sequence of bovine FASTKD3 is similar to 85% similar to the ART2A retrotransposon sequence. In addition, comparison among FASTKD3 proteins shows that the last exon is very divergent from those of Homo sapiens, Pan troglodytes and Canis familiares. We suggest that the gene structure of bovine FASTKD3 gene could have originated by several ectopic recombinations between TE copies. Additionally, the absence of TE sequences in all other species analyzed suggests that the TE insertion is clade-specific, mainly in the ruminant lineage.

Polymorphisms and DNA methylation of gene TP53 associated with extra-axial brain tumors

The p53 tumor suppressor gene is the most frequently mutated gene in human cancer; this gene is mutated in up to 50% of human tumors. It has a critical role in the cell cycle, apoptosis and cell senescence, and it participates in many crucial physiological and pathological processes. Polymorphisms of p53 have been suggested to be associated with genetically determined susceptibility in various types of cancer. Another process involved with the development and progression of tumors is DNA hypermethylation. Aberrant methylation of the promoter is an alternative epigenetic change in genetic mechanisms, leading to tumor suppressor gene inactivation. In the present study, we examined the TP53 Arg72Pro and Pro47Ser polymorphisms using PCR-RFLP and the pattern of methylation of the p53 gene by methylation-specific PCR in 90 extra-axial brain tumor samples. Patients who had the allele Pro of the TP53 Arg72Pro polymorphism had an increased risk of tumor development ( odds ratio, OR = 3.23; confidence interval at 95%, 95% CI = 1.71-6.08; P = 0.003), as did the allele Ser of TP53 Pro47Ser polymorphism (OR = 1.28; 95% CI = 0.03-2.10; P = 0.01). Comparison of overall survival of patients did not show significant differences. In the analysis of DNA methylation, we observed that 37.5% of meningiomas, 30% of schwannomas and 52.6% of metastases were hypermethylated, suggesting that methylation is important for tumor progression. We suggest that TP53 Pro47Ser and Arg72Pro polymorphisms and DNA hypermethylation are involved in susceptibility for developing extra-axial brain tumors.

Differential expression of E-cadherin gene in human neuroepithelial tumors

Cadherins are cell-to-cell adhesion molecules that play an important role in the establishment of adherent-type junctions by mediating calcium-dependent cellular interactions. The CDH1 gene encodes the transmembrane glycoprotein E-cadherin which is important in maintaining homophilic cell-cell adhesion in epithelial tissues. E-cadherin interacts with catenin proteins to maintain tissue architecture. Structural defects or loss of expression of E-cadherin have been reported as a common feature in several human cancer types. This study aimed to evaluate the expression of E-cadherin and their correlation with clinical features in microdissected brain tumor samples from 81 patients, divided into 62 astrocytic tumors grades I to IV and 19 medulloblastomas, and from 5 white matter non-neoplasic brain tissue samples. E-cadherin (CDH1) gene expression was analyzed by quantitative real-time polymerase chain reaction. Mann-Whitney, Kruskal-Wallis, Kaplan-Meir, and log-rank tests were performed for statistical analyses. We observed a decrease in expression among pathological grades of neuroepithelial tumors. Non-neoplasic brain tissue showed a higher expression level of CDH1 gene than did neuroepithelial tumors. Expression of E-cadherin gene was higher in astrocytic than embryonal tumors (P = 0.0168). Low-grade malignancy astrocytomas (grades I-II) showed higher CDH1 expression than did high-grade malignancy astrocytomas (grades III-IV) and medulloblastomas (P < 0.0001). Non-neoplasic brain tissue showed a higher expression level of CDH1 gene than grade I malignancy astrocytomas, considered as benign tumors (P = 0.0473). These results suggest that a decrease in E-cadherin gene expression level in high-grade neuroepithelial tumors may be a hallmark of malignancy in dedifferentiated tumors and that it may be possibly correlated with their progression and dissemination.

PSA and androgen-related gene (AR, CYP17, and CYP19) polymorphisms and the risk of adenocarcinoma at prostate biopsy

The aim of the present study was to examine the impact of polymorphisms in prostate-specific antigen (PSA) and androgen-related genes (AR, CYP17, and CYP19) on prostate cancer (PCa) risk in selected high-risk patients who underwent prostate biopsy. Blood samples and prostate tissues were obtained for DNA analysis. Single-nucleotide polymorphisms in the 50-untranslated regions (UTRs) of the PSA (substitution A > G at position -158) and CYP17 (substitution T > C at 50-UTR) genes were detected by polymerase chain reaction (PCR)-restriction fragment length polymorphism assays. The CAG and TTTA repeats in the AR and CYP19 genes, respectively, were genotyped by PCR-based GeneScan analysis. Patients with the GG genotype of the PSA gene had a higher risk of PCa than those with the AG or AA genotype (OR = 3.79, p = 0.00138). The AA genotype was associated with lower PSA levels (6.44 +/- 1.64 ng/mL) compared with genotypes having at least one G allele (10.44 +/- 10.06 ng/mL) (p = 0.0687, 95% CI - 0.3146 to 8.315, unpaired t-test). The multivariate analysis confirmed the association between PSA levels and PSA genotypes (AA vs. AG+GG; chi(2) = 0.0482) and CYP19 (short alleles homozygous vs. at least one long allele; chi(2) = 0.0110) genotypes. Genetic instability at the AR locus leading to somatic mosaicism was detected in one PCa patient by comparing the length of AR CAG repeats in matched peripheral blood and prostate biopsy cores. Taken together, these findings suggest that the PSA genotype should be a clinically relevant biomarker to predict the PCa risk.

Gene silencing during development of in vitro-produced female bovine embryos

In early development, female embryos (XX) produce twice the transcripts of X-linked genes compared with male embryos (XY). During the course of development, inactivation of the X chromosome equilibrates gene dosage, making the development of female embryos viable. Moreover, the biotechnologies used for producing embryos in vitro seem to work better with male embryos, making it easier for them to reach the blastocyst stage and allow for complete gestation. We investigated the expression of three X-linked genes that are involved in development, XIST, G6PD, and HPRT, and of the transcript interferon-tau, in male and female bovine blastocysts produced by nuclear transfer (NT) and by in vitro fertilization (IVF). Oocytes that had been matured in vitro were enucleated and reconstructed with somatic cells from adult animals at 18 h post-maturation. After fusion (two pulses of 2.25 kv/cm) and chemical activation (5.0 mu M ionomycin for 5 min and 2.0 mM 6-DMAP for 3 h), the oocytesomatic cell units were cultivated in CR2 with a monolayer of granulosa cells at 38.8 degrees C, in a humidified 5% CO(2) atmosphere. IVF embryos were inseminated, after centrifugation in a Percoll gradient, with 2 x 10(6) sperm/mL TALP medium supplemented with BSA and PHE and cultivated under the same conditions as the cloned embryos. We used real-time PCR to analyze the gene expression of individual blastocysts compared to expression of the housekeeping gene, GAPDH. The gene XIST was expressed in female embryos and not in male embryos produced by IVF, though it was expressed at low levels in male embryos produced by NT. Unlike previous reports, we found lower levels of the transcript of G6PD in females than in males, suggesting double silencing or other mechanisms of control of this gene. Female embryos produced by IVF expressed the HPRT gene at a higher level than female embryos produced by NT, suggesting that gene silencing proceeds faster in NT-produced female embryos due to ""inactivation memory"" from the nucleus donor. In conclusion, male and female embryos express different levels of X-chromosome genes and failures of these genes that are essential for development could reduce the viability of females. Nuclear transfer can modify this relation, possibly due to epigenetic memory, leading to frequent failures in nuclear reprogramming.

Imprinted gene expression in in vivo- and in vitro-produced bovine embryos and chorio-allantoic membranes

Cloning by nuclear transfer is often associated with poor results due to abnormal nuclear reprogramming of somatic donor cells and altered gene expression patterns. We investigated the expression patterns of imprinted genes IGF2 and IGF2R in 33- to 36-day bovine embryos and chorio-allantoic membranes derived from in vivo- and in vitro-produced embryos by somatic cell nuclear transfer (SCNT), parthenogenetic activation, and in vitro fertilization (IVF). There was a lower IGF2 expression rate in the SCNT (0.19) and parthenogenetic (0.02) groups when compared to in vivo and IVF embryos (2.01; P < 0.05). In the chorio-allantoic membranes, IGF2 showed a baseline expression pattern (P < 0.05) in parthenotes (0.001) when compared to in vivo, IVF (3.13), and SCNT (0.98) groups. IGF2R was less expressed (P < 0.05) in SCNT chorio-allantoic membranes (0.25) when compared to the in vivo group. The low expression of IGF2 in parthenogenetic embryos and chorio-allantoic membranes confirms its imprinted status in cattle. Alterations in the relative frequency of IGF2 and IGF2R transcripts were observed in SCNT-derived bovine embryos and chorioallantoic membranes, respectively, supporting the hypothesis that abnormalities in the expression of imprinted genes are causes of the low efficiency of SCNT procedures in this species.

CONTRASTING PHYLOGEOGRAPHIC PATTERNS IN MITOCHONDRIAL DNA AND MICROSATELLITES: EVIDENCE OF FEMALE PHILOPATRY AND MALE-BIASED GENE FLOW AMONG REGIONAL POPULATIONS OF THE BLUE-AND-YELLOW MACAW (PSITTACIFORMES: ARA ARARAUNA) IN BRAZIL

Comparing the patterns of population differentiation among genetic markers with different modes of inheritance call provide insights into patterns of sex-biased dispersal and gene flow. The blue-and-yellow Macaw (Ara ararauna) is a Neotropical parrot with a broad geographic distribution ill South America. However, little is known about the natural history and current status Of remaining wild populations, including levels of genetic variability. The progressive decline and possible fragmentation of populations may endanger this species in the near future. We analyzed mitochondrial DNA (mtDNA) control-region sequences and six microsatellite 106 Of Blue-and-yellow Macaws sampled throughout their geographic range ill Brazil to describe population genetic Structure, to make inferences about historical demography and dispersal behavior, and to provide insight for conservation efforts. Analyses of population genetic structure based on mtDNA showed evidence of two major populations ill western and eastern Brazil that share a few low-frequency haplotypes. This phylogeographic pattern seems to have originated by the historical isolation of Blue-and-yellow Macaw populations similar to 374,000 years ago and has been maintained by restricted gene flow and female philopatry. By contrast, variation ill biparentally inherited microsatellites was not structured geographically, Male-biased dispersal and female philopatry best explain the different patterns observed in these two markers. Because females disperse less than males, the two regional populations with well-differentiated mtDNA haplogroups should be considered two different management units for conservation purposes. Received 4 November 2007 accepted 10 December 2008.

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.

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/.