Detection of EBV-DNA in serum samples of an immunosuppressed child during a three years follow-up: association of clinical and PCR data with active infection

Twenty-four whole blood and serum samples were drawn from an eight year-old heart transplant child during a 36 months follow-up. EBV serology was positive for VCA-IgM and IgG, and negative for EBNA-IgG at the age of five years old when the child presented with signs and symptoms suggestive of acute infectious mononucleosis. After 14 months, serological parameters were: positive VCA-IgG, EBNA-IgG and negative VCA-IgM. This serological pattern has been maintained since then even during episodes suggestive of EBV reactivation. PCR amplified a specific DNA fragment from the EBV gp220 (detection limit of 100 viral copies). All twenty-four whole blood samples yielded positive results by PCR, while 12 out of 24 serum samples were positive. We aimed at analyzing whether detection of EBV-DNA in serum samples by PCR was associated with overt disease as stated by the need of antiviral treatment and hospitalization. Statistical analysis showed agreement between the two parameters evidenced by the Kappa test (value 0.750; p < 0.001). We concluded that detection of EBV-DNA in serum samples of immunosuppressed patients might be used as a laboratory marker of active EBV disease when a Real-Time PCR or another quantitative method is not available.

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

eVOC: a controlled vocabulary for unifying gene expression data.

Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.

Proof of concept for microarray-based detection of DNA-binding oncogenes in cell extracts.

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level.

Additional data for nuclear DNA give new insights into the phylogenetic position of Sorex granarius within the Sorex araneus group.

Many species contain genetic lineages that are phylogenetically intermixed with those of other species. In the Sorex araneus group, previous results based on mtDNA and Y chromosome sequence data showed an incongruent position of Sorex granarius within this group. In this study, we explored the relationship between species within the S. araneus group, aiming to resolve the particular position of S. granarius. In this context, we sequenced a total of 2447 base pairs (bp) of X-linked and nuclear genes from 47 individuals of the S. araneus group. The same taxa were also analyzed within a Bayesian framework with nine autosomal microsatellites. These analyses revealed that all markers apart from mtDNA showed similar patterns, suggesting that the problematic position of S. granarius is best explained by an incongruent behavior by mtDNA. Given their close phylogenetic relationship and their close geographic distribution, the most likely explanation for this pattern is past mtDNA introgression from S. araneus race Carlit to S. granarius.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

DNA methylation in Dictyostelium discoideum

DNA methyltransferases of type Dnmt2 are a highly conserved protein family with enigmatic function. The aim of this work was to characterize DnmA, the Dnmt2 methyltransferase in Dictyostelium discoideum, and further to investigate its implication in DNA methylation and transcriptional gene silencing. The genome of the social amoeba Dictyostelium encodes DnmA as the sole DNA methyltransferase. The enzyme bears all ten characteristic DNA methyltransferase motifs in its catalytic domain. The DnmA mRNA was found by RT-PCR to be expressed during vegetative growth and down regulated during development. Investigations using fluorescence microscopy showed that both DnmA-myc and DnmA-GFP fusions predominantly localised to the nucleus. The function of DnmA remained initially unclear, but later experiment revealed that the enzyme is an active DNA methyltransferase responsible for all DNA (cytosine) methylation in Dictyostelium. Neither in gel retardation assays, nor by the yeast two hybrid system, clues on the functionality of DnmA could be obtained. However, immunological detection of the methylation mark with an α - 5mC antibody gave initial evidence that the DNA of Dictyostelium was methylated. Furthermore, addition of 5-aza-cytidine as demethylating agent to the Dictyostelium medium and subsequent in vitro incubation of the DNA isolated from these cells with recombinant DnmA showed that the enzyme binds slightly better to this target DNA. In order to investigate further the function of the protein, a gene knock-out for dnmA was generated. The gene was successfully disrupted by homologous recombination, the knock-out strain, however, did not show any obvious phenotype under normal laboratory conditions. To identify specific target sequences for DNA methylation, a microarray analysis was carried out. Setting a threshold of at least 1.5 fold for differences in the strength of gene expression, several such genes in the knock-out strain were chosen for further investigation. Among the up-regulated genes were the ESTs representing the gag and the RT genes respectively of the retrotransposon skipper. In addition Northern blot analysis confirmed the up-regulation of skipper in the DnmA knock-out strain. Bisufite treatment and sequencing of specific DNA stretches from skipper revealed that DnmA is responsible for methylation of mostly asymmetric cytosines. Together with skipper, DIRS-1 retrotransposon was found later also to be methylated but was not present on the microarray. Furthermore, skipper transcription was also up-regulated in strains that had genes disrupted encoding components of the RNA interference pathway. In contrast, DIRS 1 expression was not affected by a loss of DnmA but was strongly increased in the strain that had the RNA directed RNA polymerase gene rrpC disrupted. Strains generated by propagating the usual wild type Ax2 and the DnmA knock-out cells over 16 rounds in development were analyzed for transposon activity. Northern blot analysis revealed activation for skipper expression, but not for DIRS-1. A large number of siRNAs were found to be correspondent to the DIRS-1 sequence, suggesting concerted regulation of DIRS-1 expression by RNAi and DNA methylation. In contrast, no siRNAs corresponding to the standard skipper element were found. The data show that DNA methylation plays a crucial role in epigenetic gene regulation in Dictyostelium and that different, partially overlapping mechanisms control transposon silencing for skipper and DIRS-1. To elucidate the mechanism of targeting the protein to particular genes in the Dictyostelium genome, some more genes which were up-regulated in the DnmA knock-out strain were analyzed by bisulfite sequencing. The chosen genes are involved in the multidrug response in other species, but their function in Dictyostelium is uncertain. Bisulfite data showed that two of these genes were methylated at asymmetrical C-residues in the wild type, but not in DnmA knock-out cells. This suggested that DNA methylation in Dictyostelium is involved not only in transposon regulation but also in transcriptional silencing of specific genes.

Optimising the analysis of transcript data using high density oligonucleotide arrays and genomic DNA-based probe selection

Background: Affymetrix GeneChip arrays are widely used for transcriptomic studies in a diverse range of species. Each gene is represented on a GeneChip array by a probe- set, consisting of up to 16 probe-pairs. Signal intensities across probe- pairs within a probe-set vary in part due to different physical hybridisation characteristics of individual probes with their target labelled transcripts. We have previously developed a technique to study the transcriptomes of heterologous species based on hybridising genomic DNA (gDNA) to a GeneChip array designed for a different species, and subsequently using only those probes with good homology. Results: Here we have investigated the effects of hybridising homologous species gDNA to study the transcriptomes of species for which the arrays have been designed. Genomic DNA from Arabidopsis thaliana and rice (Oryza sativa) were hybridised to the Affymetrix Arabidopsis ATH1 and Rice Genome GeneChip arrays respectively. Probe selection based on gDNA hybridisation intensity increased the number of genes identified as significantly differentially expressed in two published studies of Arabidopsis development, and optimised the analysis of technical replicates obtained from pooled samples of RNA from rice. Conclusion: This mixed physical and bioinformatics approach can be used to optimise estimates of gene expression when using GeneChip arrays.

Identificação de perfis diferenciais de metilação do DNA na endometriose

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Phylogenetic analysis of 16S mitochondrial DNA data in sloths and anteaters

We sequenced part of the 16S rRNA mitochondrial gene in 17 extant taxa of Pilosa (sloths and anteaters) and used these sequences along with GenBank sequences of both extant and extinct sloths to perform phylogenetic analysis based on parsimony, maximum-likelihood and Bayesian methods. By increasing the taxa density for anteaters and sloths we were able to clarify some points of the Pilosa phylogenetic tree. Our mitochondrial 16S results show Bradypodidae as a monophyletic and robustly supported clade in all the analysis. However, the Pleistocene fossil Mylodon darwinii does not group significantly to either Bradypodidae or Megalonychidae which indicates that trichotomy best represents the relationship between the families Mylodontidae, Bradypodidae and Megalonychidae. Divergence times also allowed us to discuss the taxonomic status of Cyclopes and the three species of three-toed sloths, Bradypus tridactylus, Bradypus variegatus and Bradypus torquatus. In the Bradypodidae the split between Bradypus torquatus and the proto-Bradypus tridactylus / B. variegatus was estimated as about 7.7 million years ago (MYA), while in the Myrmecophagidae the first offshoot was Cyclopes at about 31.8 MYA followed by the split between Myrmecophaga and Tamandua at 12.9 MYA. We estimate the split between sloths and anteaters to have occurred at about 37 MYA.

DNA barcode of Parodontidae species from the La Plata river basin - applying new data to clarify taxonomic problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação da expressão gênica e de lesões no DNA de índividuos portadores de diabetes mellitus tipo 2, dislipidemia e periodontite crônica

Pós-graduação em Odontologia - FOAR

Genomic characterization of the italian wolf (Canis lupus): the genes involved in black coat colour determination and application of microarray technique for snps detection.

This study provides a comprehensive genetic overview on the endangered Italian wolf population. In particular, it focuses on two research lines. On one hand, we focalised on melanism in wolf in order to isolate a mutation related with black coat colour in canids. With several reported black individuals (an exception at European level), the Italian wolf population constituted a challenging research field posing many unanswered questions. As found in North American wolf, we reported that melanism in the Italian population is caused by a different melanocortin pathway component, the K locus, in which a beta-defensin protein acts as an alternative ligand for the Mc1r. This research project was conducted in collaboration with Prof. Gregory Barsh, Department of Genetics and Paediatrics, Stanford University. On the other hand, we performed analysis on a high number of SNPs thanks to a customized Canine microarray useful to integrate or substitute the STR markers for genotyping individuals and detecting wolf-dog hybrids. Thanks to DNA microchip technology, we obtained an impressive amount of genetic data which provides a solid base for future functional genomic studies. This study was undertaken in collaboration with Prof. Robert K. Wayne, Department of Ecology and Evolutionary Biology, University of California, Los Angeles (UCLA).

Comparative DNA sequence and methylation analyses of orthologous genes in humans and non-human primates: Genetic and epigenetic footprints of evolution

Welche genetische Unterschiede machen uns verschieden von unseren nächsten Verwandten, den Schimpansen, und andererseits so ähnlich zu den Schimpansen? Was wir untersuchen und auch verstehen wollen, ist die komplexe Beziehung zwischen den multiplen genetischen und epigenetischen Unterschieden, deren Interaktion mit diversen Umwelt- und Kulturfaktoren in den beobachteten phänotypischen Unterschieden resultieren. Um aufzuklären, ob chromosomale Rearrangements zur Divergenz zwischen Mensch und Schimpanse beigetragen haben und welche selektiven Kräfte ihre Evolution geprägt haben, habe ich die kodierenden Sequenzen von 2 Mb umfassenden, die perizentrischen Inversionsbruchpunkte flankierenden Regionen auf den Chromosomen 1, 4, 5, 9, 12, 17 und 18 untersucht. Als Kontrolle dienten dabei 4 Mb umfassende kollineare Regionen auf den rearrangierten Chromosomen, welche mindestens 10 Mb von den Bruchpunktregionen entfernt lagen. Dabei konnte ich in den Bruchpunkten flankierenden Regionen im Vergleich zu den Kontrollregionen keine höhere Proteinevolutionsrate feststellen. Meine Ergebnisse unterstützen nicht die chromosomale Speziationshypothese für Mensch und Schimpanse, da der Anteil der positiv selektierten Gene (5,1% in den Bruchpunkten flankierenden Regionen und 7% in den Kontrollregionen) in beiden Regionen ähnlich war. Durch den Vergleich der Anzahl der positiv und negativ selektierten Gene per Chromosom konnte ich feststellen, dass Chromosom 9 die meisten und Chromosom 5 die wenigsten positiv selektierten Gene in den Bruchpunkt flankierenden Regionen und Kontrollregionen enthalten. Die Anzahl der negativ selektierten Gene (68) war dabei viel höher als die Anzahl der positiv selektierten Gene (17). Eine bioinformatische Analyse von publizierten Microarray-Expressionsdaten (Affymetrix Chip U95 und U133v2) ergab 31 Gene, die zwischen Mensch und Schimpanse differentiell exprimiert sind. Durch Untersuchung des dN/dS-Verhältnisses dieser 31 Gene konnte ich 7 Gene als negativ selektiert und nur 1 Gen als positiv selektiert identifizieren. Dieser Befund steht im Einklang mit dem Konzept, dass Genexpressionslevel unter stabilisierender Selektion evolvieren. Die meisten positiv selektierten Gene spielen überdies eine Rolle bei der Fortpflanzung. Viele dieser Speziesunterschiede resultieren eher aus Änderungen in der Genregulation als aus strukturellen Änderungen der Genprodukte. Man nimmt an, dass die meisten Unterschiede in der Genregulation sich auf transkriptioneller Ebene manifestieren. Im Rahmen dieser Arbeit wurden die Unterschiede in der DNA-Methylierung zwischen Mensch und Schimpanse untersucht. Dazu wurden die Methylierungsmuster der Promotor-CpG-Inseln von 12 Genen im Cortex von Menschen und Schimpansen mittels klassischer Bisulfit-Sequenzierung und Bisulfit-Pyrosequenzierung analysiert. Die Kandidatengene wurden wegen ihrer differentiellen Expressionsmuster zwischen Mensch und Schimpanse sowie wegen Ihrer Assoziation mit menschlichen Krankheiten oder dem genomischen Imprinting ausgewählt. Mit Ausnahme einiger individueller Positionen zeigte die Mehrzahl der analysierten Gene keine hohe intra- oder interspezifische Variation der DNA-Methylierung zwischen den beiden Spezies. Nur bei einem Gen, CCRK, waren deutliche intraspezifische und interspezifische Unterschiede im Grad der DNA-Methylierung festzustellen. Die differentiell methylierten CpG-Positionen lagen innerhalb eines repetitiven Alu-Sg1-Elements. Die Untersuchung des CCRK-Gens liefert eine umfassende Analyse der intra- und interspezifischen Variabilität der DNA-Methylierung einer Alu-Insertion in eine regulatorische Region. Die beobachteten Speziesunterschiede deuten darauf hin, dass die Methylierungsmuster des CCRK-Gens wahrscheinlich in Adaption an spezifische Anforderungen zur Feinabstimmung der CCRK-Regulation unter positiver Selektion evolvieren. Der Promotor des CCRK-Gens ist anfällig für epigenetische Modifikationen durch DNA-Methylierung, welche zu komplexen Transkriptionsmustern führen können. Durch ihre genomische Mobilität, ihren hohen CpG-Anteil und ihren Einfluss auf die Genexpression sind Alu-Insertionen exzellente Kandidaten für die Förderung von Veränderungen während der Entwicklungsregulation von Primatengenen. Der Vergleich der intra- und interspezifischen Methylierung von spezifischen Alu-Insertionen in anderen Genen und Geweben stellt eine erfolgversprechende Strategie dar.