Analysis of HIV- type 1 protease and reverse transcriptase in Brazilian children failing highly active antiretroviral therapy (HAART)

The aim of this study was to evaluate the genotypic resistance profiles of HIV-1 in children failing highly active antiretroviral therapy (HAART). Forty-one children (median age = 67 months) receiving HAART were submitted to genotypic testing when virological failure was detected. cDNA was extracted from PBMCs and amplified by nested PCR for the reverse transcriptase and protease regions of the pol gene. Drug resistance genotypes were determined from DNA sequencing. According to the genotypic analysis, 12/36 (33.3%) and 6/36 (16.6%) children showed resistance and possible resistance, respectively, to ZDV; 5/36 (14%) and 4/36 (11.1%), respectively, showed resistance and possible resistance to ddI; 4/36 (11.1%) showed resistance to 3TC and D4T; and 3/36 (8.3%) showed resistance to Abacavir. A high percentage (54%) of children exhibited mutations conferring resistance to NNRTI class drugs. Respective rates of resistance and possible resistance to PIs were: RTV (12.2%, 7.3%); APV (2.4%, 12.1%); SQV(0%, 12.1%); IDV (14.6%, 4.9%), NFV (22%, 4.9%), LPV/RTV (2.4%, 12.1%). Overall, 37/41 (90%) children exhibited virus with mutations related to drug resistance, while 9% exhibited resistance to all three antiretroviral drug classes.

RNA-seq analysis of the Quercus suber root response to drought

Dissertação de mestrado em Plant Molecular Biology, Biotechnology and Bioentrepreneurship

Investigación de defectos genéticos en el sistema de la fosforilasa hepática en pacientes argentinos. Definición nosológica mediante una estrategia de análisis molecular. Investigation of genetic defects in the hepatic phosphorylase system in Argentinean patients. Nosological definition by molecular analysis strategy.

Las Enfermedades de Atesoramiento de Glucógeno (EAGs) también llamadas Glucogenosis comprenden un grupo de entidades causadas por una deficiencia enzimática específica relacionada con la vía de síntesis o degradación de esta macromolécula. La heterogeneidad fenotípica de los pacientes afectados dificulta la identificación de las diferentes variantes de EAG y por ende la correcta definición nosológica. En el Centro de Estudio de las Metabolopatías Congénitas, CEMECO, se fueron definiendo los diferentes tipos de Glucogenosis a través de una estrategia multidisciplinaria que integra distintos niveles de investigación clínica y complementaria, laboratorio metabólico especializado, enzimático, histomorfológico y de análisis molecular. Sin embargo, en algunos enfermos, entre los que se encuentran aquellos con defectos en el sistema de la fosforilasa hepática (EAG-VI y EAG-IX), la exacta definición nosológica aún no está resulta. La EAG-VI se refiere a un defecto en la fosforilasa hepática, enzima codificada por el gen PYGL, mientras que la EAG-IX es causada por un defecto genético en una de las subunidades de la fosforilasa b quinasa hepática codicadas por los genes PHKA2, PHKB y PHKG2, respectivamente. El objetivo del presente trabajo es propender a la definición nosológica de pacientes con defectos en el sistema de la fosforilasa mediante una estrategia de análisis molecular investigando los genes PYGL, PHKA2, PHKB y PHKG2. Los pacientes incluidos en este estudio deberán ser compatibles de padecer una EAG-VI o EAG-IX sobre la base de síntomas clínicos y hallazgos bioquímicos. La metodología incluirá la determinación de la enzima fosforilasa b quinasa en glóbulos rojos y dentro del análisis molecular la extracción de DNA genómico a partir de sangre entera para la amplificación por PCR de los exones más las uniones exon/intron de los genes PHKG2 y PYGL y la extracción de RNA total y obtención de cDNA para posterior amplificación de los cDNA PHKA2 y PHKB. Todos los fragmentos amplificados serán sometidos a análisis de secuencia de nucleótidos. Resultados esperados. Este trabajo, primero en Argentina, permitirá establecer las bases moleculares de los defectos del sistema de la fosforilasa hepática (EAG-VI y EAG-IX). El poder lograr este nivel de investigación traerá aparejado, una oferta integrativa en el vasto capítulo de las glucogenosis hepáticas, con extraordinaria significación en la práctica asistencial para el manejo, pronóstico y correspondiente asesoramiento genético. Hepatic glycogen storage diseases (GSDs) are a group of disorders produced by a deficiency in a specific protein involved in the metabolism of glycogen causing different types of GSDs. Phenotypic heterogeneity of affected patients difficult to identify the different GSD variants and therefore the correct definition of the disease. In the “Centro de Estudio de las Metabolopatías Congénitas”, CEMECO, were defined the different GSD types by a protocol which included complex gradual levels of clinical, biochemical, enzymatic and morphological investigation. However, in some patients, like those one with defects in the hepatic phosphorylase system (GSD-VI and GSD-IX) the exact definition of the disease has not yet been resolved. The GSD-VI is produced by a defect in the PYGL gen that encode the liver phosphorylase, while the GSD-IX is caused by a genetic defect in one of the Phosphorylase b kinase subunits, encoded by the PHKA2, PHKB and PHKG2 genes, respectively. The aim of the present study is to define the phosphorylase system defects in argentinian patients through a molecular strategy that involve the investigation of PYGL, PHKA2, PHKB and PHKG2 genes. Patients included in the present study must be compatible with a GSD-VI or GSD-IX on the bases of clinical symptoms and biochemical findings. The phosphorylase b kinase activity will be assay on in blood red cells. The molecular study will include genomic DNA extraction for the amplification of PHKG2 and PYGL genes and the total RNA extraction for amplification of the PHKA2 and PHKB cDNA by PCR. All PCR-amplified fragments will be subjected to direct nucleotide sequencing. This work, first in Argentina, will make possible to establish the molecular basis of the defects on the hepatic phosphorylase system (GSD-VI and GSD IX). To achieve this level of research will entail advance in the study of the hepatic glycogen storage disease, with extraordinary significance in the treatment, prognosis and the genetic counselling.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Analysis of expressed sequence tags from Trypanosoma cruzi amastigotes

A total of 880 expressed sequence tags (EST) originated from clones randomly selected from a Trypanosoma cruzi amastigote cDNA library have been analyzed. Of these, 40% (355 ESTs) have been identified by similarity to sequences in public databases and classified according to functional categorization of their putative products. About 11% of the mRNAs expressed in amastigotes are related to the translational machinery, and a large number of them (9% of the total number of clones in the library) encode ribosomal proteins. A comparative analysis with a previous study, where clones from the same library were selected using sera from patients with Chagas disease, revealed that ribosomal proteins also represent the largest class of antigen coding genes expressed in amastigotes (54% of all immunoselected clones). However, although more than thirty classes of ribosomal proteins were identified by EST analysis, the results of the immunoscreening indicated that only a particular subset of them contains major antigenic determinants recognized by antibodies from Chagas disease patients.

Trypanosoma cruzi ribosomal protein S4: characterization of its coding locus, analysis of transcripts, and antigenicity of the protein

Two allelic genomic fragments containing ribosomal protein S4 encoding genes (rpS4) from Trypanosoma cruzi (CL-Brener strain) were isolated and characterized. One allele comprises two complete tandem repeats of a sequence encoding an rpS4 gene. In the other, only one rpS4 gene is found. Sequence comparison to the accessed data in the genome project database reveals that our two-copy allele corresponds to a variant haplotype. However, the deduced aminoacid sequence of all the gene copies is identical. The rpS4 transcripts processing sites were determined by comparison of genomic sequences with published cDNA data. The obtained sequence data demonstrates that rpS4 genes are expressed in epimastigotes, amastigotes, and trypomastigotes. A recombinant version of rpS4 was found to be an antigenic: it was recognized by 62.5% of the individuals with positive serology for T. cruzi and by 93.3% of patients with proven chronic chagasic disease.

Transcriptome analysis of the mobile genome ICEclc in Pseudomonas knackmussii B13.

Background: Integrative and conjugative elements (ICE) form a diverse group of DNA elements that are integrated in the chromosome of the bacterial host, but can occasionally excise and horizontally transfer to a new host cell. ICE come in different families, typically with a conserved core for functions controlling the element's behavior and a variable region providing auxiliary functions to the host. The ICEclc element of Pseudomonas knackmussii strain B13 is representative for a large family of chromosomal islands detected by genome sequencing approaches. It provides the host with the capacity to degrade chloroaromatics and 2-aminophenol. Results: Here we study the transcriptional organization of the ICEclc core region. By northern hybridizations, reverse-transcriptase polymerase chain reaction (RT-PCR) and Rapid Amplification of cDNA Ends (5'-RACE) fifteen transcripts were mapped in the core region. The occurrence and location of those transcripts were further confirmed by hybridizing labeled cDNA to a semi-tiling micro-array probing both strands of the ICEclc core region. Dot blot and semi-tiling array hybridizations demonstrated most of the core transcripts to be upregulated during stationary phase on 3-chlorobenzoate, but not on succinate or glucose. Conclusions: The transcription analysis of the ICEclc core region provides detailed insights in the mode of regulatory organization and will help to further understand the complex mode of behavior of this class of mobile elements. We conclude that ICEclc core transcription is concerted at a global level, more reminiscent of a phage program than of plasmid conjugation.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Quantitative sequence analysis of FBN1 premature termination codons provides evidence for incomplete NMD in leukocytes.

We improved, evaluated, and used Sanger sequencing for quantification of single nucleotide polymorphism (SNP) variants in transcripts and gDNA samples. This improved assay resulted in highly reproducible relative allele frequencies (e.g., for a heterozygous gDNA 50.0+/-1.4%, and for a missense mutation-bearing transcript 46.9+/-3.7%) with a lower detection limit of 3-9%. It provided excellent accuracy and linear correlation between expected and observed relative allele frequencies. This sequencing assay, which can also be used for the quantification of copy number variations (CNVs), methylations, mosaicisms, and DNA pools, enabled us to analyze transcripts of the FBN1 gene in fibroblasts and blood samples of patients with suspected Marfan syndrome not only qualitatively but also quantitatively. We report a total of 18 novel and 19 known FBN1 sequence variants leading to a premature termination codon (PTC), 26 of which we analyzed by quantitative sequencing both at gDNA and cDNA levels. The relative amounts of PTC-containing FBN1 transcripts in fresh and PAXgene-stabilized blood samples were significantly higher (33.0+/-3.9% to 80.0+/-7.2%) than those detected in affected fibroblasts with inhibition of nonsense-mediated mRNA decay (NMD) (11.0+/-2.1% to 25.0+/-1.8%), whereas in fibroblasts without NMD inhibition no mutant alleles could be detected. These results provide evidence for incomplete NMD in leukocytes and have particular importance for RNA-based analyses not only in FBN1 but also in other genes.

Transcriptional analysis of left-sided colitis, pancolitis, and ulcerative colitis-associated dysplasia

BACKGROUND: It is unknown why patients with extensive ulcerative colitis (UC) have a higher risk of colorectal cancer compared with patients with left-sided UC. This study characterizes the inflammatory processes in left-sided UC, pancolitis, and UC-associated dysplasia at the transcriptional level to identify potential biomarkers and transcripts of importance for the carcinogenic behavior of chronic inflammation. METHODS: The Affymetrix GeneChip Human Genome U133 Plus 2.0 was applied on colonic biopsies from UC patients with left-sided UC, pancolitis, dysplasia, and controls. Reverse transcription polymerase chain reaction and immunohistochemistry were performed for validating selected transcripts in the initial cohort and in 2 independent cohorts of patients with UC. Microarray data were analyzed by principal component analysis, and reverse transcription polymerase chain reaction and immunohistochemistry data by the Wilcoxon's rank-sum test. RESULTS: The principal component analysis results revealed separate clusters for left-sided UC, pancolitis, dysplasia, and controls. Close clustering of dysplastic and pancolitic samples indicated similarities in gene expression. Indeed, 101 and 656 parallel upregulated and downregulated transcripts, respectively, were identified in specimens from dysplasia and pancolitis. Validation of selected transcripts hereof identified insulin receptor alpha (INSRA) and MAP kinase interacting serine/threonine kinase 2 (MKNK2) with an enhanced expression in dysplasia compared with left-sided UC and controls, whereas laminin γ2 (LAMC2) was found with a lower expression in dysplasia compared with the remaining 3 groups. CONCLUSIONS: This study demonstrates pancolitis and left-sided UC as distinct inflammatory processes at the transcriptional level, and identifies INSRA, MKNK2, and LAMC2 as potential critical transcripts in the inflammation-driven preneoplastic process of UC.

Functional analysis: evaluation of response intensities--tailoring ANOVA for lists of expression subsets.

Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect.

A comprehensive analysis of gene expression profiles in distal parts of the mouse renal tubule.

The distal parts of the renal tubule play a critical role in maintaining homeostasis of extracellular fluids. In this review, we present an in-depth analysis of microarray-based gene expression profiles available for microdissected mouse distal nephron segments, i.e., the distal convoluted tubule (DCT) and the connecting tubule (CNT), and for the cortical portion of the collecting duct (CCD; Zuber et al., Proc Natl Acad Sci USA 106:16523-16528, 2009). Classification of expressed transcripts in 14 major functional gene categories demonstrated that all principal proteins involved in maintaining the salt and water balance are represented by highly abundant transcripts. However, a significant number of transcripts belonging, for instance, to categories of G-protein-coupled receptors or serine/threonine kinases exhibit high expression levels but remain unassigned to a specific renal function. We also established a list of genes differentially expressed between the DCT/CNT and the CCD. This list is enriched by genes related to segment-specific transport functions and by transcription factors directing the development of the distal nephron or collecting ducts. Collectively, this in silico analysis provides comprehensive information about relative abundance and tissue specificity of the DCT/CNT and the CCD expressed transcripts and identifies new candidate genes for renal homeostasis.

Analysis of photoreceptor abnormality in GUCY2D E837D/R838S transgenic pigs

Purpose: We generated genetically engineered pigs expressing the human dominant GUCY2DE837D/R838S allele to modelize cone dystrophy. After a functional follow-up showing reduced photopic ERG responses (ARVO 2011), we analyzed the eyes by immunohistochemistry and revealed retinal modifications in the transgenic group. Methods: Lentiviral vectors encoding the human double mutant GUCY2DE837D/R838S cDNA under the control of a portion of the pig arrestin-3 promoter (Arr3) were produced and used for lentiviral-mediated transgenesis in pigs. Animals were regularly submitted to behavioral and functional investigations and were sacrificed at 4, 7, 15 and 18 months of age for histological and RT-PCR analyses. Retinal markers were used to evaluate the retinal status of eleven transgenic pigs and 6 non-transgenic controls. The expression of the mutant cDNA was also assayed by RT-PCR. Results: A significant increase in the number of displaced nuclei in the outersegment layer is observed in transgenic animals compared to control animals independently of their age. Part of these nuclei originate from cones as demonstrated by colocalization with cone markers. No significant change in the ONL thickness (central and peripheral retina) was measured between 4 and 18 months of age, showing a slow progression of the disease in the transgenic pigs within this time-frame. Conclusions: Arr3-GUCY2DE837D/R838S pigs show signs of retinal abnormality with slow progression which parallels the loss of photopic function. Further characterization of this model should help to elucidate the molecular mechanisms underlying the disease evolution.

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.