Development of polyaniline microarray electrodes for cadmium analysis

Disposable screen-printed electrodes (SPCE) were modified using a cosmetic product to partially block the electrode surface in order to obtain a microelectrode array. The microarrays formed were electropolymerized with aniline. Scanning electron microscopy was used to evaluate the modified and polymerized electrode surface. Electrochemical characteristics of the constructed sensor for cadmium analysis were evaluated by cyclic and square-wave voltammetry. Optimized stripping procedure in which the preconcentration of cadmium was achieved by depositing at –1.20 V (vs. Ag/AgCl) resulted in a well defined anodic peak at approximately –0.7 V at pH 4.6. The achieved limit of detection was 4 × 10−9 mol dm−3. Spray modified and polymerized microarray electrodes were successfully applied to quantify cadmium in fish sample digests.

Arrow plot and CA maps on microarray preprocessing methods

Microarray allow to monitoring simultaneously thousands of genes, where the abundance of the transcripts under a same experimental condition at the same time can be quantified. Among various available array technologies, double channel cDNA microarray experiments have arisen in numerous technical protocols associated to genomic studies, which is the focus of this work. Microarray experiments involve many steps and each one can affect the quality of raw data. Background correction and normalization are preprocessing techniques to clean and correct the raw data when undesirable fluctuations arise from technical factors. Several recent studies showed that there is no preprocessing strategy that outperforms others in all circumstances and thus it seems difficult to provide general recommendations. In this work, it is proposed to use exploratory techniques to visualize the effects of preprocessing methods on statistical analysis of cancer two-channel microarray data sets, where the cancer types (classes) are known. For selecting differential expressed genes the arrow plot was used and the graph of profiles resultant from the correspondence analysis for visualizing the results. It was used 6 background methods and 6 normalization methods, performing 36 pre-processing methods and it was analyzed in a published cDNA microarray database (Liver) available at http://genome-www5.stanford.edu/ which microarrays were already classified by cancer type. All statistical analyses were performed using the R statistical software.

Desenvolvimento de Primer universal de SBE para codificação espectral de SNP

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Development and validation of gold nanoprobes for human SNP detection towards commercial application

Conventional molecular techniques for detection and characterization of relevant nucleic acid (i.e. DNA) sequences are, nowadays, cumbersome, expensive and with reduced portability. The main objective of this dissertation consisted in the optimization and validation of a fast and low-cost colorimetric nanodiagnostic methodology for the detection of single nucleotide polymorphisms (SNPs). This was done considering SNPs associated to obesity of commercial interest for STAB VIDA, and subsequent evaluation of other clinically relevant targets. Also, integration of this methodology into a microfluidic platform envisaging portability and application on points-of-care (POC) was achieved. To warrant success in pursuing these objectives, the experimental work was divided in four sections: i) genetic association of SNPs to obesity in the Portuguese population; ii) optimization and validation of the non-cross-linking approach for complete genotype characterization of these SNPs; iii) incorporation into a microfluidic platform; and iv) translation to other relevant commercial targets. FTO dbSNP rs#:9939609 carriers had higher body mass index (BMI), total body fat mass, waist perimeter and 2.5 times higher risk to obesity. AuNPs functionalized with thiolated oligonucleotides (Au-nanoprobes) were used via the non-cross-linking to validate a diagnostics approach against the gold standard technique - Sanger Sequencing - with high levels of sensitivity (87.50%) and specificity (91.67%). A proof-of-concept POC microfluidic device was assembled towards incorporation of the molecular detection strategy. In conclusion a successful framework was developed and validated for the detection of SNPs with commercial interest for STAB VIDA, towards future translation into a POC device.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

C allele of the IL-1B-511 SNP is associated with higher risk for Gastric Cancer and its premalignant lesion : a prospective case-control study in Peru

Magdeburg, Univ., Medizin. Fakultät, Diss., 2008

p.Q192R SNP of PON1 seems not to be Associated with Carotid Atherosclerosis Risk Factors in an Asymptomatic and Normolipidemic Brazilian Population Sample

Background:Evidences suggest that paraoxonase 1 (PON1) confers important antioxidant and anti-inflammatory properties when associated with high-density lipoprotein (HDL).Objective:To investigate the relationships between p.Q192R SNP ofPON1, biochemical parameters and carotid atherosclerosis in an asymptomatic, normolipidemic Brazilian population sample.Methods:We studied 584 volunteers (females n = 326, males n = 258; 19-75 years of age). Total genomic DNA was extracted and SNP was detected in the TaqMan® SNP OpenArray® genotyping platform (Applied Biosystems, Foster City, CA). Plasma lipoproteins and apolipoproteins were determined and PON1 activity was measured using paraoxon as a substrate. High-resolution β-mode ultrasonography was used to measure cIMT and the presence of carotid atherosclerotic plaques in a subgroup of individuals (n = 317).Results:The presence of p.192Q was associated with a significant increase in PON1 activity (RR = 12.30 (11.38); RQ = 46.96 (22.35); QQ = 85.35 (24.83) μmol/min; p < 0.0001), HDL-C (RR= 45 (37); RQ = 62 (39); QQ = 69 (29) mg/dL; p < 0.001) and apo A-I (RR = 140.76 ± 36.39; RQ = 147.62 ± 36.92; QQ = 147.49 ± 36.65 mg/dL; p = 0.019). Stepwise regression analysis revealed that heterozygous and p.192Q carriers influenced by 58% PON1 activity towards paraoxon. The univariate linear regression analysis demonstrated that p.Q192R SNP was not associated with mean cIMT; as a result, in the multiple regression analysis, no variables were selected with 5% significance. In logistic regression analysis, the studied parameters were not associated with the presence of carotid plaques.Conclusion:In low-risk individuals, the presence of the p.192Q variant ofPON1 is associated with a beneficial plasma lipid profile but not with carotid atherosclerosis.

Immunochip SNP array identifies novel genetic variants conferring susceptibility to candidaemia.

Candidaemia is the fourth most common cause of bloodstream infection, with a high mortality rate of up to 40%. Identification of host genetic factors that confer susceptibility to candidaemia may aid in designing adjunctive immunotherapeutic strategies. Here we hypothesize that variation in immune genes may predispose to candidaemia. We analyse 118,989 single-nucleotide polymorphisms (SNPs) across 186 loci known to be associated with immune-mediated diseases in the largest candidaemia cohort to date of 217 patients of European ancestry and a group of 11,920 controls. We validate the significant associations by comparison with a disease-matched control group. We observe significant association between candidaemia and SNPs in the CD58 (P = 1.97 × 10(-11); odds ratio (OR) = 4.68), LCE4A-C1orf68 (P = 1.98 × 10(-10); OR = 4.25) and TAGAP (P = 1.84 × 10(-8); OR = 2.96) loci. Individuals carrying two or more risk alleles have an increased risk for candidaemia of 19.4-fold compared with individuals carrying no risk allele. We identify three novel genetic risk factors for candidaemia, which we subsequently validate for their role in antifungal host defence.

IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.

MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MIMAS 3.0 is a Multiomics Information Management and Annotation System.

BACKGROUND: DNA sequence integrity, mRNA concentrations and protein-DNA interactions have been subject to genome-wide analyses based on microarrays with ever increasing efficiency and reliability over the past fifteen years. However, very recently novel technologies for Ultra High-Throughput DNA Sequencing (UHTS) have been harnessed to study these phenomena with unprecedented precision. As a consequence, the extensive bioinformatics environment available for array data management, analysis, interpretation and publication must be extended to include these novel sequencing data types. DESCRIPTION: MIMAS was originally conceived as a simple, convenient and local Microarray Information Management and Annotation System focused on GeneChips for expression profiling studies. MIMAS 3.0 enables users to manage data from high-density oligonucleotide SNP Chips, expression arrays (both 3'UTR and tiling) and promoter arrays, BeadArrays as well as UHTS data using MIAME-compliant standardized vocabulary. Importantly, researchers can export data in MAGE-TAB format and upload them to the EBI's ArrayExpress certified data repository using a one-step procedure. CONCLUSION: We have vastly extended the capability of the system such that it processes the data output of six types of GeneChips (Affymetrix), two different BeadArrays for mRNA and miRNA (Illumina) and the Genome Analyzer (a popular Ultra-High Throughput DNA Sequencer, Illumina), without compromising on its flexibility and user-friendliness. MIMAS, appropriately renamed into Multiomics Information Management and Annotation System, is currently used by scientists working in approximately 50 academic laboratories and genomics platforms in Switzerland and France. MIMAS 3.0 is freely available via http://multiomics.sourceforge.net/.

Protein-Binding Microarray Analysis of Tumor Suppressor AP2α Target Gene Specificity.

Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays.

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.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Effects of mitotane on gene expression in the adrenocortical cell line NCI-H295R: a microarray study.

Aim: The adrenolytic agent mitotane is widely used in the treatment of adrenocortical cancer; however, its mechanism of action is poorly elucidated. We have studied mitotane-induced mRNA expression changes in the NCI-H295R adrenocortical cancer cell line. Materials & methods: Cell viability and hormone assays were used to select the optimal mitotane concentration effectively inhibiting hormone secretion without affecting cell viability. RNA isolated from cultures treated for 48 and 72 h was subjected to Agilent 4×44K microarray platforms. Microarray results were validated by quantitative reverse-transcription PCR. Results: Altogether, 117 significantly differentially expressed genes were detected at 48 h and 72 h (p < 0.05) in mitotane-treated samples relative to controls. Three significantly underexpressed genes involved in steroid hormone biosynthesis (HSD3B1, HSD3B2 and CYP21A2) and four significantly overexpressed genes (GDF15, ALDH1L2, TRIB3 and SERPINE2) have been validated. Conclusion: Gene-expression changes might be involved in the adrenal action of mitotane and in the inhibition of hormone secretion. Original submitted 20 January 2012; Revision submitted 17 May 2012.