Дисертації з теми "Microarrays"

The global aim of this thesis was to study the use of microarray technology for the screening and identification of biocompatible polymers, to understand physiological phenomena, and the design of biomaterials, implant surfaces and tissue-engineering scaffolds. This work was based upon the polymer microarray platform developed by the Bradley group. Polymer microarrays were successfully applied to find the best polymer supports for: (i) mouse fibroblast cells and used to evaluate cell biocompatibility and cell morphology. Fourteen polyurethanes demonstrated significant cellular adhesion. (ii) Analysis of the adhesion of human erythroleukaemic K562 suspension cells onto biomaterials with particular families of polyurethanes and polyacrylates identified. A DNA microarray study (to access the global gene expression profiles upon cellular binding) demonstrated that interactions between cells and some polyacrylates induced a number of transcriptomic changes. These results suggested that, during these interactions, a chain of cellular changes is triggered, most notably resulting in the downregulation of membrane receptors and ligands. (iii) Identification of polymers with potential applications in the field of stem cell biology. Polymers were identified that showed attachment, promotion and stabilisation of hepatocyte-like cells. A polyurethane support (PU-134) was pinpointed, which significantly improved both hepatocyte-like cell function and “lifespan”. A second project investigated biomaterials that promoted adhesion, growth and function of endothelial progenitor cells. A new polymer matrix was identified which contained the necessary signals to promote endothelial phenotype and function. This has potential application in the creation of blood vessels and the endothelialisation of artificial vessel prostheses and stent coatings for improving angioplasty therapy. (iv) The study of bacterial adhesion, focusing on the adhesion of food-borne pathogenic bacterium Salmonella enterica serovar typhimurium, strain SL1344, and the commensal bacterium Escherichia coli, strain W3110. Several polymers were found to support selective bacterial enrichment, as well as others that minimised bacterial adhesion.

Streptococcus sanguinis is a gram-positive, non-motile bacterium native to human mouths. It is the primary cause of endocarditis and is also responsible for tooth decay. Two-component systems (TCSs) are commonly found in bacteria. In response to environmental signals, TCSs may regulate the expression of virulence factor genes. Gene co-expression networks are exploratory tools used to analyze system-level gene functionality. A gene co-expression network consists of gene expression profiles represented as nodes and gene connections, which occur if two genes are significantly co-expressed. An adjacency function transforms the similarity matrix containing co-expression similarities into the adjacency matrix containing connection strengths. Gene modules were determined from the connection strengths, and various network connectivity measures were calculated. S. sanguinis gene expression profile data was loaded for 2272 genes and 14 samples with 3 replicates each. The soft thresholding power β=6 was chosen to maximize R2 while maintaining a high mean number of connections. Nine modules were found. Possible meta-modules were found to be: Module 1: Blue & Green, Module 2: Pink, Module 3: Yellow, Brown & Red, Module 4: Black, Module 5: Magenta & Turquoise. The absolute value of module membership was found to be highly positively correlated with intramodular connectivity. Each of the nine modules were examined. Two methods (intramodular connectivity and TOM-based connectivity followed by network mapping) for identifying candidate hub genes were performed. Most modules provided similar results between the two methods. Similar rankings between the two methods can be considered equivalent and both can be used to detect candidate hub genes. Gene ontology information was unavailable to help select a module of interest. This network analysis would help researchers create new research hypotheses and design experiments for validation of candidate hub genes in biologically important modules.

Advancements in DNA microarray data sequencing have created the need for sophisticated machine learning algorithms and feature selection methods. Probabilistic graphical models, in particular, have been used to identify whether microarrays or genes cluster together in groups of individuals having a similar diagnosis. These clusters of genes are informative, but can be misleading when every gene is used in the calculation. First feature reduction techniques are explored, however the size and nature of the data prevents traditional techniques from working efficiently. Our method is to use the partial correlations between the features to create a precision matrix and predict which associations between genes are most important to predicting Leukemia diagnosis. This technique reduces the number of genes to a fraction of the original. In this approach, partial correlations are then extended into a spectral clustering approach. In particular, a variety of different Laplacian matrices are generated from the network of connections between features, and each implies a graphical network model of gene interconnectivity. Various edge and vertex weighted Laplacians are considered and compared against each other in a probabilistic graphical modeling approach. The resulting multivariate Gaussian distributed clusters are subsequently analyzed to determine which genes are activated in a patient with Leukemia. Finally, the results of this are compared against other feature engineering approaches to assess its accuracy on the Leukemia data set. The initial results show the partial correlation approach of feature selection predicts the diagnosis of a Leukemia patient with almost the same accuracy as using a machine learning algorithm on the full set of genes. More calculations of the precision matrix are needed to ensure the set of most important genes is correct. Additionally more machine learning algorithms will be implemented using the full and reduced data sets to further validate the current prediction accuracy of the partial correlation method.

DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.

Protein microarray technology has an enormous potential for in vitro diagnostics (IVD)1. Miniaturized and parallelized immunoassays are powerful tools to measure dozens of parameters from minute amounts of sample, whilst only requiring small amounts of reagent. Protein microarrays have become well-established research tools in basic and applied research and the first diagnostic products are already released on the market. However, in order for protein microarrays to become broadly accepted tools in IVD, a number of criteria have to be fulfilled concerning robustness and automation. Robustness and automation are key demands to improve assay performance and reliability of multiplexed assays, and to minimize the time of analysis. These key demands are addressed in this thesis and novel methods and techniques concerning assay automation, array fabrication as well as performance and detection strategies related to protein microarrays are presented and discussed. In the first paper an automated assay format, based on planar protein microarrays is described and evaluated by the detection of several auto-antibodies from human serum and by quantification of matrix metalloproteases present in plasma. Diffusion-rate limited solid phase reactions were enhanced by microagitation, using the surface acoustic wave technology, resulting in a slightly increased signal-to-noise ratio. In the second paper of the thesis, a novel multiplexed immunoassay system was developed by combining a direct immunoassay with a competitive system. This set-up allows quantification of analytes present in widely varying concentrations within a single multiplex assay. In the third paper, a new concept for sample deposition is introduced, addressing contemporary problems of contact or non-contact microarrayers in protein microarray fabrication. In the fourth paper, a magnetic bead-based detection method for protein microarrays is described as a cost-effective alternative approach to the commonly used fluorescence-based confocal scanning systems. The magnetic bead-based detection could easily be performed by using an ordinary flatbed scanner. In addition, applying magnetic force to the magnetic bead-based detection approach enables to run the detection step more rapidly. Finally, in paper five, a microfluidic bead-based immunoassay for multiplexed detection of receptor tyrosine kinases in breast cancer tissue is presented. Since the assay is performed inside a capillary, the amounts of sample and reagent material could be reduced by a factor of 30 or more when compared with the current standard protein microarray assay.<br>QC 20101112

Polymers have been used as biomaterials for nearly a century and have recently become the material of choice for use in tissue engineering. However, the classes of biodegradable and biocompatible polymers available for use in biomedical devices and as tissue engineering scaffolds are limited. This lack of available polymers with suitable properties could inhibit the development of biomedical devices with improved biocompatibility and hinder the growth of the fledgling tissue engineering field. Researchers in the polymer and biomaterials fields have tried to remedy this problem by applying combinatorial and high throughput methods developed in drug discovery to the search for new polymers. A recent advance has been the development of combinatorial polymer libraries printed as microarrays. This format allows the polymers to be readily screened for their cell adhesion and differentiation properties, allowing ‘hit’ materials with ideal properties to be identified. However, without knowledge of the surface properties of these novel polymers it is impossible to rationalise their biological properties. The surface characterisation of such microarrays presents numerous practical problems included small sample size, sample number and even analysis of such large amounts of data. It is the aim of this thesis to develop methods for the characterisation of the surface chemistry, wettability and protein adsorption properties of polymers in situ in microarray format and within realistic timeframes. The thesis will explore multivariate statistics in the form of PCA and PLS as methods of analysing the large amount of data acquired. The first part of this thesis describes the surface chemical analysis of a polymer microarray using ToF-SIMS and XPS. A comparison of the polymers’ surface to bulk chemistries by XPS indicated that 64 % of the polymers had a surface chemistry which differed from the bulk. This reinforces the need for characterisation of the polymers’ surface chemistries, as it is obvious that this can not be inferred from their bulk chemistries. ToF-SIMS imaging was shown to be an ideal method of studying the distribution of specific ion species across the array and to confirm that the microarray was printed in the intended layout. Principal component analysis is shown to be an ideal technique to analyse both ToF-SIMS and XPS spectral data from the arrays, allowing similarities and differences in the surface chemistry of the polymers to be easily visualised. To estimate the surface energies of the arrayed polymers it is necessary to use picolitre volume droplets to make contact angle measurements. In Chapter 4 it is shown that contact angle measurements taken from picolitre volume water droplets are equivalent to those measured from more conventional microlitre droplets. In Chapter 5 picolitre contact angle measurements are used to estimate the polar and dispersive surface energies of a polymer microarray, which has been specifically designed to exhibit a maximum range of surface energy values. The analysis shows that there is indeed great variation in the WCA and polar surface energies of the polymers, demonstrating the power of intelligently designed combinatorial libraries. To understand the chemical basis of this large range of surface energies the results are compared to surface chemical data from ToF-SIMS and XPS. Surface atomic and functional data from XPS is unable to provide any definitive explanations for the range of surface energies observed. However, information about the molecular structure of the surface from ToF-SIMS gives an insight into what surface functionalities are responsible for high and low surface energies. In Chapter 6 PLS regression is investigated further as a method for investigating surface structure-property relationships in large polymer libraries. Specifically two issues are investigated: the influence of sample number on the results obtained and the ability of PLS to make quantitative predictions. The ToF-SIMS and surface energy dataset discussed in Chapter 5 is used for this task. It is demonstrated that the results obtained from PLS models of large polymer libraries are equivalent to those obtained from much smaller datasets, in terms of the ions identified in the regression vector. Using various test sets of polymers it is shown that there is a limit to the predictive ability of PLS: specifically, as the difference between the training and test sets increases, the quality of the predictions decreases. Potential problems with data pre-processing and re-scaling are also identified. In the final experimental chapter two methods are described for investigating protein adhesion and adsorption to micro-arrayed polymers using AFM and fluorescently labelled proteins. Both methods indicate a wide range of protein adsorption properties within the group of polymers analysed. A good correlation between the two sets of data was observed which appears to validate both methods. In summary the work described in this thesis has demonstrated the feasibility of the characterisation of the surface chemistry, energetics and protein adsorption properties of a micro-arrayed polymer library within realistic time-frames. PCA and PLS have been shown to be useful tools for analysing the data obtained. It is hoped that the methods described in this thesis will allow the biological data from polymer microarrays to be rationalised using the surface properties of the polymers, allowing the design of new biomaterials.

Initial studies involved the development of a novel polymer microarray platform which would provide unsurpassed miniaturisation for polymer screening. This required substantial development and optimisation of several parameters and the best results were achieved by printing polymers dissolved in 1-methyl-2-pyrrolidinone and patterned using a contact microarrayer with solid pins. Microarray platforms were developed that used different substrates. The first one used a gold-coated substrate that quenched non-specifically bound fluorescently-labelled proteins, whereas the second utilised a hydrogel coating that prevented non-specific cellular adhesion. The platform using the gold coated substrate was ideally suited to the high throughput study of the physico-chemical properties of the arrayed polymer libraries, via scanning electron microscopy, FT-IR and TOF-SIMS. These polymer microarray platforms provided high throughput while minimising the amount of both polymers and expensive reagents used. The polymer microarrays were used with both adherent and non-adherent immortalised cell lines. In both cases, polymers could be selected that provided selective cellular immobilisation. Such methodologies were subsequently utilised to identify novel materials that allowed gentle immobilisation of human primary renal tubular epithelial cells and mouse bone marrow dendritic cells. This platform was applied to the identification of polymers with potential applications in stem cell biology. In one project polymers were screened for the selective immobilisation of multipotent mesenchymal stromal cell populations from human bone marrow. Several poly(urethanes) with large soft segments provided unexpectedly high selective adhesion of the stromal population. The second project investigated the use of novel substrates that maintained mouse embryonic stem cell cultures in their undifferentiated phenotype state. Finally, the polymer microarray platform was optimised for the study of protein adhesion.

Biocompatible polymers are used exhaustively within the biomedical arena, demonstrating a mechanical and chemical diversity that few other materials possess. As polymer technologies evolves to cater for new medical demands, even the most niche biomedical application becomes an achievable reality. However, the discovery of new polymers is hindered by the complexity and intricacy in which the biological milieu interacts with a new substrate, reducing the ability to predict the appropriateness of a certain polymer for a specific application. This drawback can be countered by the high-throughput evaluation of large numbers of chemically diverse polymer candidates. In this thesis, the use of polymer microarrays is invoked to address two separate medically-relevant issues: the control of inflammation, and the improvement of cancer screening. In addition, I provide details of how polymer microarray techniques and technology can be employed to expand the repertoire of biomaterials research. Mitochondrial DNA (mtDNA) is an alarm molecule that contributes to the cytokine storm observed during severe tissue injury. An application where control of this systemic inflammation is achieved through scavenging of mtDNA by a polymer was proposed. Primary screening highlighted that 166 out of the 380 polymers evaluated bound to blood cells, making them unsuitable for a blood-based application. The remaining 214 blood-compatible polymers were cross-examined for mtDNA binding. Through polymer microarray and subsequent scale-up of promising candidates, a poly(methoxyethyl methacrylate-co-di(ethylamino)ethyl acrylate-co-methoxyethyl acrylate) was found to have a remarkable ability to scavenge mtDNA. Removal of cell-free mtDNA using this polymer is proposed to remove a key trigger of systemic inflammation. Cervical cancer screening includes the cytological evaluation of patient material for developed or developing abnormalities. An application was sought that would enrich for cancerous/pre-cancerous cells and improve upon current standards for detection. Four cancerous cervical cell lines (HeLa, CaSki, SiHa, and C33a) and four precancerous cell lines (W12E, W12G, W12GPX, and W12GPXY) were interrogated to identify polymers with consistent binding that may improve routine cytological evaluation. A short-list of 24 polymers was assembled, and cells from liquid based cytology samples from healthy patient were spiked with DiI-labelled cancerous/precancerous cells and the short-listed polymers were re-evaluated for preferential binding. An enrichment of abnormal cervical cells was observed with three polymers, which could form the foundation for improved screening resources. Inkjet printing can be a useful tool in developing patterned substrates, such as polymer microarrays. A piezoelectric drop-on-demand printer was used to explore the methods in which these can be fabricated. A wettability assay using picolitre volumes was developed and used to characterise O2 plasma treatment of glass slides. Additionally, the printing of a cell-binding polymer using this approach enabled the decoration of cells with precise spatial resolution.

In my PhD polymer microarrays have been central in discovery of new materials for cardiovascular repair, cartilage tissue engineering and bacteria resistant medical devices. This has led to the work described in the following four chapters of my thesis. In the first part of my thesis polymers for the development of novel heart valve leaflets were identified. Diseased heart valves are currently replaced with the either synthetic or bioprosthetic (acellular xenografts) valve prostheses. While synthetic prosthesis have excellent durability, thromboembolic complications are frequent, requiring patients to undergo lifelong anti-coagulation therapy. On the other hand, the leaflets of bioprosthetic valves undergo structural deterioration, resulting in the patients having to undergo follow-up replacement surgeries. In order to overcome these shortcomings, the aim of this part of my PhD was to discover polymers that will enable the development of a ‘bio-synthetic’ heart valve, with the durability of synthetic valves and the biocompatibility of bioprosthetic vales. Polymers that bind valve interstitial cells (cells with a plastic fibroblast / myofibroblast phenotype that renew the extracellular matrix components of the valve leaflets) and also enable stable expression of key markers were identified. Immunohistochemistry and RNA expression analysis identified polymers for coating 3-D scaffolds, with the coated scaffolds showing excellent cell invasion, viability and maintenance of valve interstitial cell markers. To mimic the regions of the valve leaflets with differing stiffness, the response of valve interstitial cells to substrate stiffness was studied with various crosslinked gels. Thus, polymeric gels, prepared with the same chemical composition but with different Young’s modulus (covering 3 orders of magnitude) showed valve interstitial cell attachment with the cells showing differing behaviour based on the stiffness of the gels. In the second part of this thesis, polymers were identified for cartilage repair. Hyaline articular cartilage has very low potential for self-renewal, therefore cell-based therapies with autologous chondrocyte implantation are desired. Due to limited availability from biopsies, chondrocytes have to be expanded by in vitro culture; and fully defined synthetic culture substrates are essential for regulatory approvals. Using the high throughput approach I identified ‘hit’ polymers that allowed adhesion, proliferation and long-term culture of primary human chondrocytes and also chondrocytes derived from Mesenchymal stem cells. 2-D scale-up identified 2 lead polymers that supported long-term attachment and maintenance of chondrocyte markers. Since prolonged monolayer culture is known to induce loss of chondrocyte phenotype (dedifferentiation), 3D versions of the polymers were prepared and their potential for their long-term maintenance of chondrocytes via immunohistochemistry and RNA expression was demonstrated. The 3D gels were also used to encapsulate chondrocytes and their long-term maintenance of phenotype within these matrices, offers the exciting possibility of using these matrices for cartilage regeneration. The third part and fourth parts of the thesis focussed on reducing medical device associated infections. Thus polymers identified that prevented binding of a variety of bacteria including clinical isolates from infected medical devices, were used to coat two commercially available central venous catheters resulting in up to 96% reduction in bacterial binding. This non-binding was enhanced by the generation of polymeric nanocapsules containing the anti-bacterial eugenol (or its natural source clove oil). A coating consisting of eugenol nanocapsules entrapped within an interpenetrating network of the best bacteria repellent polymer, allowed slow-release of eugenol and further improved its performance.

Traditional microbiological experimental methods generally reveal population-wide statistics and are not capable of revealing variations between individual cells. In an effort to address this, a cheap, quick and easy means of producing micro-arrays with live bacteria immobilized on the array's coordinates has been developed. To achieve this, microcontact printing (µCP) was used to print circular PD ``islands'' onto a surface coated with either PEG or PVA. The bacteria, &lt;i&gt;Pseudomonas putida&lt;/i&gt; KT2440 were successfully immobilized on approximately 97% of the printed islands, depending on island diameter. A LIVE/DEAD® &lt;i&gt;Bac&lt;/i&gt;Light™ assay revealed that over 99% of the immobilized bacteria survive the immobilization on the array. Qualitative analysis suggests the bacteria survive for hours after immobilization, provided nutrients are available. The developed method may, by revising the stamp design and/or choice of elastomer, likely be optimized to immobilize only one bacterium per array coordinate.

We present a framework for detecting degenerate probes in a DNA microarray that may add to measurement error in hybridization experiments. We consider four types of behaviour: secondary structure formation, self-dimerization, cross-hybridization and dimerization. The framework uses a well-established model of nucleic acid sequence hybridization and a novel method for the detection of patterns in hybridization experiment data. Our primary result is the identification of unique patterns in hybridization experiment data that are correlated with each type of degenerate probe behaviour. The framework also contains a machine learning technique to learn from the hybridization experiment data. We implement the components of the framework and evaluate the ability of the framework to detect degenerate probes in the Affymetrix HuGeneFL GeneChip.

The development and identification of new biomaterials that can replace specific tissues and organs is desirable. In the presented PhD thesis polymer microarrays were applied for the screening of polyacrylates and polyurethanes and evaluation for material discovery for applications in the life sciences. In the first part of the thesis, the largest polymer microarray ever made with more than 7000 features was fabricated and subsequently used for the screening of polyacrylates that can control the fate of human embryonic stem cells. As stem cells have unique properties that offer the potential of replacing damaged or diseased tissue in future, the identification of cultivation substrates that can replace current biological and animal derived products was desirable. The water contact angle, roughness and cell doubling time of the cells on the identified polymers was determined and the stem cells characterised after 5 passages and compared to the currently most widely used animal derived substrate MatrigelTM. In the second part of the thesis, the development of a new polymer gradient microarray is presented. Initial studies involved the optimisation of printing parameters for the generation of linear polymer gradient lines and confirmed by XPS analysis. Cellular binding studies with the suspension cell line K562 and the adherent cell line HeLa were carried out and compared to previous binding studies to confirm the success of the concept. In further studies, the polymer gradients were functionalised with small molecules and proteins, allowing the generation of a protein gradient microarray with Semaphorin 3F. In binding studies with neuron cells it could be shown that the binding of the cells was concentration-dependent. The identification of polyacrylates for the effective and rapid activation and aggregation of platelets is described in the third part of the presented thesis. Here, polymer microarrays were applied for the binding of platelets in human blood samples. The amount of bound platelets as well as their activation state was compared to the natural agonist collagen by employing fluorescence intensity studies and scanning electron microscopy. In shear studies, the activation of the platelets by the polymers was evaluated under physiological conditions. The mechanism by which the polymer triggered the activation was further explored by protein binding studies. It was shown that the initial adsorption of fibrinogen and von Willebrand factor on the polymers lead to the adherence and aggregation of platelets. In the final part of the presented thesis, polymer microarrays were used to identify polymers that can sort and collect the precursor cells of platelets (megakaryocytes). For this purpose, the cell lines K562 and MEG-01 were used as cellular models. The identified polymers and the effect on the immobilised cells was further investigated by scanning electron microscopy, flow cytometry and miRNA studies. The adsorbed proteins on the different polymers were found to influence the cellular morphology on the different substrates.

Doutoramento em Engenharia Informática<br>O projecto de sequenciação do genoma humano veio abrir caminho para o surgimento de novas áreas transdisciplinares de investigação, como a biologia computacional, a bioinformática e a bioestatística. Um dos resultados emergentes desde advento foi a tecnologia de DNA microarrays, que permite o estudo do perfil da expressão de milhares de genes, quando sujeitos a perturbações externas. Apesar de ser uma tecnologia relativamente consolidada, continua a apresentar um conjunto vasto de desafios, nomeadamente do ponto de vista computacional e dos sistemas de informação. São exemplos a optimização dos procedimentos de tratamento de dados bem como o desenvolvimento de metodologias de interpretação semi-automática dos resultados. O principal objectivo deste trabalho consistiu em explorar novas soluções técnicas para agilizar os procedimentos de armazenamento, partilha e análise de dados de experiências de microarrays. Com esta finalidade, realizou-se uma análise de requisitos associados às principais etapas da execução de uma experiência, tendo sido identificados os principais défices, propostas estratégias de melhoramento e apresentadas novas soluções. Ao nível da gestão de dados laboratoriais, é proposto um LIMS (Laboratory Information Management System) que possibilita a gestão de todos os dados gerados e dos procedimentos realizados. Este sistema integra ainda uma solução que permite a partilha de experiências, de forma a promover a participação colaborativa de vários investigadores num mesmo projecto, mesmo usando LIMS distintos. No contexto da análise de dados, é apresentado um modelo que facilita a integração de algoritmos de processamento e de análise de experiências no sistema desenvolvido. Por fim, é proposta uma solução para facilitar a interpretação biológica de um conjunto de genes diferencialmente expressos, através de ferramentas que integram informação existente em diversas bases de dados biomédicas.<br>The sequencing of the human genome paved the way for the emergence of new transdisciplinary research areas, such as computational biology, bioinformatics and biostatistics. One example of such is the advent of DNA microarray technology, which allows the study of the expression of thousands of genes when subjected to an external disturbance. Despite being a well-established technology, it continues to present a wide range of challenges, particularly in terms of computing and information systems. Examples include the optimization of procedures for processing data as well as the development of methodologies for semi-automated interpretation of results. The main objective of this study was to explore new technical solutions to streamline the procedures for storing, sharing and analyzing the data from microarray experiments. To this end, it was performed an analysis of the key steps from the experiment, having been identified the major deficits, proposed strategies for improving and presented new solutions. Regarding the management of laboratory data we propose a LIMS (Laboratory Information Management System) that allows the storage of all data generated and procedures performed in the laboratory. This system also includes a solution that enables the sharing of experiments in order to promote collaborative participation of several researchers in the same project, even using different LIMS. In the context of data analysis, it is presented a model that allows the simplified integration of processing and analysis algorithms in the developed system. Finally, it is proposed a solution to facilitate the biological interpretation of a set of differentially expressed genes, using tools that integrate information from several public biomedical databases.

In microarray analysis, people are interested in those features that have different characters in diseased samples compared to normal samples. The usual p-value method of selecting significant genes either gives too many false positives or cannot detect all the significant features. The False Discovery Rate (FDR) method controls false positives and at the same time selects significant features. We introduced Benjamini's method and Storey's method to control FDR, applied the two methods to human Meningioma data. We found that Benjamini's method is more conservative and that, after the number of the tests exceeds a threshold, increase in number of tests will lead to decrease in number of significant genes. In the second chapter, we investigate ways to search interesting gene expressions that cannot be detected by linear models as t-test or ANOVA. We propose a novel approach to use quadratic logistic regression to detect genes in Meningioma data that have non-linear relationship within phenotypes. By using quadratic logistic regression, we can find genes whose expression correlates to their phenotypes both linearly and quadratically. Whether these genes have clinical significant is a very interesting question, since these genes most likely be neglected by traditional linear approach.

Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains ix, 146 p.; also includes graphics (some col.) Includes bibliographical references (p. 145-146). Available online via OhioLINK's ETD Center

A análise da expressão gênica através de dados gerados em experimentos de microarrays de DNA vem possibilitando uma melhor compreensão da dinâmica e dos mecanismos envolvidos nos processos celulares ao nível molecular. O aprimoramento desta análise é crucial para o avanço do conhecimento sobre as bases moleculares das neoplasias e para a identificação de marcadores moleculares para uso em diagnóstico, desenho de novos medicamentos em terapias anti-tumorais. Este trabalho tem como objetivos o desenvolvimento de modelos de análise desses dados, propondo uma nova forma de normalização de dados provenientes de microarrays e dois modelos para a construção de redes regulatórias de expressão gênica, sendo uma baseada na conectividade dinâmica entre diversos genes ao longo do ciclo celular e a outra que resolve o problema da dimensionalidade, em que o número de experimentos de microarrays é menor que o número de genes. Apresenta-se, ainda, um pacote de ferramentas com uma interface gráfica de fácil uso contendo diversas técnicas de análise de dados já conhecidas como também as abordagens propostas neste trabalho.<br>The analyses of DNA microarrays gene expression data are allowing a better comprehension of the dynamics and mechanisms involved in cellular processes at the molecular level. In the cancer field, the improvement of gene expression interpretation is crucial to better understand the molecular basis of the neoplasias and to identify molecular markers to be used in diagnosis and in the design of new anti-tumoral drugs. The main goals of this work were to develop a new method to normalize DNA microarray data and two models to construct gene expression regulatory networks. One method analyses the dynamic connectivity between genes through the cell cycle and the other solves the dimensionality problem in regulatory networks, meaning that the number of experiments is lower than the number of genes. We also developed a toolbox with a user-friendly interface, displaying several established statistical methods implemented to analyze gene expression data as well as the new approaches presented in this work.

Neste trabalho é proposto um estudo comparativo de alguns métodos de Agrupamento (Hierárquico, K-médias e Self-Organizing Maps) e de Classificação (K-Vizinhos, Fisher, Máxima Verossimilhança, Aggregating e Regressão Local), os quais são apresentados teoricamente. Tais métodos são testados e comparados em conjuntos de dados reais, gerados com a técnica de Microarray. Esta técnica permite mensurar os níveis de expressão de milhares de genes simultaneamente, possibilitando comparações entre amostras de tecidos pelos perfis de expressão. É apresentada uma revisão de conceitos básicos relacionados ao processo de normalização, sendo este uma das primeiras etapas da análise deste tipo de conjunto de dados. Em particular, estivemos interessados em encontrar pequenos grupos de genes que fossem ?suficientes? para distinguir amostras em condições¸ biológicas diferentes. Por fim, é proposto um método de busca que, dado os resultados de um experimento envolvendo um grande número de genes, encontra de uma forma eficiente os melhores classificadores.<br>In this work we propose a comparative study of some clustering methods (Hierarchic, K -Means and Self-Organizing Maps) and some classification methods (K-Neighbours, Fisher, Maximum Likelihood, Aggregating and Local Regression), which are presented teoretically. The methods are tested and compared based on the analysis of some real data sets, generated from Microarray experiments. This technique allows for the measurement of expression levels from thousands of genes simultaneously, thus allowing the comparative analysis of sample of tissues in relation to their expression profile. We present a review of basic concepts regarding normalization of microarray data, one of the first steps in microarray analysis. In particular, we were interested in finding small groups of genes that were ?sufficient? to identify samples originating from different biological conditions. Finally, a search method is proposed, which will find efficiently the best classifiers from the results of an experiment involving a huge number of genes.

En esta tesis se presenta un sistema de lectura eléctrica de microarrays que comprenden una serie de transductores impedimétricos con los cuales realizar la detección multiplexada de hasta 36 eventos biológicos en un mismo sustrato. Al igual que con los microarrays de lectura fluorescente, se han empleado sustratos de vidrio desechables para la fabricación del microarray. Sin embargo, a diferencia de ellos , el sistema presentado es compacto y requiere una instrumentación sencilla y de bajo coste, lo que hace que el sistema pueda ser muy útil para realizar la descentralización de este tipo de medidas analíticas. Otros sistemas de lectura eléctricos compactos reportados anteriormente se basan en la inmovilización de los receptores biológicos específicos sobre la superficie del transductor, lo que hace que sean de un solo uso y por lo tanto costosos. Nuestro sistema combina las ventajas de los sistemas eléctricos anteriores y los escáneres de fluorescencia. El array de electrodos interdigitados (IDEs) se fabricó sobre sustratos de vidrio. Las medidas conductimétricas fueron realizadas con estos transductores mediante la aplicación de reacciones de inmunoensayo que emplean la ureasa como marca. La hidrólisis de la urea catalizada por la ureasa produce especies iónicas en solución que aumentan su conductividad. Los microarrays se fabrican sobre portaobjetos de vidrio convencional. Para la lectura, se coloca sobre el microarray sobre el array de IDEs dejando un espacio de fijo entre ambos, de modo que cada punto del microarray se alinea con su IDE correspondiente. En el proceso de medida se depositaron gotas de solución de medida que contienen urea que ponían en contacto el IDE y el punto correspondiente del microarray. Sin embargo, en un primero trabajo se presentaron algunos inconvenientes importantes relacionados con la evaporación de las gotas y el cross-talk químico entre las gotas adyacentes debido a migración de especies iónicas, lo que hizo que el sistema presentase unas características de sensibilidad y límite de detección sensiblemente más limitadas que las mostradas por los sistemas de detección fluorescente. Por otra parte, se requería de un microdispensador para posicionar con precisión las gotas sobre los transductores. En un segundo trabajo, se encontró una solución para resolver estos inconvenientes y se demostró el potencial del sistema para se un competidor real, en términos de rendimiento analítico, frente a los sistemas basados en fluorescencia. Dicha solución se basó en el empleo una estructura de PDMS que incluye 36 micropocillos de 1.2 µL de volumen, los cuales se disponen sobre el array de transductores para contener el volumen de solución de urea y poder realizar la lectura de cada punto del microarray dentro de una cavidad cerrada. Con esta configuración se consiguió evitar por completo los problemas de evaporación y cross-talk químico. Por último, se presenta un tercer trabajo donde se automatizó este sistema de lectura mediante la implementación de una estructura microfluídica que incluye el array de micropocillos de PDMS así como los componentes fluídicos necesarios para realizar el llenado automático de los mismos así como su lavado posterior una vez realizada la lectura de un microarray. De esta forma, se mejoró el rendimiento del sistema de lectura a la vez que su fiabilidad al minimizar la manipulación por parte de un usuario.<br>An electrical readout system of microarrays comprising an array of conductimetric transducers, which enabled multiplexed detection of up to 36 biological events on the same substrate, is reported in this thesis. Similarly to fluorescent readout counterparts, regular glass slides were applied for carrying out the microarray. However, unlike them, the presented system is compact and requires a simple and inexpensive instrumentation, thus being ideally suited for deployment of bioarray detection approaches. Other compact electrical readout systems previously reported are based on the immobilization of the specific bioreceptors on the transducer surface, which make them single-use and thus expensive. Our system combines the merits of both previous electrical systems and the fluorescence scanner approaches. An array of 40 μm-pitch gold interdigitated electrode pairs (IDEs) was fabricated on glass substrates. Conductimetric measurements were carried out with these transducers by applying urease-based (urease labeled) immunoassay reactions. The hydrolysis of urea catalyzed by urease produces ionic species in solution that increase its conductivity. In order to carry out such detection scheme, the bioarray was developed on a regular glass slide substrate, which was then placed over the IDE microarray leaving a fixed gap and aligned so that each spot of the bioarray faced one IDE. Therein, the droplets of urea solution were placed in the gap to contact the IDEs and the corresponding spots of the bioarray. However, in the development of the first approach, some major drawbacks related to droplet evaporation and chemical cross-talk between adjacent droplets made the system to be far from achieving the performance of fluorescent detection approaches. Moreover, a microdispenser was required to accurately position the droplets. In a second approach, we found the solution for circumventing these drawbacks and the demonstration of the potential of the system as a real competitor against fluorescence based systems in terms of analytical performance. An array structure of 36 PDMS microwells having a volume of 1.2 μL were fabricated by molding and positioned over the IDE array. The geometry of each microwell includes an O-ring like structure and an empty area around it, which enabled first, to easily fill it without using any specific instrumentation and second, to ensure its liquid tightness once the bioarray was positioned over it. This set-up was demonstrated to completely avoid the evaporation and chemical cross-talk issues. Finally, a third approach is presented, where the readout automatized by means of a microfluidic structure that includes the PDMS microwells together with those fluidic components that enabled the automatic filling with the measuring solution as well as the cleaning step of the system once a microarray was measured. Working in this way improves the throughput of the electrical readout system as well as enhanced its reliability by minimizing the manipulation by the user.

Is specificity an important issue regarding affinity reagents? What about the validation of affinity reagents today, is it good enough? This depends on the application and the producer of the reagent. Validation should be the most important marketing argument that can be found.Today there is a continuous growth of both the number of affinity reagents that are produced and the different types of affinity reagents that are developed. In proteomics they become more and more important in exploring the human proteome. Therefore, validated affinity reagents should be on top of every proteomic researcher’s list. How should this be accomplished?Better international agreements on how affinity reagents should be tested to be regarded as functional reagents are needed. One of the most important issues is the specificity of the affinity reagent. An international standard for which specific validation that is needed for different kinds of applications would be very useful.In this thesis, it is shown that the protein microarray platform that was established within the HPA project at KTH is a very good tool to determine the specificity of different affinity binders.In the first study, the production of mono-specific antibodies for tissue profiling in the Human Protein Atlas (HPA) project is presented. The section describing the use of protein microarrays for validation of the antibodies is relevant for this thesis. The implementation of protein microarrays in the HPA workflow was an important addition, because a deeper insight of the specificity of all the antibodies produced were now available.In a second study, bead based arrays were compared to planar protein microarrays used in the HPA project. In this study, 100 different bead identities were coupled with 100 different antigens and mixed together to generate an array. The correlation between the two types of assays was very high and the conclusion was that the methods can be used as backup to each other.A third study was a part of an international initiative to produce renewable affinity binders against proteins containing SH2 domain. Here, the HPA protein microarrays were modified to analyze different types of reagents produced at six laboratories around the world. Monoclonal antibodies, single chain fragment and fibronectin scaffolds were tested as well as mono-specific antibodies. It was shown to be possible to adapt protein microarrays used in the HPA project to validate other kinds of affinity reagents.<br>QC 20111117<br>Development and applications of protein microarrays<br>The Swedish Human Proteome Resource (HPR) program

Proteins are essential building blocks in every living cell, and since the complete human genome was sequenced in 2004, researchers have attempted to map the human proteome, which is the functional representation of the genome. One such initiative is the Human Protein Atlas programme (HPA), which generates monospecific antibodies towards all human proteins and uses these for high-throughput tissue profiling on tissue microarrays (TMAs). The results are publically available at the website www.proteinatlas.org. In this thesis, TMAs were used for analysis of expression patterns in various research areas. Different search queries in the HPA were tested and evaluated, and a number of potential biomarkers were identified, e.g. proteins exclusively expressed in islets of Langerhans, but not in exocrine glandular cells or other abdominal organs close to pancreas. The identified candidates were further analyzed on TMAs with pancreatic tissues from normal and diabetic individuals, and colocalization studies with insulin and glucagon revealed that several of the investigated proteins (DGCR2, GBF1, GPR44 and SerpinB10) appeared to be beta cell specific. Moreover, a set of proteins differentially expressed in lung cancer stroma was further analyzed on a clinical lung cancer cohort in the TMA format, and one protein (CD99) was significantly associated with survival. In addition, TMAs with tissue samples from different species were generated, e.g. for mapping of influenza virus attachment in various human and avian tissues. The results showed that the gull influenza virus H16N3 attached to human respiratory tract and eye, suggesting possible transmission of the virus between gull and human. TMAs were also used for analysis of protein expression differences between humans and other primates, and two proteins (TCF3 and SATB2) proved to be significantly differentially expressed on the human lineage at both the protein level and the RNA level.   In conclusion, this thesis exemplifies the potential of the TMA technology, which can be used for analysis of expression patterns in a large variety of research fields, such as biomarker discovery, influenza virus research or further understanding of human evolution.

Research on the interactions between microbes and polymeric materials constitutes an important part in antimicrobial identification and provides an insight into microbial response on the polymer surfaces. Herein, a high-content screening method with polymer microarray technology was developed to investigate microbe-polymer interactions, especially in studying adhesion/repellence of microbes (bacteria and parasites). Firstly, the polymer microarray approach was used to successfully identify polymers which either selectively captured or prevented the binding of major food-borne pathogen, Salmonella Typhimurium. A parallel study with a lab strain of Escherichia coli was also carried out, revealing polymers which either displayed a common binding activity or which exhibited species discrimination. Likewise, this polymer microarray technology was applied to more bacterial strains, such as Campylobacter, Clostridium, Streptococcus, Klebsiella and their cocktails to discover families of substrates that displayed strong broad-spectrum bacterial non-binding activity. These synthetic polymers represented a novel class of coating materials which can be used to prevent surface colonisation and subsequent formation of bacterial biofilms. The study of protozoan-polymer interactions was also explored in this thesis. Polymers were identified which either bound or prevented parasites (Crysporidium parvum and Giardia lamblia) binding. Material properties, including wettability, surface roughness and polymer composition were analysed to study correlation of parasite binding and the generation of polymer structure function relationships.

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.<br>Includes bibliographical references.<br>Recent advances in de novo gene synthesis, library construction, and genomic selection for target sequencing using DNA from custom microarrays have demonstrated that microarrays can effectively be used as the world's cheapest sources of complex oligonucleotide pools. Unfortunately, commercial custom microarrays are expensive and not easily accessible to academic researchers, and technical challenges still exist for dealing with the small amount of DNA synthesized on a chip. Genomic research would certainly benefit from the creation of cheaper custom microarrays with larger oligonucleotide concentrations per spot. This thesis presents the development of a novel DNA microarray synthesis platform based on semiconductor photoelectrochemistry (PEC) designed with these needs in mind. An amorphous silicon photoconductor is activated by an optical projection system to create "virtual electrodes" that electrochemically generate protons in a site-selective manner, thereby cleaving acid-labile dimethoxytrityl protecting groups with the spatial selectivity that is required for in-situ DNA synthesis. This platform has the potential to be particularly low-cost since it employs standard phosphoramidite reagents, visible wavelength optics, and a cheaply microfabricated and reusable substrate. By incorporating a porous thin-film glass that dramatically increases the DNA quantity produced by over an order of magnitude per chip, this platform may also simplify the handling of DNA cleaved from chip and drive down the cost per base synthesized. The hybridization detection of single-base errors was successfully demonstrated on PEC synthesized microarrays. This thesis also reports a suite of new surface chemistries and high-resolution techniques for patterning biological molecules.<br>by Brian Yichiun Chow.<br>Ph.D.

Ovarian cancer has the highest mortality rate of the gynaecological cancers. This is partly due to the lack of effective screening markers. In this study, oligonucleotide microarrays complementary to -12,000 genes were used to establish a gene expression microarray (GEM) profile for normal ovarian tissue, as compared to stage III ovarian serous adenocarcinoma and omental metastases from the same individuals. The GEM profiles of the primary and secondary tumours from the same individuals were essentially alike, reflecting the fact that these tumours had already metastasised and acquired the metastatic phenotype. A novel biomarker, mammaglobin-2 (MGB2), was identified which is highly expressed specific to ovarian cancer. MGB2, in combination with other putative markers identified here, could have potential for screening.

Microarrays are now an established tool for biological research and have a wide range of applications. In this thesis I investigate the BeadArray microarray technology developed by Illumina. The design of this technology is unique and gives rise to many computational and statistical challenges. However, I show how knowledge from other microarray technologies can be used to our advantage. I describe the beadarray software package, which is now used by researchers around the world. The development of this software was motivated by the fact that Illumina's software (BeadStudio) gives a summarised view of Illumina data and does not gives users any control over several processing steps that were found to be crucial for other microarray technologies. A main feature of beadarray is the ability to access raw data. The advantages of such data include the ability to perform more detailed quality assessment and greater control over the analysis at all stages. The analysis of a control experiment shows that the processing steps used in BeadStudio can be improved. In particular, utilising variances calculated from the raw data can increase the ability to detect genes which have different expression levels between samples, a common goal for microarray studies. The data from the control experiment are made available for other researchers to use and validate their own analysis methods. One issue discovered during the analysis of the control experiment was that only half of the intended genes could be reliably measured due to problems in the design of the probes targetting particular genes. By considering a large set of publicly available Illumina arrays, I show how such unreliable measurements can affect the analysis of Illumina data. I also show how potential problems can be identified in advance of an experiment and incorporated into an analysis pipeline.

Dissertação de Mestrado em Estatística apresentada à Faculdade de Ciências da Universidade do Porto<br>A aplicação de um regime específico de quimioterapia, depende de um correcto diagnóstico do paciente. Actualmente, esse diagnóstico não é efectuado de uma forma sistemática e geral, necessitando da intervenção de diferentes especialistas. Com a monitorização da expressão de milhares de genes em simultâneo, a recente tecnologia dos microarrays de ADN representa um grande passo para a sistematização do diagnóstico oncológico. No entanto, esta tecnologia produz informação em que o número de variáveis (genes) excede largamente o número de observações (amostras), o que dificulta a utilização das ferramentas estatísticas habituais de classificação. Neste sentido, torna-se necessário implementar estratégias de redução da dimensão do espaço predictor. Contudo, esta redução, que equivale a seleccionar um subconjunto de genes do conjunto inicial, deve ser extremamente direccionada, pois sabe-se que apesar do seu elevado número, apenas uma pequena parte dos genes monitorizados determina o tipo de tecido. Identificar genes com potencial predictivo é um objectivo central dos estudos de microarray aplicados à classificação de tumores. A criação de mecanismos que permitam reter apenas estes genes é essencial, tanto a nível estatístico (pois só com redução de dimensão poderemos aplicar as metodologias habituais) como a nível de interpretação biológica.O presente estudo pretende efectuar uma introdução a este novo tipo de tecnologia e de dados, procurando mostrar algumas das metodologias utilizadas para a sua análise. Em particular, centramo-nos no estudo de diferentes estratégias de escolha de genes predictivos e na sua utilização para a classificação de tumores cancerígenos.

Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Sep. 16, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Curriculum of Genetics and Molecular Biology." Discipline: Genetics and Molecular Biology; Department/School: Medicine.

Dissertação de Mestrado em Estatística apresentada à Faculdade de Ciências da Universidade do Porto<br>A aplicação de um regime específico de quimioterapia, depende de um correcto diagnóstico do paciente. Actualmente, esse diagnóstico não é efectuado de uma forma sistemática e geral, necessitando da intervenção de diferentes especialistas. Com a monitorização da expressão de milhares de genes em simultâneo, a recente tecnologia dos microarrays de ADN representa um grande passo para a sistematização do diagnóstico oncológico. No entanto, esta tecnologia produz informação em que o número de variáveis (genes) excede largamente o número de observações (amostras), o que dificulta a utilização das ferramentas estatísticas habituais de classificação. Neste sentido, torna-se necessário implementar estratégias de redução da dimensão do espaço predictor. Contudo, esta redução, que equivale a seleccionar um subconjunto de genes do conjunto inicial, deve ser extremamente direccionada, pois sabe-se que apesar do seu elevado número, apenas uma pequena parte dos genes monitorizados determina o tipo de tecido. Identificar genes com potencial predictivo é um objectivo central dos estudos de microarray aplicados à classificação de tumores. A criação de mecanismos que permitam reter apenas estes genes é essencial, tanto a nível estatístico (pois só com redução de dimensão poderemos aplicar as metodologias habituais) como a nível de interpretação biológica.O presente estudo pretende efectuar uma introdução a este novo tipo de tecnologia e de dados, procurando mostrar algumas das metodologias utilizadas para a sua análise. Em particular, centramo-nos no estudo de diferentes estratégias de escolha de genes predictivos e na sua utilização para a classificação de tumores cancerígenos.

Horseracing is a huge industry both nationally and internationally. With large financial rewards now available at some meetings the pressure to excel has grown and as a result the desire to win has led some racehorse owners to resort to the use of performance enhancing drugs. Rumours concerning the abuse of recombinant human erythropoietin (rHuEPO) in thoroughbred horseracing have been circulating since it became readily available in the late 1980s. While there are a number of commercially available EPO enzyme-linked immunosorbent assays (ELlSAs) to detect the administration of rHuEPO to horses, these kits are all restricted in their success due to the limited amount of time EPO remains in the horse's circulation. It is thought that the horse's immune system recognises the rHuEPO as a foreign protein and produces antibodies against it. This research aims to exploit this phenomenon to develop a new sensing system for the detection of rHuEPO antibodies resulting from rHuEPO administration. This research was divided into two parts. In the first section, a simple colorimetric assay based on the aggregation of gold nanoparticles for the detection of the antibodies produced as a result of rHuEPO abuse was developed. Various forms of rHuEPO have been attached to gold nanoparticles via linkage molecules to develop colorimetric assays based on the aggregation of protein-modified gold nanoparticles and its corresponding antibody. The 17 nm protein-stabilised nanoparticles are ruby red in colour. The sensing system was tested with the anti-HuEPO antibody. Upon addition of this antibody, aggregation occurred, with a subsequent change in colour from red to purple due to a red-shift in the surface plasmon absorption band, which was monitored by UV/visible spectrophotometry. For each variant of rHuEPO, the theoretical limit of detection (LOD) was established and kinetic studies (time to complete the aggregation reaction) were investigated.

BACKGROUND:Microarrays offer a powerful tool for diverse applications plant biology and crop improvement. Recently, two comprehensive assemblies of cotton ESTs were constructed based on three Gossypium species. Using these assemblies as templates, we describe the design and creation and of a publicly available oligonucleotide array for cotton, useful for all four of the cultivated species.RESULTS:Synthetic oligonucleotide probes were generated from exemplar sequences of a global assembly of 211,397 cotton ESTs derived from >50 different cDNA libraries representing many different tissue types and tissue treatments. A total of 22,787 oligonucleotide probes are included on the arrays, optimized to target the diversity of the transcriptome and previously studied cotton genes, transcription factors, and genes with homology to Arabidopsis. A small portion of the oligonucleotides target unidentified protein coding sequences, thereby providing an element of gene discovery. Because many oligonucleotides were based on ESTs from fiber-specific cDNA libraries, the microarray has direct application for analysis of the fiber transcriptome. To illustrate the utility of the microarray, we hybridized labeled bud and leaf cDNAs from G. hirsutum and demonstrate technical consistency of results.CONCLUSION:The cotton oligonucleotide microarray provides a reproducible platform for transcription profiling in cotton, and is made publicly available through http://cottonevolution.info webcite.

The DNA microarray is a powerful tool to study expression levels of thousands of genes simultaneously. Often, cDNA libraries representing expressed genes of an organism are available, along with expressed sequence tags (ESTs). ESTs are widely used as the probes for microarrays. Designing custom microarrays, rich in genes relevant to the experimental objectives, requires selection of probes based on their sequence. We have designed a probe selection method, called GeneSieve, to select EST probes for custom microarrays. To assign annotations to the ESTs, we cluster them into contigs using PHRAP. The larger contig sequences are then used for similarity search against known proteins in model organism such as Arabidopsis thaliana. We have designed three different methods to assign annotations to the contigs: bidirectional hits (BH), bidirectional best hits (BBH), and unidirectional best hits (UBH). We apply these methods to pine and potato EST sets. Results show that the UBH method assigns unambiguous annotations to a large fraction of contigs in an organism. Hence, we use UBH to assign annotations to ESTs in GeneSieve. To select a single EST from a contig, GeneSieve assigns a quality score to each EST based on its protein homology (PH), cross hybridization (CH), and relative length (RL). We use this quality score to rank ESTs according to seven different measures: length, 3' proximity, 5' proximity, protein homology, cross hybridization, relative length, and overall quality score. Results for pine and potato EST sets indicate that EST probes selected by quality score are relatively long and give better values for protein homology and cross hybridization. Results of the GeneSieve protocol are stored in a database and linked with sequence databases and known functional category schemes such as MIPS and GO. The database is made available via a web interface. A biologist is able to select large number of EST probes based on annotations or functional categories in a quick and easy way.<br>Master of Science

2005/2006<br>Sono stati eseguiti molti studi che esplorano le potenzialità offerte dalla Surface Plamson Resonace (SPR) quale possibile tecnica per lo sviluppo di biosensori per l'analisi degli acidi nucleici. Lo scopo di questo studio è pertanto quello di esplorare la possibilità di migliorare le performances dell'SPR tramite la fabbricazione di cristalli plasmonici, così da sviluppare un nuovo strumento per gli studi di genomica funzionale, tramite una nuova architettura biologica. Questo strumento potrà essere una possibile base per un nuovo tipo di piattaforma array per lo studio del DNA grazie ad una misura diretta degli acidi nucleice che eviterà la necessità di ricorrere alla reversed-transcriptase Polymerase Chain Reaction (RT -PCR), in cui i geni possono essere solo analizzati individualmente e la misura è affetta dall'attività della polimerasi e dalla sua selettività. La tecnica SPR non era presente nel nostro gruppo, pertanto lo scopo di questo studio e anche di introdurre tale metodologia ali' interno del laboratorio quale nuova piattaforma per nuovi progetti ed applicazioni. Conseguentemente è stato necessario acquisire un'approfondita conoscenza della teoria alla base di tali tecniche e lo studio è stato svolto indagando l'ibridazione del DNA su sistemi basati sulla realizzazione di self' assembled monolayer. In particolare è stata studiata la Surface Plasmon Fluorescence Spectroscopy (SPFS) quale metodo principale di detection. La SPFS è stata dimostrata per la prima volta dal gruppo del Prof. Knoll presso il Max Planck Institute for Polymer research nel 2000. Da allora sono stati eseguiti numerosi studi sulla ibridazione del DNA. La necessità di utilizzare la fluorescenza per la rilevazione del fenomeno di ibridazione è dovuta al fatto che attualmente la SPR non è in grado di rilevare molecole così piccole. Pertanto questo studio è volto al miglioramente di tale aspetto della tecnica sfruttando le possibilità messe a disposizione della nanofabbricazione, con lo scopo finale di realizzare in futuro dei sistemi completamente label-free per lo studio degli acidi nucleici tale che sarà inoltre possibile eseguire direttamente le analisi sui campioni grezzi riducendo gli step necessari per la purificazione dei campioni. Tenuto conto che la fluorescenza viene assorbita dallo strato metallico nel caso in cui il fluoroforo sia troppo vicino alla superficie, è stata disegnata un'architettura per evitare questo problema in maniera più' semplice di come veniva fatto in altri studi. Il presente studio è composto da due parti separate che convergono verso uno stesso obiettivo, ovvero esplorare nuove metodologie analitiche per applicazioni di biomedicina molecolare. La forza di queste nuove tecnologie deriva dal potenziale offerto dalla nanofabbricazione alla biologia molecolare nel momento in cui le due scienze s'incontrano. Questo potrebbe permettere di superare gli attuali limiti tecnici legati alle tradizionali metodiche applicate in biologia molecolare. Vi sono diversi metodi per analizzare gli acidi nucleici. La SPR è stata la scelta per alcuni dei suoi aspetti peculiare. E' una metodica ottica in-situ che permette di lavorare sia in aria che in soluzione acquosa; tale caratteristica, unita al fatto di essere una metodia non distruttiva, rende la SPR particolarmente adatta per applicazioni di natura biologica. Inoltre, la possibilità in futuro di realizzare tecnologie completamente label-free potrebbe permettere, una volta realizzati gli appropriati substrati, di eseguire analisi dirette su campioni biologici senza la necessità di processarli e marcarli con fluorofori e sistemi di radiolabeling. Infine, esiste la concreta possibilità di migliorare le metodiche SPR attraverso il patteming bidimensionale dei substrati ottenibili tramite la litografia a raggi X. Un biosensore ottico è uno strumento di misura che converte la quantità misurata (analita) in un'altra quantità (output) tipicamente legata ad una delle caratteristiche dell'onda elettromagnetica. Nei sensori basati sull'SPR, all'interfaccia tra un film metallico ed un mezzo dielettrico viene eccitato un plasmone di superficie, vengono misurati i cambiamente dell'indice di rifrazione. Un cambiamento dell'indice di rifrazione produce un un cambiamento della costante di propagazione del plasmone di superficie. Questo cambiamento altera le condizioni di accoppiamento tra l'onda elettromagnetica ed il plasmone di superficie che può essere visto come un cambiamento in una delle caratteristiche dell'onda elettromagnetica interagente con il plasmone di superficie. Sulla base di quale caratteristica dell'onda elettromagnetica misuriamo, i sensori SPR possono essere classificati come sensori angolari, a lunghezza d'onda, intensità, fase o a modulazione di polarizzazione. In questo studio è stato esplorato il potenziale della SPR nell'analisi degli acidi nucleici come primo passo verso lo sviluppo di nuove piattaforme microarray per il DNA. In particolare è stata studiata la Surface Plasmon Fluorescence Spectroscopy (SPFS) tramite un sistema di marca tura indiretta dell'analita che permette di evitare la marca tura del target stesso pur facendo uso delle ottime proprietà di sensibilità di cui gode la SPFS. Inoltre è stata rafforzata la nostra convinzione che i metodi ottici, ed in particolare quelli basati sulla SPR, sono particolarmente indicati per l'analisi del DNA grazie alla loro velocità di misura, la possibilità di utilizzare sistemi label-free, la possibilità di lavorare in ambiente acquoso, di modificare la temperatura e il fatto di usare una metodica non distruttiva che permette eventuali altre rilevazioni sui campioni. In questo studio è stata investigata l'ibridazione su su di un layer di riconoscimento molecolare di un plasmide (pTNT). Sono state utilizzate due diverse architetture per il layer di riconoscimento molecolare, una prima basata sull'attacco diretto delle sonde sulla superficie metallica tramite legame zolfo-oro, ed una seconda, basata sul legame di sonde biotinilate su un film di polistirene realizzato al di sopra dello strato metallico. La seconda architettura si è dimostrata funzionali risolvendo i problemi di quenching della fluorescenza rilevati con la prima architettura. In aggiunta, questa metodica di funzionalizzazione della superficie può essere prodotta in modo estremamente rapido se comparata ad altre architetture precedentemente riportate in letteratura. La rilevazione del plasmide, il quale è marcato in modo indiretto, permette di evitare la marcatura del plasmide stesso. Pertanto non vi sono problemi di efficienza di marcatura, tenuto conto che la sonda secondaria può essere purificata prima della misura oppure acquistata. Il lavoro svolto mostra che vi è ancora un enorme potenziale da scoprire, per migliorare lo stato dell'arte. Tali miglioramenti sono in larga parte legati alle possibilità offerte dall'impiego di cristalli plsmonici nanofabbricati. Sono stati infatti prodotti substrati in grado di migliorare la tecnica SPR tramite metodi di litografia a raggi X. I pattern bidimensionali realizzati mostrano la caratteristica di indurre l'accoppiamento della luce con il layer metallico e saranno di particolare interesse in studi futuri. Infatti esperimenti preliminari realizzati utilizzando uno strumento recentemente acquisito, un elissometro VASE® Research Spectroscopic Ellipsometer (J. A. Woollam Co., lnc.), mostrano che tali cristalli plasmonici potrebbero portare ad un incremento della sensibilità della SPR label-free di un ordine di grandezza. Questo studio ha infine permesso di introdurre le metodiche SPR e SPFS nel nostro laboratorio, aprendo la strada a numerosi nuovi progetti e linee di ricerca.<br>Several studies explore the possibilities offered by the Surface Plasmon Resonance (SPR) as a possible technique to develop a biosensor devoted to DNA analysis. The aim of this study is to explore the possibility to improve the performances of the SPR using nanofabrication of plasmonic crystals, in order to develop a new tool for functional genomics studies with new biological architecture. This could be a possible base for a new type of array DNA platforms according to a direct nucleic acids measurement protocol that will avoid the time consuming and error prone reversed-transcriptase Polymerase Chain Reaction, where genes can only be analyzed individually and the measurements are affected by the polymerase activity and selectivity. The SPR technique was not yet established in our group, therefore the aim of this study is to introduce from scratch this method in our group in order to establish a new platform that could be used also for other applications. Consequently, an in dept understanding of the theory behind the technique is required and the study starts with a thorough investigation of DNA hybridization based on functional selfassembled monolayer systems. In particular, the Surface Plasmon Fluorescence Spectroscopy (SPFS) will be explored as the main detection method. The SPFS technique was firstly introduced by the Knoll' s group at the Max Planck Institute for Polymer research in 2000 Extensive DNA hybridization studies have been carried out since then The need of the fluorescence to detect the DNA hybridization is due to the fact that currently the SPR itself cannot detect such small molecules. This is not true for example for proteins since, possessing a larger size than oligonucleotides, the protein binding can be visible in both the SPR. This dual-channel sensing ability of SPFS can be fully used for uncovering more interfacial information which could be of great interest if possible also for the DNA. Therefore this study tries to improve this aspect of the technique taking into account the possibilities offered by the nanofabrication with the goal in mind to realize, in the future, a completely label-free system, in order to be able to perform DNA studies directly on the raw samples, reducing thus also the time needed to prepare the samples. Based on the understanding that fluorescence suffers severe quenching if the fluorophores are too dose to the metal, it has been designed an architecture to extend the interaction platform out of the 'quenching' region that is simpler than those previously adopted. The present study is made by two separated parts converging upon the same aim that is to exploit new analytical methodologies for molecular biomedicine applications. The power of these new technologies comes from the potentiality that nanofabrication gives to molecular biology once the two fields are joint and that may allot to overcome the present issues related to the traditional molecular biology' s techniques. Therefore, a nanofabrication approach has been applied to a nucleic acids sequence analysis. There are different ways to analyze nucleic acids but for several reasons, SPR has been the choice we decided to choose. It is an in-situ optical method that allow to work both in air and in water. The possibility to work in aqueous environment and being a non destructive method, make SPR a particularly well suited method for biological applications. In addition, the possibility in the future to develop label-free technologies may allow, once the proper substrates are realized, to perform direct analysis on biological samples without the need to process them in order to label them or purify them, step which reduce the amount of the analyte since the yield it is never 100%. Furthermore, there is the possibility to improve the SPR methods using appropriately pattemed substrates that can be realized with x-ray lithographic techniques. An optical sensor is a sensing device which, by optical means, converts the quantity measured (measurand) to another quantity ( output) which is typically encoded into one of the characteristics of a light wave. In SPR sensors, a surface plasmon is excited at the interface between a metal film and a dielectric medium (superstrate), changes in the refractive index of which are to be measured. A change in the refractive index of the superstrate produces a change n the propagation constant of the surface plasmon. This change alters the coupling condition between a light wave and the surface Plasmon, which can be observed as a change in one of the characteristics of the optical wave interacting with the surface plasmon. Based on which characteristic of the light wave interacting with the surface plasmon is measured, SPR sensors can be classified as SPR sensor with angular, wavelength, intensity, phase, or polarization modulation. In this study, Surface Plasmon Resonance' s potential for nucleic acid analysis has been explored in arder to develop the knowledge for new microarray DNA platforms. In particular, Surface Plasmon Fluorescence Spectroscopy (SPFS) has been investigated with a new indirect labeling system that allows avoiding the labeling of the targets but still making use of the high sensitivity allowed by SPFS. Moreover, we have strengthen the believe that optical methods, and especially those surface plasmon based, are well suited for DNA analysis due to the speed of the measurement, the possibility to have label-free and indirect-label methods, the possibility to work in liquid, change the temperature and, last but not least, doing a non-destructive measurement allowing the sample to be eventually further analyzed. In this study the interfacial hybridization of a plasmid has been investigated using SPR and SPFS. Two different architectures have been used for the molecular recognition layer, direct binding of the probe on the gold surface via sulfur-gold bond and functionalization of the surface using a biotinilated oligonucleotide bonded on polystyrene. The second architecture has been proven to be able to avoid the fluorescence quenching observed with the former one. Moreover, this architecture can be easily produced faster than other architectures found in literature. The detection of the plasmid, being indirect, has a very good feature: there is no need to directly label the target. Therefore no labeling efficiency issue is encountered, since the secondary probe can be purified after labeling. The work done shows that there is still a huge potential to be uncovered, in arder to improve the current state of the art. These improvements are base on the nanofabrication of plasmonic crystals. Substrates to improve the SPR technique have been indeed produced using the x-ray lithography. The bidimensional patterned substrates have shown the characteristic to induce the coupling of the light with the metal layer and they will be useful in further studies to improve the technique. Indeed, preliminary experiments performed using the new VASE® Research Spectroscopic Ellipsometer (J. A. Woollam Co., Inc.) show that using plasmonic crystals coupled with this setup may lead to an increase of sensitivity of one order of magnitude of the label free SPR. In addition, this study had the fundamental importance to introduce Surface Plasmon Resonance (SPR) and Surface Plasmon Fluorescence Spectroscopy (SPFS) techniques in our laboratory, opening countless opportunities for a great number of new projects and research lines.<br>XIX Ciclo<br>1979<br>Versione digitalizzata della tesi di dottorato cartacea.

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.