New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Mass spectrometry-based protein profiling strategies for biomarker discovery in liver and inflammatory bowel diseases

The study of protein expression profiles for biomarker discovery in serum and in mammalian cell populations needs the continuous improvement and combination of proteins/peptides separation techniques, mass spectrometry, statistical and bioinformatic approaches. In this thesis work two different mass spectrometry-based protein profiling strategies have been developed and applied to liver and inflammatory bowel diseases (IBDs) for the discovery of new biomarkers. The first of them, based on bulk solid-phase extraction combined with matrix-assisted laser desorption/ionization - Time of Flight mass spectrometry (MALDI-TOF MS) and chemometric analysis of serum samples, was applied to the study of serum protein expression profiles both in IBDs (Crohn’s disease and ulcerative colitis) and in liver diseases (cirrhosis, hepatocellular carcinoma, viral hepatitis). The approach allowed the enrichment of serum proteins/peptides due to the high interaction surface between analytes and solid phase and the high recovery due to the elution step performed directly on the MALDI-target plate. Furthermore the use of chemometric algorithm for the selection of the variables with higher discriminant power permitted to evaluate patterns of 20-30 proteins involved in the differentiation and classification of serum samples from healthy donors and diseased patients. These proteins profiles permit to discriminate among the pathologies with an optimum classification and prediction abilities. In particular in the study of inflammatory bowel diseases, after the analysis using C18 of 129 serum samples from healthy donors and Crohn’s disease, ulcerative colitis and inflammatory controls patients, a 90.7% of classification ability and a 72.9% prediction ability were obtained. In the study of liver diseases (hepatocellular carcinoma, viral hepatitis and cirrhosis) a 80.6% of prediction ability was achieved using IDA-Cu(II) as extraction procedure. The identification of the selected proteins by MALDITOF/ TOF MS analysis or by their selective enrichment followed by enzymatic digestion and MS/MS analysis may give useful information in order to identify new biomarkers involved in the diseases. The second mass spectrometry-based protein profiling strategy developed was based on a label-free liquid chromatography electrospray ionization quadrupole - time of flight differential analysis approach (LC ESI-QTOF MS), combined with targeted MS/MS analysis of only identified differences. The strategy was used for biomarker discovery in IBDs, and in particular of Crohn’s disease. The enriched serum peptidome and the subcellular fractions of intestinal epithelial cells (IECs) from healthy donors and Crohn’s disease patients were analysed. The combining of the low molecular weight serum proteins enrichment step and the LCMS approach allowed to evaluate a pattern of peptides derived from specific exoprotease activity in the coagulation and complement activation pathways. Among these peptides, particularly interesting was the discovery of clusters of peptides from fibrinopeptide A, Apolipoprotein E and A4, and complement C3 and C4. Further studies need to be performed to evaluate the specificity of these clusters and validate the results, in order to develop a rapid serum diagnostic test. The analysis by label-free LC ESI-QTOF MS differential analysis of the subcellular fractions of IECs from Crohn’s disease patients and healthy donors permitted to find many proteins that could be involved in the inflammation process. Among them heat shock protein 70, tryptase alpha-1 precursor and proteins whose upregulation can be explained by the increased activity of IECs in Crohn’s disease were identified. Follow-up studies for the validation of the results and the in-depth investigation of the inflammation pathways involved in the disease will be performed. Both the developed mass spectrometry-based protein profiling strategies have been proved to be useful tools for the discovery of disease biomarkers that need to be validated in further studies.

Identification of surface protein complexes of Streptococcus pyogenes through protein microarray technology

A systematic characterization of the composition and structure of the bacterial cell-surface proteome and its complexes can provide an invaluable tool for its comprehensive understanding. The knowledge of protein complexes composition and structure could offer new, more effective targets for a more specific and consequently effective immune response against a complex instead of a single protein. Large-scale protein-protein interaction screens are the first step towards the identification of complexes and their attribution to specific pathways. Currently, several methods exist for identifying protein interactions and protein microarrays provide the most appealing alternative to existing techniques for a high throughput screening of protein-protein interactions in vitro under reasonably straightforward conditions. In this study approximately 100 proteins of Group A Streptococcus (GAS) predicted to be secreted or surface exposed by genomic and proteomic approaches were purified in a His-tagged form and used to generate protein microarrays on nitrocellulose-coated slides. To identify protein-protein interactions each purified protein was then labeled with biotin, hybridized to the microarray and interactions were detected with Cy3-labelled streptavidin. Only reciprocal interactions, i. e. binding of the same two interactors irrespective of which of the two partners is in solid-phase or in solution, were taken as bona fide protein-protein interactions. Using this approach, we have identified 20 interactors of one of the potent toxins secreted by GAS and known as superantigens. Several of these interactors belong to the molecular chaperone or protein folding catalyst families and presumably are involved in the secretion and folding of the superantigen. In addition, a very interesting interaction was found between the superantigen and the substrate binding subunit of a well characterized ABC transporter. This finding opens a new perspective on the current understanding of how superantigens are modified by the bacterial cell in order to become major players in causing disease.

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

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

Identifikation transkriptioneller Alterationen menschlicher Tumoren und Entwicklung eines neuen auf RNA-Transfer basierenden Verfahrens zur Bestimmung der Genfunktion

Zielvorgaben der vorliegenden Arbeit war die Identifikation neuer selektiv in Tumoren aktivierter Gene sowie die Entwicklung eines methodischen Prozesses, um die molekularen Effekte der fehlerhaften Aktivierung solcher Gene zu untersuchen. Für die erste Fragestellung haben wir zwei komplementäre Methoden entwickelt. Zum einen haben wir nach neuen Mitglieder der Cancer/Germline (CG) Familie von Genen gesucht, die bereits attraktive Zielstrukturen laufender Phase I/IIa Studien sind. Zu diesem Zweck wurde ein bioinformatischer Data Mining Ansatz generiert. Dieser führte zur erfolgreichen in silico Klonierung neuer CG Gene. Zur Identifikation von in Tumorzellen überexprimierten Genen nutzten wir einen cDNA Mikroarray mit 1152 ausgewählten Genen mit direkter oder indirekter tumorimmunologischer oder tumorbiologischer Relevanz. Die komparative transkriptionelle Untersuchung von humanen Tumor- und Normalgeweben mit diesem Array führte zur Wiederentdeckung bereits bekannter, aber auch zur Aufdeckung bisher nicht beschriebener tumor-assoziierter Transkriptionsveränderungen. Der zweite große Schwerpunkt dieser Arbeit war die Technologieentwicklung eines versatilen Prozesses zur Untersuchung von molekularen Effekten eines aberrant in Zellen exprimierten Gens. Zur Simulation dieser Situation stellten wir in vitro transkribierte RNA dieses Gens her und elektroporierten diese in Zielzellen. Transkriptionsanalysen solcher Transfektanden mit Affymetrix Oligonukleotid Mikroarray deckten auf gesamt-genomischer Ebene ganze Kaskaden konsekutiver, transkriptioneller Alterationen auf.

Expression profiling in developing peach seed and mesocarp as affected by growth regulators

Jasmonates (JAs) and spermidine (Sd) influence fruit (and seed) development and ripening. In order to unravel their effects in peach fruit, at molecular level, field applications of methyl jasmonate (MJ) and propyl dihydrojasmonate (PDJ), and Sd were performed at an early developmental stage (late S1). At commercial harvest, JA-treated fruit were less ripe than controls. Realtime RT-PCR analyses confirmed a down-regulation of ethylene biosynthetic, perception and signaling genes, and flesh softening-related genes. The expression of cell wall-related genes, of a sugar-transporter and hormone-related transcript levels was also affected by JAs. Seeds from JA-treated fruit showed a shift in the expression of developmental marker genes suggesting that the developmental program was probably slowed down, in agreement with the contention that JAs divert resources from growth to defense. JAs also affected phenolic content and biosynthetic gene expression in the mesocarp. Levels of hydroxycinnamic acids, as well as those of flavan-3-ols, were enhanced, mainly by MJ, in S2. Transcript levels of phenylpropanoid pathway genes were up-regulated by MJ, in agreement with phenolic content. Sd-treated fruits at harvest showed reduced ethylene production and flesh softening. Sd induced a short-term and long-term response patterns in endogenous polyamines. At ripening the up-regulation of the ethylene biosynthetic genes was dramatically counteracted by Sd, leading to a down-regulation of softening-related genes. Hormone-related gene expression was also altered both in the short- and long-term. Gene expression analyses suggest that Sd interfered with fruit development/ripening by interacting with multiple hormonal pathways and that fruit developmental marker gene expression was shifted ahead in accord with a developmental slowing down. 24-Epibrassinolide was applied to Flaminia peaches under field conditions early (S1) or later (S3) during development. Preliminary results showed that, at harvest, treated fruit tended to be larger and less mature though quality parameters did not change relative to controls.

Strategies to identify and further characterize novel and known genes involved in regulation of skeletogenesis

372 osteochondrodysplasias and genetically determined dysostoses were reported in 2007 [Superti-Furga and Unger, 2007]. For 215 of these conditions, an association with one or more genes can be stated, while the molecular changes for the remaining syndromes remain illusive to date. Thus, the present dissertation aims at the identification of novel genes involved in processes regarding cartilage/ bone formation, growth, differentiation and homeostasis, which may serve as candidate genes for the above mentioned conditions. Two different approaches were undertaken. Firstly, a high throughput EST sequencing project from a human fetal cartilage library was performed to identify novel genes in early skeletal development (20th week of gestation until 2nd year of life) that could be investigated as potential candidate genes. 5000 EST sequences were generated and analyzed representing 1573 individual transcripts, corresponding to known (1400) and to novel, yet uncharacterized genes (173). About 7% of the proteins were already described in cartilage/ bone development or homeostasis, showing that the generated library is tissue specific. The remaining profile of this library was compared to previously published libraries from different time points (8th–12th, 18th–20th week and adult human cartilage) that also showed a similar distribution, reflecting the quality of the presented library analyzed. Furthermore, three potential candidate genes (LRRC59, CRELD2, ZNF577) were further investigated and their potential involvement in skeletogenesis was discussed. Secondly, a disease-orientated approach was undertaken to identify downstream targets of LMX1B, the gene causing Nail-Patella syndrome (NPS), and to investigate similar conditions. Like NPS, Genitopatellar syndrome (GPS) is characterized by aplasia or hypoplasia of the patella and renal anomalies. Therefore, six GPS patients were enrolled in a study to investigate the molecular changes responsible for this relatively rare disease. A 3.07 Mb deletion including LMX1B and NR5A1 (SF1) was found in one female patient that showed features of both NPS and GPS and investigations revealed a 46,XY karyotype and ovotestes indicating true hermaphroditism. The microdeletion was not seen in any of the five other patients with GPS features only, but a potential regulatory element between the two genes cannot be ruled out yet. Since Lmx1b is expressed in the dorsal limb bud and in podocytes, proteomic approaches and expression profiling were performed with murine material of the limbs and the kidneys to identify its downstream targets. After 2D-gel electrophoresis with protein extracts from E13.5 fore limb buds and newborn kidneys of Lmx1b wild type and knock-out mice and mass spectrometry analysis, only two proteins, agrin and carbonic anhydrase 2, remained of interest, but further analysis of the two genes did not show a transcriptional down regulation by Lmx1b. The focus was switched to expression profiles and RNA from newborn Lmx1b wild type and knock-out kidneys was compared by microarray analysis. Potential Lmx1b targets were almost impossible to study, because of the early death of Lmx1b deficient mice, when the glomeruli, containing podocytes, are still immature. Because Lmx1b is also expressed during limb development, RNA from wild type and knock-out Lmx1b E11.5 fore limb buds was investigated by microarray, revealing four potential Lmx1b downstream targets: neuropilin 2, single-stranded DNA binding protein 2, peroxisome proliferative activated receptor, gamma, co-activator 1 alpha, and short stature homeobox 2. Whole mount in situ hybridization strengthened a potential down regulation of neuropilin 2 by Lmx1b, but further investigations including in situ hybridization and protein-protein interaction studies will be needed.

Expression profiling und rationale Expressionsoptimierung am Beispiel eines prokaryontischen Wirt-,Vektor-Systems

Durch globale Expressionsprofil-Analysen auf Transkriptom-, Proteom- oder Metabolom-Ebene können biotechnologische Produktionsprozesse besser verstanden und die Erkenntnisse für die zielgerichtete, rationale Optimierung von Expressionssystemen genutzt werden. In der vorliegenden Arbeit wurde die Überexpression einer Glukose-Dehydrogenase (EC 1.1.5.2), die von der Roche Diagnostics GmbH für die diagnostische Anwendung optimiert worden war, in Escherichia coli untersucht. Die Enzymvariante unterscheidet sich in sieben ihrer 455 Aminosäuren vom Wildtyp-Enzym und wird im sonst isogenen Wirt-/Vektor-System in signifikant geringeren Mengen (Faktor 5) gebildet. Das prokaryontische Expressionssystem wurde auf Proteom-Ebene charakterisiert. Die 2-dimensionale differenzielle Gelelektrophorese (DIGE) wurde zuvor unter statistischen Aspekten untersucht. Unter Berücksichtigung von technischen und biologischen Variationen, falsch-positiven (α-) und falsch-negativen (β-) Fehlern sowie einem daraus abgeleiteten Versuchsdesign konnten Expressionsunterschiede als signifikant quantifiziert werden, wenn sie um den Faktor ≥ 1,4 differierten. Durch eine Hauptkomponenten-Analyse wurde gezeigt, dass die DIGE-Technologie für die Expressionsprofil-Analyse des Modellsystems geeignet ist. Der Expressionsstamm für die Enzymvariante zeichnete sich durch eine höhere Variabilität an Enzymen für den Zuckerabbau und die Nukleinsäure-Synthese aus. Im Expressionssystem für das Wildtyp-Enzym wurde eine unerwartet erhöhte Plasmidkopienzahl nachgewiesen. Als potenzieller Engpass in der Expression der rekombinanten Glukose-Dehydrogenase wurde die Löslichkeitsvermittlung identifiziert. Im Expressionsstamm für das Wildtyp-Enzym wurden viele Proteine für die Biogenese der äußeren Membran verstärkt exprimiert. Als Folge dessen wurde ein sog. envelope stress ausgelöst und die Zellen gingen in die stationäre Wuchsphase über. Die Ergebnisse der Proteomanalyse wurden weiterführend dazu genutzt, die Produktionsleistung für die Enzymvariante zu verbessern. Durch den Austausch des Replikationsursprungs im Expressionsvektor wurde die Plasmidkopienzahl erhöht und die zelluläre Expressionsleistung für die diagnostisch interessantere Enzymvariante um Faktor 7 - 9 gesteigert. Um die Löslichkeitsvermittlung während der Expression zu verbessern, wurde die Plasmidkopienzahl gesenkt und die Coexpression von Chaperonen initiiert. Die Ausbeuten aktiver Glukose-Dehydrogenase wurden durch die Renaturierung inaktiven Produkts aus dem optimierten Expressionssystem insgesamt um einen Faktor von 4,5 erhöht. Somit führte im Rahmen dieser Arbeit eine proteombasierte Expressionsprofil-Analyse zur zielgerichteten, rationalen Expressionsoptimierung eines prokaryontischen Modellsystems.

Profiling, re-factoring e ottimizzazione del middleware di coordinazione TuCSoN

In questo lavoro di tesi vengono esaminate quelle caratteristiche architetturali del middleware di coordinazione TuCSoN che maggiormente impattano sulle prestazioni dei sistemi coordinati. Laddove è stato possibile si è intervenuto sia a livello architetturale sia a livello tecnologico per migliorare le prestazioni del middleware. Come risultato finale si è ottenuto un importante incremento delle prestazioni del sistema. Non tutte le migliorie apportabili sono state realizzate, tuttavia vengono forniti alcuni spunti per possibili sviluppi futuri.

Forensisch relevante SNP-Genotypisierung mittels elektronischer Microarray-Technologie

Die vorliegende Dissertation entstand im Rahmen eines multizentrischen EU-geförderten Projektes, das die Anwendungsmöglichkeiten von Einzelnukleotid-Polymorphismen (SNPs) zur Individualisierung von Personen im Kontext der Zuordnung von biologischen Tatortspuren oder auch bei der Identifizierung unbekannter Toter behandelt. Die übergeordnete Zielsetzung des Projektes bestand darin, hochauflösende Genotypisierungsmethoden zu etablieren und zu validieren, die mit hoher Genauigkeit aber geringen Aufwand SNPs im Multiplexformat simultan analysieren können. Zunächst wurden 29 Y-chromosomale und 52 autosomale SNPs unter der Anforderung ausgewählt, dass sie als Multiplex eine möglichst hohe Individualisierungschance aufweisen. Anschließend folgten die Validierungen beider Multiplex-Systeme und der SNaPshot™-Minisequenzierungsmethode in systematischen Studien unter Beteiligung aller Arbeitsgruppen des Projektes. Die validierte Referenzmethode auf der Basis einer Minisequenzierung diente einerseits für die kontrollierte Zusammenarbeit unterschiedlicher Laboratorien und andererseits als Grundlage für die Entwicklung eines Assays zur SNP-Genotypisierung mittels der elektronischen Microarray-Technologie in dieser Arbeit. Der eigenständige Hauptteil dieser Dissertation beschreibt unter Verwendung der zuvor validierten autosomalen SNPs die Neuentwicklung und Validierung eines Hybridisierungsassays für die elektronische Microarray-Plattform der Firma Nanogen Dazu wurden im Vorfeld drei verschiedene Assays etabliert, die sich im Funktionsprinzip auf dem Microarray unterscheiden. Davon wurde leistungsorientiert das Capture down-Assay zur Weiterentwicklung ausgewählt. Nach zahlreichen Optimierungsmaßnahmen hinsichtlich PCR-Produktbehandlung, gerätespezifischer Abläufe und analysespezifischer Oligonukleotiddesigns stand das Capture down-Assay zur simultanen Typisierung von drei Individuen mit je 32 SNPs auf einem Microarray bereit. Anschließend wurde dieses Verfahren anhand von 40 DNA-Proben mit bekannten Genotypen für die 32 SNPs validiert und durch parallele SNaPshot™-Typisierung die Genauigkeit bestimmt. Das Ergebnis beweist nicht nur die Eignung des validierten Analyseassays und der elektronischen Microarray-Technologie für bestimmte Fragestellungen, sondern zeigt auch deren Vorteile in Bezug auf Schnelligkeit, Flexibilität und Effizienz. Die Automatisierung, welche die räumliche Anordnung der zu untersuchenden Fragmente unmittelbar vor der Analyse ermöglicht, reduziert unnötige Arbeitsschritte und damit die Fehlerhäufigkeit und Kontaminationsgefahr bei verbesserter Zeiteffizienz. Mit einer maximal erreichten Genauigkeit von 94% kann die Zuverlässigkeit der in der forensischen Genetik aktuell eingesetzten STR-Systeme jedoch noch nicht erreicht werden. Die Rolle des neuen Verfahrens wird damit nicht in einer Ablösung der etablierten Methoden, sondern in einer Ergänzung zur Lösung spezieller Probleme wie z.B. der Untersuchung stark degradierter DNA-Spuren zu finden sein.

MicroRNA profiling nei linfomi a cellule T periferiche

I linfomi a cellule T periferiche rappresentano circa il 12% di tutte le neoplasie linfoidi.In questo studio, abbiamo effettuato un’analisi di miRNA profiling (TaqMan Array MicroRNA Cards A) su 60 campioni FFPE suddivisi in: PTCLs/NOS (N=25), AITLs (N=10), ALCLs (N=12) e cellule T normali (N=13). Abbiamo identificato 4 miRNA differenzialmente espressi tra PTCLs e cellule T normali. Inoltre, abbiamo identificato tre set di mirna che discriminano le tre entita di PTCLs nodali

Microarray based real-time analysis of nucleic acid hybridization kinetics and thermodynamics

Ziel dieser Dissertation ist die experimentelle Charakterisierung und quantitative Beschreibung der Hybridisierung von komplementären Nukleinsäuresträngen mit oberflächengebundenen Fängermolekülen für die Entwicklung von integrierten Biosensoren. Im Gegensatz zu lösungsbasierten Verfahren ist mit Microarray Substraten die Untersuchung vieler Nukleinsäurekombinationen parallel möglich. Als biologisch relevantes Evaluierungssystem wurde das in Eukaryoten universell exprimierte Actin Gen aus unterschiedlichen Pflanzenspezies verwendet. Dieses Testsystem ermöglicht es, nahe verwandte Pflanzenarten auf Grund von geringen Unterschieden in der Gen-Sequenz (SNPs) zu charakterisieren. Aufbauend auf dieses gut studierte Modell eines House-Keeping Genes wurde ein umfassendes Microarray System, bestehend aus kurzen und langen Oligonukleotiden (mit eingebauten LNA-Molekülen), cDNAs sowie DNA und RNA Targets realisiert. Damit konnte ein für online Messung optimiertes Testsystem mit hohen Signalstärken entwickelt werden. Basierend auf den Ergebnissen wurde der gesamte Signalpfad von Nukleinsärekonzentration bis zum digitalen Wert modelliert. Die aus der Entwicklung und den Experimenten gewonnen Erkenntnisse über die Kinetik und Thermodynamik von Hybridisierung sind in drei Publikationen zusammengefasst die das Rückgrat dieser Dissertation bilden. Die erste Publikation beschreibt die Verbesserung der Reproduzierbarkeit und Spezifizität von Microarray Ergebnissen durch online Messung von Kinetik und Thermodynamik gegenüber endpunktbasierten Messungen mit Standard Microarrays. Für die Auswertung der riesigen Datenmengen wurden zwei Algorithmen entwickelt, eine reaktionskinetische Modellierung der Isothermen und ein auf der Fermi-Dirac Statistik beruhende Beschreibung des Schmelzüberganges. Diese Algorithmen werden in der zweiten Publikation beschrieben. Durch die Realisierung von gleichen Sequenzen in den chemisch unterschiedlichen Nukleinsäuren (DNA, RNA und LNA) ist es möglich, definierte Unterschiede in der Konformation des Riboserings und der C5-Methylgruppe der Pyrimidine zu untersuchen. Die kompetitive Wechselwirkung dieser unterschiedlichen Nukleinsäuren gleicher Sequenz und die Auswirkungen auf Kinetik und Thermodynamik ist das Thema der dritten Publikation. Neben der molekularbiologischen und technologischen Entwicklung im Bereich der Sensorik von Hybridisierungsreaktionen oberflächengebundener Nukleinsäuremolekülen, der automatisierten Auswertung und Modellierung der anfallenden Datenmengen und der damit verbundenen besseren quantitativen Beschreibung von Kinetik und Thermodynamik dieser Reaktionen tragen die Ergebnisse zum besseren Verständnis der physikalisch-chemischen Struktur des elementarsten biologischen Moleküls und seiner nach wie vor nicht vollständig verstandenen Spezifizität bei.