New insights about host response to smallpox using microarray data

Abstract Background Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. Results We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Conclusion Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems.

Development and validation of a Xanthomonas axonopodis pv. citri DNA microarray platform (XACarray) generated from the shotgun libraries previously used in the sequencing of this bacterial genome

Abstract Background From shotgun libraries used for the genomic sequencing of the phytopathogenic bacterium Xanthomonas axonopodis pv. citri (XAC), clones that were representative of the largest possible number of coding sequences (CDSs) were selected to create a DNA microarray platform on glass slides (XACarray). The creation of the XACarray allowed for the establishment of a tool that is capable of providing data for the analysis of global genome expression in this organism. Findings The inserts from the selected clones were amplified by PCR with the universal oligonucleotide primers M13R and M13F. The obtained products were purified and fixed in duplicate on glass slides specific for use in DNA microarrays. The number of spots on the microarray totaled 6,144 and included 768 positive controls and 624 negative controls per slide. Validation of the platform was performed through hybridization of total DNA probes from XAC labeled with different fluorophores, Cy3 and Cy5. In this validation assay, 86% of all PCR products fixed on the glass slides were confirmed to present a hybridization signal greater than twice the standard deviation of the deviation of the global median signal-to-noise ration. Conclusions Our validation of the XACArray platform using DNA-DNA hybridization revealed that it can be used to evaluate the expression of 2,365 individual CDSs from all major functional categories, which corresponds to 52.7% of the annotated CDSs of the XAC genome. As a proof of concept, we used this platform in a previously work to verify the absence of genomic regions that could not be detected by sequencing in related strains of Xanthomonas.

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

Abstract Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

cDNA-AFLP analysis of Psidium guajava L. cultivars under water stress and mechanical injury: methodological implications

Studies involving amplified fragment length polymorphism (cDNA-AFLP) have often used polyacrylamide gels with radiolabeled primers in order to establish best primer combinations, to analyze, and to recover transcript-derived fragments. Use of automatic sequencer to establish best primer combinations is convenient, because it saves time, reduces costs and risks of contamination with radioactive material and acrylamide, and allows objective band-matching and more precise evaluation of transcript-derived fragments intensities. This study aimed at examining the gene expression of commercial cultivars of P. guajava subjected to water and mechanical injury stresses, combining analyses by automatic sequencer and fluorescent kits for polyacrylamide gel electrophoresis. Firstly, 64 combinations of EcoRI and MseI primers were tested. Ten combinations with higher number of polymorphic fragments were then selected for transcript-derived fragments recovering and cluster analysis, involving 45 saplings of P. guajava. Two groups were obtained, one composed by the control samplings, and another formed by samplings undergoing stress, with no clear distinction between stress treatments. The results revealed the convenience of using a combination of automatic sequencer and fluorescent kits for polyacrylamide gel electrophoreses to examine gene expression profiles. The Unweighted Pair Group Method with Arithmetic Mean analysis using Euclidean distances points out a similar induced response mechanism of P. guajava undergoing water stress and mechanical injury.

Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

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.

Variation in peach fruit susceptibility to Monilinia laxa and gene expression

Brown rot caused by Monilinia laxa and Monilinia fructigena is considered one of the most important diseases affecting Prunus species. Although some losses can result from the rotten fruits in the orchard, most of the damage is caused to fruits during the post-harvest phase. Several studies reported that brown rot incidence during fruit development highly varies; it was found that at a period corresponding to the the pit hardening stage, fruit susceptibility drastically decreases, to be quickly restored afterwards. However the molecular basis of this phenomenon is still not well understood. Furthermore, no difference in the rot incidence was found between wound and un-wound fruits, suggesting that resistance associated more to a specifc biochemical response of the fruit, rather than to a higher mechanical resistance. So far, the interaction Monilinia-peach was analyzed through chemical approaches. In this study, a bio-molecular approach was undertaken in order to reveal alteration in gene expression associated to the variation of susceptibility. In this thesis three different methods for gene expression analysis were used to analyze the alterations in gene expression occurring in peach fruits during the pit hardening stage, in a period encompassing the temporary change in Monilinia susceptibility: real time PCR, microarray and cDNA AFLP techniques. In 2005, peach fruits (cv.K2) were weekly harvested during a 19-week long-period, starting from the fourth week after full bloom, until full maturity. At each sampling time, three replicates of 5 fruits each were dipped in the M.laxa conidial suspension or in distilled water, as negative control. The fruits were maintained at room temperature for 3 hours; afterwards, they were peeled with a scalpel; the peel was immediately frozen in liquid nitrogen and transferred to -80 °C until use. The degree of susceptibility of peach fruit to the pathogen was determined on 3 replicates of 20 fruits each, as percentage of infected fruits, after one week at 20 °C. Real time PCR analysis was performed to study the variation in expression of those genes encoding for the enzymes of the phenylpropanoid pathway (phenylalanine ammonia lyase (PAL), chalcone synthase (CHS), cinnamate 4-hydroxylase (C4H), leucoanthocyanidine reductase (LAR), hydroxycinnamoyl CoA quinate hydroxycinnamoyl transferase (HQT) and of the jasmonate pathway, such as lipoxygenase (LOX), both involved in the production of important defense compounds. Alteration in gene expression was monitored on fruit samples of a period encompassing the pit hardening stage and the corresponding temporary resistance to M.laxa infections, weekly, from the 6thto the 12th week after full bloom (AFB) inoculated with M. laxa or mock-inoculated. The data suggest a critical change in the expression level of the phenylpropanoid pathway from the 7th to the 8th week AFB; such change could be directly physiologically associated to the peach growth and it could indirectly determine the decrease of susceptibility of peach fruit to Monilinia rot during the subsequent weeks. To investigate on the transcriptome variation underneath the temporary loss of susceptibility of peach fruits to Monilinia rot, the microarray and the cDNA AFLP techniques were used. The samples harvested on the 8th week AFB (named S, for susceptible ones) and on the 12th week AFB (named R, for resistant ones) were compared, both inoculated or mock-inoculated. The microarray experiments were carried out at the University of Padua (Dept. of Environmental Agronomy and Crop Science), using the μPEACH1.0 microarray together with the suited protocols. The analysis showed that 30 genes (corresponding to the 0.6% of the total sequences (4806) contained in the μPeach1.0 microarray) were found up-regulated and 31 ( 0.6%) down regulated in RH vs. SH fruits. On the other hand, 20 genes (0.4%) were shown to be up-regulated and 13 (0.3%) down-regulated in the RI vs. SI fruit. No genes were found differentially expressed in the mock-inoculated resistant fruits (RH) vs. the inoculated resistant ones (RI). Among the up-regulated genes an ATP sulfurylase, an heat shock protein 70, the major allergen Pru P1, an harpin inducing protein and S-adenosylmethionine decarboxylase were found, conversely among the down-regulated ones, cinnamyl alcohol dehydrogenase, an histidine- containing phosphotransfer protein and the ferritin were found. The microarray experimental results and the data indirectly derived, were tested by Real Time PCR analysis. cDNA AFLP analysis was also performed on the same samples. 339 transcript derived fragments considered significant for Monilinia resistance, were selected, sequenced and classified. Genes potentially involved in cell rescue and defence were well represented (8%); several genes (12.1%) involved in the protein folding, post-transductional modification and genes (9.2%) involved in cellular transport were also found. A further 10.3% of genes were classified as involved in the metabolism of aminoacid, carbohydrate and fatty acid. On the other hand, genes involved in the protein synthesis (5.7%) and in signal transduction and communication (5.7%) were found. Among the most interesting genes found differentially expressed between susceptible and resistant fruits, genes encoding for pathogenesis related (PR) proteins were found. To investigate on the association of Monilinia resistance and PR biological function, the major allergen Pru P1 (GenBank accession AM493970) and its isoform (here named Pru P2), were expressed in heterologous system and in vitro assayed for their anti-microbial activity. The ribonuclease activity of the recombinant Pru P1 and Pru P2 proteins was assayed against peach total RNA. As the other PR10 proteins, they showed a ribonucleolytic activity, that could be important to contrast pathogen penetration. Moreover Pru P1 and Pru P2 recombinant proteins were checked for direct antimicrobial activity. No inhibitory effect of Pru P1 or Pru P2 was detected against the selected fungi.

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.

Die Identifizierung und Charakterisierung von HLA-Klasse-I-restringierten Minorhistokompatibilitätsantigenen und Leukämie-assoziierten Antigenen mittels cDNA-Expressionsklonierung

Die allogene hämatopoetische Stammzelltransplantation (allo-HSCT) bietet bei einem hohen Anteil akuter Leukämien die einzige kurative Behandlungsmöglichkeit. Um die mit ihr assoziierte Morbidität und Mortalität zu senken und ihre Effektivität zu steigern, soll die GvL (graft-versus-leukemia)-Reaktion als eigentliches Therapieziel gegenüber der unerwünschten GvHD (graft-versus-host disease) möglichst selektiv verstärkt werden. Wesentliche Mediatoren beider Effekte sind alloreaktive T-Zellen. Bei HLA-Übereinstimmung zwischen Spender und Empfänger sind so genannte Minorhistokompatibilitätsantigene (mHAgs) und Leukämie-assoziierte Antigene (LAA) die mutmaßlichen Zielstrukturen beider Reaktionen. Im Rahmen der vorliegenden Arbeit wurden in dem Leukämie-Modell der Patientin MZ201 [akute myeloische Leukämie (AML) vom Subtyp FAB M5] mittels T-Zell-basierter cDNA-Expressionsklonierung zwei neue Antigene identifiziert, die von allogenen, AML-reaktiven CD8+ T-Lymphozyten aus Blut eines HLA-passenden gesunden Spenders erkannt wurden. Es handelt sich zum einen um das HLA-B*5601-restringierte mHAg PLAUR-317P, das aus einem Polymorphismus des Gens PLAUR (plasminogen activator, urokinase receptor) resultiert. Das von den T-Zellen am Besten erkannte Peptid enthält die Aminosäuren 316 - 327. PLAUR wird in lymphohämatopoetischen Zellen und in verschiedenen Malignomen überexprimiert und ist dabei mit schlechterer Prognose und vermehrter Gewebeinvasivität assoziiert. Etwa 30% getesteter Individuen tragen das Allel PLAUR-317P. Zum anderen handelt es sich um ein Epitop aus der Signalregion des Chemokins CXCL3 [chemokine (C-X-C motif) ligand 3], das von CD8+ T-Zellen des gleichen Spenders auf Leukämiezellen der Patientin MZ201 in Assoziation mit HLA-A*0201 erkannt wurde. Auch CXCL3 wird vorwiegend in Zellen der Myelopoese exprimiert. Aufgrund ihres Expressionsmusters sind beide Antigene potentielle Zielstrukturen für die Elimination der Empfänger-Hämatopoese unter Einschluss der Leukämieblasten im Rahmen der allo-HSCT. Weiterführende Untersuchungen müssen zeigen, ob diese Antigene tatsächlich in vivo GvL-Reaktionen hervorrufen. Die Kenntnis eines repräsentativen Spektrums solcher Antigene würde verbesserte Spenderselektionen erlauben und neue Wege des adoptiven T-Zelltransfers erschließen helfen.