Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Tools in pharmacovigilance in psychiatry: therapeutic drug monitoring, pharmacogenetic tests and drug-drug interactions databases

SUMMARYIn order to increase drug safety we must better understand how medication interacts with the body of our patients and this knowledge should be made easily available for the clinicians prescribing the medication. This thesis contributes to how the knowledge of some drug properties can increase and how to make information readily accessible for the medical professionals. Furthermore it investigates the use of Therapeutic drug monitoring, drug interaction databases and pharmacogenetic tests in pharmacovigilance.Two pharmacogenetic studies in the naturalistic setting of psychiatric in-patients clinics have been performed; one with the antidepressant mirtazapine, the other with the antipsychotic clozapine. Forty-five depressed patients have been treated with mirtazapine and were followed for 8 weeks. The therapeutic effect was as seen in other previous studies. Enantioselective analyses could confirm an influence of age, gender and smoking in the pharmacokinetics of mirtazapine; it showed a significant influence of the CYP2D6 genotype on the antidepressant effective S-enantiomer, and for the first time an influence of the CYP2B6 genotype on the plasma concentrations of the 8-OH metabolite was found. The CYP2B6*/*6 genotype was associated to better treatment response. A detailed hypothesis of the metabolic pathways of mirtazapine is proposed. In the second pharmacogenetic study, analyses of 75 schizophrenic patients treated with clozapine showed the influence of CYP450 and ABCB1 genotypes on its pharmacokinetics. For the first time we could demonstrate an in vivo effect of the CYP2C19 genotype and an influence of P-glycoprotein on the plasma concentrations of clozapine. Further we confirmed in vivo the prominent role of CYP1A2 in the metabolism of clozapine.Identifying risk factors for the occurrence of serious adverse drug reactions (SADR) would allow a more individualized and safer drug therapy. SADR are rare events and therefore difficult to study. We tested the feasibility of a nested matched case-control study to examine the influence of high drug plasma levels and CYP2D6 genotypes on the risk to experience an SADR. In our sample we compared 62 SADR cases with 82 controls; both groups were psychiatric patients from the in-patient clinic Königsfelden. Drug plasma levels of >120% of the upper recommended references could be identified as a risk factor with a statistically significant odds ratio of 3.5, a similar trend could be seen for CYP2D6 poor metaboliser. Although a matched case-control design seems a valid method, 100% matching is not easy to perform in a relative small cohort of one in-patient clinic. However, a nested case-control study is feasible.On the base of the experience gained in the AMSP+ study and the fact that we have today only sparse data indicating that routine drug plasma concentration monitoring and/or pharmacogenetic testing in psychiatry are justified to minimize the risk for ADR, we developed a test algorithm named "TDM plus" (TDM plus interaction checks plus pharmacogenetic testing).Pharmacovigilance programs such as the AMSP project (AMSP = Arzneimittelsicherheit in der Psychiatrie) survey psychiatric in-patients in order to collect SADR and to detect new safety signals. Case reports of such SADR are, although anecdotal, valuable to illustrate rare clinical events and sometimes confirm theoretical assumptions of e.g. drug interactions. Seven pharmacovigilance case reports are summarized in this thesis.To provide clinicians with meaningful information on the risk of drug combinations, during the course of this thesis the internet based drug interaction program mediQ.ch (in German) has been developed. Risk estimation is based on published clinical and pharmacological information of single drugs and alimentary products, including adverse drug reaction profiles. Information on risk factors such as renal and hepatic insufficiency and specific genotypes are given. More than 20'000 drug pairs have been described in detail. Over 2000 substances with their metabolic and transport pathways are included and all information is referenced with links to the published scientific literature or other information sources. Medical professionals of more than 100 hospitals and 300 individual practitioners do consult mediQ.ch regularly. Validations with comparisons to other drug interaction programs show good results.Finally, therapeutic drug monitoring, drug interaction programs and pharmacogenetic tests are helpful tools in pharmacovigilance and should, in absence of sufficient routine tests supporting data, be used as proposed in our TDM plus algorithm.RESUMEPour améliorer la sécurité d'emploi des médicaments il est important de mieux comprendre leurs interactions dans le corps des patients. Ensuite le clinicien qui prescrit une pharmacothérapie doit avoir un accès simple à ces informations. Entre autres, cette thèse contribue à mieux connaître les caractéristiques pharmacocinétiques de deux médicaments. Elle examine aussi l'utilisation de trois outils en pharmacovigilance : le monitorage thérapeutique des taux plasmatiques des médicaments (« therapeutic drug monitoring »), un programme informatisé d'estimation du risque de combinaisons médicamenteuses, et enfin des tests pharmacogénétiques.Deux études cliniques pharmacogénétiques ont été conduites dans le cadre habituel de clinique psychiatrique : l'une avec la mirtazapine (antidépresseur), l'autre avec la clozapine (antipsychotique). On a traité 45 patients dépressifs avec de la mirtazapine pendant 8 semaines. L'effet thérapeutique était semblable à celui des études précédentes. Nous avons confirmé l'influence de l'âge et du sexe sur la pharmacocinétique de la mirtazapine et la différence dans les concentrations plasmatiques entre fumeurs et non-fumeurs. Au moyen d'analyses énantiomères sélectives, nous avons pu montrer une influence significative du génotype CYP2D6 sur l'énantiomère S+, principalement responsable de l'effet antidépresseur. Pour la première fois, nous avons trouvé une influence du génotype CYP2B6 sur les taux plasmatiques de la 8-OH-mirtazapine. Par ailleurs, le génotype CYP2B6*6/*6 était associé à une meilleure réponse thérapeutique. Une hypothèse sur les voies métaboliques détaillées de la mirtazapine est proposée. Dans la deuxième étude, 75 patients schizophrènes traités avec de la clozapine ont été examinés pour étudier l'influence des génotypes des iso-enzymes CYP450 et de la protéine de transport ABCB1 sur la pharmacocinétique de cet antipsychotique. Pour la première fois, on a montré in vivo un effet des génotypes CYP2C19 et ABCB1 sur les taux plasmatiques de la clozapine. L'importance du CYP1A2 dans le métabolisme de la clozapine a été confirmée.L'identification de facteurs de risques dans la survenue d'effets secondaire graves permettrait une thérapie plus individualisée et plus sûre. Les effets secondaires graves sont rares. Dans une étude de faisabilité (« nested matched case-control design » = étude avec appariement) nous avons comparé des patients avec effets secondaires graves à des patients-contrôles prenant le même type de médicaments mais sans effets secondaires graves. Des taux plasmatiques supérieurs à 120% de la valeur de référence haute sont associés à un risque avec « odds ratio » significatif de 3.5. Une tendance similaire est apparue pour le génotype du CYP2D6. Le « nested matched case-control design » semble une méthode valide qui présente cependant une difficulté : trouver des patients-contrôles dans le cadre d'une seule clinique psychiatrique. Par contre la conduite d'une « nested case-control study » sans appariement est recommandable.Sur la base de notre expérience de l'étude AMSP+ et le fait que nous disposons que de peux de données justifiant des monitorings de taux plasmatiques et/ou de tests pharmacogénétiques de routine, nous avons développé un test algorithme nommé « TDMplus » (TDM + vérification d'interactions médicamenteuses + tests pharmacogénétique).Des programmes de pharmacovigilances comme celui de l'AMSP (Arzneimittelsicherheit in der Psychiatrie = pharmacovigilance en psychiatrie) collectent les effets secondaires graves chez les patients psychiatriques hospitalisés pour identifier des signaux d'alertes. La publication de certains de ces cas même anecdotiques est précieuse. Elle décrit des événements rares et quelques fois une hypothèse sur le potentiel d'une interaction médicamenteuse peut ainsi être confirmée. Sept publications de cas sont résumées ici.Dans le cadre de cette thèse, on a développé un programme informatisé sur internet (en allemand) - mediQ.ch - pour estimer le potentiel de risques d'une interaction médicamenteuse afin d'offrir en ligne ces informations utiles aux cliniciens. Les estimations de risques sont fondées sur des informations cliniques (y compris les profils d'effets secondaires) et pharmacologiques pour chaque médicament ou substance combinés. Le programme donne aussi des informations sur les facteurs de risques comme l'insuffisance rénale et hépatique et certains génotypes. Actuellement il décrit en détail les interactions potentielles de plus de 20'000 paires de médicaments, et celles de 2000 substances actives avec leurs voies de métabolisation et de transport. Chaque information mentionne sa source d'origine; un lien hypertexte permet d'y accéder. Le programme mediQ.ch est régulièrement consulté par les cliniciens de 100 hôpitaux et par 300 praticiens indépendants. Les premières validations et comparaisons avec d'autres programmes sur les interactions médicamenteuses montrent de bons résultats.En conclusion : le monitorage thérapeutique des médicaments, les programmes informatisés contenant l'information sur le potentiel d'interaction médicamenteuse et les tests pharmacogénétiques sont de précieux outils en pharmacovigilance. Nous proposons de les utiliser en respectant l'algorithme « TDM plus » que nous avons développé.

MRI newsletter 8: Georeferenced biological databases - A tool for understanding mountain biodiversity

The Mountain Research Initiative invited Dr Eva Spehn, Director of the Global Mountain Biodiversity Assessment (GMBA), and Dr Antoine Guisan, head of the Spatial Ecology Group at the University of Lausanne, to introduce the reader to their coordinated efforts to advance understanding and prediction of mountain biodiversity. Antoine Guisan's EUROMONT project is one of the many scientific projects that may potentially provide data for the new GMBA initiative for a GIS mountain biodiversity database.

Reconciliation of metabolites and biochemical reactions for metabolic networks.

Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.

A novel bioinformatics pipeline to discover genes related to arbuscular mycorrhizal symbiosis based on their evolutionary conservation pattern among higher plants.

BACKGROUND: Genes involved in arbuscular mycorrhizal (AM) symbiosis have been identified primarily by mutant screens, followed by identification of the mutated genes (forward genetics). In addition, a number of AM-related genes has been identified by their AM-related expression patterns, and their function has subsequently been elucidated by knock-down or knock-out approaches (reverse genetics). However, genes that are members of functionally redundant gene families, or genes that have a vital function and therefore result in lethal mutant phenotypes, are difficult to identify. If such genes are constitutively expressed and therefore escape differential expression analyses, they remain elusive. The goal of this study was to systematically search for AM-related genes with a bioinformatics strategy that is insensitive to these problems. The central element of our approach is based on the fact that many AM-related genes are conserved only among AM-competent species. RESULTS: Our approach involves genome-wide comparisons at the proteome level of AM-competent host species with non-mycorrhizal species. Using a clustering method we first established orthologous/paralogous relationships and subsequently identified protein clusters that contain members only of the AM-competent species. Proteins of these clusters were then analyzed in an extended set of 16 plant species and ranked based on their relatedness among AM-competent monocot and dicot species, relative to non-mycorrhizal species. In addition, we combined the information on the protein-coding sequence with gene expression data and with promoter analysis. As a result we present a list of yet uncharacterized proteins that show a strongly AM-related pattern of sequence conservation, indicating that the respective genes may have been under selection for a function in AM. Among the top candidates are three genes that encode a small family of similar receptor-like kinases that are related to the S-locus receptor kinases involved in sporophytic self-incompatibility. CONCLUSIONS: We present a new systematic strategy of gene discovery based on conservation of the protein-coding sequence that complements classical forward and reverse genetics. This strategy can be applied to diverse other biological phenomena if species with established genome sequences fall into distinguished groups that differ in a defined functional trait of interest.

Database construction and Peptide identification strategies for proteogenomic studies on sequenced genomes.

Since the advent of high-throughput DNA sequencing technologies, the ever-increasing rate at which genomes have been published has generated new challenges notably at the level of genome annotation. Even if gene predictors and annotation softwares are more and more efficient, the ultimate validation is still in the observation of predicted gene product( s). Mass-spectrometry based proteomics provides the necessary high throughput technology to show evidences of protein presence and, from the identified sequences, confirmation or invalidation of predicted annotations. We review here different strategies used to perform a MS-based proteogenomics experiment with a bottom-up approach. We start from the strengths and weaknesses of the different database construction strategies, based on different genomic information (whole genome, ORF, cDNA, EST or RNA-Seq data), which are then used for matching mass spectra to peptides and proteins. We also review the important points to be considered for a correct statistical assessment of the peptide identifications. Finally, we provide references for tools used to map and visualize the peptide identifications back to the original genomic information.

The Gene Ontology: enhancements for 2011.

The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources.

AssociationViewer: a scalable and integrated software tool for visualization of large-scale variation data in genomic context.

SUMMARY: We present a tool designed for visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies. This software provides an integrated framework to facilitate the interpretation of SNP association studies in genomic context. Gene annotations can be retrieved from Ensembl, linkage disequilibrium data downloaded from HapMap and custom data imported in BED or WIG format. AssociationViewer integrates functionalities that enable the aggregation or intersection of data tracks. It implements an efficient cache system and allows the display of several, very large-scale genomic datasets. AVAILABILITY: The Java code for AssociationViewer is distributed under the GNU General Public Licence and has been tested on Microsoft Windows XP, MacOSX and GNU/Linux operating systems. It is available from the SourceForge repository. This also includes Java webstart, documentation and example datafiles.

Defining new criteria for selection of cell-based intestinal models using publicly available databases.

BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.

ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.

Animal Toxins: How is Complexity Represented in Databases?

Peptide toxins synthesized by venomous animals have been extensively studied in the last decades. To be useful to the scientific community, this knowledge has been stored, annotated and made easy to retrieve by several databases. The aim of this article is to present what type of information users can access from each database. ArachnoServer and ConoServer focus on spider toxins and cone snail toxins, respectively. UniProtKB, a generalist protein knowledgebase, has an animal toxin-dedicated annotation program that includes toxins from all venomous animals. Finally, the ATDB metadatabase compiles data and annotations from other databases and provides toxin ontology.

Defining and searching for structural motifs using DeepView/Swiss-PdbViewer.

BACKGROUND: Today, recognition and classification of sequence motifs and protein folds is a mature field, thanks to the availability of numerous comprehensive and easy to use software packages and web-based services. Recognition of structural motifs, by comparison, is less well developed and much less frequently used, possibly due to a lack of easily accessible and easy to use software. RESULTS: In this paper, we describe an extension of DeepView/Swiss-PdbViewer through which structural motifs may be defined and searched for in large protein structure databases, and we show that common structural motifs involved in stabilizing protein folds are present in evolutionarily and structurally unrelated proteins, also in deeply buried locations which are not obviously related to protein function. CONCLUSIONS: The possibility to define custom motifs and search for their occurrence in other proteins permits the identification of recurrent arrangements of residues that could have structural implications. The possibility to do so without having to maintain a complex software/hardware installation on site brings this technology to experts and non-experts alike.

Animal Toxins: How is Complexity Represented in Databases?

Peptide toxins synthesized by venomous animals have been extensively studied in the last decades. To be useful to the scientific community, this knowledge has been stored, annotated and made easy to retrieve by several databases. The aim of this article is to present what type of information users can access from each database. ArachnoServer and ConoServer focus on spider toxins and cone snail toxins, respectively. UniProtKB, a generalist protein knowledgebase, has an animal toxin-dedicated annotation program that includes toxins from all venomous animals. Finally, the ATDB metadatabase compiles data and annotations from other databases and provides toxin ontology.

Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.