A multilevel data integration resource for breast cancer study

BACKGROUND: Breast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity. RESULTS: In this work we present the Genes-to-Systems Breast Cancer (G2SBC) Database, a resource which integrates data about genes, transcripts and proteins reported in literature as altered in breast cancer cells. Beside the data integration, we provide an ontology based query system and analysis tools related to intracellular pathways, PPIs, protein structure and systems modelling, in order to facilitate the study of breast cancer using a multilevel perspective. The resource is available at the URL http://www.itb.cnr.it/breastcancer. CONCLUSIONS: The G2SBC Database represents a systems biology oriented data integration approach devoted to breast cancer. By means of the analysis capabilities provided by the web interface, it is possible to overcome the limits of reductionist resources, enabling predictions that can lead to new experiments

Bioinformatics approach for data management about bone cells grown on substitute materials

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A Grid-based solution for management and analysis of microarrays in distributed experiments

Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip® Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of uploading and accessing distributed datasets through the Grid middleware and against its ability in managing the execution of jobs on distributed computational resources. Results from the Grid test will be discussed in a further paper

The PPARγ2 P12A polymorphism is not associated with all-cause mortality in patients with type 2 diabetes mellitus

The high mortality risk of patients with type 2 diabetes mellitus may well be explained by the several comorbidities and/or complications. Also the intrinsic genetic component predisposing to diabetes might have a role in shaping the risk of diabetes-related mortality. Among type 2 diabetes mellitus SNPs, rs1801282 is of particular interest because (i) it is harbored by peroxisome proliferator-activated receptor-γ2 (PPARγ2), which is the target for thiazolidinediones which are used as antidiabetic drugs, decreasing all-cause mortality in type 2 diabetes mellitus, and (ii) it is associated with insulin resistance and related traits, risk factors for overall mortality in type 2 diabetes mellitus. We investigated the role of PPARγ2 P12A, according to a dominant model (PA + AA vs. PP individuals) on incident all-cause mortality in three cohorts of type 2 diabetes mellitus, comprising a total of 1672 patients (462 deaths) and then performed a meta-analysis of ours and all available published data. In the three cohorts pooled and analyzed together, no association between PPARγ2 P12A and all-cause mortality was observed (HR 1.02, 95 % CI 0.79–1.33). Similar results were observed after adjusting for age, sex, smoking habits, and BMI (HR 1.09, 95 % CI 0.83–1.43). In a meta-analysis of ours and all studies previously published (n = 3241 individuals; 666 events), no association was observed between PPARγ2 P12A and all-cause mortality (HR 1.07, 95 % CI 0.85–1.33). Results from our individual samples as well as from our meta-analysis suggest that the PPARγ2 P12A does not significantly affect all-cause mortality in patients with type 2 diabetes mellitus

SNPRanker: a tool for identification and scoring of SNPs associated to target genes

Summary The identification of genes and SNPs involved in human diseases remains a challenge. Many public resources, databases and applications, collect biological data and perform annotations, increasing the global biological knowledge. The need of SNPs prioritization is emerging with the development of new high-throughput genotyping technologies, which allow to develop customized disease-oriented chips. Therefore, given a list of genes related to a specific biological process or disease as input, a crucial issue is finding the most relevant SNPs to analyse. The selection of these SNPs may rely on the relevant a-priori knowledge of biomolecular features characterising all the annotated SNPs and genes of the provided list. The bioinformatics approach described here allows to retrieve a ranked list of significant SNPs from a set of input genes, such as candidate genes associated with a specific disease. The system enriches the genes set by including other genes, associated to the original ones by ontological similarity evaluation. The proposed method relies on the integration of data from public resources in a vertical perspective (from genomics to systems biology data), the evaluation of features from biomolecular knowledge, the computation of partial scores for SNPs and finally their ranking, relying on their global score. Our approach has been implemented into a web based tool called SNPRanker, which is accessible through at the URL http://www.itb.cnr.it/snpranker. An interesting application of the presented system is the prioritisation of SNPs related to genes involved in specific pathologies, in order to produce custom arrays

Effect of chestnut tannin extract (Castanea sativa Miller) on the proliferation of Cladosporium cladosporioides on sheep cheese rind during the ripening

Strains belonging to the genus Cladosporium can cause black spots on the surface of sheep cheese, making it impossible to sell. Two water solutions of chestnut tannin extract (i) 200 g L-1 (CHE200) and (ii) 400 g L-1 (CHE400), and the chestnut tannin extract powder (CHEP) were tested in a cheese making trial in which 60 cheese units were allotted to 5 experimental groups (each of 12 cheeses: C1, control 1 without any treatment; C2, control 2 treated with a silver ion solution; and cheeses LCHE200, LCHE400, and LCHEP, treated with CHE200, CHE400, and CHEP, respectively). The cheeses were ripened in a room polluted with Cladosporium cladosporioides with the aim to create conditions for the proliferation of this fungus on the cheeses. The results indicated that chestnut tannin extract at a concentration of 200 g L-1 is capable of completely inhibiting C. cladosporioides proliferation, avoiding spoilage of the sheep cheese

Effect of Dietary Chestnut or Quebracho Tannin Supplementation on Microbial Community and Fatty Acid Profile in the Rumen of Dairy Ewes

Ruminants derived products have a prominent role in diets and economy worldwide; therefore, the capability to control the rumen microbial ecosystem, for ameliorating their quality, is of fundamental importance in the livestock sector. e aim of this study was to evaluate the e ect of dietary supplementation with chestnut and quebracho tannins on microbial community and fatty acid pro le, in the rumen uid of dairy ewes. Multivariate analysis of PCR-DGGE pro les of rumen microbial communities showed a correlation among the presence of chestnut or quebracho in the diet, the speci c Butyrivibrio group DGGE pro les, the increase in 18:3 cis9, cis12, and cis15; 18:2 cis9 and cis12; 18:2 cis9 and trans11; 18:2 trans11 and cis15; and 18:1 trans11 content, and the decrease in 18:0 concentration. Phylogenetic analysis of DGGE band sequences revealed the presence of bacteria representatives related to the genera Hungatella, Ruminococcus, and Eubacterium and unclassi ed Lachnospiraceae family members, suggesting that these taxa could be a ected by tannins presence in the diets. e results of this study showed that tannins from chestnut and quebracho can reduce the biohydrogenation of unsaturated fatty acids through changes in rumen microbial communities

Development of label-free biophysical markers in osteogenic maturation

The spatial and temporal changes of morphological and mechanical properties of living cells reflect complex functionally-associated processes. Monitoring these modifications could provide a direct information on the cellular functional state. Here we present an integrated biophysical approach to the quantification of the morphological and mechanical phenotype of single cells along a maturation pathway. Specifically, quantitative phase microscopy and single cell biomechanical testing were applied to the characterization of the maturation of human foetal osteoblasts, demonstrating the ability to identify effective label-free biomarkers along this fundamental biological process