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Agency: Cordis | Branch: H2020 | Program: RIA | Phase: BIOTEC-2-2015 | Award Amount: 7.09M | Year: 2016

Omics data is not leveraged effectively in the biotechnology industry due to lack of tools to rapidly access public and private data and to design cellular manipulations or interventions based on the data. With this project we aim to make a broad spectrum of omics data useful to the biotechnology industry covering application areas ranging from industrial biotechnology to human health. We will develop novel approaches for integrative model-based omics data analysis to enable 1) Identification of novel enzymes and pathways by mining metagenomic data, 2) Data-driven design of cell factories for the production of chemicals and proteins, and 3) Analysis and design of microbial communities relevant to human health, industrial biotechnology and agriculture. All research efforts will be integrated in an interactive web-based platform that will be available for the industrial and academic research and development communities, in particular enhancing the competitiveness of biotech SMEs by economizing resources and reducing time-to-market within their respective focus areas. The platform will be composed of standardized and interoperable components that service-oriented bioinformatics SMEs involved in the project can reuse in their own products. An important aspect of the platform will be implementation of different access levels to data and software tools allowing controlling access to proprietary data and analysis tools. Two end-user companies will be involved in practical testing of the platform built within the project using proprietary omics data generated at the companies.

Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: HEALTH.2012.2.1.2-2 | Award Amount: 23.12M | Year: 2012

METACARDIS applies a systems medicine multilevel approach to identify biological relationships between gut microbiota, assessed by metagenomics, and host genome expression regulation, which will improve understanding and innovative care of cardiometabolic diseases (CMD) and their comorbidities. CMD comprise metabolic (obesity, diabetes) and heart diseases characterized by a chronic evolution in ageing populations and costly treatments. Therapies require novel integrated approaches taking into account CMD natural evolution. METACARDIS associates European leaders in metagenomics, who have been successful in establishing the structure of the human microbiome as part of the EU FP7 MetaHIT consortium, clinical and fundamental researchers, SME, patients associations and food companies to improve the understanding of pathophysiological mechanisms, prognosis and diagnosis of CMD. We will use next-generation sequencing technologies and high throughput metabolomic platforms to identify gut microbiota- and metabolomic-derived biomarkers and targets associated with CMD risks. The pathophysiological role of these markers will be tested in both preclinical models and replication cohorts allowing the study of CMD progression in patients collected in three European clinical centres of excellence. Their impact on host gene transcription will be characterised in patients selected for typical features of CMD evolution. Application of computational models and visualisation tools to complex datasets combining clinical information, environmental patterns and gut microbiome, metabolome and transcriptome data is a central integrating component in the research, which will be driven by world leaders in metagenomic and functional genomic data analysis. These studies will identify novel molecular targets, biomarkers and predictors of CMD progression, paving the way for personalized medicine in CMD.

Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: HEALTH.2010.2.1.2-1 | Award Amount: 16.86M | Year: 2011

Cancer is a complex disease involving multiple genetic and epigenetic events occurring, and influencing each other, over a long period of time. Understanding cancer, and ultimately developing effective targeted therapies, will therefore require that mutations and epigenetic alterations be systematically investigated during the multiple stages of disease development, from identifiable pre-neoplastic phases to overt cancer. Until now, no systematic effort has been undertaken to investigate these multiple layers of genome organization and function during cancer development. MODHEP aims at providing a 360 understanding of liver cancer, one of the most common types of tumors and, because of the homogeneity of the hepatic tissue, the most experimentally tractable one. The consortium brings together elite European scientists in the fields of genetics, chromatin regulation, genomics, liver cancer, computational and systems biology. This combination of skills will allow us to investigate and model at unprecedented resolution the chain of events leading from environmental perturbations and the occurrence of driver mutations to preneoplastic disease and cancer. Our experimental plan reflects some grounded assumptions: 1. cancer cannot be modeled without detailed information on the preneoplastic stages of disease; 2. genetic heterogeneity in humans would make systems-level modeling non realistic from a practical point of view. Both of these limitations are bypassed by the use of well-defined mouse models, followed by evaluation of the main conclusions in clinical samples; 3. many early stage driving events in cancer represent epigenetic alterations, which are invisible to classical genetic analysis, and are confounded by secondary and tertiary events in established tumors. Our approach will enable the identification of therapeutically relevant early-stage genetic and epigenetic alterations and the definition of their interplay in tumor development and maintenance.

Minguez P.,European Molecular Biology Laboratory EMBL | Letunic I.,Biobyte Solutions GmbH | Parca L.,European Molecular Biology Laboratory EMBL | Garcia-Alonso L.,Research Center Principe Felipe | And 4 more authors.
Nucleic Acids Research | Year: 2015

The post-translational regulation of proteins is mainly driven by two molecular events, their modification by several types of moieties and their interaction with other proteins. These two processes are interdependent and together are responsible for the function of the protein in a particular cell state. Several databases focus on the prediction and compilation of protein-protein interactions (PPIs) and no less on the collection and analysis of protein posttranslational modifications (PTMs), however, there are no resources that concentrate on describing the regulatory role of PTMs in PPIs. We developed several methods based on residue co-evolution and proximity to predict the functional associations of pairs of PTMs that we apply to modifications in the same protein and between two interacting proteins. In order to make data available for understudied organisms, PTMcode v2 (http://ptmcode.embl.de) includes a new strategy to propagate PTMs from validated modified sites through orthologous proteins. The second release of PTMcode covers 19 eukaryotic species from which we collected more than 300 000 experimentally verified PTMs (>1 300 000 propagated) of 69 types extracting the post-translational regulation of >100 000 proteins and >100 000 interactions. In total, we report 8 million associations of PTMs regulating single proteins and over 9.4 million interplays tuning PPIs. © The Author(s) 2014.

The main objective of this research proposal is to identify and elaborate those characteristics of ENM that determine their biological hazard potential. This potential includes the ability of ENM to induce damage at the cellular, tissue, or organism levels by interacting with cellular structures leading to impairment of key cellular functions. These adverse effects may be mediated by ENM-induced alterations in gene expression and translation, but may involve also epigenetic transformation of genetic functions. We believe that it will be possible to create a set of biomarkers of ENM toxicity that are relevant in assessing and predicting the safety and toxicity of ENM across species. The ENM-organism interaction is complex and depends, not simply on the composition of ENM core, but particularly on its physico-chemical properties. In fact, important physico-chemical properties are largely governed by their surface properties. All of these factors determine the binding of different biomolecules on the surface of the ENM, the formation of a corona around the ENM core. Thus, any positive or negative biological effect of ENM in organisms may be dynamically modulated by the bio-molecule corona associated with or substituted into the ENM surface rather than the ENM on its own. The bio-molecule corona of seemingly identical ENM cores may undergo dynamic changes during their passage through different biological compartments; in other words, their biological effects are governed by this complex surface chemistry. We propose that understanding the fundamental characteristics of ENM underpinning their biological effects will provide a sound foundation with which to classify ENM according to their safety. Therefore, the overarching objective of this research is to provide a means to develop a safety classification of ENM based on an understanding of their interactions with living organisms at the molecular, cellular, and organism levels based on their material characteristics.

Minguez P.,European Molecular Biology Laboratory | Letunic I.,Biobyte solutions GmbH | Parca L.,University of Rome Tor Vergata | Bork P.,European Molecular Biology Laboratory | Bork P.,Max Delbrück Center for Molecular Medicine
Nucleic Acids Research | Year: 2013

Post-translational modifications (PTMs) are involved in the regulation and structural stabilization of eukaryotic proteins. The combination of individual PTM states is a key to modulate cellular functions as became evident in a few well-studied proteins. This combinatorial setting, dubbed the PTM code, has been proposed to be extended to whole prote-omes in eukaryotes. Although we are still far from deciphering such a complex language, thousands of protein PTM sites are being mapped by high-throughput technologies, thus providing sufficient data for comparative analysis. PTMcode (http://ptmcode.embl.de) aims to compile known and predicted PTM associations to provide a framework that would enable hypothesis-driven experimental or computational analysis of various scales. In its first release, PTMcode provides PTM functional associations of 13 different PTM types within proteins in 8 eukaryotes. They are based on five evidence channels: a literature survey, residue co-evolution, structural proximity, PTMs at the same residue and location within PTM highly enriched protein regions (hotspots). PTMcode is presented as a protein-based searchable database with an interactive web interface providing the context of the co-regulation of nearly 75000 residues in >10 000 proteins. © The Author(s) 2012.

Kuhn M.,Max Planck Institute of Molecular Cell Biology and Genetics | Letunic I.,Biobyte solutions GmbH | Jensen L.J.,Novo Nordisk AS | Bork P.,Structural and Computational Biology Unit | Bork P.,Max Delbrück Center for Molecular Medicine
Nucleic Acids Research | Year: 2016

Unwanted side effects of drugs are a burden on patients and a severe impediment in the development of new drugs. At the same time, adverse drug reactions (ADRs) recorded during clinical trials are an important source of human phenotypic data. It is therefore essential to combine data on drugs, targets and side effects into a more complete picture of the therapeutic mechanism of actions of drugs and the ways in which they cause adverse reactions. To this end, we have created the SIDER ('Side Effect Resource', http://sideeffects.embl.de) database of drugs and ADRs. The current release, SIDER 4, contains data on 1430 drugs, 5880 ADRs and 140 064 drug-ADR pairs, which is an increase of 40% compared to the previous version. For more fine-grained analyses, we extracted the frequency with which side effects occur from the package inserts. This information is available for 39% of drug-ADR pairs, 19% of which can be compared to the frequency under placebo treatment. SIDER furthermore contains a data set of drug indications, extracted from the package inserts using Natural Language Processing. These drug indications are used to reduce the rate of false positives by identifying medical terms that do not correspond to ADRs. © The Author(s) 2015.

Dinkel H.,SCB Unit | Chica C.,SCB Unit | Chica C.,French Atomic Energy Commission | Via A.,University of Rome La Sapienza | And 5 more authors.
Nucleic Acids Research | Year: 2011

The Phospho.ELM resource (http://phospho.elm.eu.org) is a relational database designed to store in vivo and in vitro phosphorylation data extracted from the scientific literature and phosphoproteomicanalyses. The resource has been actively developed for more than 7 years and currently comprises 42 574 serine, threonine and tyrosine non-redundant phosphorylation sites. Several new features have been implemented, such as structural disorder/ order and accessibility information and a conservation score. Additionally, the conservation of the phosphosites can now be visualized directly on the multiple sequence alignment used for the score calculation. Finally, special emphasis has been put on linking to external resources such as interaction networks and other databases. © The Author(s) 2010.

Via A.,University of Rome La Sapienza | Diella F.,European Molecular Biology Laboratory | Diella F.,Biobyte Solutions GmbH | Gibson T.J.,European Molecular Biology Laboratory | Helmer-Citterich M.,University of Rome Tor Vergata
Frontiers in Bioscience | Year: 2011

Phosphorylation is the most widely studied posttranslational modification occurring in cells. While mass spectrometry-based proteomics experiments are uncovering thousands of novel in vivo phosphorylation sites, the identification of kinase specificity rules still remains a relatively slow and often inefficacious task. In the last twenty years, many efforts have being devoted to the experimental and computational identification of sequence and structural motifs encoding kinase-substrate interaction key residues and the phosphorylated amino acid itself. In this review, we retrace the road to the discovery of phosphorylation sequence motifs, examine the progresses achieved in the detection of three-dimensional motifs and discuss their importance in the understanding of regulation and de-regulation of many cellular processes.

Letunic I.,Biobyte Solutions GmbH | Doerks T.,EMBL | Bork P.,EMBL
Nucleic Acids Research | Year: 2015

SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's 'Genomic' mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as highresolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine. © The Author(s) 2014.

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