Search

Multiscale Genomics (MuG) Virtual Research Environment (MuGVRE) is a cloud-based computational infrastructure created to support the deployment of software tools addressing the various levels of analysis in 3D/4D genomics. Integrated tools tackle needs ranging from high computationally demanding applications (e.g. molecular dynamics simulations) to high-throughput data analysis applications (like the processing of next generation sequencing). The MuG Infrastructure is based on openNebula cloud systems implemented at the Institute for research in Biomedicine, and the Barcelona Supercomputing Center, and has specific interfaces for users and developers. Interoperability of the tools included in MuGVRE is maintained through a rich set of metadata allowing the system to associate tools and data in a transparent manner. Execution scheduling is based in a traditional queueing system to handle demand peaks in applications of fixed needs, and an elastic and multi-scale programming model (pyCOMPSs, controlled by the PMES scheduler), for complex workflows requiring distributed or multi-scale executions schemes. MuGVRE is available athttps://vre.multiscalegenomics.euand documentation and general information athttps://www.multiscalegenomics.eu. The infrastructure is open and freely accessible.

We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models. M.O. is an ICREA (Institució Catalana de Recerca i Estudis Avancats) academia researcher; Spanish Ministry of Science [RTI2018-096704-B-100]; Catalan Government [2017-SGR-134]; Instituto de Salud Carlos III–Instituto Nacional de Bioinformática, the European Union's Horizon 2020 research and innovation program, and the Biomolecular and Bioinformatics Resources Platform [ISCIII PT 17/0009/0007 co-funded by the Fondo Europeo de Desarrollo Regional FEDER; Grants Elixir-Excelerate: 676559 and BioExcel2: 823830; ERC:812850; MuG-676566]; MINECO Severo Ochoa Award of Excellence from the Government of Spain (awarded to IRB Barcelona). Funding for open access charge: Spanish Ministry of Science [RTI2018-096704-B-100].

Misfolding and aggregation of proteins in tissues is linked to the onset of a diverse set of human neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. In these pathologies proteins usually aggregate into highly ordered and β-sheet enriched amyloid fibrils. However, the formation of these toxic structures is not restricted to a reduced set of polypeptides but rather an intrinsic property of proteins. This suggests that the number of proteins involved in conformational disorders might be much larger than previously thought. The propensity of a protein to form amyloid assemblies is imprinted in its sequence and can be read using computational approaches. Here, we exploit four of these algorithms to analyze the presence of aggregation-prone regions in the sequence and structure of the extracellular domains of several neuroreceptors, with the idea of identifying patches that can interact anomalously with other aggregation-prone molecules such as the amyloid-β peptide or promote their self-assembly. The number of amyloidogenic regions in these domains is rather low but they are significantly exposed to solvent and therefore are suitable for interactions. We find a significant overlap between aggregation-prone regions and receptors interfaces and/or ligand-binding sites, which illustrates an unavoidable competition between the formation of functional native interactions and that of dangerous amyloid-like contacts leading to disease.

Aims: Disulfide-rich domains (DRDs) are small proteins whose native structure is stabilized by the presence of covalent disulfide bonds. These domains are versatile and can perform a wide range of functions. Many of these domains readily unfold on disulfide bond reduction, suggesting that in the absence of covalent bonding they might display significant disorder. Results: Here, we analyzed the degree of disorder in 97 domains representative of the different DRDs families and demonstrate that, in terms of sequence, many of them can be classified as intrinsically disordered proteins (IDPs) or contain predicted disordered regions. The analysis of the aggregation propensity of these domains indicates that, similar to IDPs, their sequences are more soluble and have less aggregating regions than those of other globular domains, suggesting that they might have evolved to avoid aggregation after protein synthesis and before they can attain its compact and covalently linked native structure. Innovation and Conclusion: DRDs, which resemble IDPs in the reduced state and become globular when their disulfide bonds are formed, illustrate the link between protein folding and aggregation propensities and how these two properties cannot be easily dissociated, determining the main traits of the folding routes followed by these small proteins to attain their native oxidized states. Antioxid. Redox Signal. 21, 368–383.

Altres ajuts: SUDOE, INTERREG IV B, FEDER [SOE4/P1/E831to S.V.]; ICREA [ICREA Academia 2009 to S.V.] Altres ajuts: EUR/SUDOE/INTERREG IV B/SOE4-P1-E831 Prions are a particular type of amyloids with the ability to self-perpetuate and propagate in vivo. Prion-like conversion underlies important biological processes but is also connected to human disease. Yeast prions are the best understood transmissible amyloids. In these proteins, prion formation from an initially soluble state involves a structural conversion, driven, in many cases, by specific domains enriched in glutamine/asparagine (Q/N) residues. Importantly, domains sharing this compositional bias are also present in the proteomes of higher organisms, thus suggesting that prion-like conversion might be an evolutionary conserved mechanism. We have recently shown that the identification and evaluation of the potency of amyloid nucleating sequences in putative prion domains allows discrimination of genuine prions. PrionW is a web application that exploits this principle to scan sequences in order to identify proteins containing Q/N enriched prion-like domains (PrLDs) in large datasets. When used to scan the complete yeast proteome, PrionW identifies previously experimentally validated prions with high accuracy. Users can analyze up to 10 000 sequences at a time, PrLD-containing proteins are identified and their putative PrLDs and amyloid nucleating cores visualized and scored. The output files can be downloaded for further analysis. PrionW server can be accessed at http://bioinf.uab.cat/prionw/.