Access Interfaces for Open Archival Information Systems based on the OAI-PMH and the OpenURL Framework for Context-Sensitive Services

In recent years, a variety of digital repository and archival systems have been developed and adopted. All of these systems aim at hosting a variety of compound digital assets and at providing tools for storing, managing and accessing those assets. This paper will focus on the definition of common and standardized access interfaces that could be deployed across such diverse digital respository and archival systems. The proposed interfaces are based on the two formal specifications that have recently emerged from the Digital Library community: The Open Archive Initiative Protocol for Metadata Harvesting (OAI-PMH) and the NISO OpenURL Framework for Context-Sensitive Services (OpenURL Standard). As will be described, the former allows for the retrieval of batches of XML-based representations of digital assets, while the latter facilitates the retrieval of disseminations of a specific digital asset or of one or more of its constituents. The core properties of the proposed interfaces are explained in terms of the Reference Model for an Open Archival Information System (OAIS).Comment: Accepted paper for PV 2005 "Ensuring Long-term Preservation and Adding Value to Scientific and Technical data" (http://www.ukoln.ac.uk/events/pv-2005/

Visual and computational analysis of structure-activity relationships in high-throughput screening data

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. This paper reviews recent work in visualisation and data mining that can be used to develop structure-activity relationships from such chemical/biological datasets

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy.

In mass spectrometry-based untargeted metabolomics, rarely more than 30% of the compounds are identified. Without the true identity of these molecules it is impossible to draw conclusions about the biological mechanisms, pathway relationships and provenance of compounds. The only way at present to address this discrepancy is to use in silico fragmentation software to identify unknown compounds by comparing and ranking theoretical MS/MS fragmentations from target structures to experimental tandem mass spectra (MS/MS). We compared the performance of four publicly available in silico fragmentation algorithms (MetFragCL, CFM-ID, MAGMa+ and MS-FINDER) that participated in the 2016 CASMI challenge. We found that optimizing the use of metadata, weighting factors and the manner of combining different tools eventually defined the ultimate outcomes of each method. We comprehensively analysed how outcomes of different tools could be combined and reached a final success rate of 93% for the training data, and 87% for the challenge data, using a combination of MAGMa+, CFM-ID and compound importance information along with MS/MS matching. Matching MS/MS spectra against the MS/MS libraries without using any in silico tool yielded 60% correct hits, showing that the use of in silico methods is still important

Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation

Differentiating signals to make biological sense – a guide through databases for MS-based non-targeted metabolomics

Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their on-line ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as ID assignment, structural assignment and interpretation of results

MetAssign: probabilistic annotation of metabolites from LC–MS data using a Bayesian clustering approach

Motivation: The use of liquid chromatography coupled to mass spectrometry (LC–MS) has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This paper looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.<p></p> Results: The Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations.<p></p> Availability: The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/

Updates in metabolomics tools and resources: 2014-2015

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources—in the form of tools, software, and databases—is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table

Betalains and phenolic compounds of leaves and stems of Alternanthera brasiliana and Alternanthera tenella

Betacyanins and phenolic compounds from acetonitrile:acidified water extracts of Alternanthera brasiliana and Alternanthera tenella were characterized and quantified using a high-performance liquid chromatography system coupled with diode array and electrospray mass spectrometry detection. Four betacyanins (amaranthine, isoamaranthine, betanin and isobetanin) were tentatively identified and quantified. Twenty eight phenolic compounds of four different families (hydroxybenzoic and hydroxycinnamic acids, flavones and flavonols) were separated and characterized on the basis of their accurate MS and MS/MS information out of which ten compounds were confirmed by authentic standards. These plant species could be considered as an especially rich source of natural bioactive compounds and potential food colorants. A. brasiliana showed the highest betacyanin and polyphenols content (89 μg/g and 35,243 μg/g, respectively). Among polyphenols, flavonols were the more abundant (kaempferol-glucoside, kaempferol-rutinoside and kaempferol-rhamnosyl-rhamnosyl-glycoside). Meanwhile, A. tenella showed a different polyphenols profile with flavones as major compounds (glucopyranosil-vitexin and vitexin). As a novelty, pentosyl-vitexin and pentosyl-isovitexin were detected for the first time in Alternanthera plants. Both A. brasiliana and A. tenella leaves showed high total polyphenol content and in vitro antioxidant activity (FRAP). These results provide an analytical base concerning the phenolic and betalains composition and the antioxidant properties of two members of the promising Alternanthera gender, for subsequent applications, such as functional food ingredients.Fil: Deladino, Lorena. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; ArgentinaFil: Alvarez, I.. Consejo Superior de Investigaciones Científicas. Instituto de Ciencia y Tecnologia de Alimentos y Nutrición; EspañaFil: De Ancos, B.. Consejo Superior de Investigaciones Científicas. Instituto de Ciencia y Tecnologia de Alimentos y Nutrición; EspañaFil: Sánchez Moreno, C.. Consejo Superior de Investigaciones Científicas. Instituto de Ciencia y Tecnologia de Alimentos y Nutrición; EspañaFil: Molina García, A. D.. Consejo Superior de Investigaciones Científicas. Instituto de Ciencia y Tecnologia de Alimentos y Nutrición; EspañaFil: Schneider Teixeira, Aline. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; Argentina. Consejo Superior de Investigaciones Científicas. Instituto de Ciencia y Tecnologia de Alimentos y Nutrición; Españ