Statistical correlations between NMR spectroscopy and direct infusion FT-ICR mass spectrometry aid annotation of unknowns in metabolomics

NMR spectroscopy and mass spectrometry are the two major analytical platforms for metabolomics, and both generate substantial data with hundreds to thousands of observed peaks for a single sample. Many of these are unknown, and peak assignment is generally complex and time-consuming. Statistical correlations between data types have proven useful in expediting this process, for example, in prioritizing candidate assignments. However, this approach has not been formally assessed for the comparison of direct-infusion mass spectrometry (DIMS) and NMR data. Here, we present a systematic analysis of a sample set (tissue extracts), and the utility of a simple correlation threshold to aid metabolite identification. The correlations were surprisingly successful in linking structurally related signals, with 15 of 26 NMR-detectable metabolites having their highest correlation to a cognate MS ion. However, we found that the distribution of the correlations was highly dependent on the nature of the MS ion, such as the adduct type. This approach should help to alleviate this important bottleneck where both 1D NMR and DIMS data sets have been collected

Combined bezafibrate and medroxyprogesterone acetate: potential novel therapy for acute myeloid leukaemia

Background: The majority of acute myeloid leukaemia (AML) patients are over sixty years of age. With current treatment regimens, survival rates amongst these, and also those younger patients who relapse, remain dismal and novel therapies are urgently required. In particular, therapies that have anti-leukaemic activity but that, unlike conventional chemotherapy, do not impair normal haemopoiesis. Principal Findings: Here we demonstrate the potent anti-leukaemic activity of the combination of the lipid-regulating drug bezafibrate (BEZ) and the sex hormone medroxyprogesterone acetate (MPA) against AML cell lines and primary AML cells. The combined activity of BEZ and MPA (B/M) converged upon the increased synthesis and reduced metabolism of prostaglandin D2 (PGD2) resulting in elevated levels of the downstream highly bioactive, anti-neoplastic prostaglandin 15-deoxy Δ12,14 PGJ2 (15d-PGJ2). BEZ increased PGD2 synthesis via the generation of reactive oxygen species (ROS) and activation of the lipid peroxidation pathway. MPA directed prostaglandin synthesis towards 15d-PGJ2 by inhibiting the PGD2 11β -ketoreductase activity of the aldo-keto reductase AKR1C3, which metabolises PGD2 to 9α11β-PGF2α. B/M treatment resulted in growth arrest, apoptosis and cell differentiation in both AML cell lines and primary AML cells and these actions were recapitulated by treatment with 15d-PGJ2. Importantly, the actions of B/M had little effect on the survival of normal adult myeloid progenitors. Significance: Collectively our data demonstrate that B/M treatment of AML cells elevated ROS and delivered the anti-neoplastic actions of 15d-PGJ2. These observations provide the mechanistic rationale for the redeployment of B/M in elderly and relapsed AML

ArDM: first results from underground commissioning

The Argon Dark Matter experiment is a ton-scale double phase argon Time Projection Chamber designed for direct Dark Matter searches. It combines the detection of scintillation light together with the ionisation charge in order to discriminate the background (electron recoils) from the WIMP signals (nuclear recoils). After a successful operation on surface at CERN, the detector was recently installed in the underground Laboratorio Subterr\'aneo de Canfranc, and the commissioning phase is ongoing. We describe the status of the installation and present first results from data collected underground with the detector filled with gas argon at room temperature.Comment: 6 pages, 3 figures, Light Detection In Noble Elements (LIDINE 2013

Status of the ArDM Experiment: First results from gaseous argon operation in deep underground environment

The Argon Dark Matter (ArDM-1t) experiment is a ton-scale liquid argon (LAr) double-phase time projection chamber designed for direct Dark Matter searches. Such a device allows to explore the low energy frontier in LAr. After successful operation on surface at CERN, the detector has been deployed underground and is presently commissioned at the Canfranc Underground Laboratory (LSC). In this paper, we describe the status of the installation and present first results on data collected in gas phase.Comment: 21 pages, 20 figure

Multi-omics bioactivity profile-based chemical grouping and read-across:a case study with Daphnia magna and azo dyes

Grouping/read-across is widely used for predicting the toxicity of data-poor target substance(s) using data-rich source substance(s). While the chemical industry and the regulators recognise its benefits, registration dossiers are often rejected due to weak analogue/category justifications based largely on the structural similarity of source and target substances. Here we demonstrate how multi-omics measurements can improve confidence in grouping via a statistical assessment of the similarity of molecular effects. Six azo dyes provided a pool of potential source substances to predict long-term toxicity to aquatic invertebrates (Daphnia magna) for the dye Disperse Yellow 3 (DY3) as the target substance. First, we assessed the structural similarities of the dyes, generating a grouping hypothesis with DY3 and two Sudan dyes within one group. Daphnia magna were exposed acutely to equi-effective doses of all seven dyes (each at 3 doses and 3 time points), transcriptomics and metabolomics data were generated from 760 samples. Multi-omics bioactivity profile-based grouping uniquely revealed that Sudan 1 (S1) is the most suitable analogue for read-across to DY3. Mapping ToxPrint structural fingerprints of the dyes onto the bioactivity profile-based grouping indicated an aromatic alcohol moiety could be responsible for this bioactivity similarity. The long-term reproductive toxicity to aquatic invertebrates of DY3 was predicted from S1 (21-day NOEC, 40 µg/L). This prediction was confirmed experimentally by measuring the toxicity of DY3 in D. magna. While limitations of this ‘omics approach are identified, the study illustrates an effective statistical approach for building chemical groups

The ArDM experiment

The aim of the ArDM project is the development and operation of a one ton double-phase liquid argon detector for direct Dark Matter searches. The detector measures both the scintillation light and the ionization charge from ionizing radiation using two independent readout systems. This paper briefly describes the detector concept and presents preliminary results from the ArDM R&D program, including a 3 l prototype developed to test the charge readout system.Comment: Proceedings of the Epiphany 2010 Conference, to be published in Acta Physica Polonica

Galaxy-M:A Galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data

BACKGROUND: Metabolomics is increasingly recognized as an invaluable tool in the biological, medical and environmental sciences yet lags behind the methodological maturity of other omics fields. To achieve its full potential, including the integration of multiple omics modalities, the accessibility, standardization and reproducibility of computational metabolomics tools must be improved significantly. RESULTS: Here we present our end-to-end mass spectrometry metabolomics workflow in the widely used platform, Galaxy. Named Galaxy-M, our workflow has been developed for both direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LC-MS) metabolomics. The range of tools presented spans from processing of raw data, e.g. peak picking and alignment, through data cleansing, e.g. missing value imputation, to preparation for statistical analysis, e.g. normalization and scaling, and principal components analysis (PCA) with associated statistical evaluation. We demonstrate the ease of using these Galaxy workflows via the analysis of DIMS and LC-MS datasets, and provide PCA scores and associated statistics to help other users to ensure that they can accurately repeat the processing and analysis of these two datasets. Galaxy and data are all provided pre-installed in a virtual machine (VM) that can be downloaded from the GigaDB repository. Additionally, source code, executables and installation instructions are available from GitHub. CONCLUSIONS: The Galaxy platform has enabled us to produce an easily accessible and reproducible computational metabolomics workflow. More tools could be added by the community to expand its functionality. We recommend that Galaxy-M workflow files are included within the supplementary information of publications, enabling metabolomics studies to achieve greater reproducibility. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13742-016-0115-8) contains supplementary material, which is available to authorized users