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

Terahertz VRT spectroscopy of the water hexamer-d<inf>12</inf> prism: Dramatic enhancement of bifurcation tunneling upon librational excitation

Using diode laser vibration-rotation-tunneling spectroscopy near 15 Thz (500 cm−1), we have measured and assigned 142 transitions to three a-type librational subbands of the water hexamer-d12 prism. These subbands reveal dramatically enhanced (ca. 1000×) tunneling splittings relative to the ground state. This enhancement is in agreement with that observed for the water dimer, trimer, and pentamer in this same frequency region. The water prism tunneling motion has been predicted to potentially describe the motions of water in interfacial and confined environments; hence, the results presented here indicate that excitation of librational vibrations has a significant impact on the hydrogen bond dynamics in these macroscopic environments.</jats:p

MetaboLab - advanced NMR data processing and analysis for metabolomics

Background\ud Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.\ud \ud Results\ud Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.\ud \ud Conclusions\ud The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.\ud \u

Quantitative lipoprotein subclass and low molecular weight metabolite analysis in human serum and plasma by 1H NMR spectroscopy in a multilaboratory trial

We report an extensive 600 MHz NMR trial of a quantitative lipoprotein and small molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including: 20 QCs, 37 commercially sourced, paired serum and plasma samples and 2 National Institute of Science and Technology, NIST, reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the nuclear magnetic resonance, NMR, spectra. For all spectrometers, the instrument specific variance in measuring internal quality controls, QCs, was lower than the percentage described by the National Cholesterol Education Program, NCEP, criteria for lipid testing (triglycerides<2.7%, cholesterol<2.8%; LDL-cholesterol<2.8%; HDL-cholesterol<2.3%), showing exceptional reproducibility for direct quantitation of lipoproteins in both matrices. The average RSD for the 105 lipoprotein parameters in the 11 instruments was 4.6% and 3.9% for the two NIST samples while it was 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance, CV, obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small molecule quantitation with the exceptional reproducibility required for clinical and other regulatory settings

Use cases, best practice and reporting standards for metabolomics in regulatory toxicology

Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases

MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures

<p>Abstract</p> <p>Background</p> <p>One-dimensional ¹H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.</p> <p>Results</p> <p>We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of ¹H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter's metabolite identification methods.</p> <p>Conclusions</p> <p>MetaboHunter is a freely accessible, easy to use and user friendly ¹H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.</p> <p>Availability</p> <p><url>http://www.nrcbioinformatics.ca/metabohunter/</url></p

Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset

We present an approach in which the semantics of an XML language is defined by means of a transformation from an XML document model (an XML schema) to an application specific model. The application specific model implements the intended behavior of documents written in the language. A transformation is specified in a model transformation language used in the Model Driven Architecture (MDA) approach for software development. Our approach provides a better separation of three concerns found in XML applications: syntax, syntax processing logic and intended meaning of the syntax. It frees the developer of low-level syntactical details and improves the adaptability and reusability of XML applications. Declarative transformation rules and the explicit application model provide a finer control over the application parts affected by adaptations. Transformation rules and the application model for an XML language may be composed with the corresponding rules and application models defined for other XML languages. In that way we achieve reuse and composition of XML applications

Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy

This work was completed through funding provided by the BBSRC [BB/L005077/1 and BB/M019985/1] and Wellcome Trust [202952/Z/16/Z]

Metabolic changes of salicylic acid-elicited Catharanthus roseus cell suspension cultures monitored by NMR-based metabolomics

The effect of salicylic acid (SA) on the metabolic profile of Catharanthus roseus suspension cells throughout a time course (0, 6, 12, 24, 48 and 72 h after treatment) was investigated using NMR spectroscopy and multivariate data analysis. When compared to control cell lines, SA-treated cells showed a high level of sugars (glucose and sucrose) up to 48 h after treatment, followed by a dynamic change in amino acids, phenylpropanoids, and tryptamine. Additionally, one compound—2,5-dihydroxybenzoic-5-O-glucoside—was detected solely in SA-treated cells