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Raw LC-ESI(-)-HRMS data of Asparagopsis armata and A. taxiformis extracts in a context of a metabolomics study on the variation of metabolites of the two algae in relation to interspecies and temporal factors

ABSTRACT: Raw data of the LC-HRMS analysis of Asparagopsis armata and A. taxiformis samples, pertaining to the publication entitled: Development of a Multiblock Metabolomics Approach to Explore Metabolite Variations of two Algae of the Genus Asparagopsis Linked to Interspecies and Temporal Factors (https://doi.org/10.1016/j.algal.2023.103138) LC-HRMS analyses were performed with a Vanquish UHPLC system from ThermoScientific (MA, USA) equipped with a Q Exactive Plus mass spectrometer with an electrospray ionization source (negative mode). MeOH are the injection solvent blanks Extraction blanks are blank samples extracted in the same way as algal samples. Pool is a set of samples for analytical drift correction (pool 1-3 and 13-15 are priming pools which are then not included in the analysis)

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Asparagopsis Taxiformis (ncbitaxon:260499) Asparagopsis Armata (ncbitaxon:31367)

SUBMITTER: Christelle Parchemin

PROVIDER: MSV000091631 | MassIVE | Tue Apr 04 08:56:00 BST 2023

REPOSITORIES: MassIVE

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Project description:Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS). This repository contains the data set from the negative ionization mode: 2 batches, 234 files (24 blanks + 26 QCs + 184 samples) in the Thermo .RAW (6.8 Go) and .mzML (18 Go) formats. The comprehensive analysis of this data set is publicly available on the Workflow4metabolomics.org e-infrastructure with two reference histories: 'W4M00002_Sacurine-comprehensive' corresponds to the preprocessing of the .mzML files, followed by signal drift and batch effect correction, normalization, filtering, statistics, and annotation of the peak table; 'W4M00001_Sacurine- statistics' starts with the peak table restricted to the 113 identified metabolites (see Roux et al. [1] for a full description and information about the annotation), and contains the statistical analysis (as described in associated publication except that the publication also describes the positive ionization mode). The intensities of the table provided in the m_sacurine.txt ISA file correspond to the peak table restricted to the 113 identified metabolites (i.e. are identical to the input of the 'W4M00001_Sacurine-statistics' history). Note that in both histories, the HU_096 sample is filtered out during the Hotelling/Quantile/MissingValue quality control sample filter, leading to 183 samples for the subsequent statistical analyzes. Notes: The 'sampling' field indicates the 9 successive weeks during which samples were collected. The 'subset' field indicates a subset of 36 files (6 blanks + 10 QCs + 20 samples) which still contain significant physiological variations (and can be used as e.g. demo or teaching material). Acknowledgements: The authors are grateful to Philippe Rocca-Serra for his help in preparing the ISA files. References: [1] Roux A, Xu Y, Heilier JF, Olivier MF, Ezan E, Tabet JC, Junot C. 2012. Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer. Anal Chem. Aug 7;84(15):6429-37. doi: 10.1021/ac300829f.

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Raw LC-ESI(-)-HRMS data of Asparagopsis armata and A. taxiformis extracts in a context of a metabolomics study on the variation of metabolites of the two algae in relation to interspecies and temporal factors

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