Data processing and statistical analysis of the metabolic profiles of Phaeodactylum tricornutum

Date 2021-06-08
Temporal extent 2021-06-08 -2021-10-12
Author(s) Mondeguer FlorenceORCID1
Affiliation(s) 1 : Ifremer, Dept DYNECO, Laboratoire Phycotoxines, F-44311 Nantes, France
DOI 10.17882/84209
Publisher SEANOE
Keyword(s) Metabolomics data set, UHPLC-QTOF-MS, chemometrics platform, Mass Profiler Professional (MPP) software
Abstract

Microalgae have evolved to face abiotic stresses by accumulating energy storage molecules such as lipids, which are also of interest for industries. A multidisciplinary approach was used to study the mechanisms involved in the transition from nitrogen-replete to nitrogen starvation conditions in the marine diatom. Metabolomic analysis resulted in the detection of 4267 compounds ranging from 0.1 and 2.8 kDa in size. In order to reduce the number of compounds to elucidate, the change in compound detected quantity was compared to the change in transcript abundance during the time course of the experiment. As a preliminary step, only compounds and transcripts which change in abundance compared to the control conditions are significant at least on a timepoint were retained. After this first screening, each compound pattern has been compared with each gene. In order to be as stringent as possible, only the combinations which display a significant direct correlation (|slope|=1, from 0.95 to 1.05; p>0.05). The results shown 419 compound-gene combinations which include 115 compounds. The 115 compounds were kept for further analyses and elucidation.

Licence CC-BY-NC-ND
Utilisation Formal permission induced by existence of a license. Exclusive right granted by law for a specified period of time. Data under Licence ouverte / Open licence : http://www.etalab.gouv.fr/pages/licence-ouverte-open-licence-5899923.html
Acknowledgements Author would like to thank Manoela Sibat (Phycotoxins Laboratory, IFREMER, Nantes, France) for the technical help during metabolomic analyses
Sensor metadata

Data processing and statistical analysis of the metabolic profiles were performed on an LC/MS Metabolomics Discovery Workflow using Mass Profiler Professional Software and an Agilent 1290 Infinity II LC system coupled to a high resolution time-of-flight mass spectrometer (Q-Tof 6550 iFunnel, Agilent technologies, CA, USA) equipped with a Dual Jet Stream® electrospray ionization (ESI) source (positive, negative mode) The full history (tools, parameters, input and output data files) is publicly available

Data
File Size Format Processing Access
Worflow for interpretation of UHPLC-QTOF-MS metabolomics data set performed using chemometrics platform -Localisation T:\Data QToF\FMOMIC-8\SEXTANT-SEANOE 72 MB .tar Processed data Open access
Contribution of metabolomics in the identification of transcription factors regulating the accumulation of lipids by microalgae during stress 9 MB PDF Processed data Open access
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How to cite 

Mondeguer Florence (2021). Data processing and statistical analysis of the metabolic profiles of Phaeodactylum tricornutum. SEANOE. https://doi.org/10.17882/84209