Metabolomics,Multiomics

Dataset Information

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Metabolomics approach to understand the resource partitioning in Chlorella during growth


ABSTRACT: We use untargeted high-resolution mass spectrometry to understand the metabolic differences at exponential and stationary growth stages using 22 Chlorella strains collected from South East Asia. Using this data, we demonstrate the use of a filtering procedure based on the SVD on the untargeted metabolite profile data, compared over two growth stages and run in four batches, and to remove structure in data related to day of sample assay. This approach preserves signal of demonstrable biological origin (strain-related variation in mass feature intensity) after minimizing the influence of batch effects. Our approach will be broadly applicable in metabolomics analysis to identify and remove batch effects. See MTBLS129 for associated study.

OTHER RELATED OMICS DATASETS IN: PRJNA125229PXD006204PXD018322PXD006154

INSTRUMENT(S): 6540 Q-TOF LC/MS (Agilent)

SUBMITTER: Shivshankar Umashankar 

PROVIDER: MTBLS193 | MetaboLights | 2016-10-03

REPOSITORIES: MetaboLights

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Publications

Coordinate Regulation of Metabolite Glycosylation and Stress Hormone Biosynthesis by TT8 in Arabidopsis.

Rai Amit A   Umashankar Shivshankar S   Rai Megha M   Kiat Lim Boon LB   Bing Johanan Aow Shao JA   Swarup Sanjay S  

Plant physiology 20160718 4


Secondary metabolites play a key role in coordinating ecology and defense strategies of plants. Diversity of these metabolites arises by conjugation of core structures with diverse chemical moieties, such as sugars in glycosylation. Active pools of phytohormones, including those involved in plant stress response, are also regulated by glycosylation. While much is known about the enzymes involved in glycosylation, we know little about their regulation or coordination with other processes. We char  ...[more]

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