An untargeted gas chromatography mass spectrometry metabolomics platform for marine polychaetes

被引:10
作者
Fernandez-Varela, R. [1 ,2 ]
Tomasi, G. [1 ]
Christensen, J. H. [1 ]
机构
[1] Univ Copenhagen, Fac Sci, Dept Plant & Environm Sci, DK-1871 Frederiksberg C, Denmark
[2] Chr Hansen AS, Assays Dept, DK-2970 Horsholm, Denmark
关键词
Marine polychaetes; Nereis virens; Derivatization; GC-MS; XCMS; Environmental metabolomics; ENVIRONMENTAL METABOLOMICS; EXTRACTION STRATEGIES; EARTHWORM RESPONSES; NMR; NORMALIZATION; H-1-NMR; SAMPLES; METABOLISM; PROTOCOL; PYRENE;
D O I
10.1016/j.chroma.2015.01.025
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The development of an appropriate extraction method for untargeted environmental metabolomic analysis of marine polychaetes could promote their use for environmental monitoring purposes. To this end, we compared four extraction methods on the marine polychaete Nereis virens both exposed to crude oil and non-exposed. XCMS was used for feature detection and preprocessing; different normalization and scaling approaches were tested; and principal component analysis (PCA) was used together with basic statistical tests to ascertain common metabolic patterns and determine the most suitable extraction method. We conclude that a two-step extraction procedure with 80:20 (v/v) methanol:water on freeze dried polychaete tissue provides the best trade-off between analysis time, and extraction efficiency and intermediate reproducibility. No definitive conclusions could be drawn about the ability of the method to discriminate controls and crude oils in actual biological replicates because the experiment was carried out by design on analytical replicates only. We show that the normalization to the sum of all the common features, and the use of a weighted least squares criterion to fit the PCA by means of scaling to the median absolute deviation (MAD) of the pooled quality control samples significantly improved the clustering of controls and crude oil exposed samples. The scaling alone led to an increase of 19% in explained variance compared to ordinary PCA. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:133 / 141
页数:9
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