A non-directed approach to the differential analysis of multiple LC-MS-derived metabolic profiles

被引:62
作者
Vorst, O. [1 ]
de Vos, C. H. R. [1 ]
Lommen, A. [1 ,4 ]
Staps, R. V. [1 ]
Visser, R. G. F. [2 ]
Bino, R. J. [1 ,3 ]
Hall, R. D. [1 ,5 ]
机构
[1] Plant Res Int, NL-6700 AA Wageningen, Netherlands
[2] Lab Plant Breeding, NL-6700 AJ Wageningen, Netherlands
[3] Univ Wageningen & Res Ctr, Lab Plant Physiol, NL-6703 BD Wageningen, Netherlands
[4] RIKILT Inst Food Safety, NL-6700 AE Wageningen, Netherlands
[5] Ctr BioSyst Genom CBSG, NL-6700 AB Wageningen, Netherlands
关键词
metabolomics; spectral alignment; data mining; potato; liquid chromatography-mass spectrometry; multivariate analysis;
D O I
10.1007/s11306-005-4432-7
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
An essential element of any strategy for non-targeted metabolomics analysis of complex biological extracts is the capacity to perform comparisons between large numbers of samples. As the most widely used technologies are all based on mass spectrometry (e.g. GCMS, LCMS), this entails that we must be able to compare reliably and (semi)automatically large series of chromatographic mass spectra from which compositional differences are to be extracted in a statistically justifiable manner. In this paper we describe a novel approach for the extraction of relevant information from multiple full-scan metabolic profiles derived from LC-MS analyses. Specifically-designed software has made it possible to combine all mass peaks on the basis of retention time and m/z values only, without prior identification, to produce a data matrix output which can then be used for multivariate statistical analysis. To demonstrate the capacity of this approach, aqueous methanol extracts from potato tuber tissues of eight contrasting genotypes, harvested at two developmental stages have been used. Our results showed that it is possible to discover reproducibly discriminatory mass peaks related both to the genetic origin of the material as well as the developmental stage at which it was harvested. In addition the limitations of the approach are explored by a careful evaluation of the alignment quality.
引用
收藏
页码:169 / 180
页数:12
相关论文
共 28 条
[1]   DNA microarrays for functional plant genomics [J].
Aharoni, A ;
Vorst, O .
PLANT MOLECULAR BIOLOGY, 2002, 48 (1-2) :99-118
[2]   Potential of metabolomics as a functional genomics tool [J].
Bino, RJ ;
Hall, RD ;
Fiehn, O ;
Kopka, J ;
Saito, K ;
Draper, J ;
Nikolau, BJ ;
Mendes, P ;
Roessner-Tunali, U ;
Beale, MH ;
Trethewey, RN ;
Lange, BM ;
Wurtele, ES ;
Sumner, LW .
TRENDS IN PLANT SCIENCE, 2004, 9 (09) :418-425
[3]   Plant proteome analysis [J].
Cánovas, FM ;
Dumas-Gaudot, E ;
Recorbet, G ;
Jorrin, J ;
Mock, HP ;
Rossignol, M .
PROTEOMICS, 2004, 4 (02) :285-298
[4]   Innovation - Metabolite profiling: from diagnostics to systems biology [J].
Fernie, AR ;
Trethewey, RN ;
Krotzky, AJ ;
Willmitzer, L .
NATURE REVIEWS MOLECULAR CELL BIOLOGY, 2004, 5 (09) :763-769
[5]   Metabolite profiling for plant functional genomics [J].
Fiehn, O ;
Kopka, J ;
Dörmann, P ;
Altmann, T ;
Trethewey, RN ;
Willmitzer, L .
NATURE BIOTECHNOLOGY, 2000, 18 (11) :1157-1161
[6]   Metabolomics - the link between genotypes and phenotypes [J].
Fiehn, O .
PLANT MOLECULAR BIOLOGY, 2002, 48 (1-2) :155-171
[7]   Proteomics of Arabidopsis seed germination. A comparative study of wild-type and gibberellin-deficient seeds [J].
Gallardo, K ;
Job, C ;
Groot, SPC ;
Puype, M ;
Demol, H ;
Vandekerckhove, J ;
Job, D .
PLANT PHYSIOLOGY, 2002, 129 (02) :823-837
[8]  
GAMBOA BCC, 2002, THESIS WAGENINGEN
[9]   A functional genomics approach toward the understanding of secondary metabolism in plant cells [J].
Goossens, A ;
Häkkinen, ST ;
Laakso, I ;
Seppänen-Laakso, T ;
Biondi, S ;
De Sutter, V ;
Lammertyn, F ;
Nuutila, AM ;
Söderlund, H ;
Zabeau, M ;
Inzé, D ;
Oksman-Caldentey, KM .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (14) :8595-8600
[10]  
Hall Robert, 2002, Plant Cell, V14, P1437, DOI 10.1105/tpc.140720