Metabolic fingerprinting with capillary electrophoresis

García-Pérez, Isabel; Vallejo, María S.; Garcı́a, Antonia; Legido‐Quigley, Cristina; Barbas, Coral

doi:10.1016/j.chroma.2008.07.025

Cited by 75 publications

(58 citation statements)

References 88 publications

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“…Mass spectrometry is similarly employed for metabolic fingerprinting and is typically favored for its sensitivity in more global metabolic profiling applications, but generally requires upstream chromatographic separations due to the limited molecular-weight diversity of metabolites [37][38][39]. Raman and Fourier-transform infrared (FT-IR) spectroscopies have also been successfully utilized [31,40] for metabolomic studies, and capillary electrophoresis has recently been shown to provide useful data [41,42] in fingerprinting experiments.…”

Section: Metabolomics Datasetsmentioning

confidence: 99%

Multivariate Analysis in Metabolomics

Worley¹,

Powers²

2012

CMB

322

388

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Metabolomics aims to provide a global snapshot of all small-molecule metabolites in cells and biological fluids, free of observational biases inherent to more focused studies of metabolism. However, the staggeringly high information content of such global analyses introduces a challenge of its own; efficiently forming biologically relevant conclusions from any given metabolomics dataset indeed requires specialized forms of data analysis. One approach to finding meaning in metabolomics datasets involves multivariate analysis (MVA) methods such as principal component analysis (PCA) and partial least squares projection to latent structures (PLS), where spectral features contributing most to variation or separation are identified for further analysis. However, as with any mathematical treatment, these methods are not a panacea; this review discusses the use of multivariate analysis for metabolomics, as well as common pitfalls and misconceptions.

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Section: Metabolomics Datasetsmentioning

confidence: 99%

Multivariate Analysis in Metabolomics

Worley¹,

Powers²

2012

CMB

322

388

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“…(12) and thymol methyl ether (14), and the larger amount of β-phellandrene (10). Meanwhile, (-)-α-pinene (2), (+)-β-pinene (5), δ-2-carene (8) and terpinolene (11) allowed the differentiation of P. maximinoi samples. Finally, P. caribaea is differentiated from the other species by the medium contents of the volatile compounds analyzed.…”

Section: Principal Component Analysismentioning

confidence: 99%

“…6 Chemometric and bioinformatic methodologies are being extensively applied in taxonomic and metabolomic studies. [7][8][9][10][11][12][13][14] For instance, Scrivant et al 15 succeeded in delimiting the species of Bothriochloa, by studying the essential oil composition by means of GC-MS (gas chromatography-mass spectrometry). Fischedick et al 16 discriminated varieties of Cannabis by GC, using the quantitative data for monoterpenoids, sesquiterpenoids and cannabinoids.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of five pine species cultivated in Brazil based on chemometric analysis of their volatiles identified by gas chromatography-mass spectrometry

Marques¹,

Frensch²,

Zaleski³

et al. 2012

J. Braz. Chem. Soc.

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A composição dos voláteis emitidos por diferentes árvores é usada com sucesso como marcador em uma grande variedade de estudos, como a quimiotaxonomia. A caracterização dos voláteis emitidos por diferentes espécies de Pinus provou ser uma ferramenta importante para entender o processo de seleção de plantas hospedeiras por insetos herbívoros. Os voláteis dos galhos de cinco espécies de Pinus (P. caribaea, P. elliottii, P. maximinoi, P. patula e P. taeda) foram coletados por aeração e analisados por cromatografia gasosa com detector de ionização de chama (GC-FID), utilizando colunas de fase não-polar e quiral, e espectrometria de massas (GC-MS) com analisador de quadrupolo. A composição relativa foi usada para análises de componentes principais (PCA) e de agrupamento hierárquico (HCA) para a discriminação das cinco espécies.The composition of the volatiles emitted by different trees has been successfully used as a marker in a wide variety of studies, such as chemotaxonomy. Characterization of the volatiles emitted by different species of Pinus has proven to be an important tool to understand the process of host-tree selection by herbivorous insects. The volatiles present in samples of the branches of five species of Pinus (P. caribaea, P. elliottii, P. maximinoi, P. patula and P. taeda) were collected by aeration, and the contents analyzed by gas chromatography using a flame ionization detector (GC-FID), applying non-polar and chiral column phases, and mass spectrometry (GC-MS) using a quadrupole mass analyzer. The relative composition of the different volatiles was used to perform a discriminant analysis among the five pine species, by means of cluster (HCA) and principal component (PCA) analyses. Keywords: Pinus, volatiles, principal component analysis, hierarchical component analysis, chemotaxonomy IntroductionThe genus Pinus (Pinaceae) comprises 105 tree species, which are important and often dominant vegetation in large land areas of the Northern Hemisphere. 1 In addition to their wood and other products of high economic value, trees of Pinus influence ecosystems in various ways as they affect biochemical processes and hydrological regimes, and provide food and create habitat for animals. Pinus trees are cultivated in many countries, both inside and outside their natural habitats. 2 In Brazil, pine trees, mainly Pinus taeda L. and Pinus elliottii Engelmann, have been cultivated on a commercial scale for over 30 years. 3 Currently there are about 2 million hectares of commercial pine plantations, in large continuous areas and generally in stands with a narrow genetic base, Marques et al. 1757 Vol. 23, No. 9, 2012 mainly in the South and Southeast Regions. 4 The product of these plantations is mostly destined for the timber and cellulose industries. 5 Since 2001, the banded pine weevil Pissodes castaneus (De Geer, 1775), which attacks preferentially P. taeda, has become an important pest of pine trees in Brazil. In 2002, 7.6% of the trees of a Pinus taeda plantation in Cambará do Sul City (Rio Grande do Sul...

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“…Substantial effort has been devoted to the algorithm development for such a purpose (Fruetel et al 2006;García-Péreza et al 2008;Liu et al 2008;Stein and Scott 1994). As this process requires reference to a library of peak information, extracted from known chemicals measured in similar environment, we will refer to it as Pattern Matching.…”

Section: Pattern Matching -Inferring Chemical Identitymentioning

confidence: 99%