Chemometric evaluation of Saccharomyces cerevisiae metabolic profiles using LC–MS

Farrés, Mireia; Piña, Benjamı́n; Tauler, Romà

doi:10.1007/s11306-014-0689-z

Cited by 54 publications

(52 citation statements)

References 49 publications

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“…37 In a very efficient way PLS-DA estimates the best linear combinations of the independent original X-values (latent variables, LV), which optimally correlate with the observed changes of the dependent variable, y (set of binary variables describing the categories of X). 38 The computed score plots give an idea of similarity among the samples whereas the loading plots show the importance of each variable in the modeling. 39 To obtain the PLS-DA model, the second derivative was applied to the spectra (as in the PCA procedure) and the OSC (orthogonal signal correction) algorithm 40 was utilized to eliminate unnecessary information from the model.…”

Section: Ftir Data Treatment Model and Validationmentioning

confidence: 99%

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confidence: 99%

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Irrigation and Light Access Effects on Coffea arabica L. Leaves by FTIR‑Chemometric Analysis

Sanchez¹,

Pauli²,

Scheel³

et al. 2017

J. Braz. Chem. Soc.

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Coffee bean chemical compositions has been extensively studied. However, there is a small amount of research on other parts of the coffee plant, including leaves. Fourier transform infrared (FTIR) spectral profiles of Coffea arabica L. cv. IAPAR 59 leaf extracts from a simplex-centroid design were studied by principal component analysis (PCA) to evaluate the effect of solvent extractor on its metabolites. PCA indicated that the extractor solvents containing ethanol were the most suitable for this study. FTIR spectra in conjunction with orthogonal signal correction and partial least squares-discrimination analysis (OSC-PLS-DA) were used to classify and discriminate the leaves of irrigated and non-irrigated plants by bands related to carbohydrates, amino acids and lipids. Leaves receiving different intensities of solar radiation were also discriminated by bands corresponding to caffeine, carbohydrates and lipids. FTIR spectral profile analyzed with chemometric tools showed to be a useful, powerful and simple procedure to discriminate coffee leaves collected from different microclimate conditions. Keywords:Coffea arabica leaves, simplex-centroid design, FTIR spectroscopy, chemometric analysis, environmental conditions IntroductionThe coffee plant is a woody, perennial, evergreen and dicotyledon species that belongs to the Rubiaceae family. 1,2 Among several species of the genus Coffea, two are considered economically important, i.e. Coffea canephora Pierre (Robusta coffee) and Coffea arabica L. (Arabica coffee). 3 The latter species represents 70% of world coffee production 2 due to finer flavor and aroma, and therefore is more consumed than Robusta. 4 Coffee is one of the most consumed beverages in the world 5,6 and an important raw material of the international trade. 4 Thus, due to its importance, the chemical composition of coffee beans has been extensively studied. However, there is relatively little research carried out on metabolites in other coffee plant parts, including the leaves.7-11 Phenolic compounds found in the coffee leaves 7 have been shown to be potentially beneficial for health, although the influence of consumption of these compounds on the human body requires further research. Other metabolite groups are found in coffee leaves, such as alkaloids, 12 several carbohydrates 13,14 and lipids 9 among others.Plant metabolites are susceptible to environmental changes and their responses can be evaluated by metabolomics analysis. 15 In periods of drought or excessive sun exposure, environmental stress can affect physiological processes in plants owing to their necessity to adapt to the new situation. In excess, these conditions can affect metabolic activities such as photosynthesis and growth rate modifying carbohydrate levels and protein synthesis. [16][17][18][19][20] In coffee plants, these changes may influence the metabolic quantities and consequently, the coffee bean quality. 9,21 Information about chemical modifications in coffee Sanchez et al. 169 Vol. 29, No. 1, 2018 leaves subjecte...

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Section: Ftir Data Treatment Model and Validationmentioning

confidence: 99%

mentioning

confidence: 99%

Irrigation and Light Access Effects on Coffea arabica L. Leaves by FTIR‑Chemometric Analysis

Sanchez¹,

Pauli²,

Scheel³

et al. 2017

J. Braz. Chem. Soc.

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“…MCR-ALS has been applied to the resolution of elution/concentration and mass spectra profiles for the different components existing in complex cell lipid mixtures analyzed by chromatographic methods [14]. Recently, it has also been applied successfully to resolve complex omics profiling problems, such as in lipidomics [18,19] and metabolomics [20] studies.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the effects of As(III) treatment on cyanobacteria lipidomic profiles by LC-MS and MCR-ALS

et al. 2016

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Cyanobacteria are a group of photosynthetic, nitrogen-fixing bacteria present in a wide variety of habitats such as freshwater, marine, and terrestrial ecosystems. In this work, the effects of As(III), a major toxic environmental pollutant, on the lipidomic profiles of two cyanobacteria species (Anabaena and Planktothrix agardhii) were assessed by means of a recently proposed method based on the concept of regions of interest (ROI) in liquid chromatography mass spectroscopy (LC-MS) together with multivariate curve resolution alternating least squares (MCR-ALS). Cyanobacteria were exposed to two concentrations of As(III) for a week, and lipid extracts were analyzed by ultrahigh-performance liquid chromatography/time-of-flight mass spectrometry in full scan mode. The data obtained were compressed by means of the ROI strategy, and the resulting LC-MS data sets were analyzed by the MCR-ALS method. Comparison of profile peak areas resolved by MCR-ALS in control and exposed samples allowed the discrimination of lipids whose concentrations were changed due to As(III) treatment. The tentative identification of these lipids revealed an important reduction of the levels of some galactolipids such as monogalactosyldiacylglycerol, the pigment chlorophyll a and its degradation product, pheophytin a, as well as carotene compounds such as 3-hydroxycarotene and carotene-3,3'-dione, all of these compounds being essential in the photosynthetic process. These results suggested that As(III) induced important changes in the composition of lipids of cyanobacteria, which were able to compromise their energy production processes. Graphical abstract Steps of the proposed LC-MS + MCR-ALS procedure.

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“…MCR-ALS is used in a wide variety of applications as, for instance, the resolution of overlapped chromatographic peaks in environmental samples. MCR-ALS has been recently proposed as an alternative approach to detect potential biomarkers in untargeted metabolomics studies [10]. MCR-ALS decomposes the experimental LC-MS data matrix into their factor contributions which can be assigned to the chromatographic elution profiles and to the mass spectra of each resolved component.…”

Section: Introductionmentioning

confidence: 99%

“…The main difference between these two approaches lies in peak detection and resolution. While XCMS identifies each feature characterized by its retention time and a unique m/z value, MCR-ALS resolves mathematical components characterized by their elution profiles and mass spectra (with more than one possible MS feature assigned to the same elution profile) [6,10]. With the aim of comparing these two approaches, in the present work, the same metabolomic data set was processed by means of XCMS and by MCR-ALS, and further evaluated by using other chemometric methods for exploration and discrimination purposes.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of changes induced in rice metabolome by Cd and Cu exposure using LC-MS with XCMS and MCR-ALS data analysis strategies

et al. 2015

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The comprehensive analysis of untargeted metabolomics data acquired using LC-MS is still a major challenge. Different data analysis tools have been developed in recent years such as XCMS (various forms (X) of chromatography mass spectrometry) and multivariate curve resolution alternating least squares (MCR-ALS)-based strategies. In this work, metabolites extracted from rice tissues cultivated in an environmental test chamber were subjected to untargeted full-scan LC-MS analysis, and the obtained data sets were analyzed using XCMS and MCR-ALS. These approaches were compared in the investigation of the effects of copper and cadmium exposure on rice tissue (roots and aerial parts) samples. Both methods give, as a result of their application, the whole set of resolved elution and spectra profiles of the extracted metabolites in control and metal-treated samples, as well as the values of their corresponding chromatographic peak areas. The effects caused by the two considered metals on rice samples were assessed by further chemometric analysis and statistical evaluation of these peak area values. Results showed that there was a statistically significant interaction between the considered factors (type of metal of treatment and tissue). Also, the discrimination of the samples according to both factors was possible. A tentative identification of the most discriminant metabolites (biomarkers) was assessed. It is finally concluded that both XCMS- and MCR-ALS-based strategies provided similar results in all the considered cases despite the completely different approaches used by these two methods in the chromatographic peak resolution and detection strategies. Finally, advantages and disadvantages of using these two methods are discussed. Graphical Abstract Summary of the workflow for untargeted metabolomics using the compared approaches.

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Chemometric evaluation of Saccharomyces cerevisiae metabolic profiles using LC–MS

Cited by 54 publications

References 49 publications

Irrigation and Light Access Effects on Coffea arabica L. Leaves by FTIR‑Chemometric Analysis

Irrigation and Light Access Effects on Coffea arabica L. Leaves by FTIR‑Chemometric Analysis

Assessment of the effects of As(III) treatment on cyanobacteria lipidomic profiles by LC-MS and MCR-ALS

Evaluation of changes induced in rice metabolome by Cd and Cu exposure using LC-MS with XCMS and MCR-ALS data analysis strategies

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