Metabolomics—The State of Art

Plant Metabolomics: A Characterisation of Plant Responses to Abiotic Stresses

“…The analysis, chemical characterisation and quantification of these metabolites usually involves a multidisciplinary approach, based on different analytical techniques. Metabolomics studies have been applied to different fields (Krastanov, 2010), ranging from environmental science, food science, human safety and plant biology (Bundy et al, 2008;Cevallos-Cevallos et al, 2009;Fukushima et al, 2009). The aim of the metabolomic approach is to identify a much larger possible number of metabolites to better understand the biological system under investigation.…”

Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration

“…blood plasma and serum, urine, saliva, solid tissues and cultured cells). According to the kind of sample to analyze, several approaches are used, as described in details elsewhere [18][19][20][21]. Samples are usually homogenized or pulverized into smaller particles to increase their surface area for the exposure to the extraction buffer, which is chosen in accordance to their chemical characteristics.…”

“…gas chromatography, high-performance liquid chromatography, ultra-high-performance liquid chromatography and capillary electrophoresis) are combined with compound detection techniques, such as mass spectrometry (MS) or nuclear magnetic resonance (NMR). Each detection or separation method has different resolution, sensitivity and technological limitations in identifying metabolites, and it is chosen in accordance to the chemical and physical characteristic of each sample and to the kind of analysis to be performed (targeted or untargeted) [12,15,18]. MS is the most widely applied technique, as it allows reliable metabolite identification, particularly when used in tandem with chromatographic separation methods so as to enhance its mass-resolving capabilities.…”

“…Although several literature about metabolomic data production and analysis techniques exist [3][4][5][15][16][17][18][19][20][21][22][23], to the best of our knowledge, a comprehensive review illustrating the available tools for the analysis and integration of metabolomic data with other 'omics' data has not been reported yet. Here, we describe and compare four tools (MetaCore TM , MetaboAnalyst, InCroMAP and 3Omics [24][25][26][27]), which we selected among the several ones currently available for metabolomic data analysis and integration (Table 1 have not yet overcome the previous ones.…”

Metabolomics applied in bioenergy

“…For comparison of biological groups (e.g., control and treated samples, mutant and wild type), a wealth of statistical and machine learning algorithms using unsupervised (e.g., hierarchical clustering and principal component analysis) or supervised (e.g., ANOVA, partial least squares) methods enable comprehensive identification of variables (metabolic features) in order to capture the dimension of variation among the entire dataset ( Figure 1E) [69,70,74,80,81]. After this, data visualization tools allow for the simplification and incorporation of metabolic data into biochemical pathways, facilitating interpretation ( Figure 1E).…”