<i>Leishmania infantum</i> altered metabolic pathways in R <i>vs</i> SNT.

<p><i>Leishmania infantum</i> metabolic pathways with the higher divergence among the groups of parasites studied (R <i>vs</i> SNT strains). Variation of the metabolites inside the metabolic pathways are represented in green (increase), red (decrease) or black (lack of statistical significance). Those that incorporates ¹³C appeared underlined.</p

PCA models for ¹³C.

<p>PCA models for the whole data set filtered according to their presence in at leasts 50% of the QCs for the ¹³C arginine experiment. Panels: A LC-MS. 3 components. R² = 0.428. Q² = 0.107. B.- CE-MS. 2 components. R² = 0.577. Q² = 0.424.</p

Venn diagram.

<p>Venn diagram for the number of compounds identified in each technique.</p

<i>Leishmania infantum</i> altered metabolic pathways in ST <i>vs</i> SNT.

<p><i>Leishmania infantum</i> metabolic pathways with the higher divergence among the groups of parasites studied (ST <i>vs</i> SNT strains). Variation of the metabolites inside the metabolic pathways are represented in green (increase), red (decrease) or black (lack of statistical significance). Those that incorporates ¹³C appeared underlined.</p

Biochemical classification.

<p>Biochemical classification of the identified compounds per each technique expressed as percentage. Green: amines. Cyan: amino acids, peptides and conjugates. Yellow: carbohydrates. Orange: fatty acids. Light blue: glycerophospholipids. Red: ketones and aldehydes. Ochre: organic acids. Purple: purines, pyrimidines and conjugates. Pink: sphingolipids and spingoid bases. Brown: sterol and prenol lipids.</p

PCA models.

<p>PCA models for the whole data set filtered according to their presence in at leasts 50% of the QCs. Panels: A.- LC-MS. 2 components. R² = 0.62. Q² = -0.029. B.- CE-MS. 2 components. R² = 0.872. Q² = 0.694. C.- GC-MS. 2 components. R² = 0.515. Q² = 0.235. Each group is obtained from four samples, except R in CE-MS that consisted of three due to some problems during the sample treatment.</p

Compounds identified by LC-MS/MS and their characteristic fragments.

<p>Compounds identified by LC-MS/MS and their characteristic fragments.</p

METABOLÔMICA: DEFINIÇÕES, ESTADO-DA-ARTE E APLICAÇÕES REPRESENTATIVAS

Metabolomics is an emerging and promising omics approach used to understand biological mechanisms. By untargeted and targeted metabolomics analyses, metabolites are determined in biological samples (fluids, cells, tissues, etc.) by comparison of control groups with altered groups, undergoing different therapies, submitted to differing stress levels, dietary modulation, or promoted by a disease, or specific condition, etc., using sophisticated analytical techniques, and advanced data treatment and statistical analyses. In this review, the concepts involved in metabolomics studies were presented, describing in details all steps involved in the metabolomics workflow, for untargeted and targeted strategies. Finally, the potential of metabolomics is illustrated by applications in representative areas: clinical, environmental, food and nutrition, forensic toxicology, microbiology, parasitology, plants, and sports. Relevant reviews were compiled to characterize each of these areas, and a corresponding application of untargeted and targeted metabolomics were described

METABOLOMICS: DEFINITIONS, STATE-OF-THE-ART AND REPRESENTATIVE APPLICATIONS

<p></p><p>Metabolomics is an emerging and promising omics approach used to understand biological mechanisms. By untargeted and targeted metabolomics analyses, metabolites are determined in biological samples (fluids, cells, tissues, etc.) by comparison of control groups with altered groups, undergoing different therapies, submitted to differing stress levels, dietary modulation, or promoted by a disease, or specific condition, etc., using sophisticated analytical techniques, and advanced data treatment and statistical analyses. In this review, the concepts involved in metabolomics studies were presented, describing in details all steps involved in the metabolomics workflow, for untargeted and targeted strategies. Finally, the potential of metabolomics is illustrated by applications in representative areas: clinical, environmental, food and nutrition, forensic toxicology, microbiology, parasitology, plants, and sports. Relevant reviews were compiled to characterize each of these areas, and a corresponding application of untargeted and targeted metabolomics were described.</p><p></p