BackgroundBioinformatic tools for the enrichment of ‘omics’ datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined.ResultsAn exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard’s distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites.ConclusionsWe have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.Electronic supplementary materialThe online version of this article (10.1186/s12859-017-2006-0) contains supplementary material, which is available to authorized users.
Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified into four sex-matched groups by their BMI [non-obese versus morbid obese] and the increased risk of developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] was analyzed by LC- and FIA-ESI-MS/MS-driven metabolomic approaches. Altered levels of [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: R=-0.56, p=0.0003; lysoPC C18:1: R=-0.61, p=0.0001; lysoPC C18:2 R=-0.64, p<0.0001]. Several amino acids were biomarkers of risk of diabetes onset associated to obesity. For instance, glutamate significantly associated with fasting insulin [R=0.5, p=0.0019] and HOMA-IR [R=0.46, p=0.0072], while glycine showed negative associations [fasting insulin: R=-0.51, p=0.0017; HOMA-IR: R=-0.49, p=0.0033], and the branched chain amino acid valine associated to prediabetes and insulin resistance in a BMI-independent manner [fasting insulin: R=0.37, p=0.0479; HOMA-IR: R=0.37, p=0.0468]. Minority sphingolipids including specific [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, hence deserving attention as potential targets for early diagnosis or therapeutic intervention.
28Stress and welfare are important factors to animal production in a context of growing production 29 optimization and scrutiny by the general public. In a context in which animal and human health are 30 intertwined aspects of the one-health concept it is of utmost importance to define markers for stress 31 and welfare. These are important tools for producers, retailers, regulatory agents and ultimately 32 consumers to effectively monitor and assess the welfare state of production animals. Proteomics is 33 the science that studies the proteins existing in a given tissue or fluid. In this review we address this
Versican is a hyaluronan-binding, extracellular chondroitin sulfate proteoglycan produced by several tumor types, including malignant melanoma, which exists as four different splice variants. The short V3 isoform contains the G1 and G3 terminal domains of versican that may potentially interact directly or indirectly with the hyaluronan receptor CD44 and the EGFR, respectively. We have previously described that overexpression of V3 in MeWo human melanoma cells markedly reduces tumor cell growth in vitro and in vivo. In this study we have investigated the signaling mechanism of V3 by silencing the expression of CD44 in control and V3-expressing melanoma cells. Suppression of CD44 had the same effects on cell proliferation and cell migration than those provoked by V3 expression, suggesting that V3 acts through a CD44-mediated mechanism. Furthermore, CD44-dependent hyaluronan internalization was blocked by V3 expression and CD44 silencing, leading to an accumulation of this glycosaminoglycan in the pericellular matrix and to changes in cell migration on hyaluronan. Furthermore, ERK1/2 and p38 activation after EGF treatment were decreased in V3-expressing cells suggesting that V3 may also interact with the EGFR through its G3 domain. The existence of a EGFR/ErbB2 receptor complex able to interact with CD44 was identified in MeWo melanoma cells. V3 overexpression resulted in a reduced interaction between EGFR/ErbB2 and CD44 in response to EGF treatment. Our results indicate that the V3 isoform of versican interferes with CD44 and the CD44-EGFR/ErbB2 interaction, altering the signaling pathways, such as ERK1/2 and p38 MAPK, that regulate cell proliferation and migration.Versican belongs to the family of the large chondroitin sulfate proteoglycans located within the extracellular matrix (ECM) 5 (1, 2). Overproduction of versican is a common feature of several tumor types and it is usually related to poor prognosis (3-10). Versican has been postulated to contribute to the proliferative, adhesive and migratory state of tumor cells, as well as being an important modulator of tumor cell attachment to the interstitial stromal matrix of the tumor. This wide range of functions has been attributed to its ability to interact with other extracellular matrix and cell surface components through its three structural domains: the N-terminal region (G1 domain) that binds hyaluronan (HA), the central G2 domain that carries the glycosaminoglycan chains (GAG-␣ and GAG-) and the C-terminal globular region (G3 domain) that interacts with simple carbohydrates, glycosaminoglycans, and other proteins such as tenascin. This latter domain also contains two epidermal growth factor (EGF)-like repeats (11)(12)(13)(14). In mammals, versican appears as four possible spliced variants (12, 15). V0 contains G1, G2 (GAG-␣ and GAG-), and G3 domains; V1 contains G1, G2 (GAG-), and G3 domains; V2 contains G1, G2 (GAG-␣), and G3 domain; and V3 lacks any GAG subdomain and only contains G1 and G3 domains. Despite the loss of the GAG chains, the V3 isoform ...
BackgroundThe objective assessment of animal stress and welfare requires proper laboratory biomarkers. In this work, we have analyzed the changes in serum composition in gilts after switching their housing, from pen to individual stalls, which is generally accepted to cause animal discomfort.ResultsBlood and saliva samples were collected a day before and up to four days after changing the housing system. Biochemical analyses showed adaptive changes in lipid and protein metabolism after the housing switch, whereas cortisol and muscular markers showed a large variability between animals. 2D-DIGE and iTRAQ proteomic approaches revealed variations in serum protein composition after changing housing and diet of gilts. Both techniques showed alterations in two main homeostatic mechanisms: the innate immune and redox systems. The acute phase proteins haptoglobin, apolipoprotein A-I and α1-antichymotrypsin 3, and the antioxidant enzyme peroxiredoxin 2 were found differentially expressed by 2D-DIGE. Other proteins related to the innate immune system, including lactotransferrin, protegrin 3 and galectin 1 were also identified by iTRAQ, as well as oxidative stress enzymes such as peroxiredoxin 2 and glutathione peroxidase 3. Proteomics also revealed the decrease of apolipoproteins, and the presence of intracellular proteins in serum, which may indicate physical injury to tissues.ConclusionsHousing of gilts in individual stalls and diet change increase lipid and protein catabolism, oxidative stress, activate the innate immune system and cause a certain degree of tissue damage. We propose that valuable assays for stress assessment in gilts may be based on a score composed by a combination of salivary cortisol, lipid metabolites, innate immunity and oxidative stress markers and intracellular proteins.Electronic supplementary materialThe online version of this article (doi:10.1186/s12917-016-0887-1) contains supplementary material, which is available to authorized users.
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