Visceral Adipose Tissue Phospholipid Signature of Insulin Sensitivity and Obesity.

Alterations in visceral adipose tissue (VAT) are closely linked to cardiometabolic abnormalities. The aim of this work is to define a metabolic signature in VAT of insulin resistance (IR) dependent on, and independent of, obesity. An untargeted UPLC-Q-Exactive metabolomic approach was carried out on the VAT of obese insulin-sensitive (IS) and insulin-resistant subjects (N = 11 and N = 25, respectively) and nonobese IS and IR subjects (N = 25 and N = 10, respectively). The VAT metabolome in obesity was defined among other things by changes in the metabolism of lipids, nucleotides, carbohydrates, and amino acids, whereas when combined with high IR, it affected the metabolism of 18 carbon fatty acyl-containing phospholipid species. A multimetabolite model created by glycerophosphatidylinositol (18:0); glycerophosphatidylethanolamine (18:2); glycerophosphatidylserine (18:0); and glycerophosphatidylcholine (18:0/18:1), (18:2/18:2), and (18:2/18:3) exhibited a highly predictive performance to identify the metabotype of "insulin-sensitive obesity" among obese individuals [area under the curve (AUC) 96.7% (91.9-100)] and within the entire study population [AUC 87.6% (79.0-96.2)]. We demonstrated that IR has a unique and shared metabolic signature dependent on, and independent of, obesity. For it to be used in clinical practice, these findings need to be validated in a more accessible sample, such as blood.

Characterization of Metabolomic Profile Associated with Metabolic Improvement after Bariatric Surgery in Subjects with Morbid Obesity.

The exact impact of bariatric surgery in metabolically "healthy" (MH) or "unhealthy" (MU) phenotypes for the study of the metabolic improvement is still unknown. We applied an untargeted LC-ESI-TripleTOF-MS-driven metabolomics approach in serum samples from 39 patients with morbid obesity (MH and MU) 1, 3, and 6 months after bariatric surgery. Multiple factor analysis, along with correlation and enrichment analyses, was carried out to distinguish those metabolites associated with metabolic improvement. Hydroxypropionic acids, medium-/long-chain hydroxy fatty acids, and bile acid glucuronides were the most discriminative biomarkers of response between MH and MU phenotypes. Hydroxypropionic (hydroxyphenyllactic-related) acids, amino acids, and glycerolipids were the most significant clusters of metabolites altered after bariatric surgery in MU ( p < 0.001). After surgery, MU and MH changed toward a common metabolic state 3 months after surgery. We observed a negative correlation with changes in waist circumference and cholesterol levels with metabolites of lipid metabolism. Glycemic variables were correlated with hexoses, which, in turn, correlated with gluconic acid and amino acid metabolism. Finally, we noted that hydroxyphenyllactic acid was associated with amino acid and lipid metabolism. Microbial metabolism of amino acid and BA glucuronidation pathways may be the key points of metabolic rearrangement after surgery.

Metabotypes of response to bariatric surgery independent of the magnitude of weight loss.

OBJECTIVE: Bariatric surgery is considered the most efficient treatment for morbid obesity and its related diseases. However, its role as a metabolic modifier is not well understood. We aimed to determine biosignatures of response to bariatric surgery and elucidate short-term metabolic adaptations. METHODS: We used a LC- and FIA-ESI-MS/MS approach to quantify acylcarnitines, (lyso)phosphatidylcholines, sphingomyelins, amino acids, biogenic amines and hexoses in serum samples of subjects with morbid obesity (n = 39) before and 1, 3 and 6 months after bariatric surgery. K-means cluster analysis allowed to distinguish metabotypes of response to bariatric surgery. RESULTS: For the first time, global metabolic changes following bariatric surgery independent of the baseline health status of the subjects have been revealed. We identify two metabolic phenotypes (metabotypes) at the interval 6 months-baseline after surgery, which presented differences in the levels of compounds of urea metabolism, gluconeogenic precursors and (lyso)phospholipid particles. Clinically, metabotypes were different in terms of the degree of improvement in insulin resistance, cholesterol, low-density lipoproteins and uric acid independent of the magnitude of weight loss. CONCLUSIONS: This study opens new perspectives and new hypotheses on the metabolic benefits of bariatric surgery and understanding of the biology of obesity and its associated diseases.

Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes.

This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity ( n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9-91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results.

Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

BACKGROUND: Bioinformatic 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. RESULTS: An 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. CONCLUSIONS: We 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.

Detailed characterisation of STC-1 cells and the pGIP/Neo sub-clone suggests the incretin hormones are translationally regulated.

STC-1 is a heterogeneous plurihormonal cell line producing several prominent gut peptide hormones. pGIP/Neo is a genetically selected sub-clone of STC-1 with augmented levels of glucose-dependent insulinotropic peptide (GIP). Morphometric parameters, hormone concentrations, mRNA transcripts, hormone immunocytochemistry and nutrient utilisation/production of these two cell lines were compared. Proglucagon-derived peptides (Glucagon-like peptide-1 (GLP-1) and - 2(GLP-2)) were lower in sub-clone cells than progenitor cells. High Content Analysis found altered intracellular GLP-1, GIP, cholecystokinin (CCK) and peptide YY (PYY) levels and differing hormone co-localisation. The proportion pGIP/Neo cells containing GIP immunoreactivity (82%) was greater than STC-1 (65%), as were the proportion with 'GIP only', 'GLP-1+GIP' or 'GIP+PYY' immunoreactivity. Most surprisingly mRNA transcripts of the proglucagon and GIP genes were inversely correlated to the levels of their translated peptides. This strongly suggests that proglucagon and GIP are encoded on 'translationally regulated genes' - a characteristic possessed by other endocrine hormones. Metabolomic profiling revealed differences in cellular nutrient utilisation/production and that under normal culture conditions both cell lines exhibit signs of overflow metabolism. These studies provide an insight into the metabolism and properties of these valuable cells, suggesting for the first time that incretin hormone genes are translationally regulated.

Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes.

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.

Biochemical and proteomic analyses of the physiological response induced by individual housing in gilts provide new potential stress markers.

BACKGROUND: The 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. RESULTS: Blood 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. CONCLUSIONS: Housing 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.

Concentration and pattern changes of porcine serum apolipoprotein A-I in four different infectious diseases.

Apolipoprotein A-I (Apo A-I) is a major protein in lipid/lipoprotein metabolism and decreased serum levels have been observed in many species in response to inflammatory and infectious challenges. Little is known about the porcine homologue, therefore in this work we have characterized it through biochemical and proteomic techniques. In 2DE, porcine serum Apo A-I is found as three spots, the two more acidic ones corresponding to the mature protein, the more basic spot to the protein precursor. Despite high sequence coverage in LC-MS/MS, we did not find a sequence or PTM difference between the two mature protein species. Besides this biochemical characterization, we measured overall levels and relative species abundance of serum Apo A-I in four different viral and bacterial porcine infectious diseases. Lower overall amounts of Apo A-I were observed in Salmonella typhimurium and Escherichia coli infections. In the 2DE protein pattern, an increase of the protein precursor together with a lower level of mature protein species were detected in the porcine circovirus type 2-systemic disease and S. typhimurium infection. These results reveal that both the porcine serum Apo A-I concentration and the species pattern are influenced by the nature of the infectious disease.

Proteomics on porcine haptoglobin and IgG/IgA show protein species distribution and glycosylation pattern to remain similar in PCV2-SD infection.

Haptoglobin (Hp) and immunoglobulins are plasma glycoproteins involved in the immune reaction of the organism after infection and/or inflammation. Porcine circovirus type 2-systemic disease (PCV2-SD), formerly known as postweaning multisystemic wasting syndrome (PMWS), is a globally spread pig disease of great economic impact. PCV2-SD affects the immunological system of pigs causing immunosuppression. The aim of this work was to characterize the Hp protein species of healthy and PCV2-SD affected pigs, as well as the protein backbone and the glycan chain composition of porcine Hp. PCV2-SD affected pigs had an increased overall Hp level, but it did not affect the ratio between Hp species. Glycoproteomic analysis of the Hp ß subunits confirmed that porcine Hp is N-glycosylated and, unexpectedly, O-glycosylated, a PTM that is not found on Hp from healthy humans. The glyco-profile of porcine IgG and IgA heavy chains was also characterized; decreased levels of both proteins were found in the investigated group of PCV2-SD affected pigs. Obtained results indicate that no significant changes in the N- and O-glycosylation patterns of these major porcine plasma glycoproteins were detectable between healthy and PCV2-SD affected animals. BIOLOGICAL SIGNIFICANCE: PCV2-SD is a disease of great economic importance for pig production, characterized by a complex response of the immune system. In the search of a better diagnostic/prognostic marker for porcine PCV2-SD, extensive analyses of the Hp protein backbone and the glycan chains were thoroughly analyzed by various techniques. This resulted in detection and confirmation of Hp O-glycosylation and the glyco-profiling of porcine IgG and IgA. The N- and O-glycosylation of these major porcine plasma glycoproteins appears to be not affected by PCV2-SD infection. Interestingly, these data suggest that this viral infection, which significantly affects the immune responses of the host, leaves the biosynthetic glycosylation processes in the liver and immune cells unaffected. Lack of PTM changes is in contrast to findings in humans where for both proteins pattern changes have been reported in several chronic and inflammatory diseases. This underlines the importance of studying species in detail and not reaching to conclusions by analogy. Furthermore, since Hp is usually quantified by immunoassays in clinical routine analyses, our findings indicate that no bias in Hp determination capabilities due to an altered carbohydrate pattern is to be expected.

Proteomic analysis reveals oxidative stress response as the main adaptative physiological mechanism in cows under different production systems.

Three groups of cows representing three ranges of welfare in the production system were included in the study: two groups of Bruna dels Pirineus beef cattle maintained under different management systems (good and semiferal conditions) and a group of Alberes cows, a breed that lives in the mountains (hardest conditions). In order to identify new stress/welfare biomarkers, serum from Bruna cows living in both environments was subjected to DIGE labelling, two-dimensional electrophoresis and MALDI-MS or ion trap MS. Identification was achieved for 15 proteins, which mainly belonged to three biological functions, the oxidative stress pathway (glutathione peroxidase (GPx) and paraoxonase (PON-1)), the acute phase protein family (Heremans Schmid glycoprotein alpha2 (α2-HSG)) and the complement system. Biological validation included the Alberes breed. GPx and PON-1 were validated by an enzymatic assay and found to be higher and lower, respectively, in cows living in hard conditions. α2-HSG was validated by ELISA and found to be reduced in hard conditions. Other biomarkers of the redox status were also altered by living conditions: protein carbonyl content, superoxide dismutase (SOD) and glutathione reductase (GR). Our results show that changes in the redox system are the main adaptation of cows living in challenging environmental conditions.

Role of versican V0/V1 and CD44 in the regulation of human melanoma cell behavior.

Versican is a hyaluronan-binding, large extracellular matrix chondroitin sulfate proteoglycan whose expression is increased in malignant melanoma. Binding to hyaluronan allows versican to indirectly interact with the hyaluronan cell surface receptor CD44. The aim of this work was to study the effect of silencing the large versican isoforms (V0 and V1) and CD44 in the SK-mel-131 human melanoma cell line. Versican V0/V1 or CD44 silencing caused a decrease in cell proliferation and migration, both in wound healing assays and in Transwell chambers. Versican V0/V1 silencing also caused an increased adhesion to type I collagen, laminin and fibronectin. These results support the proposed role of versican as a proliferative, anti-adhesive and pro-migratory molecule. On the other hand, CD44 silencing caused a decrease in cell adhesion to vitronectin, fibronectin and hyaluronan. CD44 silencing inhibited the binding of a FITC-hyaluronan complex to the cell surface and its internalization into the cytoplasm. Our results indicate that both versican and CD44 play an important role regulating the behavior of malignant melanoma cells.

V3 versican isoform alters the behavior of human melanoma cells by interfering with CD44/ErbB-dependent signaling.

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.

Enrichment of low-abundance proteins from bovine and porcine serum samples for proteomic studies.

One of the main applications of serum proteomics is the identification of new biomarkers for animal disease or animal production. However, potential obstacles to these studies are the poor performance of affinity serum depletion methods based on human antigens when using animal samples, and loss of minor serum components bound to albumin and other proteins. In the present study, we have analyzed the efficiency and reproducibility of the ProteoMiner® beads with bovine and porcine serum samples, and compared to a traditional immunoaffinity-based albumin and IgG depletion system specific for human samples. The ProteoMiner kit is based on the use of a combinatorial peptide binding library and intends to enrich low-abundance proteins.