Serum UPLC-MS/MS metabolic profiling in an experimental model for acute-liver injury reveals potential biomarkers for hepatotoxicity

A key interest in clinical diagnosis and pharmaceutical industry is to have a repertoire of noninvasive biomarkers to??individually or in combination??be able to infer or predict the degree of liver injury caused by pathological conditions or drugs. Metabolomics??a comprehensive study of global metabolites??has become a highly sensitive and powerful tool for biomarker discovery thanks to recent technological advances. An ultra-performance liquid chromatography/time-of-flight tandem mass spectrometry (UPLC/TOF MS/MS)-based metabolomics approach was employed to investigate sera from galactosamine-treated rats to find potential biomarkers for acute liver injury. Hepatic damage was quantified by determining serum transaminase activity and in situ liver histological lesions. Principal component analysis in combination with coefficient of correlation analysis was used for biomarker selection and identification. According to the data, serum levels of several metabolites including glucose, amino acids, and membrane lipids were significantly modified, some of them showing a high correlation with the degree of liver damage determined by histological examination of the livers. In conclusion, this study supports that UPLC-MS/MS based serum metabolomics in experimental animal models could be a powerful approach to search for biomarkers for drug- or disease-induced liver injury.     

Canonical correlation analysis of marine macrobenthos survey data

Canonical correlation analysis is applied to measurements of environmental variables and species distributions made during a survey of macrobenthos around a sewage-treatment farm drain. The implications of data reduction, necessary to enable the method to proceed, are discussed. The amount of data was reduced by discarding the rarest species, discarding species occurring at fewest stations, and including only those species and environmental variables which correlated highly with the greatest number of other variables. Only the third data-reduction scheme gave ecologically sensible results. Use of station scores on the first two canonical variates (CV1 and CV2) enabled the sampling grid to be divided into a group of nearshore stations, a group of intermediate depth, and a group of deep offshore stations. Loadings of environmental variables on the canonical variates were found to be unstable but correlations between these variables and canonical variates enabled the variates to be interpreted: CV1 as a gradient of depth and associated changes in sediment characteristics, CV2 with depth- and nutrient-related components, and CV3 as patchiness in sediment characteristics different from that normally expected with depth. Use of correlations between species and canonical variates enables definition of two major species groups, one confined to nearshore environments and a second offshore. These groups (and their sub-groups) related well to groups defined previously by hierarchical classification. It is concluded that, with careful attention to the method of data reduction, canonical correlation analysis can be an effective tool in the analysis of marine benthic survey data.     

Metabolic alterations of impaired fasting glucose by GC/MS based plasma metabolic profiling combined with chemometrics

In this paper, a new strategy for processing GC/MS based metabolic profiling data via multivariate methods was proposed, which is applied to a small pilot study of impaired fasting glucose. The data obtained from plasma samples of impaired fasting glucose patients and healthy controls were first treated by principal component analysis and partial least squares-discriminant analysis to explore the differences and discriminators of the two groups. Subsequently, correlation analyses were employed to examine the relationships between blood glucose and the discriminators or their linear combination, thus may be considered as potential biomarkers of impaired fasting glucose. The results showed that the metabolic patterns of the two groups were different. Furthermore, eleven metabolites were screened as discriminators. Levels of nine of the eleven discriminators, say lactate, 2-ketoisocaproic acid, alanine, α-hydroxyisobutyric acid, urea, phosphoric acid, α-glycerophosphoric acid, palmitic acid and stearic acid, were found to be significantly higher in impaired fasting glucose patients, while 1-monopalmitin and 1-monostearin showed the opposite trend. Correlation analysis indicated that 2-ketoisocaproic acid, stearic acid were positively, while 1-monopalmitin and 1-monostearin were negatively correlated with blood glucose. Moreover, blood glucose correlated well with the linear combination of the eleven discriminators by canonical correlation analysis. The results have demonstrated that 2-ketoisocaproic acid, stearic acid and the linear combination of the eleven discriminators may be considered as the potential biomarkers of impaired fasting glucose and the proposed method may be useful in a larger study for exploring the metabolic alterations and biomarker candidates of diseases.     

Choosing the number of principal coordinates when using CAP,the canonical analysis of principal coordinates

This study explores various options available for choosing the number of principal coordinates m in the canonical analysis of principal coordinates ‘CAP’, a useful procedure that has wide‐ranging application wherever multivariate data sets are collected or generated. Choosing too few coordinates (small m) in this constrained (i.e. hypothesis‐based) ordination procedure may lead to inadequate separation of the groups (when used as a canonical discriminant analysis) or to inadequate correlation between explanatory and response variables (when used as a canonical correlations analysis), whereas choosing too many (large m) may lead to overparameterization, resulting in overfitting of the data and spurious relationships. It is shown here that the optimum number of principal coordinates is simply the one that results in the smallest P value in the canonical analysis carried out using permutations. For data in which more than one m value results in the same minimum P value, m should be chosen from that set to be the number of principal coordinates that minimizes the leave‐one‐out residual sum of squares. This choice of m provides suitable solutions for each of the 17 case studies investigated here (which yielded 17 canonical discriminant analyses and 7 canonical correlation analyses).     

Comparative Circadian Metabolomics Reveal Differential Effects of Nutritional Challenge in the Serum and Liver

Diagnosis and therapeutic interventions in pathological conditions rely upon clinical monitoring of key metabolites in the serum. Recent studies show that a wide range of metabolic pathways are controlled by circadian rhythms whose oscillation is affected by nutritional challenges, underscoring the importance of assessing a temporal window for clinical testing and thereby questioning the accuracy of the reading of critical pathological markers in circulation. We have been interested in studying the communication between peripheral tissues under metabolic homeostasis perturbation. Here we present a comparative circadian metabolomic analysis on serum and liver in mice under high fat diet. Our data reveal that the nutritional challenge induces a loss of serum metabolite rhythmicity compared with liver, indicating a circadian misalignment between the tissues analyzed. Importantly, our results show that the levels of serum metabolites do not reflect the circadian liver metabolic signature or the effect of nutritional challenge. This notion reveals the possibility that misleading reads of metabolites in circulation may result in misdiagnosis and improper treatments. Our findings also demonstrate a tissue-specific and time-dependent disruption of metabolic homeostasis in response to altered nutrition.     

Development and validation of a UPLC/MS method for a nutritional metabolomic study of human plasma

In order to study the effect of a diet on metabolites found in body fluids such as plasma, we have developed and validated a UPLC/MS method. While methods using NMR have been well established to analyse different biological tissues, recent studies have described robust untargeted UPLC-MS methods for plasma analysis. One major concern when profiling plasma is the presence of an important quantity of proteins which have to be precipitated without any loss of metabolites prior to LC/MS analysis. The utilization of untargeted approaches in nutritional metabolomics still suffers from the lack of identification of specific biomarkers. We therefore suggest an alternative method still using a global approach but focusing at the same time on metabolites previously described in human plasma in order to detect biomarkers of metabolic dysregulations. Thus, to fulfil our objectives, analytical parameters were tested (i) the anticoagulant type for sample collection, (ii) the protein precipitation method and (iii) UPLC/MS analytical conditions. Three protein precipitation methods and two anticoagulants were tested and compared. The method utilizing blood collection on heparin and methanol precipitation was chosen for giving the most reproducible results while keeping the complexity of the sample. Finally, a validation was proposed to evaluate the stability of this analytical method applied to a large batch of samples for nutritional metabolomic studies.     

Between Metabolite Relationships: an essential aspect of metabolic change

Not only the levels of individual metabolites, but also the relations between the levels of different metabolites may indicate (experimentally induced) changes in a biological system. Component analysis methods in current 'standard' use for metabolomics, such as Principal Component Analysis (PCA), do not focus on changes in these relations. We therefore propose the concept of 'Between Metabolite Relationships' (BMRs): common changes in the covariance (or correlation) between all metabolites in an organism. Such structural changes may indicate metabolic change brought about by experimental manipulation but which are lost with standard data analysis methods. These BMRs can be analysed by the INdividual Differences SCALing (INDSCAL) method. First the BMR quantification is described and subsequently the INDSCAL method. Finally, two studies illustrate the power and the applicability of BMRs in metabolomics. The first study is about the induced plant response of cabbage to herbivory, of which BMRs are a considerable part. In the second study-a human nutritional intervention study of green tea extract-standard data analysis tools did not reveal any metabolic change, although the BMRs were considerably affected. The presented results show that BMRs can be easily implemented in a wide variety of metabolomic studies. They provide a new source of information to describe biological systems in a way that fits flawlessly into the next generation of systems biology questions, dealing with personalized responses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0316-1) contains supplementary material, which is available to authorized users.     

Microbial metabolites are associated with a high adherence to a Mediterranean dietary pattern using a 1H-NMR-based untargeted metabolomics approach

The study of biomarkers of dietary patterns including the Mediterranean diet (MedDiet) is scarce and could improve the assessment of these patterns. Moreover, it could provide a better understanding of health benefits of dietary patterns in nutritional epidemiology. We aimed to determine a robust and accurate biomarker associated with a high adherence to a MedDiet pattern that included dietary assessment and its biological effect. In this cross-sectional study, we included 56 and 63 individuals with high (H-MDA) and low (L-MDA) MedDiet adherence categories, respectively, all from the Prevención con Dieta Mediterránea trial. A ¹H-NMR-based untargeted metabolomics approach was applied to urine samples. Multivariate statistical analyses were conducted to determine the metabolite differences between groups. A stepwise logistic regression and receiver operating characteristic curves were used to build and evaluate the prediction model for H-MDA. Thirty-four metabolites were identified as discriminant between H-MDA and L-MDA. The fingerprint associated with H-MDA included higher excretion of proline betaine and phenylacetylglutamine, among others, and decreased amounts of metabolites related to glucose metabolism. Three microbial metabolites — phenylacetylglutamine, p-cresol and 4-hydroxyphenylacetate — were included in the prediction model of H-MDA (95% specificity, 95% sensitivity and 97% area under the curve). The model composed of microbial metabolites was the biomarker that defined high adherence to a Mediterranean dietary pattern. The overall metabolite profiling identified reflects the metabolic modulation produced by H-MDA. The proposed biomarker may be a better tool for assessing and aiding nutritional epidemiology in future associations between H-MDA and the prevention or amelioration of chronic diseases.     

Integrated analysis of proteomics-delineated and metabolomics-delineated hepatic metabolic responses to (−)-hydroxycitric acid in chick embryos

(−)-Hydroxycitric acid [(−)-HCA] is widely used as a nutritional supplement to control body weight and fat accumulation in animals and humans, whereas the underlying biochemical mechanism is unclear. Broiler chicken was used as a model for studies of obesity due to its natural hyperglycemia and being insulin resistant. The current study aimed to obtain a systematic view of serum metabolites and hepatic proteins and well understand the mechanism of hepatic metabolic response to (−)-HCA treatment in chick embryos. The results showed that 22, 90, and 82 of differentially expressed proteins were identified at E14d, E19d, and H1d in chick embryos treated with (−)-HCA, respectively. Meanwhile, 5, 83, and 88 of serum metabolites significantly changed at E14d, E19d, and H1d in chick embryos after (−)-HCA treatment. Bioinformatics analysis showed that the key proteins and metabolites, which were significantly altered in chick embryos treated with (−)-HCA, were mainly involved in the citrate cycle, glycolysis/gluconeogenesis, fatty acid metabolism, and pyruvate metabolism. Our data indicated that (−)-HCA treatment might promote fat metabolism via regulating the key protein expression levels and metabolite contents in the citrate cycle, glycolysis/gluconeogenesis, and oxidative phosphorylation during chicken embryonic development. These results will deepen our understanding of the mechanism of fat reduction by (−)-HCA and provide substantial information for (−)-HCA as a nutritional supplement to control body weight gain and curb obesity-related diseases.     

Predicting ligand binding residues and functional sites using multipositional correlations with graph theoretic clustering and kernel CCA

We present a new computational method for predicting ligand binding residues and functional sites in protein sequences. These residues and sites tend to be not only conserved, but also exhibit strong correlation due to the selection pressure during evolution in order to maintain the required structure and/or function. To explore the effect of correlations among multiple positions in the sequences, the method uses graph theoretic clustering and kernel-based canonical correlation analysis (kCCA) to identify binding and functional sites in protein sequences as the residues that exhibit strong correlation between the residues’ evolutionary characterization at the sites and the structure-based functional classification of the proteins in the context of a functional family. The results of testing the method on two well-curated data sets show that the prediction accuracy as measured by Receiver Operating Characteristic (ROC) scores improves significantly when multipositional correlations are accounted for.     

Milk metabolites can characterise individual differences in animal resilience to a nutritional challenge in lactating dairy goats

The aim of this study is built in two phases: to quantify the ability of novel milk metabolites to measure between-animal variability in response and recovery profiles to a short-term nutritional challenge, then to derive a resilience index from the relationship between these individual variations. At two different stages of lactation, sixteen lactating dairy goats were exposed to a 2-d underfeeding challenge. The first challenge was in late lactation, and the second was carried out on the same goats early in the following lactation. During the entire experiment period, samples were taken at each milking for milk metabolite measures. For each metabolite, the response profile of each goat was characterised using a piecewise model for describing the dynamic pattern of response and recovery profiles after the challenge relative to the start of the nutritional challenge. Cluster Analysis identified three types of response/recovery profiles per metabolite. Using cluster membership, multiple correspondence analyses (MCAs) were performed to further characterise response profile types across animals and metabolites. This MCA analysis identified three groups of animals. Further, discriminant path analysis was able to separate these groups of multivariate response/recovery profile type based on threshold levels of three milk metabolites: β-hydroxybutyrate, free glucose and uric acid. Further analyses were done to explore the possibility of developing an index of resilience from milk metabolite measures. Different types of performance response to short-term nutritional challenge can be distinguished using multivariate analyses of a panel of milk metabolites.     

Comparison of the Mantel test and alternative approaches for detecting complex multivariate relationships in the spatial analysis of genetic data

The Mantel test is widely used to test the linear or monotonic independence of the elements in two distance matrices. It is one of the few appropriate tests when the hypothesis under study can only be formulated in terms of distances; this is often the case with genetic data. In particular, the Mantel test has been widely used to test for spatial relationship between genetic data and spatial layout of the sampling locations. We describe the domain of application of the Mantel test and derived forms. Formula development demonstrates that the sum-of-squares (SS) partitioned in Mantel tests and regression on distance matrices differs from the SS partitioned in linear correlation, regression and canonical analysis. Numerical simulations show that in tests of significance of the relationship between simple variables and multivariate data tables, the power of linear correlation, regression and canonical analysis is far greater than that of the Mantel test and derived forms, meaning that the former methods are much more likely than the latter to detect a relationship when one is present in the data. Examples of difference in power are given for the detection of spatial gradients. Furthermore, the Mantel test does not correctly estimate the proportion of the original data variation explained by spatial structures. The Mantel test should not be used as a general method for the investigation of linear relationships or spatial structures in univariate or multivariate data. Its use should be restricted to tests of hypotheses that can only be formulated in terms of distances.     

老年住院患者营养不良状况分析

目的:利用简易营养评价精法(short-form mini-nutritional assessment,MNA-SF)评价住院老年患者营养状况,并探讨老年患者营养状况与躯体功能的关系。方法:选取我院老年病及内科收治的年龄≥65岁的住院患者共104例,使用MNA-SF评价患者的营养状况,根据患者年龄、性别、慢性病等情况入组营养不良患者36例,营养良好患者68例,比较两组患者的饮食习惯、躯体功能,并对营养评分与握力、步速进行相关性分析。结果:与营养良好组相比,营养不良组进食肉食次数较少(16%vs 48%, P=0.012),握力[(11.67±9.89)kg vs (20.46±9.89)kg, P0.001]及步速(0.46±0.641m/s vs 1.16±0.65m/s,P0.001)均显著降低。老年住院患者MNA-SF得分与握力及步速呈显著正相关(r=0.562, P0.001)和(r=0.600,P0.001)。结论:住院老年患者的营养状况与进食肉食次数、握力和步速相关。     

Phenolic constituents and genetic profile of Hypericum perforatum L. from India

The content of hypericins (hypericin and pseudohypericin), hyperforin, and flavonoids (rutin, hyperoside, quercitrin, and quercetin) and genetic profiles of eight accessions of Hypericum perforatum L., collected from different locations in India, have been determined. The secondary metabolite content was determined using a highly selective LC/MS/MS method. Pearson and Spearman's correlation coefficient were used to investigate the relationships between the secondary metabolites and a significant positive correlation was found between hypericin and pseudohypericin contents. Genetic profiling was undertaken using the random amplification of polymorphic DNA (RAPD) and single sequence repeat (SSR) methods. Among the 49 random primers used for the initial screening, only nine yielded polymorphic RAPD profiles. The SSR analysis shows that seven out of the 11 primers were polymorphic. There exists only a partial correlation between the chemical content and genetic profiling data among the accessions under study.     

Methylation potential associated with diet,genotype, protein,and metabolite levels in the Delta Obesity Vitamin Study

Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6–14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-014-0403-9) contains supplementary material, which is available to authorized users.     

Metabolite profiling of Douglas-fir (Pseudotsuga menziesii) field trials reveals strong environmental and weak genetic variation

The primary objective of this study was to assess metabolomics for its capacity to discern biological variation among 10 full-sib families of a Douglas-fir tree breeding population, replicated on two sites. The differential accumulation of small metabolites in developing xylem was examined through metabolite profiles (139 metabolites common to 181 individual trees) generated by gas chromatography mass spectrometry and a series of statistical analyses that incorporated family, site, and tree growth and quantitative phenotypic wood traits (wood density, microfibril angle, wood chemistry and fiber morphology). Multivariate discriminant, canonical discriminant and factor analyses and broad-sense heritabilities revealed that metabolic and phenotypic traits alike were strongly related to site, while similar associations relating to genetic (family) structure were weak in comparison. Canonical correlation analysis subsequently identified correlations between specific phenotypic traits (i.e. tree growth, fibre morphology and wood chemistry) and metabolic traits (i.e. carbohydrate and lignin biosynthetic metabolites), demonstrating a coherent relationship between genetics, metabolism, environmental and phenotypic expression in wood-forming tissue. The association between cambial metabolites and tree phenotype, as revealed by metabolite profiling, demonstrates the value of metabolomics for systems biology approaches to understanding tree growth and secondary cell wall biosynthesis in plants.     

Metabolic profiling based on LC/MS to evaluate unintended effects of transgenic rice with cry1Ac and sck genes

As a primary characteristic of substantial equivalence, the evaluation of unintended effects of genetically modified plants has been evolving into an important field of research. In this study, a metabolic profiling method for rice seeds was developed using rapid resolution liquid chromatography/quadrupole time-of-flight mass spectrometry. The analytical properties of the method, including the linearity, reproducibility, intra-day precision and inter-day precision, were investigated and were found to be satisfactory. The method was then applied to investigate the differences between transgenic rice and its native counterparts, in addition to the differences found between native rice with different sowing dates or locations. Global metabolic phenotype differences were visualized, and metabolites from different discriminated groups were discovered using multivariate data analysis. The results indicated that environmental factors played a greater role than gene modification for most metabolites, including tryptophan, 9,10,13-trihydroxyoctadec-11-enoic acid, and lysophosphatidylethanolamine 16:0. The concentrations of phytosphingosine, palmitic acid, 5-hydroxy-2-octadenoic acid and three other unidentified metabolites varied slightly due to gene modification.     

Prey use and nutritional differences between reproductive states and age classes in Atlantic spotted dolphins (Stenella frontalis) in the Bahamas

Nutritional quality of prey is a significant driver of predator foraging patterns. In mammals, nutritional needs are known to change across ontogeny and reproductive state; however, little is known about nutrition in marine mammals. For this study, we used observational data of diurnal foraging events, collected annually from 1992 to 2009, to investigate nutrition and prey use in Atlantic spotted dolphins (Stenella frontalis) on Little Bahama Bank, Bahamas, between reproductive states (lactating, pregnant, nonreproductively active [NRA]. We also investigated the impact of age class association (various calf age groups [ages 1–6], older “noncalf” juveniles, and adults) on foraging group nutrition and prey use. To obtain representative nutrient values, we measured calories, lipids, proteins, and moisture in common prey. Using nutritional values and observational data, we investigated the influence of nutritional value on prey use. Results indicated that specific nutrients were targeted by different reproductive states and age class groups. Nutritional intake of all nutrients was higher for lactating females than pregnant females, but lower than NRA females. Investigation of age group associations revealed that nutritional intake of all four nutrients was higher for noncalf than calf‐associated groups. This study represents one of the first investigations of intraspecific prey use and nutritional differences in cetaceans.