Metabolomics—The State of Art

Medicinal Plants against Viral Infections: A Review of Metabolomics Evidence for the Antiviral Properties and Potentials in Plant Sources

Most plants have developed unique mechanisms to cope with harsh environmental conditions to compensate for their lack of mobility. A key part of their coping mechanisms is the synthesis of secondary metabolites. In addition to their role in plants' defense against pathogens, they also possess therapeutic properties against diseases, and their use by humans predates written history. Viruses are a unique class of submicroscopic agents, incapable of independent existence outside a living host. Pathogenic viruses continue to pose a significant threat to global health, leading to innumerable fatalities on a yearly basis. The use of medicinal plants as a natural source of antiviral agents has been widely reported in literature in the past decades. Metabolomics is a powerful research tool for the identification of plant metabolites with antiviral potentials. It can be used to isolate compounds with antiviral capacities in plants and study the biosynthetic pathways involved in viral disease progression. This review discusses the use of medicinal plants as antiviral agents, with a special focus on the metabolomics evidence supporting their efficacy. Suggestions are made for the optimization of various metabolomics methods of characterizing the bioactive compounds in plants and subsequently understanding the mechanisms of their operation.

Non-Targeted Metabolomics Analysis Revealed the Characteristic Non-Volatile and Volatile Metabolites in the Rougui Wuyi Rock Tea (Camellia sinensis) from Different Culturing Regions

Rougui Wuyi Rock tea (WRT) with special flavor can be affected by multiple factors that are closely related to the culturing regions of tea plants. The present research adopted non-targeted metabolomics based on liquid chromatography–mass spectrometry (LC-MS) and gas chromatography–mass spectrometry (GC-MS), aroma activity value method (OAV), and chemometrics to analyze the characteristic metabolites of three Rougui WRTs from different culturing regions. The results of sensory evaluation showed that the three Rougui Wuyi Rock teas had significantly different flavor qualities, especially in taste and aroma. Rougui (RG) had a heavy and mellow taste, while cinnamon-like odor Rougui (GPRG) and floral and fruity odor Rougui (HGRG) had a thick, sweet, and fresh taste. The cinnamon-like odor was more obvious and persistent in GPRG than in RG and HGRG. HGRG had floral and fruity characteristics such as clean and lasting, gentle, and heavy, which was more obvious than in RG and GPRG. The results of principal component analysis (PCA) showed that there were significant metabolic differences among the three Rougui WRTs. According to the projection value of variable importance (VIP) of the partial least squares discriminant analysis (PLS–DA), 24 differential non-volatile metabolites were identified. The PLSR analysis results showed that rutin, silibinin, arginine, lysine, dihydrocapsaicin, etc. may be the characteristic non-volatiles that form the different taste outlines of Rougui WRT. A total of 90 volatiles, including aldehydes, alcohols, esters, and hydrocarbons, were identified from the three flavors of Rougui WRT by using GC-MS. Based on OAV values and PLS-DA analysis, a total of 16 characteristic volatiles were identified. The PLSR analysis results showed that 1-penten-3-ol, α-pinene, 2-carene, β-Pinene, dehydrolinalool, adipaldehyde, D-limonene, saffron aldehyde, and 6-methyl-5-hepten-2-one may be the characteristic volatiles that form the different aroma profile of Rougui WRT. These results provide the theoretical basis for understanding the characteristic metabolites that contribute to the distinctive flavors of Rougui WRT.

The state of the art in plant lipidomics

Lipids are a group of compounds with diverse structures that perform several important functions in plants. To unravel and better understand their in vivo functions, plant biologists have been using various lipidomic technologies including liquid-chromatography (LC)-mass spectrometry (MS). However, there are still significant challenges in LC-MS based plant lipidomics, which need to be addressed. In this review, we provide an overview of the key developments in LC-MS based lipidomic approaches to detect and identify plant lipids with emphasis on areas that can be further improved. Given that the cellular lipidome is estimated to contain hundreds of thousands of lipids,^1,2 many of the lipid structures remain to be discovered. Furthermore, the plant lipidome is considered to be significantly more complex compared to that of mammals. Recent technical developments in mass spectrometry have made the detection of novel lipids possible; hence, approaches that can be used for plant lipid discovery are also discussed.

Metabolite profiling of the post-ovulatory oocytes of the common carp, Cyprinus carpio: A 1H NMR-based metabolomics approach

A metabolomics study was conducted to investigate the molecular bases of oocyte over-ripening in common carp, Cyprinus carpio from a metabolic point of view. The ovulation was induced in fish brooders by intramuscular injection of pituitary extract and oocytes were collected four times post-ovulation with 30 min intervals. A set of 32 metabolites were identified on the NMR spectra of the oocytes, which mainly included energy-linked metabolites, amino acids, methylated metabolites and citric acid cycle (TCA) intermediates. PCA and PLS-DA models clearly separated the post ovulations times, indicating the effects of post-ovulation time on oocyte metabolome content. Based on the loading plot outputs, 15 metabolites including tryptophan, cysteine, AMP, tyrosine, valine, creatine phosphate (PCr), ATP, leucine, inosine, malate, acetate, TMAO, glucose, fumarate and lysine had more effects on the separation of post ovulation times. According to the results of metabolite profiling, the concentrations of glutamine, alanine, tryptophan, lysine and cysteine mostly significantly (P < 0.01) increased at 90 and 120 min post-ovulation. The concentrations of PCr, ATP, inosine and guanosine were relatively stable until 60 min post-ovulation, while significantly (P < 0.01) decreased at 90 and 120 min post ovulation. The TCA metabolites succinate, malate and fumarate significantly (P < 0.01) elevated at 90 and 120 min post-ovulation. AMP concentrations remained relatively unchanged until 30 min and then progressively decreased with time post ovulation (P < 0.01). The concentrations of lactate showed significant elevations at 90 and 120 min post ovulation (P < 0.01). In conclusion, the energetic potentials of the oocytes reduced with time post ovulation. There were apparent elevations in the concentrations of free amino acids, which may be associated with the onset of proteolytic activities in the post ovulatory oocytes. In addition, we found some changes in the apoptotic-related metabolites, which may support the results of previous studies regarding the oxidative stress and following apoptosis in post ovulatory oocytes of fish.

Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body?

This work will review the metabolic information that various studies have obtained in recent years on bladder cancer, with particular attention to discovering biomarkers in urine for the diagnosis and prognosis of this disease. In principle, they would be capable of complementing cystoscopy, an invasive but nowadays irreplaceable technique or, in the best case, of replacing it. We will evaluate the degree of reproducibility that the different experiments have shown in the indication of biomarkers, and a synthesis will be attempted to obtain a consensus list that is more likely to become a guideline for clinical practice. In further analysis, we will inquire into the origin of these dysregulated metabolites in patients with bladder cancer. For this purpose, it will be helpful to compare the imbalances measured in urine with those known inside tumor cells or tissues. Although the urine analysis is sometimes considered a liquid biopsy because of its direct contact with the tumor in the bladder wall, it contains metabolites from all organs and tissues of the body, and the tumor is separated from urine by the most impermeable barrier found in mammals. The distinction between the specific and systemic responses can help understand the disease and its consequences in more depth.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

Vibrio harveyi Infection Significantly Alters Amino Acid and Carbohydrate Metabolism in Whiteleg Shrimp, Litopenaeus vannamei

Vibrio harveyi is one of the pathogens that threaten the shrimp farming industry. However, metabolic changes induced by V. harveyi infection in shrimp remain unknown. In this study, we first conducted high resolution-magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR)-based metabolomics studies on gill, hepatopancreas, and haemolymph of V. harveyi-infected white leg shrimp, Litopenaeus vannamei. Using multivariate statistical analysis, we observed a clear separation between the early (3 and 9 h post-injection (hpi)) and late phases (24, 72 and 144 hpi) of the infection in all tissues. Moreover, metabolic changes in response to V. harveyi infection were faster in the haemolymph in the early phase and significantly changed in the late phase of the infection in the gills. Extensive changes were observed in the hepatopancreas, with 24 hpi being the turning point of progression from early to late phase infection in the hepatopancreas. V. harveyi infection increased the energy demand in L. vannamei and the amino acid and carbohydrate metabolism pathways also exhibited significant changes depending on the tissue. Thus, each tissue displayed different metabolic changes, depending on the progress of the infection.

Metabolomic and gene expression approaches reveal the developmental and environmental regulation of the secondary metabolism of yacón (Smallanthus sonchifolius, Asteraceae)

Acting as chemical defense or signaling compounds, secondary metabolites (SMs) play an essential role in the evolutionary success of many angiosperm plant families. However, the adaptive advantages that SMs confer, and the influence of environmental and developmental factors on SMs expression, remains poorly understood. A study of taxa endemic to the variable Andean climate, using a metabolomics approach, may provide further insight. By analyzing gene expression patterns and metabolic fingerprints, we report herein the developmental and environmental regulation of the secondary metabolism of Smallanthus sonchifolius (yacón), a medicinal Andean plant. Our results demonstrate a clear developmental stage dependent regulation of the secondary metabolism of yacón leaves wherein the metabolic diversity increases with plant age. However, environmental factors seem to regulate biosynthetic pathways, creating differences in the expression of chemical classes, pointing to an association between transcription levels of relevant genes and the relative amounts of more than 40 different metabolites. This study suggests that the secondary metabolism of yacón is regulated by a complex interplay between environmental factors and developmental stage and provides insight into the regulatory factors and adaptive roles of SMs in Andean taxa.

Genetic and chemical diversity among yacon [Smallanthus sonchifolius (Poepp. et Endl.) H. Robinson] accessions based on iPBS markers and metabolomic fingerprinting

The present study is focused on the characterization of yacon [Smallanthus sonchifolius (Poepp. et Endl.) H. Robinson] accessions from different geographic origins (Bolivia, Ecuador, and Peru) by iPBS markers and metabolomic fingerprinting. The results showed that the number of amplified polymorphic fragment levels ranged from 20 up to 27 with a level of polymorphism ranging from 80 to 100%. Five of the iPBS primers used in this study provided no specific banding pattern able to discriminate between the different yacon accessions. However, two iPBS primer pairs were able to separate Peru accessions from those of Ecuador and Bolivia. The UPLC-HRMS/MS-based metabolomic fingerprinting showed highly similar metabolomic fingerprints characterized by the accumulation of high quantities of sesquiterpene lactones and diterpenes, but no apparent geographic clustering. The present study demonstrates that yacon accessions from different geographical origins maintained ex situ (in the Czech Republic) present a rather low chemical and genetic diversity.

Untargeted LC-MS metabolomic studies of Asteraceae species to discover inhibitors of Leishmania major dihydroorotate dehydrogenase

INTRODUCTION

Interesting data about the family Asteraceae as a new source of Leishmania major dihydroorotate dehydrogenase (LmDHODH) inhibitors are presented. This key macromolecular target for parasites causing neglected diseases catalyzes the fourth reaction of the de novo pyrimidine biosynthetic pathway, which takes part in major cell functions, including DNA and RNA biosynthesis.

OBJECTIVES

We aimed to (1) determine LmDHODH inhibitor candidates, revealing the type of chemistry underlying such bioactivity, and (2) predict the inhibitory potential of extracts from new untested plant species, classifying them as active or inactive based on their LC-MS based metabolic fingerprints.

METHODS

Extracts from 150 species were screened for the inhibition of LmDHODH, and untargeted UHPLC-(ESI)-HRMS metabolomic studies were carried out in combination with in silico approaches.

RESULTS

The IC₅₀ values determined for a subset of 59 species ranged from 148 µg mL^-1 to 9.4 mg mL^-1. Dereplication of the metabolic fingerprints allowed the identification of 48 metabolites. A reliable OPLS-DA model (R² > 0.9, Q² > 0.7, RMSE_CV < 0.3) indicated the inhibitor candidates; nine of these metabolites were identified using data from isolated chemical standards, one of which-4,5-di-O-E-caffeoylquinic acid (IC₅₀ 73 µM)-was capable of inhibiting LmDHODH. The predictive OPLS model was also effective, with 60% correct predictions for the test set.

CONCLUSION

Our approach was validated for (1) the discovery of LmDHODH inhibitors or interesting starting points for the optimization of new leishmanicides from Asteraceae species and (2) the prediction of extracts from untested species, classifying them as active or inactive.

Untargeted Metabolomics Approach Reveals Differences in Host Plant Chemistry Before and After Infestation With Different Pea Aphid Host Races

The pea aphid (Acyrthosiphon pisum), a phloem-sucking insect, has undergone a rapid radiation together with the domestication and anthropogenic range expansion of several of its legume host plants. This insect species is a complex of at least 15 genetically different host races that can all develop on the universal host plant Vicia faba. However, each host race is specialized on a particular plant species, such as Medicago sativa, Trifolium pratense, or Pisum sativum, which makes it an attractive model insect to study ecological speciation. Previous work revealed that pea aphid host plants produce a specific phytohormone profile depending on the host plant – host race combination. Native aphid races induce lower defense hormone levels in their host plant than non-native pea aphid races. Whether these changes in hormone levels also lead to changes in other metabolites is still unknown. We used a mass spectrometry-based untargeted metabolomic approach to identify plant chemical compounds that vary among different host plant-host race combinations and might therefore, be involved in pea aphid host race specialization. We found significant differences among the metabolic fingerprints of the four legume species studied prior to aphid infestation, which correlated with aphid performance. After infestation, the metabolic profiles of M. sativa and T. pratense plants infested with their respective native aphid host race were consistently different from profiles after infestation with non-native host races and from uninfested control plants. The metabolic profiles of P. sativum plants infested with their native aphid host race were also different from plants infested with non-native host races, but not different from uninfested control plants. The compounds responsible for these differences were putatively identified as flavonoids, saponins, non-proteinogenic amino acids and peptides among others. As members of these compound classes are known for their activity against insects and aphids in particular, they may be responsible for the differential performance of host races on native vs. non-native host plants. We conclude that the untargeted metabolomic approach is suitable to identify candidate compounds involved in the specificity of pea aphid – host plant interactions.

Animal study of the anti-diarrhea effect and microbial diversity of dark tea produced by the Yao population of Guangxi

Chinese dark teas (CDTs) are a special type of tea traditionally consumed by ethnic minorities around the border regions of China.

Targeted Metabolomics of Xylose-Fermenting Yeasts Based on Mass Spectrometry

Mass spectrometry is a sensitive and selective analytical technique that enables detection and quantitation of low abundance compounds in a complex sample matrix. Targeted metabolomics allows for quantitative analysis of metabolites, providing kinetic information of production and consumption rates, an essential step to investigate microbial metabolism. Here, we describe a targeted metabolomics protocol for yeast samples, from sample preparation to mass spectrometry analysis, which enables the identification of metabolic fluxes after xylose consumption. Sample preparation methods were optimized for quenching of yeast metabolism followed by intracellular metabolite extraction, using cold methanol and boiling ethanol protocols. Ultrahigh performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) methods using ion pair chromatography (IPC) and hydrophilic interaction liquid chromatography (HILIC) allowed for the quantitation of 18 metabolites involved in central carbon metabolism (glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle). The protocol here described was successfully applied to quantify metabolites in Scheffersomyces stipitis, Spathaspora passalidarum, Spathaspora arborariae, and Candida tenuis samples after xylose consumption.

Liver transcriptomic and plasma metabolomic profiles of fattening lambs are modified by feed restriction during the suckling period

The increasing world population is driving demand for improved efficiency of feed resources of livestock. However, the molecular mechanisms behind various feed efficiency traits and their regulation by nutrition remain poorly understood. Here, we aimed to identify differentially expressed (DE) genes in the liver tissues of fattening Merino lambs and differences in metabolites accumulated in plasma to identify modified metabolic pathways as a consequence of milk restriction during the suckling period. Twenty-four male Merino lambs (4.81 ± 0.256 kg) were divided into 2 groups (n = 12 per dietary treatment). The first group (ad libitum, ADL) was kept permanently with the dams, whereas the other group (restricted, RES) was milk restricted. When they reached 15 kg of live body weight (LBW), all the animals were offered the same complete pelleted diet at the same level (35 g DM/kg LBW per day) to ensure no differences in dry matter intake. All the lambs were harvested when they reached 27 kg of LBW. For transcriptomic analysis, 4 liver samples from each group (8 samples in total) were selected for RNA sequencing (RNA-seq), and plasma samples from all animals (24 samples in total) were used to perform a nontargeted metabolomic analysis on a hybrid quadrupole-time-of-flight mass spectrometer coupled to an ultra-high performance liquid chromatographic system (UHPLC/QTOF-MS). Thirty-eight DE annotated genes were identified by RNA-seq, with 23 DE genes being down-regulated and 15 up-regulated in the liver of RES lambs relative to the ADL group (P < 0.10). Also, the metabolomic assay identified 38 differentially accumulated compounds (P < 0.10). In general, those genes and pathways involved in protein synthesis or protease inhibitors were down-regulated in the RES group, whereas those related to proteolytic degradation were up-regulated, thus suggesting a higher catabolism of proteins in these lambs. RES lambs showed over-expression of xenobiotic metabolism pathways, whereas those genes related to β-oxidation of fatty acids were down-regulated. According to the data obtained, early feed restriction during the suckling period of Merino lambs promoted long-term effects on both the hepatic transcriptomic profile and plasma metabolic profile, which might have modified fatty acids metabolism, catabolism of proteins, and detoxification of xenobiotics, thus reducing feed efficiency during the fattening period.

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

Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration.

Effects of Pu-erh ripened tea on hyperuricemic mice studied by serum metabolomics

To evaluate effects of Pu-erh ripened tea in hyperuricemic mice, a mouse hyperuricemia model was developed by oral administration of potassium oxonate for 7 d. Serum metabolomics, based on gas chromatography-mass spectrometry, was used to generate metabolic profiles from normal control, hyperuricemic and allopurinol-treated hyperuricemic mice, as well as hyperuricemic mice given Pu-erh ripened tea at three doses. Pu-erh ripened tea significantly lowered serum uric acid levels. Twelve potential biomarkers associated with hyperuricemia were identified. Pu-erh ripened tea and allopurinol differed in their metabolic effects in the hyperuricemic mice. Levels of glutamic acid, indolelactate, L-allothreonine, nicotinoylglycine, isoleucine, l-cysteine and glycocyamine, all involved in amino acid metabolism, were significantly changed in hyperuricemic mice treated Pu-erh ripened tea. Thus, modulating amino acid metabolism might be the primary mechanism of anti-hyperuricemia by Pu-erh ripened tea.

Amniotic fluid metabolomics and biochemistry analysis provides novel insights into the diet-regulated foetal growth in a pig model

Foetal loss and intrauterine growth restriction are major problems in mammals, but there are few effective ways in preventing it. Intriguingly, chitosan oligosaccharide (COS), a biomaterial derived from chitosan, can promote foetal survival and growth. Therefore, we have investigated how COS affects foetal survival and growth in a pig model. Fifty-two sows were divided into two treatment groups (n = 26) and fed either solely a control diet or a control diet that includes 100 mg/kg COS. Amniotic fluid and foetus samples from six sows that were of average body weight in each group were collected on gestation day 35. We applied a ¹H NMR-based metabolomics approach combined with biochemistry analysis to track the changes that occurred in the amniotic fluid of pregnant sows after COS intervention. Maternal COS inclusion had enhanced (P < 0.05) the foetal survival rate and size at 35 days. COS supplementation had both increased (P < 0.05) SOD, CAT and T-AOC activities and elevated (P < 0.05) IL-10, IgG and IgM concentrations in the amniotic fluid. Moreover, COS had affected (P < 0.05) the amniotic fluid’s lysine, citrate, glucose and hypoxanthine levels. Overall, COS inclusion induced amniotic fluid antioxidant status and metabolic profiles modifications characterising improvements in foetal survival and growth in a pig model.

The effects of thawing on the plasma metabolome: evaluating differences between thawed plasma and multi-organ samples

INTRODUCTION

Post-collection handling, storage and transportation can affect the quality of blood samples. Pre-analytical biases can easily be introduced and can jeopardize accurate profiling of the plasma metabolome. Consequently, a mouse study must be carefully planned in order to avoid any kind of bias that can be introduced, in order not to compromise the outcome of the study. The storage and shipment of the samples should be made in such a way that the freeze-thaw cycles are kept to a minimum. In order to keep the latent effects on the stability of the blood metabolome to a minimum it is essential to study the effect that the post-collection and pre-analytical error have on the metabolome.

OBJECTIVES

The aim of this study was to investigate the effects of thawing on the metabolic profiles of different sample types.

METHODS

In the present study, a metabolomics approach was utilized to obtain a thawing profile of plasma samples obtained on three different days of experiment. The plasma samples were collected from the tail on day 1 and 3, while retro-orbital sampling was used on day 5. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC TOF-MS).

RESULTS

The thawed plasma samples were found to be characterized by higher levels of amino acids, fatty acids, glycerol metabolites and purine and pyrimidine metabolites as a result of protein degradation, cell degradation and increased phospholipase activity. The consensus profile was thereafter compared to the previously published study comparing thawing profiles of tissue samples from gut, kidney, liver, muscle and pancreas.

CONCLUSIONS

The comparison between thawed organ samples and thawed plasma samples indicate that the organ samples are more sensitive to thawing, however thawing still affected all investigated sample types.

Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein "phosphoglycerate mutase 2" and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.

The potential biomarkers of drug addiction: proteomic and metabolomics challenges

Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

Metabolomics of Human Amniotic Fluid and Maternal Plasma during Normal Pregnancy

Metabolic profiles of amniotic fluid and maternal blood are sources of valuable information about fetus development and can be potentially useful in diagnosis of pregnancy disorders. In this study, we applied 1H NMR-based metabolic profiling to track metabolic changes occurring in amniotic fluid (AF) and plasma (PL) of healthy mothers over the course of pregnancy. AF and PL samples were collected in the 2nd (T2) and 3rd (T3) trimester, prolonged pregnancy (PP) until time of delivery (TD). A multivariate data analysis of both biofluids reviled a metabolic switch-like transition between 2nd and 3rd trimester, which was followed by metabolic stabilization throughout the rest of pregnancy probably reflecting the stabilization of fetal maturation and development. The differences were further tested using univariate statistics at α = 0.001. In plasma the progression from T2 to T3 was related to increasing levels of glycerol, choline and ketone bodies (3-hydroxybutyrate and acetoacetate) while pyruvate concentration was significantly decreased. In amniotic fluid, T2 to T3 transition was associated with decreasing levels of glucose, carnitine, amino acids (valine, leucine, isoleucine, alanine, methionine, tyrosine, and phenylalanine) and increasing levels of creatinine, succinate, pyruvate, choline, N,N-dimethylglycine and urocanate. Lactate to pyruvate ratio was decreased in AF and conversely increased in PL. The results of our study, show that metabolomics profiling can be used to better understand physiological changes of the complex interdependencies of the mother, the placenta and the fetus during pregnancy. In the future, these results might be a useful reference point for analysis of complicated pregnancies.

New findings on the in vivo antioxidant activity of Curcuma longa extract by an integrated (1)H NMR and HPLC-MS metabolomic approach

Curcuminoids possess powerful antioxidant activity as demonstrated in many chemical in vitro tests and in several in vivo trials. Nevertheless, the mechanism of this activity is not completely elucidated and studies on the in vivo antioxidant effects are still needed. Metabolomics may be used as an attractive approach for such studies and in this paper, we describe the effects of oral administration of a Curcuma longa L. extract (150 mg/kg of total curcuminoids) to 12 healthy rats with particular attention to urinary markers of oxidative stress. The experiment was carried out over 33 days and changes in the 24-h urine samples metabolome were evaluated by (1)H NMR and HPLC-MS. Both techniques produced similar representations for the collected samples confirming our previous study. Modifications of the urinary metabolome lead to the observation of different variables proving the complementarity of (1)H NMR and HPLC-MS for metabolomic purposes. The urinary levels of allantoin, m-tyrosine, 8-hydroxy-2'-deoxyguanosine, and nitrotyrosine were decreased in the treated group thus supporting an in vivo antioxidant effect of the oral administration of Curcuma extract to healthy rats. On the other hand, urinary TMAO levels were higher in the treated compared to the control group suggesting a role of curcumin supplementation on microbiota or on TMAO urinary excretion. Furthermore, the urinary levels of the sulphur containing compounds taurine and cystine were also changed suggesting a role for such constituents in the biochemical pathways involved in Curcuma extract bioactivity and indicating the need for further investigation on the complex role of antioxidant curcumin effects.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Investigating associations between milk metabolite profiles and milk traits of Holstein cows

In the field of dairy cattle research, it is of great interest to improve the detection and prevention of diseases (e.g., mastitis and ketosis) and monitor specific traits related to the state of health and management. During the standard milk performance test, traditional milk traits are monitored, and quality and quantity are screened. In addition to the standard test, it is also now possible to analyze milk metabolites in a high-throughput manner and to consider them in connection with milk traits to identify functionally important metabolites that can also serve as biomarker candidates. We present a study in which 190 milk metabolites and 14 milk traits of 1,305 Holstein cows on 18 commercial farms were investigated to characterize interrelations of milk metabolites between each other, to milk traits from the milk standard performance test, and to influencing factors such as farm and sire effect (half-sib structure). The effect of influencing factors (e.g., farm) varied among metabolites and traditional milk traits. The investigations of associations between metabolites and milk traits revealed groups of metabolites that show, for example, positive correlations to protein and casein, and negative correlations to lactose and pH. On the other hand, groups of metabolites jointly associated with the investigated milk traits can be identified and functionally discussed. To enable a multivariate investigation, 2 machine learning methods were applied to detect important metabolites that are highly correlated with the investigated traditional milk traits. For somatic cell score, uracil, lactic acid, and 9 other important metabolites were detected. Lactic acid has already been proposed as a biomarker candidate for mastitis in the recent literature. In conclusion, we found sets of metabolites eligible to predict milk traits, enabling the analysis of milk traits from a metabolic perspective and discussion of the possible functional background for some of the detected associations.