Characterization of ankylosing spondylitis and rheumatoid arthritis using <Superscript>1</Superscript>H NMR-based metabolomics of human fecal extracts

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by ¹H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by ¹H NMR metabolomics.

     

Variation of the microbiota and metabolome along the canine gastrointestinal tract

Introduction

The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.

Objective

To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.

Methods

Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.

Results

Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.

Conclusion

The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Characterizing alternative feeds for rainbow trout (<Emphasis Type="Italic">O. mykiss</Emphasis>) by <Superscript>1</Superscript>H NMR metabolomics

Introduction

Fish feed formulations are constantly evolving to improve the quality of diets for farmed fish and to ensure the sustainability of the aquaculture sector. Nowadays, insect, microalgae and yeast are feedstuff candidates for new feeds. However, the characterization of aquafeed is still based on proximate and targeted analyses which may not be sufficient to assess feed quality.

Objectives

Our aim was to highlight the soluble compounds that specifically differ between selected plant-based feeds complemented with alternative feedstuffs and discuss their origin and potential for fish nutrition.

Methods

A growth trial was carried out to evaluate growth performances and feed conversion ratios of fish fed plant-based, commercial, insect, spirulina and yeast feeds. ¹H NMR metabolomics profiling of each feed was performed using a CPMG sequence on polar extracts. Spectra were processed, and data were analyzed using multivariate and univariate analyses to compare alternative feeds to a plant-based feed.

Results

Fish fed insect or yeast feed showed the best growth performances associated with the lowest feed conversion ratios compared to plant-based feed. Soluble compound ¹H NMR profiles of insect and spirulina alternative feeds differed significantly from the plant-based one that clustered with yeast feed. In insect and spirulina feeds, specific differences compared to plant-based feed concerned glycerol and 3-hydroxybutyrate, respectively.

Conclusion

This strategy based on compositional differences between plant-based and alternative feeds can be useful for detecting compounds unsuspected until now that could impact fish metabolism.

     

Characterization of trotter horses urine metabolome by means of proton nuclear magnetic resonance spectroscopy

Background

Metabolomics has been recognized as a powerful approach for disease screening. In order to highlight potential health issues in subjects, a key factor is the possibility to compare quantitatively the metabolome of their biofluids with reference values from healthy individuals. Such efforts towards the systematic characterization of the metabolome of biofluids in perfect health conditions, far from concluded for humans, have barely begun on horses.

Objectives

The present work attempts, for the first time, to give reference quantitative values for the molecules mostly represented in the urine metabolome of horses at rest and under light training, as observable by ¹H-NMR.

Methods

The metabolome of ten trotter horses, four male and six female, ranging from 3 to 8 years of age, has been observed by ¹H-NMR spectroscopy before and after three training sessions.

Results

We could characterize and quantify 54 molecules in trotter horse urine, originated from diet, protein digestion, energy generation or gut-microbial co-metabolism.

Conclusion

We were able to describe how gender, age and exercise affected their concentration, by means of a two steps protocol based on univariate and robust principal component analysis.

     

<Superscript>1</Superscript>H NMR-based metabolomics approach reveals metabolic alterations in response to dietary imbalances in <Emphasis Type="Italic">Megalobrama amblycephala</Emphasis>

Introduction

High-fat and high-carbohydrate diets cause a number of metabolic disorders in mammals. However, little is known about metabolomic changes caused by dietary imbalances in fish.

Objectives

The objective of this study was to assess the impacts of high-fat diet (HFD), high-carbohydrate diet (HCD) and high-fat-high-carbohydrate diet (HFHCD) on metabolites in a farmed cyprinid fish Megalobrama amblycephala.

Methods

We have employed the ¹H NMR-based metabolomic approach to measure the concentrations of metabolites in plasma and liver of four different diet groups: HFD, HCD, HFHCD and control. Multivariate statistical analyses were used to determine significantly changed metabolites between all group-pairs.

Results

All three test diets have affected metabolic profiles, phenotypes and clinical chemistry. High-fat diets (HFD, HFHCD) resulted in a higher average weight than HCD, but high-carbohydrate diets (HCD, HFHCD) caused signs of liver damage. HCD has resulted in elevated metabolites in energy pathways, leading to further disturbances in creatine pathway. Excess of carbohydrate and lipid metabolism products in the HFHCD group appears to have caused “congestion” of the TCA cycle, causing a significant decline in the numbers of amino acids entering the cycle, which in turn resulted in elevated levels of seven amino acids in this group. Gut microbiota metabolites (TMA) exhibited a strong positive correlation with the carbohydrate content and a negative correlation with the fat content in diets.

Conclusion

These results provide an important insight into the diet-affected metabolic disorders that often lead to financial losses in the aquaculture of Megalobrama amblycephala.

Graphical Abstract

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Metabolic changes of genetically engineered grapes (<Emphasis Type="Italic">Vitis vinifera</Emphasis> L.) studied by <Superscript>1</Superscript>H-NMR,metabolite heatmaps and <Emphasis Type="Italic">i</Emphasis>PLS

Introduction

The Deficiens Homologue 9-iaaM (DefH9-iaaM) gene is an ovule-specific auxin-synthesizing gene which is expressed specifically in placenta/ovules and promotes auxin-synthesis. It was introduced into the genome of two grape cultivars Thompson Seedless and Silcora and both transgenic cultivars had an increased number of berries per bunch.

Objectives

This study investigates the down-stream metabolic changes of Silcora and Thompson seedless grape cultivars when genetically modified through the insertion of the DefH9-iaaM gene into their genome.

Methods

The effects of the genetic modification upon the grape metabolome were evaluated through ¹H-NMR and exploratory data analysis. Chemometric tools such as Interval Partial Least Squares regression and metabolite heatmaps were employed for scrutinizing the changes in the transgenic metabolome as compared to the wild type one.

Results

The results show that the pleiotropic effect on the grape metabolome as a function of the gene modifications is relatively low, although the insertion of the transgene caused a decrement in malic acid and proline and an increment in p-coumaric acid content. In addition, the concentration of malic acid was successfully correlated with the number of inserted copies of transgene in the Silcora cultivar, proving that the increased production of berries, promoted by the inserted gene, is achieved at the expense of a decrement in malic acid concentration.

Conclusion

NMR together with chemometrics is able to identify specific metabolites that were up- or down regulated in the genetically engineered plants allowing highlighting alterations in the down-stream metabolic pathways due to the up-stream genetic modifications.

     

LC–MS-based metabolome analysis on steroid metabolites from the starfish <Emphasis Type="Italic">Patiria</Emphasis> (=<Emphasis Type="Italic">Asterina</Emphasis>) <Emphasis Type="Italic">pectinifera</Emphasis> in conditions of active feeding and stresses

Introduction

Starfish are recognized as interesting source of natural steroid products with pharmaceutical potential. Polar steroid metabolites of starfish have unique chemical structures and exhibit various biological activities but their biological functions are controversial.

Objectives

The objective of this study was to investigate the response of polar steroid metabolome of the starfish Patiria (=Asterina) pectinifera on various environmental factors and stresses.

Methods

Here we first have applied MS-based environmental metabolomics to elucidate the metabolic changes of polar steroid metabolome of starfish. Using HPLC–ESI–Q/TOF–MS approach followed by statistical analysis including principal component analysis and partial least squares discriminant analysis for data classification and potential biomarkers selection, we investigated the changes induced by feeding, injury, variations in water temperature and salinity, and oxygen deficiency.

Results

According to multivariate and univariate statistical analysis the responses to feeding, injury and water heating were better expressed than the others and have some similarity in their action on the steroid metabolome of the starfish P. pectinifera. Most constituents of asterosaponin pool were reduced and most constituents of polyhydroxysteroid and related glycoside pool were increased at that.

Conclusion

Our results indicate that various metabolic changes in polar steroid constituents of P. pectinifera are induced by feeding and stresses. We believe that these responses are connected with biological multifunctionality of these compounds.

     

Metabolome variability for two Mediterranean sponge species of the genus <Emphasis Type="Italic">Haliclona</Emphasis>: specificity,time, and space

Introduction

The study of natural variation of metabolites brings valuable information on the physiological state of the organisms as well as their phenotypic traits. In marine organisms, metabolome variability has mostly been addressed through targeted studies on metabolites of ecological or pharmaceutical interest. However, comparative metabolomics has demonstrated its potential to address the overall and complex metabolic variability of organisms.

Objectives

In this study, the intraspecific (temporal and spatial) variability of two Mediterranean Haliclona sponges (H. fulva and H. mucosa) was investigated through an untargeted and then targeted metabolomics approach and further compared to their interspecific variability.

Methods

Samples of both species were collected monthly during 1 year in the coralligenous habitat of the Northwestern Mediterranean sae at Marseille and Nice. Their metabolomic profiles were obtained by UHPLC-QqToF analyses.

Results

Marked variations were noticed in April and May for both species including a decrease in Shannon’s diversity and concentration in specialized metabolites together with an increase in fatty acids and lyso-PAF like molecules. Spatial variations across different sampling sites could also be observed for both species, however in a lesser extent.

Conclusions

Synchronous metabolic changes possibly triggered by physiological factors like reproduction and/or environmental factors like an increase in the water temperature were highlighted for both Mediterranean Haliclona species inhabiting close habitats but displaying different biosynthetic pathways. Despite significative intraspecific variations, metabolomic variability remains minor when compared to interspecific variations for these congenerous species, therefore suggesting the predominance of genetic information of the holobiont in the observed metabolome.

     

Metabolomic study of the response to cold shock in a strain of <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> isolated from cloud water

Introduction

Active microorganisms have been recently discovered in clouds, thus demonstrating the capacity of microorganisms to exist in harsh environments, including exposure to UV and oxidants, osmotic and cold shocks, etc. It is important to understand how microorganisms respond to and survive such stresses at the metabolic level.

Objectives

The objective of this work is to assess metabolome modulation in a strain of Pseudomonas syringae isolated from cloud water and facing temperature downshift from 17 to 5 °C by identifying key molecules and pathways of the response/adaptation to cold shock.

Methods

Bacterial extracts from suspensions of cells grown at 17 °C and further incubated in microcosms at 5 and 17 °C to mimic cloud conditions were analysed by combining LC-MS and NMR; the results were evaluated in comparison to similar suspensions kept at constant temperature. The differences in the metabolome profiles were deciphered using multivariate statistics (PLS-DA).

Results

Key cold shock biomarkers were observed, including cryoprotectants (trehalose, glucose, glycerol, carnitine, glutamate), antioxidants (glutathione and carnitine) and their precursors, alkaloids (bellendine and slaframine) and metabolites involved in energy metabolism (ATP, carbohydrates). Furthermore, new short peptides (nine dipeptides and a tetrapeptide) were found that have no known function.

Conclusions

This study shows that in response to cold temperatures, Pseudomonas syringae PDD-32b-74 demonstrates numerous metabolism modifications to counteract the impacts of low temperatures.

     

The metabolome 18 years on: a concept comes of age

Background

The term ‘metabolome’ was introduced to the scientific literature in September 1998.

Aim and key scientific concepts of the review

To mark its 18-year-old ‘coming of age’, two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

     

Metabolic profiling identifies trehalose as an abundant and diurnally fluctuating metabolite in the microalga <Emphasis Type="Italic">Ostreococcus tauri</Emphasis>

Introduction

The picoeukaryotic alga Ostreococcus tauri (Chlorophyta) belongs to the widespread group of marine prasinophytes. Despite its ecological importance, little is known about the metabolism of this alga.

Objectives

In this work, changes in the metabolome were quantified when O. tauri was grown under alternating cycles of 12 h light and 12 h darkness.

Methods

Algal metabolism was analyzed by gas chromatography-mass spectrometry. Using fluorescence-activated cell sorting, the bacteria associated with O. tauri were depleted to below 0.1% of total cells at the time of metabolic profiling.

Results

Of 111 metabolites quantified over light–dark cycles, 20 (18%) showed clear diurnal variations. The strongest fluctuations were found for trehalose. With an intracellular concentration of 1.6 mM in the dark, this disaccharide was six times more abundant at night than during the day. This fluctuation pattern of trehalose may be a consequence of starch degradation or of the synchronized cell cycle. On the other hand, maltose (and also sucrose) was below the detection limit (~10 μM). Accumulation of glycine in the light is in agreement with the presence of a classical glycolate pathway of photorespiration. We also provide evidence for the presence of fatty acid methyl and ethyl esters in O. tauri.

Conclusions

This study shows how the metabolism of O. tauri adapts to day and night and gives new insights into the configuration of the carbon metabolism. In addition, several less common metabolites were identified.

     

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.

     

ASICS: an automatic method for identification and quantification of metabolites in complex 1D <Superscript>1</Superscript>H NMR spectra

Introduction

Experiments in metabolomics rely on the identification and quantification of metabolites in complex biological mixtures. This remains one of the major challenges in NMR/mass spectrometry analysis of metabolic profiles. These features are mandatory to make metabolomics asserting a general approach to test a priori formulated hypotheses on the basis of exhaustive metabolome characterization rather than an exploratory tool dealing with unknown metabolic features.

Objectives

In this article we propose a method, named ASICS, based on a strong statistical theory that handles automatically the metabolites identification and quantification in proton NMR spectra.

Methods

A statistical linear model is built to explain a complex spectrum using a library containing pure metabolite spectra. This model can handle local or global chemical shift variations due to experimental conditions using a warping function. A statistical lasso-type estimator identifies and quantifies the metabolites in the complex spectrum. This estimator shows good statistical properties and handles peak overlapping issues.

Results

The performances of the method were investigated on known mixtures (such as synthetic urine) and on plasma datasets from duck and human. Results show noteworthy performances, outperforming current existing methods.

Conclusion

ASICS is a completely automated procedure to identify and quantify metabolites in ¹H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.

     

Diagnosis of <Emphasis Type="Italic">Clostridium difficile</Emphasis> infection using an UPLC–MS based metabolomics method

Introduction

The fecal metabolome of Clostridium difficile (CD) infection is far from being understood, particularly its non-volatile organic compounds. The drawbacks of current tests used to diagnose CD infection hinder their application.

Objective

The aims of this study were to find new characteristic fecal metabolites of CD infection and develop a metabolomics model for the diagnosis of CD infection.

Methods

Ultra-performance liquid chromatography-mass spectrometry (UPLC–MS) was used to characterize the fecal metabolome of CD positive and negative diarrhea and healthy control stool samples.

Results

Diarrhea and healthy control samples showed distinct clusters in the principal components analysis score plot, and CD positive group and CD negative group demonstrated clearer separation in a partial least squares discriminate analysis model. The relative abundance of sphingosine, chenodeoxycholic acid, phenylalanine, lysophosphatidylcholine (C16:0), and propylene glycol stearate was higher, and the relative abundance of fatty amide, glycochenodeoxycholic acid, tyrosine, linoleyl carnitine, and sphingomyelin was lower in CD positive diarrhea groups, than in the CD negative group. A linear discriminant analysis model based on capsiamide, dihydrosphingosine, and glycochenodeoxycholic acid was further constructed to identify CD infection in diarrhea. The leave-one-out cross-validation accuracy and area under receiver operating characteristic curve for the training set/external validation set were 90.00/78.57%, and 0.900/0.7917 respectively.

Conclusions

Compared with other hospital-onset diarrhea, CD diarrhea has distinct fecal metabolome characteristics. Our UPLC–MS metabolomics model might be useful tool for diagnosing CD diarrhea.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

Profiling of faecal water and urine metabolites among Papua New Guinea highlanders believed to be adapted to low protein intake

Introduction

Adequate amount of proteins from foods are normally needed to maintain muscle mass of the human body. Although protein intakes of Papua New Guinea (PNG) highlanders are less than biologically adequate, protein deficiency related disorders have rarely been reported. It has been postulated that gut microbiota play a role in such low-protein-adaptation.

Objective

To explore underlying biological mechanisms of low-protein adaptation among PNG highlanders by investigating metabolomic profiles of faecal water and urine.

Methods

We performed metabolome analysis using faecal water extracted from faecal samples of PNG highlanders, PNG non-highlanders and Japanese subjects. We paid special attention to amino acids and other metabolites produced by gut microbiota, as well as to metabolites involved in nitrogen recycling in the human gut.

Results

Our results indicated that amino acid levels were higher in faecal water from PNG highlanders than PNG non-highlanders, but amino acid levels did not differ between PNG highlanders and Japanese subjects. Among PNG highlander samples, amino acid levels tended to be higher in those who consumed less protein.

Conclusion

We speculated that a greater proportion of urea was excreted to the intestine among the PNG highlanders than other groups, and that the urea was used for nitrogen salvage. Intestinal bacteria are essential for producing ammonia from urea and also for producing amino acids from ammonia, which is a key process in low-protein adaptation. Profiling the gut microbiota of PNG highlanders is an important avenue for further research into the mechanisms of low-protein adaptation.

     

Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs

Introduction

Dog breeds are a consequence of artificial selection for specific attributes. These closed genetic populations have metabolic and physiological characteristics that may be revealed by metabolomic analysis.

Objectives

To identify and characterise the drivers of metabolic differences in the fasted plasma metabolome and then determine metabolites differentiating breeds.

Methods

Fasted plasma samples were collected from dogs maintained under two environmental conditions (controlled and client-owned at home). The former (n = 33) consisted of three breeds (Labrador Retriever, Cocker Spaniel and Miniature Schnauzer) fed a single diet batch, the latter (n = 96), client-owned dogs consisted of 9 breeds (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese) consuming various diets under differing feeding regimens. Triplicate samples were taken from Beagle (n = 10) and Labrador Retriever (n = 9) over 3 months. Non-targeted metabolite fingerprinting was performed using flow infusion electrospray-ionization mass spectrometry which was coupled with multivariate data analysis. Metadata factors including age, gender, sexual status, weight, diet and breed were investigated.

Results

Breed differences were identified in the plasma metabolome of dogs housed in a controlled environment. Triplicate samples from two breeds identified intra-individual variability, yet breed separation was still observed. The main drivers of variance in dogs maintained in the home environment were associated with breed and gender. Furthermore, metabolite signals were identified that discriminated between Labrador Retriever and Cocker Spaniels in both environments.

Conclusion

Metabolite fingerprinting of plasma samples can be used to investigate breed differences in client-owned dogs, despite added variance of diet, sexual status and environment.