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.

     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.

     

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.

     

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.

     

Deep learning for DNase I hypersensitive sites identification

Background

The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources available on line including experimental datasets and computational tools, the complex language of DHSs remains incompletely understood.

Methods

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) which combined Inception like networks with a gating mechanism for the response of multiple patterns and longterm association in DNA sequences to predict multi-scale DHSs in Arabidopsis, rice and Homo sapiens.

Results

Our method obtains 0.961 area under curve (AUC) on Arabidopsis, 0.969 AUC on rice and 0.918 AUC on Homo sapiens.

Conclusions

Our method provides an efficient and accurate way to identify multi-scale DHSs sequences by deep learning.

     

The targeting of starch binding domains from starch synthase III to the cell wall alters cell wall composition and properties

Key message

Starch binding domains of starch synthase III from Arabidopsis thaliana (SBD123) binds preferentially to cell wall polysaccharides rather than to starch in vitro. Transgenic plants overexpressing SBD123 in the cell wall are larger than wild type. Cell wall components are altered in transgenic plants. Transgenic plants are more susceptible to digestion than wild type and present higher released glucose content. Our results suggest that the transgenic plants have an advantage for the production of bioethanol in terms of saccharification of essential substrates.

Abstract

The plant cell wall, which represents a major source of biomass for biofuel production, is composed of cellulose, hemicelluloses, pectins and lignin. A potential biotechnological target for improving the production of biofuels is the modification of plant cell walls. This modification is achieved via several strategies, including, among others, altering biosynthetic pathways and modifying the associations and structures of various cell wall components. In this study, we modified the cell wall of A. thaliana by targeting the starch-binding domains of A. thaliana starch synthase III to this structure. The resulting transgenic plants (E8-SDB123) showed an increased biomass, higher levels of both fermentable sugars and hydrolyzed cellulose and altered cell wall properties such as higher laxity and degradability, which are valuable characteristics for the second-generation biofuels industry. The increased biomass and degradability phenotype of E8-SBD123 plants could be explained by the putative cell-wall loosening effect of the in tandem starch binding domains. Based on these results, our approach represents a promising biotechnological tool for reducing of biomass recalcitrance and therefore, the need for pretreatments.

     

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.

     

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

Introduction

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

Objectives

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

Methods

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

Results

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p?<?0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI)?=?0.940 and 0.929 for HG and LG, respectively.

Conclusion

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.

     

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.

     

High-frequency fire alters soil and plant chemistry but does not lead to nitrogen-limited growth of <Emphasis Type="Italic">Eucalyptus pilularis</Emphasis> seedlings

Background and aims

The current study was undertaken to investigate the mechanism underlying Boron (B)-alleviated phosphate (P) deficiency in Arabidopsis thaliana. Furthermore, we were interested to explore whether this alleviation of P deficiency by B could extend to Brassica crops.

Methods

Arabidopsis thaliana or Brassica oleracea plants were grown under P-sufficient or -deficient condition with or without extra B for 7 days, then shoots and roots of B. oleracea were sampled for analysis of soluble P content while those of A. thaliana were harvested for analysis of total P content, soluble P content and nitric oxide (NO) as well as for cell wall extraction and RNA isolation.

Results

A. thaliana plants showed reduced root growth and decreased P content in the root under P-deficient conditions, but improved root growth when supplemented with additional B. Further analysis revealed that exogenous B elevated the cell wall pectin content and facilitated the release of P in P-deficient seedlings, thus more soluble P was available to sustain growth under P deficiency. Furthermore, B supplement also increased soluble P in P-deficient cabbage (Brassica oleracea var. capitata L.), an economically important vegetable crop. P deficiency alone was sufficient to induce NO accumulation, and in combination with B application further enhanced NO accumulation, while exogenous application of NO scavenger c-PTIO [2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide] counteracted this positive effect of B, indicating that NO is positively involved in B-mediated alleviation of P deficiency.

Conclusions

Our study reveals the critical role of B in improving the growth of P-deficient plants, and also provides evidence implicating the involvement of NO signal.

     

Quantifying the cellular NAD+ metabolome using a tandem liquid chromatography mass spectrometry approach

Introduction

Nicotinamide adenine dinucleotide (NAD⁺) is an essential pyridine nucleotide that serves as a key hydride transfer coenzyme for several oxidoreductases. It is also the substrate for intracellular secondary messenger signalling by CD38 glycohydrolases, DNA repair by poly(adenosine diphosphate ribose) polymerase, and epigenetic regulation of gene expression by a class of histone deacetylase enzymes known as sirtuins. The measurement of NAD⁺ and its related metabolites (hereafter, the NAD⁺ metabolome) represents an important indicator of cellular function.

Objectives

A study was performed to develop a sensitive, selective, robust, reproducible, and rapid method for the concurrent quantitative determination of intracellular levels of the NAD⁺ metabolome in glial and oocyte cell extracts using liquid chromatography coupled to mass spectrometry (LC/MS/MS).

Methods

The metabolites were separated on a versatile amino column using a dual HILIC-RP gradient with heated electrospray (HESI) tandem mass spectrometry detection in mixed polarity multiple reaction monitoring mode.

Results

Quantification of 17 metabolites in the NAD⁺ metabolome in U251 human astroglioma cells could be achieved. Changes in NAD⁺ metabolism in U251 cell line, and murine oocytes under different culture conditions were also investigated.

Conclusion

This method can be used as a sensitive profiling tool, tailoring chromatography for metabolites that express significant pathophysiological changes in several disease conditions and is indispensable for targeted analysis.

     

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.

     

Automation of chemical assignment for identifying molecular formula of S-containing metabolites by combining metabolomics and chemoinformatics with <Superscript>34</Superscript>S labeling

Introduction

Sulfur-containing metabolites (S-metabolites) in organisms including plants have unique benefits to humans. So far, few analytical methods have explored such metabolites.

Objectives

We aimed to develop an automatic chemically assigning platform by metabolomics and chemoinformatics with ³⁴S labeling to identify the molecular formula of S-metabolites.

Methods

Direct infusion analysis using Fourier transform ion cyclotron resonance-mass spectrometry provided ultra-high-resolution data including clearly separated isotopic ions—¹⁵N, ³⁴S, ¹⁸O, and ¹³C₂—in the flower, silique, leaf, stem, and root of non-labeled and ³⁴S-labeled Arabidopsis thaliana. Chemoinformatic analysis assigned several elemental compositions of S-metabolites to the acquired S-containing monoisotopic ions using mass accuracy and peak resolution in the non-labeled metabolome data. Possible elemental compositions were characterized on the basis of diagnostic scores of the exact mass and isotopic ion pattern, and a database search. By comparing elemental compositions assigned to the ³⁴S-labeled data with those assigned to the non-labeled data, the elemental composition of S-metabolites were determined. The determined elemental compositions were surveyed using the in-house database, which stores molecular formulae downloaded from metabolome databases.

Results

We identified 35 molecular formulae for known S-metabolites and characterized 72 for unknown. Chemoinformatics required around 1.5 min to analyze a pair of the non-labeled and ³⁴S-labeled data of the organ.

Conclusion

In this study, we developed an automation platform for automatically identifying the presence of S-metabolites. We identified the molecular formula of known S-metabolites, which are accessible in free databases, together with that of unknown. This analytical method did not focus on identifying the structure of S-metabolites, but on the automatic identification of their molecular formula.