Magnetic Resonance Metabolic Profiling of Breast Cancer Tissue Obtained with Core Needle Biopsy for Predicting Pathologic Response to Neoadjuvant Chemotherapy

The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB) samples using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA). Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.     

Metabolic profiling of cervical tubercular lymphadenitis tissues by proton HR-MAS NMR spectroscopy

Proton metabolic profiling of incisional biopsied cervical lymph node tissue specimens of 109 patients suffering from tubercular (CTBL) and non-specific (NSCLA) lymphadenitis were analyzed by high resolution magic angle spinning (HR-MAS) NMR spectroscopy. In the present study, 40 endogenous metabolites namely, myo-inositol (m-Ins), branched chain amino acids (BCAA), glutamate, serine, taurine (Tau) aromatic amino acids, choline (Cho) containing compounds and glucose were characterized. To the best of our knowledge, this is the first report on metabolic profiling of cervical tubercular lymph node tissues using HR-MAS NMR spectroscopy. The principal component analysis revealed a clear discrimination between CTBL and NSCLA tissues. Increase in the concentration of mobile poly unsaturated fatty acids, BCAA, Cho, Tau, glycine and a decrease in the concentration of lactate, phosphocholine and m-Ins was observed in CTBL cases. The partial least square discriminant analysis (PLS-DA) with R ² = 0.95 and Q ² = 0.92 provided >98 % of correct classification between the two groups. A PLS-DA training set model of 75 % (CTBL = 54, NSCLA = 27) of the subjects when subjected for prediction of 25 % cases (CTBL = 18, NSCLA = 10) as an unknown dataset provided more than 98 % of diagnostic accuracy in their respective histological categories. The receiver operator characteristic curve was generated from PLS-DA factor-1 projected an area under the curve of 0.962. The metabolic profile obtained from HR-MAS NMR spectroscopy may be used as surrogate markers in vivo MRS for differentiating between CTBL and NSCLA cases non-invasively.     

1H HRMAS-NMR based metabolic fingerprints for discrimination of cheeses based on sensory qualities

In this study, the ¹H HRMAS-NMR (High-resolution Magic Angle Spinning-Nuclear Magnetic Resonance) spectra of 52 cheese samples obtained from the South Korean dairy farms were evaluated for their metabolic profiling and intensities associating with the sensory qualities. The NMR profiles displayed a broad range of compounds comprising amino acids, carbohydrates, organic acids, and phospholipids. Afterwards, the cheese samples were categorized into three groups (more likeness - G1, moderate likeness - G2, less likeness - G3), in relating to their sensory scores. The NMR data of the samples were later investigated through multivariate statistical tools to define the variations in metabolic fingerprints of every cheese sample and their intensities hailing in individual sensory groups. The unsupervised PCA employing all cheese samples unveiled the uniqueness in metabolite profiles of the brown and cheddar type cheeses (outliers). Moreover, Gouda and other types of cheeses displayed samples positioning in respective of their metabolite profiles. The pairwise comparison of sensory groups in the supervised models perceived better separation in OPLS-DA than PLS-DA. The corresponding VIP (PLS-DA) and loading (OPLS-DA) plots revealed amino acids and organic acids (lactate, citrate) as significant variables. The discrimination of G 1 Gouda type of cheeses against G 2 and G 3 was highly associated with their citrate levels. Further investigation using heatmaps displayed clear differentiation between each sensory group in terms of the levels of amino acids, lactate, citrate, phospholipids, and glycerol, conveying these variations are likely due to proteolytic and metabolic processes in cheese ripening. This study concluded that ¹H HRMAS-NMR metabolite profile of the Korean cheeses is consistence with their sensory qualities. Further, the candidate metabolites identified in this study confers their potential application as biomarkers in cheese industries for faster and effective validation of sensory characteristics.     

Metabolic signatures of esophageal cancer: NMR-based metabolomics and UHPLC-based focused metabolomics of blood serum

Focused metabolic profiling is a powerful tool for the determination of biomarkers. Here, a more global proton nuclear magnetic resonance (¹H NMR)-based metabolomic approach coupled with a relative simple ultra high performance liquid chromatography (UHPLC)-based focused metabolomic approach was developed and compared to characterize the systemic metabolic disturbances underlying esophageal cancer (EC) and identify possible early biomarkers for clinical prognosis. Serum metabolic profiling of patients with EC (n = 25) and healthy controls (n = 25) was performed by using both ¹H NMR and UHPLC, and metabolite identification was achieved by multivariate statistical analysis. Using orthogonal projection to least squares discriminant analysis (OPLS-DA), we could distinguish EC patients from healthy controls. The predictive power of the model derived from the UHPLC-based focused metabolomics performed better in both sensitivity and specificity than the results from the NMR-based metabolomics, suggesting that the focused metabolomic technique may be of advantage in the future for the determination of biomarkers. Moreover, focused metabolic profiling is highly simple, accurate and specific, and should prove equally valuable in metabolomic research applications. A total of nineteen significantly altered metabolites were identified as the potential disease associated biomarkers. Significant changes in lipid metabolism, amino acid metabolism, glycolysis, ketogenesis, tricarboxylic acid (TCA) cycle and energy metabolism were observed in EC patients compared with the healthy controls. These results demonstrated that metabolic profiling of serum could be useful as a screening tool for early EC diagnosis and prognosis, and might enhance our understanding of the mechanisms involved in the tumor progression.     

Application of 1H-NMR Metabolomic Profiling for Reef-Building Corals

In light of global reef decline new methods to accurately, cheaply, and quickly evaluate coral metabolic states are needed to assess reef health. Metabolomic profiling can describe the response of individuals to disturbance (i.e., shifts in environmental conditions) across biological models and is a powerful approach for characterizing and comparing coral metabolism. For the first time, we assess the utility of a proton-nuclear magnetic resonance spectroscopy (¹H-NMR)-based metabolomics approach in characterizing coral metabolite profiles by 1) investigating technical, intra-, and inter-sample variation, 2) evaluating the ability to recover targeted metabolite spikes, and 3) assessing the potential for this method to differentiate among coral species. Our results indicate ¹H-NMR profiling of Porites compressa corals is highly reproducible and exhibits low levels of variability within and among colonies. The spiking experiments validate the sensitivity of our methods and showcase the capacity of orthogonal partial least squares discriminate analysis (OPLS-DA) to distinguish between profiles spiked with varying metabolite concentrations (0 mM, 0.1 mM, and 10 mM). Finally, ¹H-NMR metabolomics coupled with OPLS-DA, revealed species-specific patterns in metabolite profiles among four reef-building corals (Pocillopora damicornis, Porites lobata, Montipora aequituberculata, and Seriatopora hystrix). Collectively, these data indicate that ¹H-NMR metabolomic techniques can profile reef-building coral metabolomes and have the potential to provide an integrated picture of the coral phenotype in response to environmental change.     

Metabolic profiles of genetically modified potatoes using a combination of metabolite fingerprinting and multivariate analysis

Comprehensive metabolite fingerprinting of transgenic potatoes that constitutively express human beta amyloid, curdlan synthase (CRDS), and glycogen synthase (glgA); and of wild-type potatoes was carried out using FT-IR and ¹H NMR spectroscopy in combination with multivariate analyses. Comparison of metabolic patterns between transgenic and wild-type potatoes revealed that there were neither quantitative nor qualitative differences in metabolites between transgenic potatoes expressing human beta amyloid, CRDS or glgA, and non-transformed control potatoes. However, there were metabolic differences between two control potato lines — one that was fresh and the other stored. After 1 week of storage, comprehensive metabolite patterns were significantly modified. Although the differences between CRDS and glgA transgenic and control potato lines were small, PCA analysis of FT-IR and ¹H NMR spectral data identified two distinct control lines. These results suggest that the comprehensive metabolite changes in control potato lines, which occurred after 1 week of storage, were greater than the differences between CRDS and glgA transgenic and wild-type potato lines. Thus, the combination of FT-IR and ¹H NMR spectral data and multivariate analysis was valuable for the detection of comprehensive differences in metabolic profiles between transgenic and non-transformed control plants, even though peak-signal overlap prevented assignment of pure compounds. The combination of FT-IR and ¹H NMR spectral data and multivariate analysis is a simple and rapid method for evaluation of the metabolic equivalence of GM crops.     

HR-MAS MR Spectroscopy of Breast Cancer Tissue Obtained with Core Needle Biopsy: Correlation with Prognostic Factors

The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization.     

1H NMR-Based Metabolite Profiling of Planktonic and Biofilm Cells in Acinetobacter baumannii 1656-2

Acinetobacter baumannii is an aerobic and gram-negative pathogenic bacterium that is resistant to most antibiotics. Recently, A. baumannii 1656-2 exhibited the ability to form biofilms under clinical conditions. In this study, global metabolite profiling of both planktonic and biofilm forms of A. baumannii 1656-2 was performed using high-resolution nuclear magnetic resonance (NMR) spectroscopy and multivariate statistical analysis to investigate the metabolic patterns leading to biofilm formation. Principal components analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) score plots showed a distinct separation between planktonic and biofilm cells. Metabolites including acetates, pyruvate, succinate, UDP-glucose, AMP, glutamate, and lysine were increasingly involved in the energy metabolism of biofilm formation. In particular, the ratio of N-acetyl-D-glucosamine (GlcNAc) to D-glucosamine (GlcNH₂) was significantly higher during biofilm formation than under the planktonic condition. This study demonstrates that NMR-based global metabolite profiling of bacterial cells can provide valuable insight into the metabolic changes in multidrug resistant and biofilm-forming bacteria such as A. baumannii 1656-2.     

Quantitative analysis of metabolite concentrations in human urine samples using 13C{1H} NMR spectroscopy

Targeted profiling is a library-based method of using mathematically modeled reference spectra for quantification of metabolite concentrations in NMR mixture analysis. Metabolomics studies of biofluids, such as urine, represent a highly complex problem in this area, and for this reason targeted profiling of ¹H NMR spectra can be hampered. A number of the issues relating to ¹H NMR spectroscopy can be overcome using ¹³C{¹H} NMR spectroscopy. In this work, a ¹³C{¹H} NMR database was created using Chenomx NMR Suite, incorporating 120 metabolites. The ¹³C{¹H} NMR database was standardized through the analysis of a series of metabolite solutions containing varying concentrations of 19 distinct metabolites, where the metabolite concentrations were varied across a range of values including biological ranges. Subsequently, the NMR spectra of urine samples were collected using ¹³C{¹H} NMR spectroscopy and profiled using the ¹³C{¹H} NMR library. In total, about 30 metabolites were conclusively identified and quantified in the urine samples using ¹³C{¹H} NMR targeted profiling. The proton decoupling and larger spectral window provided easier identification and more accurate quantification for specific classes of metabolites, such as sugars and amino acids with overlap in the aliphatic region of the ¹H NMR spectrum. We discuss potential application areas in which ¹³C{¹H} NMR targeted profiling may be superior to ¹H NMR targeted profiling.     

The Effect of Antitumor Glycosides on Glioma Cells and Tissues as Studied by Proton HR-MAS NMR Spectroscopy

The effect of the treatment with glycolipid derivatives on the metabolic profile of intact glioma cells and tumor tissues, investigated using proton high resolution magic angle spinning (¹H HR-MAS) nuclear magnetic resonance (NMR) spectroscopy, is reported here. Two compounds were used, a glycoside and its thioglycoside analogue, both showing anti-proliferative activity on glioma C6 cell cultures; however, only the thioglycoside exhibited antitumor activity in vivo. At the drug concentrations showing anti-proliferative activity in cell culture (20 and 40 µM), significant increases in choline containing metabolites were observed in the ¹H NMR spectra of the same intact cells. In vivo experiments in nude mice bearing tumors derived from implanted C6 glioma cells, showed that reduction of tumor volume was associated with significant changes in the metabolic profile of the same intact tumor tissues; and were similar to those observed in cell culture. Specifically, the activity of the compounds is mainly associated with an increase in choline and phosphocholine, in both the cell cultures and tumoral tissues. Taurine, a metabolite that has been considered a biomarker of apoptosis, correlated with the reduction of tumor volume. Thus, the results indicate that the mode of action of the glycoside involves, at least in part, alteration of phospholipid metabolism, resulting in cell death.     

Revealing the metabonomic variation of EC using 1H-NMR spectroscopy and its association with the clinicopathological characteristics

In this study, (1)H NMR-based metabonomics has been applied to investigate esophageal cancer metabolic signatures in plasma and urine, purpose of assessing the diagnostic potential of this approach and gaining novel insights into esophageal cancer metabolism and systemic effects. Plasma and urine samples from esophageal cancer patients (n = 108) and a control healthy group (n = 40) were analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy (600 MHz), and their spectral profiles subjected to Orthogonal Projections to Latent Structures (OPLS-DA) for multivariate statistics. Potential metabolic biomarkers were identified using data base comparisons used for examining the significance of metabolites. Compared to healthy controls, esophageal cancer plasma had higher levels of dimethylamine, α-glucose, β-glucose, citric acid, together with lower levels of Leucine, alanine, isoleucine, valine, glycoprotein, lactate, acetone, acetate, choline, isobutyrate, unsaturated lipid, VLDL, LDL, 1-methylhistidine; Compared to healthy controls, esophageal cancer urine had higher levels of Mannitol, glutamate, γ-propalanine, phenylalanine, acetate, allantoin, pyruvate, tyrosine, β-glucose and guinolinate, together with lower levels of N-acetylcysteine, valine, dihydrothymine, hippurate, methylguanidine, 1-methylnicotin- amide and Citric acid; Very good discrimination between cancer and control groups was achieved by multivariate modeling of plasma and urinary profiles. (1)H NMR-based metabolite profiling analysis was shown to be an effective approach to differentiating between patients with EC and healthy subjects. Good sensitivity and selectivity were shown by using the metabolite markers discovered to predict the classification of samples from the healthy control group and the patients with the disease. Plasma and urine metabolic profiling may have potential for early diagnosis of EC and may enhance our understanding of its mechanisms.     

Discovery of Infection Associated Metabolic Markers in Human African Trypanosomiasis

Human African trypanosomiasis (HAT) remains a major neglected tropical disease in Sub-Saharan Africa. As clinical symptoms are usually non-specific, new diagnostic and prognostic markers are urgently needed to enhance the number of identified cases and optimise treatment. This is particularly important for disease caused by Trypanosoma brucei rhodesiense, where indirect immunodiagnostic approaches have to date been unsuccessful. We have conducted global metabolic profiling of plasma from T.b.rhodesiense HAT patients and endemic controls, using ¹H nuclear magnetic resonance (NMR) spectroscopy and ultra-performance liquid chromatography, coupled with mass spectrometry (UPLC-MS) and identified differences in the lipid, amino acid and metabolite profiles. Altogether 16 significantly disease discriminatory metabolite markers were found using NMR, and a further 37 lipid markers via UPLC-MS. These included significantly higher levels of phenylalanine, formate, creatinine, N-acetylated glycoprotein and triglycerides in patients relative to controls. HAT patients also displayed lower concentrations of histidine, sphingomyelins, lysophosphatidylcholines, and several polyunsaturated phosphatidylcholines. While the disease metabolite profile was partially consistent with previous data published in experimental rodent infection, we also found unique lipid and amino acid profile markers highlighting subtle but important differences between the host response to trypanosome infections between animal models and natural human infections. Our results demonstrate the potential of metabolic profiling in the identification of novel diagnostic biomarkers and the elucidation of pathogenetic mechanisms in this disease.     

Metabolic Responses to Orientia tsutsugamushi Infection in a Mouse Model

Tsutsugamushi disease is an infectious disease transmitted to humans through the bite of the Orientia tsutsugamushi-infected chigger mite; however, host-pathogen interactions and the precise mechanisms of damage in O. tsutsugamushi infections have not been fully elucidated. Here, we analyzed the global metabolic effects of O. tsutsugamushi infection on the host using ¹H-NMR and UPLC-Q-TOF mass spectroscopy coupled with multivariate statistical analysis. In addition, the effect of O. tsutsugamushi infection on metabolite concentrations over time was analyzed by two-way ANOVAs. Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed distinct metabolic patterns between control and O. tsutsugamushi-infected mice in liver, spleen, and serum samples. O. tsutsugamushi infection caused decreased energy production and deficiencies in both remethylation sources and glutathione. In addition, O. tsutsugamushi infection accelerated uncommon energy production pathways (i.e., excess fatty acid and protein oxidation) in host body. Infection resulted in an enlarged spleen with distinct phospholipid and amino acid characteristics. This study suggests that metabolite profiling of multiple organ tissues and serum could provide insight into global metabolic changes and mechanisms of pathology in O. tsutsugamushi-infected hosts.     

Metabolite fingerprinting and profiling in plants using NMR

Although less sensitive than mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy provides a powerful complementary technique for the identification and quantitative analysis of plant metabolites either in vivo or in tissue extracts. In one approach, metabolite fingerprinting, multivariate analysis of unassigned 1H NMR spectra is used to compare the overall metabolic composition of wild-type, mutant, and transgenic plant material, and to assess the impact of stress conditions on the plant metabolome. Metabolite fingerprinting by NMR is a fast, convenient, and effective tool for discriminating between groups of related samples and it identifies the most important regions of the spectrum for further analysis. In a second approach, metabolite profiling, the 1H NMR spectra of tissue extracts are assigned, a process that typically identifies 20-40 metabolites in an unfractionated extract. These profiles may also be used to compare groups of samples, and significant differences in metabolite concentrations provide the basis for hypotheses on the underlying causes for the observed segregation of the groups. Both approaches generate a metabolic phenotype for a plant, based on a system-wide but incomplete analysis of the plant metabolome. However, a review of the literature suggests that the emphasis so far has been on the accumulation of analytical data and sample classification, and that the potential of 1H NMR spectroscopy as a tool for probing the operation of metabolic networks, or as a functional genomics tool for identifying gene function, is largely untapped.     

Taxonomic discrimination of cyanobacteria by metabolic fingerprinting using proton nuclear magnetic resonance spectra and multivariate statistical analysis

When whole-cell extracts are analyzed, proton nuclear magnetic resonance (¹H NMR) spectroscopy provides biochemical profiles that contain overlapping signals of the majority of the compounds. To determine whether cyanobacteria could be taxonomically discriminated on the basis of metabolic fingerprinting, we subjected whole-cell extracts of the cyanobacteria to¹H NMR. The¹H NMR spectra revealed a predominance of signals in the aliphatic region. Principal component analysis (PCA) of the data then enabled discrimination of the cyanobacteria. The hierarchical dendrogram, based on PCA of the aliphatic region data, showed that six cyanobacterial taxa were discriminated from two eukaryotic microalgal species, and that the six taxa could be subsequently divided into three groups. This agrees with the current taxonomy of cyanobacteria. Therefore, our overall results indicate that metabolic fingerprinting using¹H NMR spectra and multivariate statistical analysis provide a simple, rapid method for the taxonomical discrimination of cyanobacteria.     

Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were recorded by both ¹H NMR and accurate mass LC-quadrupole time-of-flight (QTOF) MS. Different analytical selectivities were found for these both profiling techniques. In fact, NMR and LCMS provided complementary data, as the metabolites detected belong to essentially different metabolic pathways. Yet, upon unsupervised multivariate analysis, both NMR and LCMS datasets revealed a clear segregation of, on the one hand, the cherry tomatoes and, on the other hand, the beef and round tomatoes. Intra-method (NMR–NMR, LCMS–LCMS) and inter-method (NMR–LCMS) correlation analyses were performed enabling the annotation of metabolites from highly correlating metabolite signals. Signals belonging to the same metabolite or to chemically related metabolites are among the highest correlations found. Inter-method correlation analysis produced highly informative and complementary information for the identification of metabolites, even in de case of low abundant NMR signals. The applied approach appears to be a promising strategy in extending the analytical capacities of these metabolomics techniques with regard to the discovery and identification of biomarkers and yet unknown metabolites. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Discrimination of Ipomoea aquatica cultivars and bioactivity correlations using NMR-based metabolomics approach

Ipomoea aquatica Forsk is a green leafy vegetable that is a rich source of minerals, proteins, vitamins, amino acids, and secondary metabolites. Different types of I. aquatica cultivars are grown for consumption but little is known about the metabolites variation. Proton nuclear magnetic resonance (¹H NMR) spectroscopy combined with multivariate data analysis was applied for metabolic profiling of three I. aquatica cultivars including “broad leaf (K-25)”, “bamboo leaf (K-88)”, and “special pointed leaf (K-11)”. The orthogonal partial least squares discriminant analysis (OPLS-DA) indicated a clear separation among cultivars. The relative levels of various compounds, such as amino acids, organic acids, sugars, and phenolic compounds were specific to each cultivar. The K-11 cultivar was different from the other cultivars due to a high phenolic content. The content of sugars and some amino acids was higher in K-88 and K-25 possessed a higher content of organic acids. The in vitro study revealed that the I. aquatica cultivars exhibited potent antioxidant and α-glucosidase activities. The results of this study indicate that the K-11 cultivar was the most active due to the abundance of epicatechin, 4,5-dicaffeoylquinic, protocatechuic acid, and rutin.     

Toward Arabidopsis thaliana hydrophilic metabolome: assessment of extraction methods and quantitative 1H NMR

Our goal was to establish the hydrophilic metabolome of heterotrophic Arabidopsis thaliana cells grown in suspension, a cellular model of plant sink tissues. Water‐soluble metabolites were extracted using four protocols: perchloric acid, boiling ethanol, methanol and methanol/chloroform (M/Chl). They were detected and quantified using ¹H nuclear magnetic resonance (NMR) spectroscopy at 400 MHz. Extraction yields and reproducibility of the extraction methods were investigated. The effects of cell harvest protocol, cell grinding and lyophilization and storage conditions on the measured metabolic profiles were also studied. These quantitative studies demonstrated for the first time that the four extraction protocols commonly used do lead to quite similar molecular compositions as analyzed by ¹H NMR. The M/Chl method proved effective and reliable to prepare series of physiologically significant extracts from plant cells for ¹H NMR analysis. Reproducibility of the detected metabolome was assessed over long periods of time by analyzing a large number of separate extracts prepared from independent cultures. Larger variations in the NMR metabolite profiles could be correlated to changes in physiological parameters of the culture medium. Quantitative resolved ¹H NMR of cell extracts proved to be robust and reliable for routine metabolite profiling of plant cell cultures.     

Metabolic changes in droplet vitrified semen of wild endangered Persian sturgeon Acipenser persicus (Borodin, 1997)

Comparative quantitative metabolite profiling can be used for better understanding of cell functions and dysfunctions in particular circumstances such as sperm banking which is an important approach for cryopreservation of endangered species. Cryopreservation techniques have some deleterious effects on spermatozoa which put the obtained results in controversy. Therefore, in the present study, quantitative ¹H NMR (Nuclear Magnetic Resonance) based metabolite profiling was conducted to evaluate metabolite changes related to energetics and some other detected metabolites in vitrified semen of critically endangered wild Acipenser persicus. The semen was diluted with extenders containing 0, 5, 10, and 15 μM of fish antifreeze protein (AFP) type III as a cryoprotectant. Semen-extenders were vitrified and stored for two days. Based on post-thaw motility duration and motility percentage assessments, two treatments with 10 μM and 0 μM of AFP had the highest and the lowest motility percentages respectively and they were objected to ¹H NMR spectroscopy investigations in order to reveal the extremes of the metabolites dynamic range. Univariate (ANOVA) and multivariate (PCA) analysis of the resulting metabolic profiles indicated significant changes (P > 0.05) in metabolites. The level of some metabolites including acetate, adenine, creatine, creatine phosphate, lactate, betaine, sarcosine, β-alanine and trimethylamine N-oxide significantly decreased in vitrified semen while some others such as creatinine, guanidinoacetate, N, N-dimethylglycine, and glycine significantly increased. There were also significant differences between vitrified treatments in levels of creatine, creatine phosphate, creatinine, glucose, guanidinoacetate, lactate, N, N-dimethylglycine, and glycine, suggesting how fish AFP type III can be effective as a cryoprotectant.