Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Rice SUB1A constrains remodelling of the transcriptome and metabolome during submergence to facilitate post-submergence recovery.

The rice (Oryza sativa L.) ethylene-responsive transcription factor gene SUB1A-1 confers tolerance to prolonged, complete submergence by limiting underwater elongation growth. Upon desubmergence, SUB1A-1 genotypes rapidly recover photosynthetic function and recommence development towards flowering. The underpinnings of the transition from stress amelioration to the return to homeostasis are not well known. Here, transcriptomic and metabolomic analyses were conducted to identify mechanisms by which SUB1A improves physiological function over the 24 hr following a sublethal submergence event. Evaluation of near-isogenic genotypes after submergence and over a day of reaeration demonstrated that SUB1A transiently constrains the remodelling of cellular activities associated with growth. SUB1A influenced the abundance of ca. 1,400 transcripts and had a continued impact on metabolite content, particularly free amino acids, glucose, and sucrose, throughout the recovery period. SUB1A promoted recovery of metabolic homeostasis but had limited influence on mRNAs associated with growth processes and photosynthesis. The involvement of low energy sensing during submergence and recovery was supported by dynamics in trehalose-6-phosphate and mRNAs encoding key enzymes and signalling proteins, which were modulated by SUB1A. This study provides new evidence of convergent signalling pathways critical to the rapidly reversible management of carbon and nitrogen metabolism in submergence resilient rice.

Two Rumex species from contrasting hydrological niches regulate flooding tolerance through distinct mechanisms.

Global climate change has increased flooding events, which affect both natural vegetation dynamics and crop productivity. The flooded environment is lethal for most plant species because it restricts gas exchange and induces an energy and carbon crisis. Flooding survival strategies have been studied in Oryza sativa, a cultivated monocot. However, our understanding of plant adaptation to natural flood-prone environments remains scant, even though wild plants represent a valuable resource of tolerance mechanisms that could be used to generate stress-tolerant crops. Here we identify mechanisms that mediate the distinct flooding survival strategies of two related wild dicot species: Rumex palustris and Rumex acetosa. Whole transcriptome sequencing and metabolite profiling reveal flooding-induced metabolic reprogramming specific to R. acetosa. By contrast, R. palustris uses the early flooding signal ethylene to increase survival by regulating shade avoidance and photomorphogenesis genes to outgrow submergence and by priming submerged plants for future low oxygen stress. These results provide molecular resolution of flooding survival strategies of two species occupying distinct hydrological niches. Learning how these contrasting flood adaptive strategies evolved in nature will be instrumental for the development of stress-tolerant crop varieties that deliver enhanced yields in a changing climate.

Characterization of distinct root and shoot responses to low-oxygen stress in Arabidopsis with a focus on primary C- and N-metabolism.

Oxygen deficiency, caused by flooding of all or a portion of a plant, leads to significant gene regulatory and metabolic responses associated with survival. When oxygen-deprived in light, aerial organs and root systems respond in distinct manners because of their respective autotrophy and heterotrophy, as well as intrinsic differences in cell biology and organ function. To better understand organ-specific responses to oxygen deficiency, we monitored changes in the metabolome of roots and shoots of Arabidopsis thaliana seedlings using gas chromatography-mass spectrometry and (1) H-nuclear magnetic resonance spectroscopy. Only roots accumulated high amounts of γ-aminobutyrate (GABA) and lactate, whereas both organs accumulated alanine (Ala) upon hypoxia. Meta-analysis of gene regulation data revealed higher induction of mRNAs coding for fermentative enzymes in roots as compared with shoots. However, the elevation in GABA level was not correlated with changes in transcript abundance, supporting the proposal that post-translational mechanisms are important in metabolic acclimation to hypoxia. The biosynthesis, degradation and function of GABA and Ala during oxygen deprivation and re-aeration is discussed. Finally, a systematic survey of low-oxygen mediated regulation of genes associated with primary metabolism across organs and cell types reveals exciting new avenues for future studies.

Comparison of GC-MS and NMR for metabolite profiling of rice subjected to submergence stress.

Natural disasters such as drought, extreme temperatures, and flooding can severely impact crop production. Understanding the metabolic response of crops threatened with these disasters provides insights into biological response mechanisms that can influence survival. In this study, a comparative analysis of GC-MS and (1)H NMR results was conducted for wild-type and tolerant rice varieties stressed by up to 3 days of submergence and allowed 1 day of postsubmergence recovery. Most metabolomics studies are conducted using a single analytical platform. Each platform, however, has inherent advantages and disadvantages that can influence the analytical coverage of the metabolome. In this work, a more thorough analysis of the plant stress response was possible through the use of both (1)H NMR and GC-MS. Several metabolites, such as S-methyl methionine and the dipeptide alanylglycine, were only detected and quantified by (1)H NMR. The high dynamic range of NMR, as compared with that of the GC-TOF-MS used in this study, provided broad coverage of the metabolome in a single experiment. The sensitivity of GC-MS facilitated the quantitation of sugars, organic acids, and amino acids, some of which were not detected by NMR, and provided additional insights into the regulation of the TCA cycle. The combined metabolic information provided by (1)H NMR and GC-MS was essential for understanding the complex biochemical and molecular response of rice plants to submergence.

VIZR--an automated chemometric technique for metabolic profiling.

A chemometric technique, visual interpretation of z-score ratios (VIZR), written in the open source code R, has been developed to identify metabolic differences between individual biosamples and a control group. To demonstrate the capabilities of VIZR, 49 urine samples were collected from healthy volunteers: 41 samples were collected randomly following a normal dietary routine and 7 test samples were collected after dietary supplementation with either ibuprofen or alcoholic beverages. An eighth test sample was prepared by 50% dilution of a control sample. Sample analysis was conducted by (1)H nuclear magnetic resonance (NMR) spectroscopy and the collected data were subjected to VIZR analysis, which successfully discriminated each of the 8 test samples from the 41 control samples. In addition, VIZR analysis revealed the NMR spectral regions responsible for the disparity between the individual test samples and the control group. The self-normalizing nature of the VIZR calculation provides a robust analysis independent of dilution effects, which is especially important in urine analyses. Potential applications of VIZR include high-throughput data analysis for toxicological profiling, disease diagnosis, and biomarker identification in any type of biosample for which a control dataset can be established. Although demonstrated herein for the statistical analysis of (1)H NMR data, the VIZR program is platform independent and could be applied to digitized metabolic datasets acquired using other techniques including hyphenated mass spectrometry measurements.

Differential metabolic regulation governed by the rice SUB1A gene during submergence stress and identification of alanylglycine by 1H NMR spectroscopy.

Although the genetic mechanism of submergence survival for rice varieties containing the SUB1A gene has been elucidated, the downstream metabolic effects have not yet been evaluated. In this study, the metabolomes of Oryza sativa ssp. japonica cv. M202 and cv. M202(Sub1) were profiled using (1)H NMR spectroscopy to compare the metabolic effect of submergence stress and recovery on rice in the presence or absence of SUB1A. Significant changes were observed in the NMR resonances of compounds in pathways important for carbohydrate metabolism. The presence of SUB1A in M202(Sub1) was correlated with suppression of carbohydrate metabolism in shoot tissue, consistent with the role of SUB1A in limiting starch catabolism to fuel elongation growth. The absence of SUB1A in M202 was correlated with greater consumption of sucrose stores and accumulation of amino acids that are synthesized from glycolysis intermediates and pyruvate. Under submergence conditions, alanine, a product of pyruvate metabolism, showed the largest difference between the two varieties, but elevated levels of glutamine, glutamate, leucine, isoleucine, threonine, and valine were also higher in M202 compared with the M202(Sub1) variety. The identification and characterization of alanylglycine (AlaGly) in rice is also reported. After 3 days of submergence stress, AlaGly levels decreased significantly in both genotypes but did not recover within 1 day of desubmergence with the other metabolites evaluated. The influence of SUB1A on dynamic changes in the metabolome during complete submergence provides new insights into the functional roles of a single gene in invoking a quiescence strategy that helps stabilize crop production in submergence-prone fields.

Quantitative NMR for bioanalysis and metabolomics.

Over the last several decades, significant technical and experimental advances have made quantitative nuclear magnetic resonance (qNMR) a valuable analytical tool for quantitative measurements on a wide variety of samples. In particular, qNMR has emerged as an important method for metabolomics studies where it is used for interrogation of large sets of biological samples and the resulting spectra are treated with multivariate statistical analysis methods. In this review, recent developments in instrumentation and pulse sequences will be discussed as well as the practical considerations necessary for acquisition of quantitative NMR experiments with an emphasis on their use for bioanalysis. Recent examples of the application of qNMR for metabolomics/metabonomics studies, the characterization of biologicals such as heparin, antibodies, and vaccines, and the analysis of botanical natural products will be presented and the future directions of qNMR discussed.

A comparison of metabolite extraction strategies for 1H-NMR-based metabolic profiling using mature leaf tissue from the model plant Arabidopsis thaliana.

Metabolite analysis is recognized as an important facet of systems biology, however complete metabolome characterization has not been realized due to challenges in sample preparation, inherent instrumental limitations and the labor intensive task of data interpretation. This work aims to compare several commonly used metabolite extraction strategies for their effect on the (1)H nuclear magnetic resonance (NMR) metabolic profile of extracts of the model plant Arabidopsis thaliana. Extractions were carried out on aliquots from a pool of homogenized plant tissue using CD(3)CN/D(2)O, buffered D(2)O, perchloric acid in D(2)O, CD(3)OD/D(2)O and CD(3)OD/D(2)O/CDCl(3) as the extraction solvents. The effects of lyophilization as a sample pretreatment, solvent evaporation and extract fractionation for removal of interfering species were studied. Representative spectra are presented for qualitative interpretation. Analytical reproducibility was evaluated by principal components analysis. Perchloric acid facilitated acid-catalyzed cleavage of sucrose, further complicating biological interpretation of the resulting metabolite profile. The solvent system CD(3)OD/D(2)O/CDCl(3) gave the least reproducible results in our hands. D(2)O extracts suffered from poor stability probably due to contamination by soluble enzymes, which were not denatured in this solvent. CD(3)CN/D(2)O extracts showed greater stability than D(2)O alone, but problems were encountered due to degradation of (1)H NMR spectral resolution during lengthy acquisitions due to partial phase separation. In addition, this solvent system produced spectra with significant contamination by lipids that obscured spectral regions containing the resonances of the aliphatic amino acids. These problems were solved by speedvacuuming the CD(3)CN/D(2)O extract and reconstituting in D(2)O solution.

Dynamic Metabolic Response to Adriamycin-Induced Senescence in Breast Cancer Cells.

Cellular senescence displays a heterogeneous set of phenotypes linked to tumor suppression; however, after drug treatment, senescence may also be involved in stable or recurrent cancer. Metabolic changes during senescence can provide detailed information on cellular status and may also have implications for the development of effective treatment strategies. The metabolic response to Adriamycin (ADR) treatment, which causes senescence as well as cell death, was obtained with the aid of metabolic profiling and isotope tracing in two human breast cancer cell lines, MCF7 and MDA-MB-231. After 5 days of ADR treatment, more than 60% of remaining, intact cells entered into a senescent state, characterized by enlarged and flattened morphology and positive blue staining using SA-ß-gal. Metabolic trajectory analysis showed that the two cell lines' responses were significantly different and were divided into two distinct stages. The metabolic shift from the first stage to the second was reflected by a partial recovery of the TCA cycle, as well as amino acid and lipid metabolisms. Isotope tracing analysis indicated that the higher level of glutamine metabolism helped maintain senescence. The results suggest that the dynamic changes during senescence indicate a multi-step process involving important metabolic pathways which might allow breast cancer cells to adapt to persistent ADR treatment, while the higher level of anapleurosis may be important for maintaining the senescent state. Ultimately, a better understanding of metabolic changes during senescence might provide targets for cancer therapy and tumor eradication.

A Metabolomics Study of BPTES Altered Metabolism in Human Breast Cancer Cell Lines.

The Warburg effect is a well-known phenomenon in cancer, but the glutamine addiction in which cancer cells utilize glutamine as an alternative source of energy is less well known. Recent efforts have focused on preventing cancer cell proliferation associated with glutamine addiction by targeting glutaminase using the inhibitor BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide). In the current study, an investigation of the BPTES induced changes in metabolism was made in two human breast cancer cell lines, MCF7 (an estrogen receptor dependent cell line) and MDA-MB231 (a triple negative cell line), relative to the non-cancerous cell line, MCF10A. NMR spectroscopy combined with a recently established smart-isotope tagging approach enabled quantitative analysis of 41 unique metabolites representing numerous metabolite classes including carbohydrates, amino acids, carboxylic acids and nucleotides. BPTES induced metabolism changes in the cancer cell lines were especially pronounced under hypoxic conditions with up to 1/3 of the metabolites altered significantly (p < 0.05) relative to untreated cells. The BPTES induced changes were more pronounced for MCF7 cells, with 14 metabolites altered significantly (p < 0.05) compared to seven for MDA-MB231. Analyses of the results indicate that BPTES affected numerous metabolic pathways including glycolysis, TCA cycle, nucleotide and amino acid metabolism in cancer. The distinct metabolic responses to BPTES treatment determined in the two breast cancer cell lines offer valuable metabolic information for the exploration of the therapeutic responses to breast cancer.

Metabolism and Biodegradation of Spacecraft Cleaning Reagents by Strains of Spacecraft-Associated Acinetobacter.

Spacecraft assembly facilities are oligotrophic and low-humidity environments, which are routinely cleaned using alcohol wipes for benchtops and spacecraft materials, and alkaline detergents for floors. Despite these cleaning protocols, spacecraft assembly facilities possess a persistent, diverse, dynamic, and low abundant core microbiome, where the Acinetobacter are among the dominant members of the community. In this report, we show that several spacecraft-associated Acinetobacter metabolize or biodegrade the spacecraft cleaning reagents of ethanol (ethyl alcohol), 2-propanol (isopropyl alcohol), and Kleenol 30 (floor detergent) under ultraminimal conditions. Using cultivation and stable isotope labeling studies, we show that ethanol is a sole carbon source when cultivating in 0.2 × M9 minimal medium containing 26 µM Fe(NH4)2(SO4)2. Although cultures expectedly did not grow solely on 2-propanol, cultivations on mixtures of ethanol and 2-propanol exhibited enhanced plate counts at mole ratios of ≤0.50. In support, enzymology experiments on cellular extracts were consistent with oxidation of ethanol and 2-propanol by a membrane-bound alcohol dehydrogenase. In the presence of Kleenol 30, untargeted metabolite profiling on ultraminimal cultures of Acinetobacter radioresistens 50v1 indicated (1) biodegradation of Kleenol 30 into products including ethylene glycols, (2) the potential metabolism of decanoate (formed during incubation of Kleenol 30 in 0.2 × M9), and (3) decreases in the abundances of several hydroxy- and ketoacids in the extracellular metabolome. In ultraminimal medium (when using ethanol as a sole carbon source), A. radioresistens 50v1 also exhibits a remarkable survival against hydrogen peroxide (∼1.5-log loss, ∼108 colony forming units (cfu)/mL, 10 mM H2O2), indicating a considerable tolerance toward oxidative stress under nutrient-restricted conditions. Together, these results suggest that the spacecraft cleaning reagents may (1) serve as nutrient sources under oligotrophic conditions and (2) sustain extremotolerances against the oxidative stresses associated with low-humidity environments. In perspective, this study provides a plausible biochemical rationale to the observed microbial ecology dynamics of spacecraft-associated environments.

Separation of ten phosphorylated mono-and disaccharides using HILIC and ion-pairing interactions.

Phosphorylated carbohydrates are indispensable cogs in several key metabolic wheels for all forms of life. Here, a straightforward liquid chromatography method coupled to mass spectrometry detection was developed for phosphorylated sugars. For separation of the targeted compounds, hydrophilic interaction chromatography (HILIC) was used with a bridged-ethylene hybrid amide column under alkaline conditions using triethylamine as a mobile phase modifier. Methylphosphonic acid was added to the aqueous mobile phase to reduce the tailing of compounds containing phosphate groups, which are known to interact with stainless steel components of the separation system. Under alkaline conditions and addition of methylphosphonic acid, the retention behavior can be attributed to both conventional HILIC mechanisms as well as ion-pairing interactions in the mobile phase. This hypothesis is supported by comparing the retention behavior of phosphorylated sugars and unmodified sugars. The HILIC method resolved eight biologically important phosphorylated sugars and thereby enables simultaneous detection and quantification of these compounds: fructose-1,6-bisphosphate, glucose-1-phosphate, glucose-6-phosphate, lactose-1-phosphate, mannose-6-phosphate, ribose-5-phosphate, sucrose-6-phosphate, and threhalose-6-phosphate. Fructose-1-phosphate and fructose-6-phosphate were not resolved but quantification of total fructose-phosphate is possible.

1H NMR-based metabolomics methods for chemical genomics experiments.

Metabolomics and chemical genomics studies can each provide unique insights into plant biology. Although a variety of analytical techniques can be used for the interrogation of plant systems, nuclear magnetic resonance (NMR) provides unbiased characterization of abundant metabolites. An example methodology is provided for probing the metabolism of Arabidopsis thaliana in a chemical genomics experiment including methods for tissue treatment, tissue collection, metabolite extraction, and methods to minimize variance in biological and technical sample replicates. Additionally, considerations and methods for data analysis, including multivariate statistics, univariate statistics, and data interpretation are included. The process is illustrated by examining the metabolic effects of chemical treatment of Arabidopsis with Sortin 1, also known as vacuolar protein sorting inhibitor 1. Sortin 1 was applied to Arabidopsis seedlings to examine metabolic effects in a chemical genomics experiment and to demonstrate the utility of metabolomics in conjunction with other "omics" techniques.